Local adaptation and the evolution of species' ranges under climate change.

PubMed

Atkins, K E; Travis, J M J

2010-10-07

The potential impact of climate change on biodiversity is well documented. A well developed range of statistical methods currently exists that projects the possible future habitat of a species directly from the current climate and a species distribution. However, studies incorporating ecological and evolutionary processes remain limited. Here, we focus on the potential role that local adaptation to climate may play in driving the range dynamics of sessile organisms. Incorporating environmental adaptation into a stochastic simulation yields several new insights. Counter-intuitively, our simulation results suggest that species with broader ranges are not necessarily more robust to climate change. Instead, species with broader ranges can be more susceptible to extinction as locally adapted genotypes are often blocked from range shifting by the presence of cooler adapted genotypes that persist even when their optimum climate has left them behind. Interestingly, our results also suggest that it will not always be the cold-adapted phenotypes that drive polewards range expansion. Instead, range shifts may be driven by phenotypes conferring adaptation to conditions prevalent towards the centre of a species' equilibrium distribution. This may have important consequences for the conservation method termed predictive provenancing. These initial results highlight the potential importance of local adaptation in determining how species will respond to climate change and we argue that this is an area requiring urgent theoretical and empirical attention. 2010 Elsevier Ltd. All rights reserved.

A Flight Control System for Small Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Tunik, A. A.; Nadsadnaya, O. I.

2018-03-01

The program adaptation of the controller for the flight control system (FCS) of an unmanned aerial vehicle (UAV) is considered. Linearized flight dynamic models depend mainly on the true airspeed of the UAV, which is measured by the onboard air data system. This enables its use for program adaptation of the FCS over the full range of altitudes and velocities, which define the flight operating range. FCS with program adaptation, based on static feedback (SF), is selected. The SF parameters for every sub-range of the true airspeed are determined using the linear matrix inequality approach in the case of discrete systems for synthesis of a suboptimal robust H ∞-controller. The use of the Lagrange interpolation between true airspeed sub-ranges provides continuous adaptation. The efficiency of the proposed approach is shown against an example of the heading stabilization system.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

A Numerical Study of Mesh Adaptivity in Multiphase Flows with Non-Newtonian Fluids

NASA Astrophysics Data System (ADS)

Percival, James; Pavlidis, Dimitrios; Xie, Zhihua; Alberini, Federico; Simmons, Mark; Pain, Christopher; Matar, Omar

2014-11-01

We present an investigation into the computational efficiency benefits of dynamic mesh adaptivity in the numerical simulation of transient multiphase fluid flow problems involving Non-Newtonian fluids. Such fluids appear in a range of industrial applications, from printing inks to toothpastes and introduce new challenges for mesh adaptivity due to the additional ``memory'' of viscoelastic fluids. Nevertheless, the multiscale nature of these flows implies huge potential benefits for a successful implementation. The study is performed using the open source package Fluidity, which couples an unstructured mesh control volume finite element solver for the multiphase Navier-Stokes equations to a dynamic anisotropic mesh adaptivity algorithm, based on estimated solution interpolation error criteria, and conservative mesh-to-mesh interpolation routine. The code is applied to problems involving rheologies ranging from simple Newtonian to shear-thinning to viscoelastic materials and verified against experimental data for various industrial and microfluidic flows. This work was undertaken as part of the EPSRC MEMPHIS programme grant EP/K003976/1.

Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

Numerous examples of material systems that dynamically interact with and adapt to the surrounding environment are found in nature, from hair-based mechanoreceptors in animals to self-shaping seed dispersal units in plants to remodeling bone in vertebrates. Inspired by such fascinating biological structures, a wide range of synthetic material systems have been created to replicate the design concepts of dynamic natural architectures. Examples of biological structures and their man-made counterparts are herein revisited to illustrate how dynamic and adaptive responses emerge from the intimate microscale combination of building blocks with intrinsic nanoscale properties. By using top-down photolithographic methods and bottom-up assembly approaches, biologically inspired dynamic material systems have been created 1) to sense liquid flow with hair-inspired microelectromechanical systems, 2) to autonomously change shape by utilizing plantlike heterogeneous architectures, 3) to homeostatically influence the surrounding environment through self-regulating adaptive surfaces, and 4) to spatially concentrate chemical species by using synthetic microcompartments. The ever-increasing complexity and remarkable functionalities of such synthetic systems offer an encouraging perspective to the rich set of dynamic and adaptive properties that can potentially be implemented in future man-made material systems. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Dynamic Range Paradox: A Central Auditory Model of Intensity Change Detection

PubMed Central

Simpson, Andrew J.R.; Reiss, Joshua D.

2013-01-01

In this paper we use empirical loudness modeling to explore a perceptual sub-category of the dynamic range problem of auditory neuroscience. Humans are able to reliably report perceived intensity (loudness), and discriminate fine intensity differences, over a very large dynamic range. It is usually assumed that loudness and intensity change detection operate upon the same neural signal, and that intensity change detection may be predicted from loudness data and vice versa. However, while loudness grows as intensity is increased, improvement in intensity discrimination performance does not follow the same trend and so dynamic range estimations of the underlying neural signal from loudness data contradict estimations based on intensity just-noticeable difference (JND) data. In order to account for this apparent paradox we draw on recent advances in auditory neuroscience. We test the hypothesis that a central model, featuring central adaptation to the mean loudness level and operating on the detection of maximum central-loudness rate of change, can account for the paradoxical data. We use numerical optimization to find adaptation parameters that fit data for continuous-pedestal intensity change detection over a wide dynamic range. The optimized model is tested on a selection of equivalent pseudo-continuous intensity change detection data. We also report a supplementary experiment which confirms the modeling assumption that the detection process may be modeled as rate-of-change. Data are obtained from a listening test (N = 10) using linearly ramped increment-decrement envelopes applied to pseudo-continuous noise with an overall level of 33 dB SPL. Increments with half-ramp durations between 5 and 50,000 ms are used. The intensity JND is shown to increase towards long duration ramps (p<10−6). From the modeling, the following central adaptation parameters are derived; central dynamic range of 0.215 sones, 95% central normalization, and a central loudness JND constant of 5.5×10−5 sones per ms. Through our findings, we argue that loudness reflects peripheral neural coding, and the intensity JND reflects central neural coding. PMID:23536749

Electroencephalographic compression based on modulated filter banks and wavelet transform.

PubMed

Bazán-Prieto, Carlos; Cárdenas-Barrera, Julián; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando

2011-01-01

Due to the large volume of information generated in an electroencephalographic (EEG) study, compression is needed for storage, processing or transmission for analysis. In this paper we evaluate and compare two lossy compression techniques applied to EEG signals. It compares the performance of compression schemes with decomposition by filter banks or wavelet Packets transformation, seeking the best value for compression, best quality and more efficient real time implementation. Due to specific properties of EEG signals, we propose a quantization stage adapted to the dynamic range of each band, looking for higher quality. The results show that the compressor with filter bank performs better than transform methods. Quantization adapted to the dynamic range significantly enhances the quality.

Range dynamics of mountain plants decrease with elevation.

PubMed

Rumpf, Sabine B; Hülber, Karl; Klonner, Günther; Moser, Dietmar; Schütz, Martin; Wessely, Johannes; Willner, Wolfgang; Zimmermann, Niklaus E; Dullinger, Stefan

2018-02-20

Many studies report that mountain plant species are shifting upward in elevation. However, the majority of these reports focus on shifts of upper limits. Here, we expand the focus and simultaneously analyze changes of both range limits, optima, and abundances of 183 mountain plant species. We therefore resurveyed 1,576 vegetation plots first recorded before 1970 in the European Alps. We found that both range limits and optima shifted upward in elevation, but the most pronounced trend was a mean increase in species abundance. Despite huge species-specific variation, range dynamics showed a consistent trend along the elevational gradient: Both range limits and optima shifted upslope faster the lower they were situated historically, and species' abundance increased more for species from lower elevations. Traits affecting the species' dispersal and persistence capacity were not related to their range dynamics. Using indicator values to stratify species by their thermal and nutrient demands revealed that elevational ranges of thermophilic species tended to expand, while those of cold-adapted species tended to contract. Abundance increases were strongest for nutriphilous species. These results suggest that recent climate warming interacted with airborne nitrogen deposition in driving the observed dynamics. So far, the majority of species appear as "winners" of recent changes, yet "losers" are overrepresented among high-elevation, cold-adapted species with low nutrient demands. In the decades to come, high-alpine species may hence face the double pressure of climatic changes and novel, superior competitors that move up faster than they themselves can escape to even higher elevations.

A NOISE ADAPTIVE FUZZY EQUALIZATION METHOD FOR PROCESSING SOLAR EXTREME ULTRAVIOLET IMAGES

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

Druckmueller, M., E-mail: druckmuller@fme.vutbr.cz

A new image enhancement tool ideally suited for the visualization of fine structures in extreme ultraviolet images of the corona is presented in this paper. The Noise Adaptive Fuzzy Equalization method is particularly suited for the exceptionally high dynamic range images from the Atmospheric Imaging Assembly instrument on the Solar Dynamics Observatory. This method produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform which are often used for that purpose.

Introduction to State Estimation of High-Rate System Dynamics.

PubMed

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

Adaptive dynamics on an environmental gradient that changes over a geological time-scale.

PubMed

Fortelius, Mikael; Geritz, Stefan; Gyllenberg, Mats; Toivonen, Jaakko

2015-07-07

The standard adaptive dynamics framework assumes two timescales, i.e. fast population dynamics and slow evolutionary dynamics. We further assume a third timescale, which is even slower than the evolutionary timescale. We call this the geological timescale and we assume that slow climatic change occurs within this timescale. We study the evolution of our model population over this very slow geological timescale with bifurcation plots of the standard adaptive dynamics framework. The bifurcation parameter being varied describes the abiotic environment that changes over the geological timescale. We construct evolutionary trees over the geological timescale and observe both gradual phenotypic evolution and punctuated branching events. We concur with the established notion that branching of a monomorphic population on an environmental gradient only happens when the gradient is not too shallow and not too steep. However, we show that evolution within the habitat can produce polymorphic populations that inhabit steep gradients. What is necessary is that the environmental gradient at some point in time is such that the initial branching of the monomorphic population can occur. We also find that phenotypes adapted to environments in the middle of the existing environmental range are more likely to branch than phenotypes adapted to extreme environments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptation without parameter change: Dynamic gain control in motion detection

PubMed Central

Borst, Alexander; Flanagin, Virginia L.; Sompolinsky, Haim

2005-01-01

Many sensory systems adapt their input-output relationship to changes in the statistics of the ambient stimulus. Such adaptive behavior has been measured in a motion detection sensitive neuron of the fly visual system, H1. The rapid adaptation of the velocity response gain has been interpreted as evidence of optimal matching of the H1 response to the dynamic range of the stimulus, thereby maximizing its information transmission. Here, we show that correlation-type motion detectors, which are commonly thought to underlie fly motion vision, intrinsically possess adaptive properties. Increasing the amplitude of the velocity fluctuations leads to a decrease of the effective gain and the time constant of the velocity response without any change in the parameters of these detectors. The seemingly complex property of this adaptation turns out to be a straightforward consequence of the multidimensionality of the stimulus and the nonlinear nature of the system. PMID:15833815

Effective Dynamic Range and Retest Reliability of Dark-Adapted Two-Color Fundus-Controlled Perimetry in Patients With Macular Diseases.

PubMed

Pfau, Maximilian; Lindner, Moritz; Müller, Philipp L; Birtel, Johannes; Finger, Robert P; Harmening, Wolf M; Fleckenstein, Monika; Holz, Frank G; Schmitz-Valckenberg, Steffen

2017-05-01

To determine the effective dynamic range (EDR), retest reliability, and number of discriminable steps (DS) for mesopic and dark-adapted two-color fundus-controlled perimetry (FCP) using the S-MAIA (Scotopic-Macular Integrity Assessment) "micro-perimeter." In this prospective cross-sectional study, each of the 52 eyes of 52 subjects with various macular diseases (mean age 62.0 ± 16.9 years; range, 19.1-90.1 years) underwent duplicate mesopic (achromatic stimuli, 400-800 nm), dark-adapted cyan (505 nm), and dark-adapted red (627 nm) FCP using a grid of 61 stimuli covering 18° of the central retina. The EDR, the number of DS, and the retest reliability for point-wise sensitivity (PWS) were analyzed. The effects of fixation stability, sensitivity, and age on retest reliability were examined using mixed-effects models. The EDR was 10 to 30 dB with five DS for mesopic and 4 to 17 dB with four DS for dark-adapted cyan and red testing. PWS retest reliability was good among all three types of retinal sensitivity assessments (coefficient of repeatability ±5.79, ±4.72, and ±4.77 dB, respectively) and did not depend on fixation stability or age. PWS had no effect on retest variability in dark-adapted cyan and dark-adapted red testing but had a minor effect in mesopic testing. Combined mesopic and dark-adapted two-color FCP allows for reliable topographic testing of cone and rod function in patients with various macular diseases with and without foveal fixation. Retest reliability is homogeneous across eccentricities and various degrees of scotoma depth, including zones at risk for disease progression. These reliability estimates can serve for the design of future clinical trials.

Spatiotemporal variation in resource selection: Insights from the American marten (Martes Americana)

Treesearch

Andrew J. Shirk; Martin G. Raphael; Samuel A. Cushman

2014-01-01

Behavioral and genetic adaptations to spatiotemporal variation in habitat conditions allow species to maximize their biogeographic range and persist over time in dynamic environments. An understanding of these local adaptations can be used to guide management and conservation of populations over broad extents encompassing diverse habitats. This understanding is often...

Introduction to State Estimation of High-Rate System Dynamics

PubMed Central

Dodson, Jacob; Joyce, Bryan

2018-01-01

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. PMID:29342855

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors

PubMed Central

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-01-01

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison. PMID:29614028

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

PubMed

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-04-03

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

High dynamic range adaptive real-time smart camera: an overview of the HDR-ARTiST project

NASA Astrophysics Data System (ADS)

Lapray, Pierre-Jean; Heyrman, Barthélémy; Ginhac, Dominique

2015-04-01

Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor.

Generalised optical differentiation wavefront sensor: a sensitive high dynamic range wavefront sensor.

PubMed

Haffert, S Y

2016-08-22

Current wavefront sensors for high resolution imaging have either a large dynamic range or a high sensitivity. A new kind of wavefront sensor is developed which can have both: the Generalised Optical Differentiation wavefront sensor. This new wavefront sensor is based on the principles of optical differentiation by amplitude filters. We have extended the theory behind linear optical differentiation and generalised it to nonlinear filters. We used numerical simulations and laboratory experiments to investigate the properties of the generalised wavefront sensor. With this we created a new filter that can decouple the dynamic range from the sensitivity. These properties make it suitable for adaptive optic systems where a large range of phase aberrations have to be measured with high precision.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

PubMed

Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

2016-02-01

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.

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.

Dynamic neural networks based on-line identification and control of high performance motor drives

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Kotaru, Raj

1995-01-01

In the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.

Color transfer between high-dynamic-range images

NASA Astrophysics Data System (ADS)

Hristova, Hristina; Cozot, Rémi; Le Meur, Olivier; Bouatouch, Kadi

2015-09-01

Color transfer methods alter the look of a source image with regards to a reference image. So far, the proposed color transfer methods have been limited to low-dynamic-range (LDR) images. Unlike LDR images, which are display-dependent, high-dynamic-range (HDR) images contain real physical values of the world luminance and are able to capture high luminance variations and finest details of real world scenes. Therefore, there exists a strong discrepancy between the two types of images. In this paper, we bridge the gap between the color transfer domain and the HDR imagery by introducing HDR extensions to LDR color transfer methods. We tackle the main issues of applying a color transfer between two HDR images. First, to address the nature of light and color distributions in the context of HDR imagery, we carry out modifications of traditional color spaces. Furthermore, we ensure high precision in the quantization of the dynamic range for histogram computations. As image clustering (based on light and colors) proved to be an important aspect of color transfer, we analyze it and adapt it to the HDR domain. Our framework has been applied to several state-of-the-art color transfer methods. Qualitative experiments have shown that results obtained with the proposed adaptation approach exhibit less artifacts and are visually more pleasing than results obtained when straightforwardly applying existing color transfer methods to HDR images.

An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

NASA Astrophysics Data System (ADS)

Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

2018-05-01

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

Improved laser-based triangulation sensor with enhanced range and resolution through adaptive optics-based active beam control.

PubMed

Reza, Syed Azer; Khwaja, Tariq Shamim; Mazhar, Mohsin Ali; Niazi, Haris Khan; Nawab, Rahma

2017-07-20

Various existing target ranging techniques are limited in terms of the dynamic range of operation and measurement resolution. These limitations arise as a result of a particular measurement methodology, the finite processing capability of the hardware components deployed within the sensor module, and the medium through which the target is viewed. Generally, improving the sensor range adversely affects its resolution and vice versa. Often, a distance sensor is designed for an optimal range/resolution setting depending on its intended application. Optical triangulation is broadly classified as a spatial-signal-processing-based ranging technique and measures target distance from the location of the reflected spot on a position sensitive detector (PSD). In most triangulation sensors that use lasers as a light source, beam divergence-which severely affects sensor measurement range-is often ignored in calculations. In this paper, we first discuss in detail the limitations to ranging imposed by beam divergence, which, in effect, sets the sensor dynamic range. Next, we show how the resolution of laser-based triangulation sensors is limited by the interpixel pitch of a finite-sized PSD. In this paper, through the use of tunable focus lenses (TFLs), we propose a novel design of a triangulation-based optical rangefinder that improves both the sensor resolution and its dynamic range through adaptive electronic control of beam propagation parameters. We present the theory and operation of the proposed sensor and clearly demonstrate a range and resolution improvement with the use of TFLs. Experimental results in support of our claims are shown to be in strong agreement with theory.

Anticipation from sensation: using anticipating synchronization to stabilize a system with inherent sensory delay.

PubMed

Eberle, Henry; Nasuto, Slawomir J; Hayashi, Yoshikatsu

2018-03-01

We present a novel way of using a dynamical model for predictive tracking control that can adapt to a wide range of delays without parameter update. This is achieved by incorporating the paradigm of anticipating synchronization (AS), where a 'slave' system predicts a 'master' via delayed self-feedback. By treating the delayed output of the plant as one half of a 'sensory' AS coupling, the plant and an internal dynamical model can be synchronized such that the plant consistently leads the target's motion. We use two simulated robotic systems with differing arrangements of the plant and internal model ('parallel' and 'serial') to demonstrate that this form of control adapts to a wide range of delays without requiring the parameters of the controller to be changed.

A detail enhancement and dynamic range adjustment algorithm for high dynamic range images

NASA Astrophysics Data System (ADS)

Xu, Bo; Wang, Huachuang; Liang, Mingtao; Yu, Cong; Hu, Jinlong; Cheng, Hua

2014-08-01

Although high dynamic range (HDR) images contain large amounts of information, they have weak texture and low contrast. What's more, these images are difficult to be reproduced on low dynamic range displaying mediums. If much more information is to be acquired when these images are displayed on PCs, some specific transforms, such as compressing the dynamic range, enhancing the portions of little difference in original contrast and highlighting the texture details on the premise of keeping the parts of large contrast, are needed. To this ends, a multi-scale guided filter enhancement algorithm which derives from the single-scale guided filter based on the analysis of non-physical model is proposed in this paper. Firstly, this algorithm decomposes the original HDR images into base image and detail images of different scales, and then it adaptively selects a transform function which acts on the enhanced detail images and original images. By comparing the treatment effects of HDR images and low dynamic range (LDR) images of different scene features, it proves that this algorithm, on the basis of maintaining the hierarchy and texture details of images, not only improves the contrast and enhances the details of images, but also adjusts the dynamic range well. Thus, it is much suitable for human observation or analytical processing of machines.

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

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

Zhang, Gaigong; Lin, Lin, E-mail: linlin@math.berkeley.edu; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynmanmore » forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Since the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H{sub 2} and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.« less

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

DOE PAGES

Zhang, Gaigong; Lin, Lin; Hu, Wei; ...

2017-01-27

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynmanmore » forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Sin ce the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H 2 and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.« less

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

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

Zhang, Gaigong; Lin, Lin; Hu, Wei

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynmanmore » forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Sin ce the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H 2 and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.« less

Adaptive local basis set for Kohn-Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

NASA Astrophysics Data System (ADS)

Zhang, Gaigong; Lin, Lin; Hu, Wei; Yang, Chao; Pask, John E.

2017-04-01

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn-Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann-Feynman forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Since the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann-Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H2 and liquid Al-Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.

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

PubMed

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

2017-05-01

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

Effects of local adaptation and interspecific competition on species' responses to climate change.

PubMed

Bocedi, Greta; Atkins, Katherine E; Liao, Jishan; Henry, Roslyn C; Travis, Justin M J; Hellmann, Jessica J

2013-09-01

Local adaptation and species interactions have been shown to affect geographic ranges; therefore, we need models of climate impact that include both factors. To identify possible dynamics of species when including these factors, we ran simulations of two competing species using an individual-based, coupled map-lattice model using a linear climatic gradient that varies across latitude and is warmed over time. Reproductive success is governed by an individual's adaptation to local climate as well as its location relative to global constraints. In exploratory experiments varying the strength of adaptation and competition, competition reduces genetic diversity and slows range change, although the two species can coexist in the absence of climate change and shift in the absence of competitors. We also found that one species can drive the other to extinction, sometimes long after climate change ends. Weak selection on local adaptation and poor dispersal ability also caused surfing of cooler-adapted phenotypes from the expanding margin backwards, causing loss of warmer-adapted phenotypes. Finally, geographic ranges can become disjointed, losing centrally-adapted genotypes. These initial results suggest that the interplay between local adaptation and interspecific competition can significantly influence species' responses to climate change, in a way that demands future research. © 2013 New York Academy of Sciences.

White noise analysis of Phycomyces light growth response system. I. Normal intensity range.

PubMed Central

Lipson, E D

1975-01-01

The Wiener-Lee-Schetzen method for the identification of a nonlinear system through white gaussian noise stimulation was applied to the transient light growth response of the sporangiophore of Phycomyces. In order to cover a moderate dynamic range of light intensity I, the imput variable was defined to be log I. The experiments were performed in the normal range of light intensity, centered about I0 = 10(-6) W/cm2. The kernels of the Wierner functionals were computed up to second order. Within the range of a few decades the system is reasonably linear with log I. The main nonlinear feature of the second-order kernel corresponds to the property of rectification. Power spectral analysis reveals that the slow dynamics of the system are of at least fifth order. The system can be represented approximately by a linear transfer function, including a first-order high-pass (adaptation) filter with a 4 min time constant and an underdamped fourth-order low-pass filter. Accordingly a linear electronic circuit was constructed to simulate the small scale response characteristics. In terms of the adaptation model of Delbrück and Reichardt (1956, in Cellular Mechanisms in Differentiation and Growth, Princeton University Press), kernels were deduced for the dynamic dependence of the growth velocity (output) on the "subjective intensity", a presumed internal variable. Finally the linear electronic simulator above was generalized to accommodate the large scale nonlinearity of the adaptation model and to serve as a tool for deeper test of the model. PMID:1203444

Membrane adaptive optics

NASA Astrophysics Data System (ADS)

Marker, Dan K.; Wilkes, James M.; Ruggiero, Eric J.; Inman, Daniel J.

2005-08-01

An innovative adaptive optic is discussed that provides a range of capabilities unavailable with either existing, or newly reported, research devices. It is believed that this device will be inexpensive and uncomplicated to construct and operate, with a large correction range that should dramatically relax the static and dynamic structural tolerances of a telescope. As the areal density of a telescope primary is reduced, the optimal optical figure and the structural stiffness are inherently compromised and this phenomenon will require a responsive, range-enhanced wavefront corrector. In addition to correcting for the aberrations in such innovative primary mirrors, sufficient throw remains to provide non-mechanical steering to dramatically improve the Field of regard. Time dependent changes such as thermal disturbances can also be accommodated. The proposed adaptive optic will overcome some of the issues facing conventional deformable mirrors, as well as current and proposed MEMS-based deformable mirrors and liquid crystal based adaptive optics. Such a device is scalable to meter diameter apertures, eliminates high actuation voltages with minimal power consumption, provides long throw optical path correction, provides polychromatic dispersion free operation, dramatically reduces the effects of adjacent actuator influence, and provides a nearly 100% useful aperture. This article will reveal top-level details of the proposed construction and include portions of a static, dynamic, and residual aberration analysis. This device will enable certain designs previously conceived by visionaries in the optical community.

Blurred Star Image Processing for Star Sensors under Dynamic Conditions

PubMed Central

Zhang, Weina; Quan, Wei; Guo, Lei

2012-01-01

The precision of star point location is significant to identify the star map and to acquire the aircraft attitude for star sensors. Under dynamic conditions, star images are not only corrupted by various noises, but also blurred due to the angular rate of the star sensor. According to different angular rates under dynamic conditions, a novel method is proposed in this article, which includes a denoising method based on adaptive wavelet threshold and a restoration method based on the large angular rate. The adaptive threshold is adopted for denoising the star image when the angular rate is in the dynamic range. Then, the mathematical model of motion blur is deduced so as to restore the blurred star map due to large angular rate. Simulation results validate the effectiveness of the proposed method, which is suitable for blurred star image processing and practical for attitude determination of satellites under dynamic conditions. PMID:22778666

Assessing the stability of tree ranges and influence of disturbance in eastern US forests

Treesearch

C.W. Woodall; K. Zhu; J.A. Westfall; C.M. Oswalt; A.W. D' Amato; B.F. Walters; H.E. Lintz

2013-01-01

Shifts in tree species ranges may occur due to global climate change, which in turn may be exacerbated by natural disturbance events. Within the context of global climate change, developing techniques to monitor tree range dynamics as affected by natural disturbances may enable mitigation/adaptation of projected impacts. Using a forest inventory across the eastern U.S...

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments

PubMed Central

van Boxtel, Coco; van Heerden, Johan H.; Nordholt, Niclas; Schmidt, Phillipp

2017-01-01

Natural selection has shaped the strategies for survival and growth of microorganisms. The success of microorganisms depends not only on slow evolutionary tuning but also on the ability to adapt to unpredictable changes in their environment. In principle, adaptive strategies range from purely deterministic mechanisms to those that exploit the randomness intrinsic to many cellular and molecular processes. Depending on the environment and selective pressures, particular strategies can lie somewhere along this continuum. In recent years, non-genetic cell-to-cell differences have received a lot of attention, not least because of their potential impact on the ability of microbial populations to survive in dynamic environments. Using several examples, we describe the origins of spontaneous and induced mechanisms of phenotypic adaptation. We identify some of the commonalities of these examples and consider the potential role of chance and constraints in microbial phenotypic adaptation. PMID:28701503

Architecture for Adaptive Intelligent Systems

NASA Technical Reports Server (NTRS)

Hayes-Roth, Barbara

1993-01-01

We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring.

Anticipation from sensation: using anticipating synchronization to stabilize a system with inherent sensory delay

PubMed Central

Nasuto, Slawomir J.; Hayashi, Yoshikatsu

2018-01-01

We present a novel way of using a dynamical model for predictive tracking control that can adapt to a wide range of delays without parameter update. This is achieved by incorporating the paradigm of anticipating synchronization (AS), where a ‘slave’ system predicts a ‘master’ via delayed self-feedback. By treating the delayed output of the plant as one half of a ‘sensory’ AS coupling, the plant and an internal dynamical model can be synchronized such that the plant consistently leads the target’s motion. We use two simulated robotic systems with differing arrangements of the plant and internal model (‘parallel’ and ‘serial’) to demonstrate that this form of control adapts to a wide range of delays without requiring the parameters of the controller to be changed. PMID:29657750

Adaptive wing static aeroelastic roll control

NASA Astrophysics Data System (ADS)

Ehlers, Steven M.; Weisshaar, Terrence A.

1993-09-01

Control of the static aeroelastic characteristics of a swept uniform wing in roll using an adaptive structure is examined. The wing structure is modeled as a uniform beam with bending and torsional deformation freedom. Aerodynamic loads are obtained from strip theory. The structure model includes coefficients representing torsional and bending actuation provided by embedded piezoelectric material layers. The wing is made adaptive by requiring the electric field applied to the piezoelectric material layers to be proportional to the wing root loads. The proportionality factor, or feedback gain, is used to control static aeroelastic rolling properties. Example wing configurations are used to illustrate the capabilities of the adaptive structure. The results show that rolling power, damping-in-roll and aileron effectiveness can be controlled by adjusting the feedback gain. And that dynamic pressure affects the gain required. Gain scheduling can be used to set and maintain rolling properties over a range of dynamic pressures. An adaptive wing provides a method for active aeroelastic tailoring of structural response to meet changing structural performance requirements during a roll maneuver.

Predicting Adaptive Behavior in the Environment from Central Nervous System Dynamics

PubMed Central

Proekt, Alex; Wong, Jane; Zhurov, Yuriy; Kozlova, Nataliya; Weiss, Klaudiusz R.; Brezina, Vladimir

2008-01-01

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem—to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics—in effect, autonomous Aplysia agents—in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal “goal,” emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals. PMID:18989362

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

PubMed

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

Effects of controlled element dynamics on human feedforward behavior in ramp-tracking tasks.

PubMed

Laurense, Vincent A; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus René M; Mulder, Max

2015-02-01

In real-life manual control tasks, human controllers are often required to follow a visible and predictable reference signal, enabling them to use feedforward control actions in conjunction with feedback actions that compensate for errors. Little is known about human control behavior in these situations. This paper investigates how humans adapt their feedforward control dynamics to the controlled element dynamics in a combined ramp-tracking and disturbance-rejection task. A human-in-the-loop experiment is performed with a pursuit display and vehicle-like controlled elements, ranging from a single integrator through second-order systems with a break frequency at either 3, 2, or 1 rad/s, to a double integrator. Because the potential benefits of feedforward control increase with steeper ramp segments in the target signal, three steepness levels are tested to investigate their possible effect on feedforward control with the various controlled elements. Analyses with four novel models of the operator, fitted to time-domain data, reveal feedforward control for all tested controlled elements and both (nonzero) tested levels of ramp steepness. For the range of controlled element dynamics investigated, it is found that humans adapt to these dynamics in their feedforward response, with a close to perfect inversion of the controlled element dynamics. No significant effects of ramp steepness on the feedforward model parameters are found.

Dynamic balance during walking adaptability tasks in individuals post-stroke.

PubMed

Vistamehr, Arian; Balasubramanian, Chitralakshmi K; Clark, David J; Neptune, Richard R; Fox, Emily J

2018-06-06

Maintaining dynamic balance during community ambulation is a major challenge post-stroke. Community ambulation requires performance of steady-state level walking as well as tasks that require walking adaptability. Prior studies on balance control post-stroke have mainly focused on steady-state walking, but walking adaptability tasks have received little attention. The purpose of this study was to quantify and compare dynamic balance requirements during common walking adaptability tasks post-stroke and in healthy adults and identify differences in underlying mechanisms used for maintaining dynamic balance. Kinematic data were collected from fifteen individuals with post-stroke hemiparesis during steady-state forward and backward walking, obstacle negotiation, and step-up tasks. In addition, data from ten healthy adults provided the basis for comparison. Dynamic balance was quantified using the peak-to-peak range of whole-body angular-momentum in each anatomical plane during the paretic, nonparetic and healthy control single-leg-stance phase of the gait cycle. To understand differences in some of the key underlying mechanisms for maintaining dynamic balance, foot placement and plantarflexor muscle activation were examined. Individuals post-stroke had significant dynamic balance deficits in the frontal plane across most tasks, particularly during the paretic single-leg-stance. Frontal plane balance deficits were associated with wider paretic foot placement, elevated body center-of-mass, and lower soleus activity. Further, the obstacle negotiation task imposed a higher balance requirement, particularly during the trailing leg single-stance. Thus, improving paretic foot placement and ankle plantarflexor activity, particularly during obstacle negotiation, may be important rehabilitation targets to enhance dynamic balance during post-stroke community ambulation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Chest CT window settings with multiscale adaptive histogram equalization: pilot study.

PubMed

Fayad, Laura M; Jin, Yinpeng; Laine, Andrew F; Berkmen, Yahya M; Pearson, Gregory D; Freedman, Benjamin; Van Heertum, Ronald

2002-06-01

Multiscale adaptive histogram equalization (MAHE), a wavelet-based algorithm, was investigated as a method of automatic simultaneous display of the full dynamic contrast range of a computed tomographic image. Interpretation times were significantly lower for MAHE-enhanced images compared with those for conventionally displayed images. Diagnostic accuracy, however, was insufficient in this pilot study to allow recommendation of MAHE as a replacement for conventional window display.

Experimental Adaptation of Burkholderia cenocepacia to Onion Medium Reduces Host Range ▿ † ‡

PubMed Central

Ellis, Crystal N.; Cooper, Vaughn S.

2010-01-01

It is unclear whether adaptation to a new host typically broadens or compromises host range, yet the answer bears on the fate of emergent pathogens and symbionts. We investigated this dynamic using a soil isolate of Burkholderia cenocepacia, a species that normally inhabits the rhizosphere, is related to the onion pathogen B. cepacia, and can infect the lungs of cystic fibrosis patients. We hypothesized that adaptation of B. cenocepacia to a novel host would compromise fitness and virulence in alternative hosts. We modeled adaptation to a specific host by experimentally evolving 12 populations of B. cenocepacia in liquid medium composed of macerated onion tissue for 1,000 generations. The mean fitness of all populations increased by 78% relative to the ancestor, but significant variation among lines was observed. Populations also varied in several phenotypes related to host association, including motility, biofilm formation, and quorum-sensing function. Together, these results suggest that each population adapted by fixing different sets of adaptive mutations. However, this adaptation was consistently accompanied by a loss of pathogenicity to the nematode Caenorhabditis elegans; by 500 generations most populations became unable to kill nematodes. In conclusion, we observed a narrowing of host range as a consequence of prolonged adaptation to an environment simulating a specific host, and we suggest that emergent pathogens may face similar consequences if they become host-restricted. PMID:20154121

Evaluation of a software module for adaptive treatment planning and re-irradiation.

PubMed

Richter, Anne; Weick, Stefan; Krieger, Thomas; Exner, Florian; Kellner, Sonja; Polat, Bülent; Flentje, Michael

2017-12-28

The aim of this work is to validate the Dynamic Planning Module in terms of usability and acceptance in the treatment planning workflow. The Dynamic Planning Module was used for decision making whether a plan adaptation was necessary within one course of radiation therapy. The Module was also used for patients scheduled for re-irradiation to estimate the dose in the pretreated region and calculate the accumulated dose to critical organs at risk. During one year, 370 patients were scheduled for plan adaptation or re-irradiation. All patient cases were classified according to their treated body region. For a sub-group of 20 patients treated with RT for lung cancer, the dosimetric effect of plan adaptation during the main treatment course was evaluated in detail. Changes in tumor volume, frequency of re-planning and the time interval between treatment start and plan adaptation were assessed. The Dynamic Planning Tool was used in 20% of treated patients per year for both approaches nearly equally (42% plan adaptation and 58% re-irradiation). Most cases were assessed for the thoracic body region (51%) followed by pelvis (21%) and head and neck cases (10%). The sub-group evaluation showed that unintended plan adaptation was performed in 38% of the scheduled cases. A median time span between first day of treatment and necessity of adaptation of 17 days (range 4-35 days) was observed. PTV changed by 12 ± 12% on average (maximum change 42%). PTV decreased in 18 of 20 cases due to tumor shrinkage and increased in 2 of 20 cases. Re-planning resulted in a reduction of the mean lung dose of the ipsilateral side in 15 of 20 cases. The experience of one year showed high acceptance of the Dynamic Planning Module in our department for both physicians and medical physicists. The re-planning can potentially reduce the accumulated dose to the organs at risk and ensure a better target volume coverage. In the re-irradiation situation, the Dynamic Planning Tool was used to consider the pretreatment dose, to adapt the actual treatment schema more specifically and to review the accumulated dose.

A Sound Therapy-Based Intervention to Expand the Auditory Dynamic Range for Loudness among Persons with Sensorineural Hearing Losses: Case Evidence Showcasing Treatment Efficacy

PubMed Central

Formby, Craig; Sherlock, LaGuinn P.; Hawley, Monica L.; Gold, Susan L.

2017-01-01

Case evidence is presented that highlights the clinical relevance and significance of a novel sound therapy-based treatment. This intervention has been shown to be efficacious in a randomized controlled trial for promoting expansion of the dynamic range for loudness and increased sound tolerance among persons with sensorineural hearing losses. Prior to treatment, these individuals were unable to use aided sound effectively because of their limited dynamic ranges. These promising treatment effects are shown in this article to be functionally significant, giving rise to improved speech understanding and enhanced hearing aid benefit and satisfaction, and, in turn, to enhanced quality of life posttreatment. These posttreatment sound therapy effects also are shown to be sustained, in whole or part, with aided environmental sound and to be dependent on specialized counseling to maximize treatment benefit. Importantly, the treatment appears to be efficacious for hearing-impaired persons with primary hyperacusis (i.e., abnormally reduced loudness discomfort levels [LDLs]) and for persons with loudness recruitment (i.e., LDLs within the typical range), which suggests the intervention should generalize across most individuals with reduced dynamic ranges owing to sensorineural hearing loss. An exception presented in this article is for a person describing the perceptual experience of pronounced loudness adaptation, which apparently rendered the sound therapy inaudible and ineffectual for this individual. Ultimately, these case examples showcase the enormous potential of a surprisingly simple sound therapy intervention, which has utility for virtually all audiologists to master and empower the adaptive plasticity of the auditory system to achieve remarkable treatment benefits for large numbers of individuals with sensorineural hearing losses. PMID:28286368

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999. Pt. 1

NASA Technical Reports Server (NTRS)

Woodrow Whitlow, Jr. (Editor); Todd, Emily N. (Editor)

1999-01-01

These proceedings represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

PubMed Central

Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

2016-01-01

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter—describing somatic integration—and the spike-history filter—accounting for spike-frequency adaptation—dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations. PMID:26907675

Gain-adaptive vector quantization for medium-rate speech coding

NASA Technical Reports Server (NTRS)

Chen, J.-H.; Gersho, A.

1985-01-01

A class of adaptive vector quantizers (VQs) that can dynamically adjust the 'gain' of codevectors according to the input signal level is introduced. The encoder uses a gain estimator to determine a suitable normalization of each input vector prior to VQ coding. The normalized vectors have reduced dynamic range and can then be more efficiently coded. At the receiver, the VQ decoder output is multiplied by the estimated gain. Both forward and backward adaptation are considered and several different gain estimators are compared and evaluated. An approach to optimizing the design of gain estimators is introduced. Some of the more obvious techniques for achieving gain adaptation are substantially less effective than the use of optimized gain estimators. A novel design technique that is needed to generate the appropriate gain-normalized codebook for the vector quantizer is introduced. Experimental results show that a significant gain in segmental SNR can be obtained over nonadaptive VQ with a negligible increase in complexity.

Adaptive beam shaping by controlled thermal lensing in optical elements

NASA Astrophysics Data System (ADS)

Arain, Muzammil A.; Quetschke, Volker; Gleason, Joseph; Williams, Luke F.; Rakhmanov, Malik; Lee, Jinho; Cruz, Rachel J.; Mueller, Guido; Tanner, D. B.; Reitze, David. H.

2007-04-01

We describe an adaptive optical system for use as a tunable focusing element. The system provides adaptive beam shaping via controlled thermal lensing in the optical elements. The system is agile, remotely controllable, touch free, and vacuum compatible; it offers a wide dynamic range, aberration-free focal length tuning, and can provide both positive and negative lensing effects. Focusing is obtained through dynamic heating of an optical element by an external pump beam. The system is especially suitable for use in interferometric gravitational wave interferometers employing high laser power, allowing for in situ control of the laser modal properties and compensation for thermal lensing of the primary laser. Using CO2 laser heating of fused-silica substrates, we demonstrate a focal length variable from infinity to 4.0 m, with a slope of 0.082 diopter/W of absorbed heat. For on-axis operation, no higher-order modes are introduced by the adaptive optical element. Theoretical modeling of the induced optical path change and predicted thermal lens agrees well with measurement.

Lessons from Jurassic Park: patients as complex adaptive systems.

PubMed

Katerndahl, David A

2009-08-01

With realization that non-linearity is generally the rule rather than the exception in nature, viewing patients and families as complex adaptive systems may lead to a better understanding of health and illness. Doctors who successfully practise the 'art' of medicine may recognize non-linear principles at work without having the jargon needed to label them. Complex adaptive systems are systems composed of multiple components that display complexity and adaptation to input. These systems consist of self-organized components, which display complex dynamics, ranging from simple periodicity to chaotic and random patterns showing trends over time. Understanding the non-linear dynamics of phenomena both internal and external to our patients can (1) improve our definition of 'health'; (2) improve our understanding of patients, disease and the systems in which they converge; (3) be applied to future monitoring systems; and (4) be used to possibly engineer change. Such a non-linear view of the world is quite congruent with the generalist perspective.

Adaptive beam shaping by controlled thermal lensing in optical elements.

PubMed

Arain, Muzammil A; Quetschke, Volker; Gleason, Joseph; Williams, Luke F; Rakhmanov, Malik; Lee, Jinho; Cruz, Rachel J; Mueller, Guido; Tanner, D B; Reitze, David H

2007-04-20

We describe an adaptive optical system for use as a tunable focusing element. The system provides adaptive beam shaping via controlled thermal lensing in the optical elements. The system is agile, remotely controllable, touch free, and vacuum compatible; it offers a wide dynamic range, aberration-free focal length tuning, and can provide both positive and negative lensing effects. Focusing is obtained through dynamic heating of an optical element by an external pump beam. The system is especially suitable for use in interferometric gravitational wave interferometers employing high laser power, allowing for in situ control of the laser modal properties and compensation for thermal lensing of the primary laser. Using CO(2) laser heating of fused-silica substrates, we demonstrate a focal length variable from infinity to 4.0 m, with a slope of 0.082 diopter/W of absorbed heat. For on-axis operation, no higher-order modes are introduced by the adaptive optical element. Theoretical modeling of the induced optical path change and predicted thermal lens agrees well with measurement.

Model-based assessment of aspen responses to elk herbivory in Rocky Mountain National Park

Treesearch

Peter J. Weisberg; Michael B. Coughenour

2001-01-01

In Rocky Mountain National Park, aspen has been observed to decline on elk winter range for many decades. The SAVANNA ecosystem model was adapted to explore interactions between elk herbivory and aspen dynamics on the elk winter range. Several scenarios were explored that considered different levels of overall elk population; different levels of elk utilization of...

Enhanced weak-signal sensitivity in two-photon microscopy by adaptive illumination.

PubMed

Chu, Kengyeh K; Lim, Daryl; Mertz, Jerome

2007-10-01

We describe a technique to enhance both the weak-signal relative sensitivity and the dynamic range of a laser scanning optical microscope. The technique is based on maintaining a fixed detection power by fast feedback control of the illumination power, thereby transferring high measurement resolution to weak signals while virtually eliminating the possibility of image saturation. We analyze and demonstrate the benefits of adaptive illumination in two-photon fluorescence microscopy.

Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

NASA Astrophysics Data System (ADS)

Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

2009-01-01

For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller.

PubMed

Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; Del Toro Matamoros, Raúl M

2016-05-12

The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value.

Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller †

PubMed Central

Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; del Toro Matamoros, Raúl M.

2016-01-01

The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. PMID:27187397

Transitions from trees to cycles in adaptive flow networks

NASA Astrophysics Data System (ADS)

Martens, Erik A.; Klemm, Konstantin

2017-11-01

Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply. Theoretical and experimental studies have found that real-world transport networks exhibit both tree-like motifs and cycles. When the network is subject to load fluctuations, the presence of cyclic motifs may help to reduce flow fluctuations and, thus, render supply in the network more robust. While previous studies considered network topology via optimization principles, here, we take a dynamical systems approach and study a simple model of a flow network with dynamically adapting weights (conductances). We assume a spatially non-uniform distribution of rapidly fluctuating loads in the sinks and investigate what network configurations are dynamically stable. The network converges to a spatially non-uniform stable configuration composed of both cyclic and tree-like structures. Cyclic structures emerge locally in a transcritical bifurcation as the amplitude of the load fluctuations is increased. The resulting adaptive dynamics thus partitions the network into two distinct regions with cyclic and tree-like structures. The location of the boundary between these two regions is determined by the amplitude of the fluctuations. These findings may explain why natural transport networks display cyclic structures in the micro-vascular regions near terminal nodes, but tree-like features in the regions with larger veins.

Circuit Motifs for Contrast-Adaptive Differentiation in Early Sensory Systems: The Role of Presynaptic Inhibition and Short-Term Plasticity

PubMed Central

Zhang, Danke; Wu, Si; Rasch, Malte J.

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems. PMID:25723493

Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity.

PubMed

Zhang, Danke; Wu, Si; Rasch, Malte J

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

Bonato, C; Blok, M S; Dinani, H T; Berry, D W; Markham, M L; Twitchen, D J; Hanson, R

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

NASA Astrophysics Data System (ADS)

Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

High-speed adaptive optics for imaging of the living human eye

PubMed Central

Yu, Yongxin; Zhang, Tianjiao; Meadway, Alexander; Wang, Xiaolin; Zhang, Yuhua

2015-01-01

The discovery of high frequency temporal fluctuation of human ocular wave aberration dictates the necessity of high speed adaptive optics (AO) correction for high resolution retinal imaging. We present a high speed AO system for an experimental adaptive optics scanning laser ophthalmoscope (AOSLO). We developed a custom high speed Shack-Hartmann wavefront sensor and maximized the wavefront detection speed based upon a trade-off among the wavefront spatial sampling density, the dynamic range, and the measurement sensitivity. We examined the temporal dynamic property of the ocular wavefront under the AOSLO imaging condition and improved the dual-thread AO control strategy. The high speed AO can be operated with a closed-loop frequency up to 110 Hz. Experiment results demonstrated that the high speed AO system can provide improved compensation for the wave aberration up to 30 Hz in the living human eye. PMID:26368408

Emerging hierarchies in dynamically adapting webs

NASA Astrophysics Data System (ADS)

Katifori, Eleni; Graewer, Johannes; Magnasco, Marcelo; Modes, Carl

Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. We quantify the hierarchical organization of the networks by developing an algorithm that decomposes the architecture to multiple scales and analyzes how the organization in each scale relates to that of the scale above and below it. The methodologies developed in this work are applicable to a wide range of systems including the slime mold physarum polycephalum, human microvasculature, and force chains in granular media.

The paradox of enrichment in an adaptive world

PubMed Central

Mougi, Akihiko; Nishimura, Kinya

2008-01-01

Paradoxically, enrichment can destabilize a predator–prey food web. While adaptive dynamics can greatly influence the stability of interaction systems, few theoretical studies have examined the effect of the adaptive dynamics of interaction-related traits on the possibility of resolution of the paradox of enrichment. We consider the evolution of attack and defence traits of a predator and two prey species in a one predator–two prey system in which the predator practises optimal diet use. The results showed that optimal foraging alone cannot eliminate a pattern of destabilization with enrichment, but trait evolution of the predator or prey can change the pattern to one of stabilization, implying a possible resolution of the paradox of enrichment. Furthermore, trait evolution in all species can broaden the parameter range of stabilization. Importantly, rapid evolution can stabilize this system, but weaken its stability in the face of enrichment. PMID:18700201

Incremental update of electrostatic interactions in adaptively restrained particle simulations.

PubMed

Edorh, Semeho Prince A; Redon, Stéphane

2018-04-06

The computation of long-range potentials is one of the demanding tasks in Molecular Dynamics. During the last decades, an inventive panoply of methods was developed to reduce the CPU time of this task. In this work, we propose a fast method dedicated to the computation of the electrostatic potential in adaptively restrained systems. We exploit the fact that, in such systems, only some particles are allowed to move at each timestep. We developed an incremental algorithm derived from a multigrid-based alternative to traditional Fourier-based methods. Our algorithm was implemented inside LAMMPS, a popular molecular dynamics simulation package. We evaluated the method on different systems. We showed that the new algorithm's computational complexity scales with the number of active particles in the simulated system, and is able to outperform the well-established Particle Particle Particle Mesh (P3M) for adaptively restrained simulations. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

DYNAMISM OF DOT SUBRETINAL DRUSENOID DEPOSITS IN AGE-RELATED MACULAR DEGENERATION DEMONSTRATED WITH ADAPTIVE OPTICS IMAGING.

PubMed

Zhang, Yuhua; Wang, Xiaolin; Godara, Pooja; Zhang, Tianjiao; Clark, Mark E; Witherspoon, C Douglas; Spaide, Richard F; Owsley, Cynthia; Curcio, Christine A

2018-01-01

To investigate the natural history of dot subretinal drusenoid deposits (SDD) in age-related macular degeneration, using high-resolution adaptive optics scanning laser ophthalmoscopy. Six eyes of four patients with intermediate age-related macular degeneration were studied at baseline and 1 year later. Individual dot SDD within the central 30° retina were examined with adaptive optics scanning laser ophthalmoscopy and optical coherence tomography. A total of 269 solitary SDD were identified at baseline. Over 12.25 ± 1.18 months, all 35 Stage 1 SDD progressed to advanced stages. Eighteen (60%) Stage 2 lesions progressed to Stage 3 and 12 (40%) remained at Stage 2. Of 204 Stage 3 SDD, 12 (6.4%) disappeared and the rest remained. Twelve new SDD were identified, including 6 (50%) at Stage 1, 2 (16.7%) at Stage 2, and 4 (33.3%) at Stage 3. The mean percentage of the retina affected by dot SDD, measured by the adaptive optics scanning laser ophthalmoscopy, increased in 5/6 eyes (from 2.31% to 5.08% in the most changed eye) and decreased slightly in 1/6 eye (from 10.67% to 10.54%). Dynamism, the absolute value of the areas affected by new and regressed lesions, ranged from 0.7% to 9.3%. Adaptive optics scanning laser ophthalmoscopy reveals that dot SDD, like drusen, are dynamic.

Chemical and Biological Dynamics Using Droplet-Based Microfluidics.

PubMed

Dressler, Oliver J; Casadevall I Solvas, Xavier; deMello, Andrew J

2017-06-12

Recent years have witnessed an increased use of droplet-based microfluidic techniques in a wide variety of chemical and biological assays. Nevertheless, obtaining dynamic data from these platforms has remained challenging, as this often requires reading the same droplets (possibly thousands of them) multiple times over a wide range of intervals (from milliseconds to hours). In this review, we introduce the elemental techniques for the formation and manipulation of microfluidic droplets, together with the most recent developments in these areas. We then discuss a wide range of analytical methods that have been successfully adapted for analyte detection in droplets. Finally, we highlight a diversity of studies where droplet-based microfluidic strategies have enabled the characterization of dynamic systems that would otherwise have remained unexplorable.

Adaptive Optics For Imaging Bright Objects Next To Dim Ones

NASA Technical Reports Server (NTRS)

Shao, Michael; Yu, Jeffrey W.; Malbet, Fabien

1996-01-01

Adaptive optics used in imaging optical systems, according to proposal, to enhance high-dynamic-range images (images of bright objects next to dim objects). Designed to alter wavefronts to correct for effects of scattering of light from small bumps on imaging optics. Original intended application of concept in advanced camera installed on Hubble Space Telescope for imaging of such phenomena as large planets near stars other than Sun. Also applicable to other high-quality telescopes and cameras.

Adaptive servo control for umbilical mating

NASA Technical Reports Server (NTRS)

Zia, Omar

1988-01-01

Robotic applications at Kennedy Space Center are unique and in many cases require the fime positioning of heavy loads in dynamic environments. Performing such operations is beyond the capabilities of an off-the-shelf industrial robot. Therefore Robotics Applications Development Laboratory at Kennedy Space Center has put together an integrated system that coordinates state of the art robotic system providing an excellent easy to use testbed for NASA sensor integration experiments. This paper reviews the ways of improving the dynamic response of the robot operating under force feedback with varying dynamic internal perturbations in order to provide continuous stable operations under variable load conditions. The goal is to improve the stability of the system with force feedback using the adaptive control feature of existing system over a wide range of random motions. The effect of load variations on the dynamics and the transfer function (order or values of the parameters) of the system has been investigated, more accurate models of the system have been determined and analyzed.

Competition and facilitation may lead to asymmetric range shift dynamics with climate change.

PubMed

Ettinger, Ailene; HilleRisLambers, Janneke

2017-09-01

Forecasts of widespread range shifts with climate change stem from assumptions that climate drives species' distributions. However, local adaptation and biotic interactions also influence range limits and thus may impact range shifts. Despite the potential importance of these factors, few studies have directly tested their effects on performance at range limits. We address how population-level variation and biotic interactions may affect range shifts by transplanting seeds and seedlings of western North American conifers of different origin populations into different competitive neighborhoods within and beyond their elevational ranges and monitoring their performance. We find evidence that competition with neighboring trees limits performance within current ranges, but that interactions between adults and juveniles switch from competitive to facilitative at upper range limits. Local adaptation had weaker effects on performance that did not predictably vary with range position or seed origin. Our findings suggest that competitive interactions may slow species turnover within forests at lower range limits, whereas facilitative interactions may accelerate the pace of tree expansions upward near timberline. © 2017 John Wiley & Sons Ltd.

The Center for Multiscale Plasma Dynamics, Final Report

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

Gombosi, Tamas I.

The University of Michigan participated in the joint UCLA/Maryland fusion science center focused on plasma physics problems for which the traditional separation of the dynamics into microscale and macroscale processes breaks down. These processes involve large scale flows and magnetic fields tightly coupled to the small scale, kinetic dynamics of turbulence, particle acceleration and energy cascade. The interaction between these vastly disparate scales controls the evolution of the system. The enormous range of temporal and spatial scales associated with these problems renders direct simulation intractable even in computations that use the largest existing parallel computers. Our efforts focused on twomore » main problems: the development of Hall MHD solvers on solution adaptive grids and the development of solution adaptive grids using generalized coordinates so that the proper geometry of inertial confinement can be taken into account and efficient refinement strategies can be obtained.« less

Anti-dynamic-crosstalk method for single photon LIDAR detection

NASA Astrophysics Data System (ADS)

Zhang, Fan; Liu, Qiang; Gong, Mali; Fu, Xing

2017-11-01

With increasing number of vehicles equipped with light detection and ranging (LIDAR), crosstalk is identified as a critical and urgent issue in the range detection for active collision avoidance. Chaotic pulse position modulation (CPPM) applied in the transmitting pulse train has been shown to prevent crosstalk as well as range ambiguity. However, static and unified strategy on discrimination threshold and the number of accumulated pulse is not valid against crosstalk with varying number of sources and varying intensity of each source. This paper presents an adaptive algorithm to distinguish the target echo from crosstalk with dynamic and unknown level of intensity in the context of intelligent vehicles. New strategy is given based on receiver operating characteristics (ROC) curves that consider the detection requirements of the probability of detection and false alarm for the scenario with varying crosstalk. In the adaptive algorithm, the detected results are compared by the new strategy with both the number of accumulated pulses and the threshold being raised step by step, so that the target echo can be exactly identified from crosstalk with the dynamic and unknown level of intensity. The validity of the algorithm has been verified through the experiments with a single photon detector and the time correlated single photo counting (TCSPC) technique, demonstrating a marked drop in required shots for identifying the target compared with static and unified strategy

Where you stand depends on where you sit: Qualitative inquiry into notions of fire adaptation

USGS Publications Warehouse

Brenkert-Smith, Hannah; Meldrum, James; Champ, Patricia A.; Barth, Christopher

2017-01-01

Wildfire and the threat it poses to society represents an example of the complex, dynamic relationship between social and ecological systems. Increasingly, wildfire adaptation is posited as a pathway to shift the approach to fire from a suppression paradigm that seeks to control fire to a paradigm that focuses on “living with” and “adapting to” wildfire. In this study, we seek insights into what it means to adapt to wildfire from a range of stakeholders whose efforts contribute to the management of wildfire. Study participants provided insights into the meaning, relevance, and use of the concept of fire adaptation as it relates to their wildfire-related activities. A key finding of this investigation suggests that social scale is of key importance in the conceptualization and understanding of adaptation for participating stakeholders. Indeed, where you stand in terms of understandings of fire adaptation depends in large part on where you sit.

Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach.

PubMed

Kim, Woojae; Pitt, Mark A; Lu, Zhong-Lin; Myung, Jay I

2017-11-01

Experimentation is at the heart of scientific inquiry. In the behavioral and neural sciences, where only a limited number of observations can often be made, it is ideal to design an experiment that leads to the rapid accumulation of information about the phenomenon under study. Adaptive experimentation has the potential to accelerate scientific progress by maximizing inferential gain in such research settings. To date, most adaptive experiments have relied on myopic, one-step-ahead strategies in which the stimulus on each trial is selected to maximize inference on the next trial only. A lingering question in the field has been how much additional benefit would be gained by optimizing beyond the next trial. A range of technical challenges has prevented this important question from being addressed adequately. This study applies dynamic programming (DP), a technique applicable for such full-horizon, "global" optimization, to model-based perceptual threshold estimation, a domain that has been a major beneficiary of adaptive methods. The results provide insight into conditions that will benefit from optimizing beyond the next trial. Implications for the use of adaptive methods in cognitive science are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Neural controller for adaptive movements with unforeseen payloads.

PubMed

Kuperstein, M; Wang, J

1990-01-01

A theory and computer simulation of a neural controller that learns to move and position a link carrying an unforeseen payload accurately are presented. The neural controller learns adaptive dynamic control from its own experience. It does not use information about link mass, link length, or direction of gravity, and it uses only indirect uncalibrated information about payload and actuator limits. Its average positioning accuracy across a large range of payloads after learning is 3% of the positioning range. This neural controller can be used as a basis for coordinating any number of sensory inputs with limbs of any number of joints. The feedforward nature of control allows parallel implementation in real time across multiple joints.

Task path planning, scheduling and learning for free-ranging robot systems

NASA Technical Reports Server (NTRS)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Neural Computations in a Dynamical System with Multiple Time Scales.

PubMed

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Adaptive relative pose control of spacecraft with model couplings and uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2018-02-01

The spacecraft pose tracking control problem for an uncertain pursuer approaching to a space target is researched in this paper. After modeling the nonlinearly coupled dynamics for relative translational and rotational motions between two spacecraft, position tracking and attitude synchronization controllers are developed independently by using a robust adaptive control approach. The unknown kinematic couplings, parametric uncertainties, and bounded external disturbances are handled with adaptive updating laws. It is proved via Lyapunov method that the pose tracking errors converge to zero asymptotically. Spacecraft close-range rendezvous and proximity operations are introduced as an example to validate the effectiveness of the proposed control approach.

A Novel Concept for a Deformable Membrane Mirror for Correction of Large Amplitude Aberrations

NASA Technical Reports Server (NTRS)

Moore, Jim; Patrick, Brian

2006-01-01

Very large, light weight mirrors are being developed for applications in space. Due to launch mass and volume restrictions these mirrors will need to be much more flexible than traditional optics. The use of primary mirrors with these characteristics will lead to requirements for adaptive optics capable of correcting wave front errors with large amplitude relatively low spatial frequency aberrations. The use of low modulus membrane mirrors actuated with electrostatic attraction forces is a potential solution for this application. Several different electrostatic membrane mirrors are now available commercially. However, as the dynamic range requirement of the adaptive mirror is increased the separation distance between the membrane and the electrodes must increase to accommodate the required face sheet deformations. The actuation force applied to the mirror decreases inversely proportional to the square of the separation distance; thus for large dynamic ranges the voltage requirement can rapidly increase into the high voltage regime. Experimentation with mirrors operating in the KV range has shown that at the higher voltages a serious problem with electrostatic field cross coupling between actuators can occur. Voltage changes on individual actuators affect the voltage of other actuators making the system very difficult to control. A novel solution has been proposed that combines high voltage electrodes with mechanical actuation to overcome this problem. In this design an array of electrodes are mounted to a backing structure via light weight large dynamic range flextensional actuators. With this design the control input becomes the separation distance between the electrode and the mirror. The voltage on each of the actuators is set to a uniform relatively high voltage, thus the problem of cross talk between actuators is avoided and the favorable distributed load characteristic of electrostatic actuation is retained. Initial testing and modeling of this concept demonstrates that this is an attractive concept for increasing the dynamic range capability of electrostatic deformable mirrors.

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

PubMed

Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

Wavelet and adaptive methods for time dependent problems and applications in aerosol dynamics

NASA Astrophysics Data System (ADS)

Guo, Qiang

Time dependent partial differential equations (PDEs) are widely used as mathematical models of environmental problems. Aerosols are now clearly identified as an important factor in many environmental aspects of climate and radiative forcing processes, as well as in the health effects of air quality. The mathematical models for the aerosol dynamics with respect to size distribution are nonlinear partial differential and integral equations, which describe processes of condensation, coagulation and deposition. Simulating the general aerosol dynamic equations on time, particle size and space exhibits serious difficulties because the size dimension ranges from a few nanometer to several micrometer while the spatial dimension is usually described with kilometers. Therefore, it is an important and challenging task to develop efficient techniques for solving time dependent dynamic equations. In this thesis, we develop and analyze efficient wavelet and adaptive methods for the time dependent dynamic equations on particle size and further apply them to the spatial aerosol dynamic systems. Wavelet Galerkin method is proposed to solve the aerosol dynamic equations on time and particle size due to the fact that aerosol distribution changes strongly along size direction and the wavelet technique can solve it very efficiently. Daubechies' wavelets are considered in the study due to the fact that they possess useful properties like orthogonality, compact support, exact representation of polynomials to a certain degree. Another problem encountered in the solution of the aerosol dynamic equations results from the hyperbolic form due to the condensation growth term. We propose a new characteristic-based fully adaptive multiresolution numerical scheme for solving the aerosol dynamic equation, which combines the attractive advantages of adaptive multiresolution technique and the characteristics method. On the aspect of theoretical analysis, the global existence and uniqueness of solutions of continuous time wavelet numerical methods for the nonlinear aerosol dynamics are proved by using Schauder's fixed point theorem and the variational technique. Optimal error estimates are derived for both continuous and discrete time wavelet Galerkin schemes. We further derive reliable and efficient a posteriori error estimate which is based on stable multiresolution wavelet bases and an adaptive space-time algorithm for efficient solution of linear parabolic differential equations. The adaptive space refinement strategies based on the locality of corresponding multiresolution processes are proved to converge. At last, we develop efficient numerical methods by combining the wavelet methods proposed in previous parts and the splitting technique to solve the spatial aerosol dynamic equations. Wavelet methods along the particle size direction and the upstream finite difference method along the spatial direction are alternately used in each time interval. Numerical experiments are taken to show the effectiveness of our developed methods.

A conceptual framework for addressing complexity and unfolding transition dynamics when developing sustainable adaptation strategies in urban water management.

PubMed

Fratini, C F; Elle, M; Jensen, M B; Mikkelsen, P S

2012-01-01

To achieve a successful and sustainable adaptation to climate change we need to transform the way we think about change. Much water management research has focused on technical innovation with a range of new solutions developed to achieve a 'more sustainable and integrated urban water management cycle'. But Danish municipalities and utility companies are struggling to bring such solutions into practice. 'Green infrastructure', for example, requires the consideration of a larger range of aspects related to the urban context than the traditional urban water system optimization. There is the need for standardized methods and guidelines to organize transdisciplinary processes where different types of knowledge and perspectives are taken into account. On the basis of the macro-meso-micro pattern inspired by complexity science and transition theory, we developed a conceptual framework to organize processes addressing the complexity characterizing urban water management in the context of climate change. In this paper the framework is used to organize a research process aiming at understanding and unfolding urban dynamics for sustainable transition. The final goal is to enable local authorities and utilities to create the basis for managing and catalysing the technical and organizational innovation necessary for a sustainable transition towards climate change adaptation in urban areas.

High-dynamic range imaging techniques based on both color-separation algorithms used in conventional graphic arts and the human visual perception modeling

NASA Astrophysics Data System (ADS)

Lo, Mei-Chun; Hsieh, Tsung-Hsien; Perng, Ruey-Kuen; Chen, Jiong-Qiao

2010-01-01

The aim of this research is to derive illuminant-independent type of HDR imaging modules which can optimally multispectrally reconstruct of every color concerned in high-dynamic-range of original images for preferable cross-media color reproduction applications. Each module, based on either of broadband and multispectral approach, would be incorporated models of perceptual HDR tone-mapping, device characterization. In this study, an xvYCC format of HDR digital camera was used to capture HDR scene images for test. A tone-mapping module was derived based on a multiscale representation of the human visual system and used equations similar to a photoreceptor adaptation equation, proposed by Michaelis-Menten. Additionally, an adaptive bilateral type of gamut mapping algorithm, using approach of a multiple conversing-points (previously derived), was incorporated with or without adaptive Un-sharp Masking (USM) to carry out the optimization of HDR image rendering. An LCD with standard color space of Adobe RGB (D65) was used as a soft-proofing platform to display/represent HDR original RGB images, and also evaluate both renditionquality and prediction-performance of modules derived. Also, another LCD with standard color space of sRGB was used to test gamut-mapping algorithms, used to be integrated with tone-mapping module derived.

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

PubMed

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

Dynamic social community detection and its applications.

PubMed

Nguyen, Nam P; Dinh, Thang N; Shen, Yilin; Thai, My T

2014-01-01

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods.

Dynamic Social Community Detection and Its Applications

PubMed Central

Nguyen, Nam P.; Dinh, Thang N.; Shen, Yilin; Thai, My T.

2014-01-01

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods. PMID:24722164

Handling Qualities Evaluations of Low Complexity Model Reference Adaptive Controllers for Reduced Pitch and Roll Damping Scenarios

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Johnson, Marcus; Nguyen, Nhan

2011-01-01

National Aeronautics and Space Administration (NASA) researchers have conducted a series of flight experiments designed to study the effects of varying levels of adaptive controller complexity on the performance and handling qualities of an aircraft under various simulated failure or damage conditions. A baseline, nonlinear dynamic inversion controller was augmented with three variations of a model reference adaptive control design. The simplest design consisted of a single adaptive parameter in each of the pitch and roll axes computed using a basic gradient-based update law. A second design was built upon the first by increasing the complexity of the update law. The third and most complex design added an additional adaptive parameter to each axis. Flight tests were conducted using NASA s Full-scale Advanced Systems Testbed, a highly modified F-18 aircraft that contains a research flight control system capable of housing advanced flight controls experiments. Each controller was evaluated against a suite of simulated failures and damage ranging from destabilization of the pitch and roll axes to significant coupling between the axes. Two pilots evaluated the three adaptive controllers as well as the non-adaptive baseline controller in a variety of dynamic maneuvers and precision flying tasks designed to uncover potential deficiencies in the handling qualities of the aircraft, and adverse interactions between the pilot and the adaptive controllers. The work was completed as part of the Integrated Resilient Aircraft Control Project under NASA s Aviation Safety Program.

35-GHz radar sensor for automotive collision avoidance

NASA Astrophysics Data System (ADS)

Zhang, Jun

1999-07-01

This paper describes the development of a radar sensor system used for automotive collision avoidance. Because the heavy truck may have great larger radar cross section than a motorcyclist has, the radar receiver may have a large dynamic range. And multi-targets at different speed may confuse the echo spectrum causing the ambiguity between range and speed of target. To get more information about target and background and to adapt to the large dynamic range and multi-targets, a frequency modulated and pseudo- random binary sequences phase modulated continuous wave radar system is described. The analysis of this double- modulation system is given. A high-speed signal processing and data processing component are used to process and combine the data and information from echo at different direction and at every moment.

Understanding global health governance as a complex adaptive system.

PubMed

Hill, Peter S

2011-01-01

The transition from international to global health reflects the rapid growth in the numbers and nature of stakeholders in health, as well as the constant change embodied in the process of globalisation itself. This paper argues that global health governance shares the characteristics of complex adaptive systems, with its multiple and diverse players, and their polyvalent and constantly evolving relationships, and rich and dynamic interactions. The sheer quantum of initiatives, the multiple networks through which stakeholders (re)configure their influence, the range of contexts in which development for health is played out - all compound the complexity of this system. This paper maps out the characteristics of complex adaptive systems as they apply to global health governance, linking them to developments in the past two decades, and the multiple responses to these changes. Examining global health governance through the frame of complexity theory offers insight into the current dynamics of governance, and while providing a framework for making meaning of the whole, opens up ways of accessing this complexity through local points of engagement.

Method Engineering: A Service-Oriented Approach

NASA Astrophysics Data System (ADS)

Cauvet, Corine

In the past, a large variety of methods have been published ranging from very generic frameworks to methods for specific information systems. Method Engineering has emerged as a research discipline for designing, constructing and adapting methods for Information Systems development. Several approaches have been proposed as paradigms in method engineering. The meta modeling approach provides means for building methods by instantiation, the component-based approach aims at supporting the development of methods by using modularization constructs such as method fragments, method chunks and method components. This chapter presents an approach (SO2M) for method engineering based on the service paradigm. We consider services as autonomous computational entities that are self-describing, self-configuring and self-adapting. They can be described, published, discovered and dynamically composed for processing a consumer's demand (a developer's requirement). The method service concept is proposed to capture a development process fragment for achieving a goal. Goal orientation in service specification and the principle of service dynamic composition support method construction and method adaptation to different development contexts.

Adaptive learning and control for MIMO system based on adaptive dynamic programming.

PubMed

Fu, Jian; He, Haibo; Zhou, Xinmin

2011-07-01

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past decades, several generations of ADP design have been proposed in the literature, which have demonstrated many successful applications in various benchmarks and industrial applications. While many of the existing researches focus on multiple-inputs-single-output system with steepest descent search, in this paper we investigate a generalized multiple-input-multiple-output (GMIMO) ADP design for online learning and control, which is more applicable to a wide range of practical real-world applications. Furthermore, an improved weight-updating algorithm based on recursive Levenberg-Marquardt methods is presented and embodied in the GMIMO approach to improve its performance. Finally, we test the performance of this approach based on a practical complex system, namely, the learning and control of the tension and height of the looper system in a hot strip mill. Experimental results demonstrate that the proposed approach can achieve effective and robust performance.

Generalization in Adaptation to Stable and Unstable Dynamics

PubMed Central

Kadiallah, Abdelhamid; Franklin, David W.; Burdet, Etienne

2012-01-01

Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. PMID:23056191

Adaptive-network models of collective dynamics

NASA Astrophysics Data System (ADS)

Zschaler, G.

2012-09-01

Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge. Moreover, we show what minimal microscopic interaction rules determine whether the transition to collective motion is continuous or discontinuous. Second, we consider a model of opinion formation in groups of individuals, where we focus on the effect of directed links in adaptive networks. Extending the adaptive voter model to directed networks, we find a novel fragmentation mechanism, by which the network breaks into distinct components of opposing agents. This fragmentation is mediated by the formation of self-stabilizing structures in the network, which do not occur in the undirected case. We find that they are related to degree correlations stemming from the interplay of link directionality and adaptive topological change. Third, we discuss a model for the evolution of cooperation among self-interested agents, in which the adaptive nature of their interaction network gives rise to a novel dynamical mechanism promoting cooperation. We show that even full cooperation can be achieved asymptotically if the networks' adaptive response to the agents' dynamics is sufficiently fast.

Method and algorithm of automatic estimation of road surface type for variable damping control

NASA Astrophysics Data System (ADS)

Dąbrowski, K.; Ślaski, G.

2016-09-01

In this paper authors presented an idea of road surface estimation (recognition) on a base of suspension dynamic response signals statistical analysis. For preliminary analysis cumulated distribution function (CDF) was used, and some conclusion that various roads have responses values in a different ranges of limits for the same percentage of samples or for the same limits different percentages of samples are located within the range between limit values. That was the base for developed and presented algorithm which was tested using suspension response signals recorded during road test riding over various surfaces. Proposed algorithm can be essential part of adaptive damping control algorithm for a vehicle suspension or adaptive control strategy for suspension damping control.

Ultra-high contrast retinal display system for single photoreceptor psychophysics

PubMed Central

Domdei, Niklas; Domdei, Lennart; Reiniger, Jenny L.; Linden, Michael; Holz, Frank G.; Roorda, Austin; Harmening, Wolf M.

2017-01-01

Due to the enormous dynamic range of human photoreceptors in response to light, studying their visual function in the intact retina challenges the stimulation hardware, specifically with regard to the displayable luminance contrast. The adaptive optics scanning laser ophthalmoscope (AOSLO) is an optical platform that focuses light to extremely small retinal extents, approaching the size of single photoreceptor cells. However, the current light modulation techniques produce spurious visible backgrounds which fundamentally limit experimental options. To remove unwanted background light and to improve contrast for high dynamic range visual stimulation in an AOSLO, we cascaded two commercial fiber-coupled acousto-optic modulators (AOMs) and measured their combined optical contrast. By compensating for zero-point differences in the individual AOMs, we demonstrate a multiplicative extinction ratio in the cascade that was in accordance with the extinction ratios of both single AOMs. When latency differences in the AOM response functions were individually corrected, single switch events as short as 50 ns with radiant power contrasts up to 1:1010 were achieved. This is the highest visual contrast reported for any display system so far. We show psychophysically that this contrast ratio is sufficient to stimulate single foveal photoreceptor cells with small and bright enough visible targets that do not contain a detectable background. Background-free stimulation will enable photoreceptor testing with custom adaptation lights. Furthermore, a larger dynamic range in displayable light levels can drive photoreceptor responses in cones as well as in rods. PMID:29359094

Improvements on Fresnel arrays for high contrast imaging

NASA Astrophysics Data System (ADS)

Wilhem, Roux; Laurent, Koechlin

2018-03-01

The Fresnel Diffractive Array Imager (FDAI) is based on a new optical concept for space telescopes, developed at Institut de Recherche en Astrophysique et Planétologie (IRAP), Toulouse, France. For the visible and near-infrared it has already proven its performances in resolution and dynamic range. We propose it now for astrophysical applications in the ultraviolet with apertures from 6 to 30 meters, aimed at imaging in UV faint astrophysical sources close to bright ones, as well as other applications requiring high dynamic range. Of course the project needs first a probatory mission at small aperture to validate the concept in space. In collaboration with institutes in Spain and Russia, we will propose to board a small prototype of Fresnel imager on the International Space Station (ISS), with a program combining technical tests and astrophysical targets. The spectral domain should contain the Lyman- α line ( λ = 121 nm). As part of its preparation, we improve the Fresnel array design for a better Point Spread Function in UV, presently on a small laboratory prototype working at 260 nm. Moreover, we plan to validate a new optical design and chromatic correction adapted to UV. In this article we present the results of numerical propagations showing the improvement in dynamic range obtained by combining and adapting three methods : central obturation, optimization of the bars mesh holding the Fresnel rings, and orthogonal apodization. We briefly present the proposed astrophysical program of a probatory mission with such UV optics.

High Dynamic Range Spectral Imaging Pipeline For Multispectral Filter Array Cameras.

PubMed

Lapray, Pierre-Jean; Thomas, Jean-Baptiste; Gouton, Pierre

2017-06-03

Spectral filter arrays imaging exhibits a strong similarity with color filter arrays. This permits us to embed this technology in practical vision systems with little adaptation of the existing solutions. In this communication, we define an imaging pipeline that permits high dynamic range (HDR)-spectral imaging, which is extended from color filter arrays. We propose an implementation of this pipeline on a prototype sensor and evaluate the quality of our implementation results on real data with objective metrics and visual examples. We demonstrate that we reduce noise, and, in particular we solve the problem of noise generated by the lack of energy balance. Data are provided to the community in an image database for further research.

Structural flexibility and protein adaptation to temperature: Molecular dynamics analysis of malate dehydrogenases of marine molluscs.

PubMed

Dong, Yun-Wei; Liao, Ming-Ling; Meng, Xian-Liang; Somero, George N

2018-02-06

Orthologous proteins of species adapted to different temperatures exhibit differences in stability and function that are interpreted to reflect adaptive variation in structural "flexibility." However, quantifying flexibility and comparing flexibility across proteins has remained a challenge. To address this issue, we examined temperature effects on cytosolic malate dehydrogenase (cMDH) orthologs from differently thermally adapted congeners of five genera of marine molluscs whose field body temperatures span a range of ∼60 °C. We describe consistent patterns of convergent evolution in adaptation of function [temperature effects on K M of cofactor (NADH)] and structural stability (rate of heat denaturation of activity). To determine how these differences depend on flexibilities of overall structure and of regions known to be important in binding and catalysis, we performed molecular dynamics simulation (MDS) analyses. MDS analyses revealed a significant negative correlation between adaptation temperature and heat-induced increase of backbone atom movements [root mean square deviation (rmsd) of main-chain atoms]. Root mean square fluctuations (RMSFs) of movement by individual amino acid residues varied across the sequence in a qualitatively similar pattern among orthologs. Regions of sequence involved in ligand binding and catalysis-termed mobile regions 1 and 2 (MR1 and MR2), respectively-showed the largest values for RMSF. Heat-induced changes in RMSF values across the sequence and, importantly, in MR1 and MR2 were greatest in cold-adapted species. MDS methods are shown to provide powerful tools for examining adaptation of enzymes by providing a quantitative index of protein flexibility and identifying sequence regions where adaptive change in flexibility occurs.

Theoretical Perspectives on the Statics and Dynamics of Species’ Borders in Patchy Environments

PubMed Central

Holt, Robert D.; Barfield, Michael

2016-01-01

Understanding range limits is a fundamental problem in ecology and evolutionary biology. In 1963, Mayr argued that “contaminating” gene flow from central populations constrained adaptation in marginal populations, preventing range expansion, while in 1984, Bradshaw suggested that absence of genetic variation prevented species from occurring everywhere. Understanding stability of range boundaries requires unraveling the interplay of demography, gene flow, and evolution of populations in concrete landscape settings. We walk through a set of interrelated spatial scenarios that illustrate interesting complexities of this interplay. To motivate our individual-based model results, we consider a hypothetical zooplankter in a landscape of discrete water bodies coupled by dispersal. We examine how patterns of dispersal influence adaptation in sink habitats where conditions are outside the species’ niche. The likelihood of observing niche evolution (and thus range expansion) over any given timescale depends on (1) the degree of initial maladaptation; (2) pattern (pulsed vs. continuous, uni- vs. bidirectional), timing (juvenile vs. adult), and rate of dispersal (and hence population size); (3) mutation rate; (4) sexuality; and (5) the degree of heterogeneity in the occupied range. We also show how the genetic architecture of polygenic adaptation is influenced by the interplay of selection and dispersal in heterogeneous landscapes. PMID:21956092

High-resolution adaptive optics scanning laser ophthalmoscope with multiple deformable mirrors

DOEpatents

Chen, Diana C.; Olivier, Scot S.; Jones; Steven M.

2010-02-23

An adaptive optics scanning laser ophthalmoscopes is introduced to produce non-invasive views of the human retina. The use of dual deformable mirrors improved the dynamic range for correction of the wavefront aberrations compared with the use of the MEMS mirror alone, and improved the quality of the wavefront correction compared with the use of the bimorph mirror alone. The large-stroke bimorph deformable mirror improved the capability for axial sectioning with the confocal imaging system by providing an easier way to move the focus axially through different layers of the retina.

Adaptive finite-volume WENO schemes on dynamically redistributed grids for compressible Euler equations

NASA Astrophysics Data System (ADS)

Pathak, Harshavardhana S.; Shukla, Ratnesh K.

2016-08-01

A high-order adaptive finite-volume method is presented for simulating inviscid compressible flows on time-dependent redistributed grids. The method achieves dynamic adaptation through a combination of time-dependent mesh node clustering in regions characterized by strong solution gradients and an optimal selection of the order of accuracy and the associated reconstruction stencil in a conservative finite-volume framework. This combined approach maximizes spatial resolution in discontinuous regions that require low-order approximations for oscillation-free shock capturing. Over smooth regions, high-order discretization through finite-volume WENO schemes minimizes numerical dissipation and provides excellent resolution of intricate flow features. The method including the moving mesh equations and the compressible flow solver is formulated entirely on a transformed time-independent computational domain discretized using a simple uniform Cartesian mesh. Approximations for the metric terms that enforce discrete geometric conservation law while preserving the fourth-order accuracy of the two-point Gaussian quadrature rule are developed. Spurious Cartesian grid induced shock instabilities such as carbuncles that feature in a local one-dimensional contact capturing treatment along the cell face normals are effectively eliminated through upwind flux calculation using a rotated Hartex-Lax-van Leer contact resolving (HLLC) approximate Riemann solver for the Euler equations in generalized coordinates. Numerical experiments with the fifth and ninth-order WENO reconstructions at the two-point Gaussian quadrature nodes, over a range of challenging test cases, indicate that the redistributed mesh effectively adapts to the dynamic flow gradients thereby improving the solution accuracy substantially even when the initial starting mesh is non-adaptive. The high adaptivity combined with the fifth and especially the ninth-order WENO reconstruction allows remarkably sharp capture of discontinuous propagating shocks with simultaneous resolution of smooth yet complex small scale unsteady flow features to an exceptional detail.

Prediction of pilot-aircraft stability boundaries and performance contours

NASA Technical Reports Server (NTRS)

Stengel, R. F.; Broussard, J. R.

1977-01-01

Control-theoretic pilot models can provide important new insights regarding the stability and performance characteristics of the pilot-aircraft system. Optimal-control pilot models can be formed for a wide range of flight conditions, suggesting that the human pilot can maintain stability if he adapts his control strategy to the aircraft's changing dynamics. Of particular concern is the effect of sub-optimal pilot adaptation as an aircraft transitions from low to high angle-of-attack during rapid maneuvering, as the changes in aircraft stability and control response can be extreme. This paper examines the effects of optimal and sub-optimal effort during a typical 'high-g' maneuver, and it introduces the concept of minimum-control effort (MCE) adaptation. Limited experimental results tend to support the MCE adaptation concept.

Dynamic blocked transfer stiffness method of characterizing the magnetic field and frequency dependent dynamic viscoelastic properties of MRE

NASA Astrophysics Data System (ADS)

Poojary, Umanath R.; Hegde, Sriharsha; Gangadharan, K. V.

2016-11-01

Magneto rheological elastomer (MRE) is a potential resilient element for the semi active vibration isolator. MRE based isolators adapt to different frequency of vibrations arising from the source to isolate the structure over wider frequency range. The performance of MRE isolator depends on the magnetic field and frequency dependent characteristics of MRE. Present study is focused on experimentally evaluating the dynamic stiffness and loss factor of MRE through dynamic blocked transfer stiffness method. The dynamic stiffness variations of MRE exhibit strong magnetic field and mild frequency dependency. Enhancements in dynamic stiffness saturate with the increase in magnetic field and the frequency. The inconsistent variations of loss factor with the magnetic field substantiate the inability of MRE to have independent control over its damping characteristics.

Resilience of Adapting Networks: Results from a Stylized Infrastructure Model.

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

Beyeler, Walter E.; Vugrin, Eric D.; Forden, Geoffrey Ethan

2015-01-01

Adaptation is believed to be a source of resilience in systems. It has been difficult to measure the contribution of adaptation to resilience, unlike other resilience mechanisms such as restoration and recovery. One difficulty comes from treating adaptation as a deus ex machina that is interjected after a disruption. This provides no basis for bounding possible adaptive responses. We can bracket the possible effects of adaptation when we recognize that it occurs continuously, and is in part responsible for the current system’s properties. In this way the dynamics of the system’s pre-disruption structure provides information about post-disruption adaptive reaction. Seenmore » as an ongoing process, adaptation has been argued to produce “robust-yet-fragile” systems. Such systems perform well under historical stresses but become committed to specific features of those stresses in a way that makes them vulnerable to system-level collapse when those features change. In effect adaptation lessens the cost of disruptions within a certain historical range, at the expense of increased cost from disruptions outside that range. Historical adaptive responses leave a signature in the structure of the system. Studies of ecological networks have suggested structural metrics that pick out systemic resilience in the underlying ecosystems. If these metrics are generally reliable indicators of resilience they provide another strategy for gaging adaptive resilience. To progress in understanding how the process of adaptation and the property of resilience interrelate in infrastructure systems, we pose some specific questions: Does adaptation confer resilience?; Does it confer resilience to novel shocks as well, or does it tune the system to fragility?; Can structural features predict resilience to novel shocks?; Are there policies or constraints on the adaptive process that improve resilience?.« less

FACTORS CONTROLLING ZOSTERA MARINA L. GROWTH IN THE EASTERN AND WESTERN PACIFIC OCEAN: COMPARISONS BETWEEN SOUTH KOREA AND OREGON, USA

EPA Science Inventory

Zostera marina distribution is circum-global and tolerates a wide range of environmental conditions. Consequently, it is likely that populations have adapted to local environmental conditions of light, temperature and nutrient supply. We compared Z. marina growth dynamics over a ...

Adaptation and resiliency in Swedish families.

PubMed

Kiehl, Ermalynn M; Carson, David K; Dykes, Anna-Karin

2007-09-01

A longitudinal research project began in 1993 of Norwegian, Swedish and American mothers' perception of her family's dynamics and adaptation during childbearing and childrearing. Results indicated that Swedish mothers adapted better than other mothers. In 2003, a mixed design study was conducted with original Swedish mothers that aimed to describe the experience of motherhood, the meaning mothers attached to events in their lives that made adaptation necessary, and ways in which they achieved adaptation. Fourteen mothers completed quantitative instruments and 13 of those mothers were interviewed. Audiotaped interviews were transcribed and analysed for themes using a protocol based on a model of family resiliency. Quantitative findings revealed statistically significant findings in areas of children, mother's work outside the home and families in which a major illness had occurred. Qualitative findings revealed that protective factors far outweighed vulnerability and risk factors. Mothers' satisfaction with life manifested itself in love of home, contentment with employment, fulfillment from an active and healthy life and support from a society that provides a wide range of social benefits for the family. Vulnerability occurred primarily when mothers were tired, lacked personal time or someone in the family was experiencing a serious illness. Results of this study enhance the scholarly scientific knowledge about the uniqueness of Swedish mothers, and increased understanding of family dynamics and adaptation. Many of the findings relate in some way to overall social benefits and supports available for families.

Deficits in context-dependent adaptive coding of reward in schizophrenia

PubMed Central

Kirschner, Matthias; Hager, Oliver M; Bischof, Martin; Hartmann-Riemer, Matthias N; Kluge, Agne; Seifritz, Erich; Tobler, Philippe N; Kaiser, Stefan

2016-01-01

Theoretical principles of information processing and empirical findings suggest that to efficiently represent all possible rewards in the natural environment, reward-sensitive neurons have to adapt their coding range dynamically to the current reward context. Adaptation ensures that the reward system is most sensitive for the most likely rewards, enabling the system to efficiently represent a potentially infinite range of reward information. A deficit in neural adaptation would prevent precise representation of rewards and could have detrimental effects for an organism’s ability to optimally engage with its environment. In schizophrenia, reward processing is known to be impaired and has been linked to different symptom dimensions. However, despite the fundamental significance of coding reward adaptively, no study has elucidated whether adaptive reward processing is impaired in schizophrenia. We therefore studied patients with schizophrenia (n=27) and healthy controls (n=25), using functional magnetic resonance imaging in combination with a variant of the monetary incentive delay task. Compared with healthy controls, patients with schizophrenia showed less efficient neural adaptation to the current reward context, which leads to imprecise neural representation of reward. Importantly, the deficit correlated with total symptom severity. Our results suggest that some of the deficits in reward processing in schizophrenia might be due to inefficient neural adaptation to the current reward context. Furthermore, because adaptive coding is a ubiquitous feature of the brain, we believe that our findings provide an avenue in defining a general impairment in neural information processing underlying this debilitating disorder. PMID:27430009

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Dynamic hydraulic fluid stimulation regulated intramedullary pressure.

PubMed

Hu, Minyi; Serra-Hsu, Frederick; Bethel, Neville; Lin, Liangjun; Ferreri, Suzanne; Cheng, Jiqi; Qin, Yi-Xian

2013-11-01

Physical signals within the bone, i.e. generated from mechanical loading, have the potential to initiate skeletal adaptation. Strong evidence has pointed to bone fluid flow (BFF) as a media between an external load and the bone cells, in which altered velocity and pressure can ultimately initiate the mechanotransduction and the remodeling process within the bone. Load-induced BFF can be altered by factors such as intramedullary pressure (ImP) and/or bone matrix strain, mediating bone adaptation. Previous studies have shown that BFF induced by ImP alone, with minimum bone strain, can initiate bone remodeling. However, identifying induced ImP dynamics and bone strain factor in vivo using a non-invasive method still remains challenging. To apply ImP as a means for alteration of BFF, it was hypothesized that non-invasive dynamic hydraulic stimulation (DHS) can induce local ImP with minimal bone strain to potentially elicit osteogenic adaptive responses via bone-muscle coupling. The goal of this study was to evaluate the immediate effects on local and distant ImP and strain in response to a range of loading frequencies using DHS. Simultaneous femoral and tibial ImP and bone strain values were measured in three 15-month-old female Sprague Dawley rats during DHS loading on the tibia with frequencies of 1Hz to 10Hz. DHS showed noticeable effects on ImP induction in the stimulated tibia in a nonlinear fashion in response to DHS over the range of loading frequencies, where they peaked at 2Hz. DHS at various loading frequencies generated minimal bone strain in the tibiae. Maximal bone strain measured at all loading frequencies was less than 8με. No detectable induction of ImP or bone strain was observed in the femur. This study suggested that oscillatory DHS may regulate the local fluid dynamics with minimal mechanical strain in the bone, which serves critically in bone adaptation. These results clearly implied DHS's potential as an effective, non-invasive intervention for osteopenia and osteoporosis treatments. © 2013. Published by Elsevier Inc. All rights reserved.

Desiccation and Mortality Dynamics in Seedlings of Different European Beech (Fagus sylvatica L.) Populations under Extreme Drought Conditions.

PubMed

Bolte, Andreas; Czajkowski, Tomasz; Cocozza, Claudia; Tognetti, Roberto; de Miguel, Marina; Pšidová, Eva; Ditmarová, Ĺubica; Dinca, Lucian; Delzon, Sylvain; Cochard, Hervè; Ræbild, Anders; de Luis, Martin; Cvjetkovic, Branislav; Heiri, Caroline; Müller, Jürgen

2016-01-01

European beech (Fagus sylvatica L., hereafter beech), one of the major native tree species in Europe, is known to be drought sensitive. Thus, the identification of critical thresholds of drought impact intensity and duration are of high interest for assessing the adaptive potential of European beech to climate change in its native range. In a common garden experiment with one-year-old seedlings originating from central and marginal origins in six European countries (Denmark, Germany, France, Romania, Bosnia-Herzegovina, and Spain), we applied extreme drought stress and observed desiccation and mortality processes among the different populations and related them to plant water status (predawn water potential, ΨPD) and soil hydraulic traits. For the lethal drought assessment, we used a critical threshold of soil water availability that is reached when 50% mortality in seedling populations occurs (LD50SWA). We found significant population differences in LD50SWA (10.5-17.8%), and mortality dynamics that suggest a genetic difference in drought resistance between populations. The LD50SWA values correlate significantly with the mean growing season precipitation at population origins, but not with the geographic margins of beech range. Thus, beech range marginality may be more due to climatic conditions than to geographic range. The outcome of this study suggests the genetic variation has a major influence on the varying adaptive potential of the investigated populations.

Integrating Climate Change Adaptation into Public Health Practice: Using Adaptive Management to Increase Adaptive Capacity and Build Resilience

PubMed Central

McDowell, Julia Z.; Luber, George

2011-01-01

Background: Climate change is expected to have a range of health impacts, some of which are already apparent. Public health adaptation is imperative, but there has been little discussion of how to increase adaptive capacity and resilience in public health systems. Objectives: We explored possible explanations for the lack of work on adaptive capacity, outline climate–health challenges that may lie outside public health’s coping range, and consider changes in practice that could increase public health’s adaptive capacity. Methods: We conducted a substantive, interdisciplinary literature review focused on climate change adaptation in public health, social learning, and management of socioeconomic systems exhibiting dynamic complexity. Discussion: There are two competing views of how public health should engage climate change adaptation. Perspectives differ on whether climate change will primarily amplify existing hazards, requiring enhancement of existing public health functions, or present categorically distinct threats requiring innovative management strategies. In some contexts, distinctly climate-sensitive health threats may overwhelm public health’s adaptive capacity. Addressing these threats will require increased emphasis on institutional learning, innovative management strategies, and new and improved tools. Adaptive management, an iterative framework that embraces uncertainty, uses modeling, and integrates learning, may be a useful approach. We illustrate its application to extreme heat in an urban setting. Conclusions: Increasing public health capacity will be necessary for certain climate–health threats. Focusing efforts to increase adaptive capacity in specific areas, promoting institutional learning, embracing adaptive management, and developing tools to facilitate these processes are important priorities and can improve the resilience of local public health systems to climate change. PMID:21997387

Adaptive control of dynamic balance in human gait on a split-belt treadmill.

PubMed

Buurke, Tom J W; Lamoth, Claudine J C; Vervoort, Danique; van der Woude, Lucas H V; den Otter, Rob

2018-05-17

Human bipedal gait is inherently unstable and staying upright requires adaptive control of dynamic balance. Little is known about adaptive control of dynamic balance in reaction to long-term, continuous perturbations. We examined how dynamic balance control adapts to a continuous perturbation in gait, by letting people walk faster with one leg than the other on a treadmill with two belts (i.e. split-belt walking). In addition, we assessed whether changes in mediolateral dynamic balance control coincide with changes in energy use during split-belt adaptation. In nine minutes of split-belt gait, mediolateral margins of stability and mediolateral foot roll-off changed during adaptation to the imposed gait asymmetry, especially on the fast side, and returned to baseline during washout. Interestingly, no changes in mediolateral foot placement (i.e. step width) were found during split-belt adaptation. Furthermore, the initial margin of stability and subsequent mediolateral foot roll-off were strongly coupled to maintain mediolateral dynamic balance throughout the gait cycle. Consistent with previous results net metabolic power was reduced during split-belt adaptation, but changes in mediolateral dynamic balance control were not correlated with the reduction of net metabolic power during split-belt adaptation. Overall, this study has shown that a complementary mechanism of relative foot positioning and mediolateral foot roll-off adapts to continuously imposed gait asymmetry to maintain dynamic balance in human bipedal gait. © 2018. Published by The Company of Biologists Ltd.

Stability and diversity in collective adaptation

NASA Astrophysics Data System (ADS)

Sato, Yuzuru; Akiyama, Eizo; Crutchfield, James P.

2005-10-01

We derive a class of macroscopic differential equations that describe collective adaptation, starting from a discrete-time stochastic microscopic model. The behavior of each agent is a dynamic balance between adaptation that locally achieves the best action and memory loss that leads to randomized behavior. We show that, although individual agents interact with their environment and other agents in a purely self-interested way, macroscopic behavior can be interpreted as game dynamics. Application to several familiar, explicit game interactions shows that the adaptation dynamics exhibits a diversity of collective behaviors. The simplicity of the assumptions underlying the macroscopic equations suggests that these behaviors should be expected broadly in collective adaptation. We also analyze the adaptation dynamics from an information-theoretic viewpoint and discuss self-organization induced by the dynamics of uncertainty, giving a novel view of collective adaptation.

Adaptive dynamical networks

NASA Astrophysics Data System (ADS)

Maslennikov, O. V.; Nekorkin, V. I.

2017-10-01

Dynamical networks are systems of active elements (nodes) interacting with each other through links. Examples are power grids, neural structures, coupled chemical oscillators, and communications networks, all of which are characterized by a networked structure and intrinsic dynamics of their interacting components. If the coupling structure of a dynamical network can change over time due to nodal dynamics, then such a system is called an adaptive dynamical network. The term ‘adaptive’ implies that the coupling topology can be rewired; the term ‘dynamical’ implies the presence of internal node and link dynamics. The main results of research on adaptive dynamical networks are reviewed. Key notions and definitions of the theory of complex networks are given, and major collective effects that emerge in adaptive dynamical networks are described.

Launch vehicle payload adapter design with vibration isolation features

NASA Astrophysics Data System (ADS)

Thomas, Gareth R.; Fadick, Cynthia M.; Fram, Bryan J.

2005-05-01

Payloads, such as satellites or spacecraft, which are mounted on launch vehicles, are subject to severe vibrations during flight. These vibrations are induced by multiple sources that occur between liftoff and the instant of final separation from the launch vehicle. A direct result of the severe vibrations is that fatigue damage and failure can be incurred by sensitive payload components. For this reason a payload adapter has been designed with special emphasis on its vibration isolation characteristics. The design consists of an annular plate that has top and bottom face sheets separated by radial ribs and close-out rings. These components are manufactured from graphite epoxy composites to ensure a high stiffness to weight ratio. The design is tuned to keep the frequency of the axial mode of vibration of the payload on the flexibility of the adapter to a low value. This is the main strategy adopted for isolating the payload from damaging vibrations in the intermediate to higher frequency range (45Hz-200Hz). A design challenge for this type of adapter is to keep the pitch frequency of the payload above a critical value in order to avoid dynamic interactions with the launch vehicle control system. This high frequency requirement conflicts with the low axial mode frequency requirement and this problem is overcome by innovative tuning of the directional stiffnesses of the composite parts. A second design strategy that is utilized to achieve good isolation characteristics is the use of constrained layer damping. This feature is particularly effective at keeping the responses to a minimum for one of the most important dynamic loading mechanisms. This mechanism consists of the almost-tonal vibratory load associated with the resonant burn condition present in any stage powered by a solid rocket motor. The frequency of such a load typically falls in the 45-75Hz range and this phenomenon drives the low frequency design of the adapter. Detailed finite element analysis is used throughout to qualify the design for vibration isolation performance as well as confirm its static and dynamic strength.

Mobile interfaces: Liquids as a perfect structural material for multifunctional, antifouling surfaces

DOE PAGES

Grinthal, Alison; Aizenberg, Joanna

2013-10-14

Life creates some of its most robust, extreme surface materials not from solids but from liquids: a purely liquid interface, stabilized by underlying nanotexture, makes carnivorous plant leaves ultraslippery, the eye optically perfect and dirt-resistant, our knees lubricated and pressure-tolerant, and insect feet reversibly adhesive and shape-adaptive. Novel liquid surfaces based on this idea have recently been shown to display unprecedented omniphobic, self-healing, anti-ice, antifouling, optical, and adaptive properties. In this Perspective, we present a framework and a path forward for developing and designing such liquid surfaces into sophisticated, versatile multifunctional materials. Drawing on concepts from solid materials design andmore » fluid dynamics, we outline how the continuous dynamics, responsiveness, and multiscale patternability of a liquid surface layer can be harnessed to create a wide range of unique, active interfacial functions-able to operate in harsh, changing environments-not achievable with static solids. We discuss how, in partnership with the underlying substrate, the liquid surface can be programmed to adaptively and reversibly reconfigure from a defect-free, molecularly smooth, transparent interface through a range of finely tuned liquid topographies in response to environmental stimuli. In conclusion, with nearly unlimited design possibilities and unmatched interfacial properties, liquid materials-as long-term stable interfaces yet in their fully liquid state-may potentially transform surface design everywhere from medicine to architecture to energy infrastructure.« less

High dynamic range hyperspectral imaging for camouflage performance test and evaluation

NASA Astrophysics Data System (ADS)

Pearce, D.; Feenan, J.

2016-10-01

This paper demonstrates the use of high dynamic range processing applied to the specific technique of hyper-spectral imaging with linescan spectrometers. The technique provides an improvement in signal to noise for reflectance estimation. This is demonstrated for field measurements of rural imagery collected from a ground-based linescan spectrometer of rural scenes. Once fully developed, the specific application is expected to improve the colour estimation approaches and consequently the test and evaluation accuracy of camouflage performance tests. Data are presented on both field and laboratory experiments that have been used to evaluate the improvements granted by the adoption of high dynamic range data acquisition in the field of hyperspectral imaging. High dynamic ranging imaging is well suited to the hyperspectral domain due to the large variation in solar irradiance across the visible and short wave infra-red (SWIR) spectrum coupled with the wavelength dependence of the nominal silicon detector response. Under field measurement conditions it is generally impractical to provide artificial illumination; consequently, an adaptation of the hyperspectral imaging and re ectance estimation process has been developed to accommodate the solar spectrum. This is shown to improve the signal to noise ratio for the re ectance estimation process of scene materials in the 400-500 nm and 700-900 nm regions.

Real-Time Adaptive Control of Flow-Induced Cavity Tones

NASA Technical Reports Server (NTRS)

Kegerise, Michael A.; Cabell, Randolph H.; Cattafesta, Louis N.

2004-01-01

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. The adaptive control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. The algorithm was also able t o maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are colocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible. In the control-algorithm development, the cavity dynamics are treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support this treatment.

Short-Term Memories in "Drosophila" Are Governed by General and Specific Genetic Systems

ERIC Educational Resources Information Center

Zars, Troy

2010-01-01

In a dynamic environment, there is an adaptive value in the ability of animals to acquire and express memories. That both simple and complex animals can learn is therefore not surprising. How animals have solved this problem genetically and anatomically probably lies somewhere in a range between a single molecular/anatomical mechanism that applies…

Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter

NASA Astrophysics Data System (ADS)

Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun

2018-03-01

The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.

Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

PubMed

Chen, Tien-Chi; Yu, Chih-Hsien

2009-07-01

A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

Robust Wave-front Correction in a Small Scale Adaptive Optics System Using a Membrane Deformable Mirror

NASA Astrophysics Data System (ADS)

Choi, Y.; Park, S.; Baik, S.; Jung, J.; Lee, S.; Yoo, J.

A small scale laboratory adaptive optics system using a Shack-Hartmann wave-front sensor (WFS) and a membrane deformable mirror (DM) has been built for robust image acquisition. In this study, an adaptive limited control technique is adopted to maintain the long-term correction stability of an adaptive optics system. To prevent the waste of dynamic correction range for correcting small residual wave-front distortions which are inefficient to correct, the built system tries to limit wave-front correction when a similar small difference wave-front pattern is repeatedly generated. Also, the effect of mechanical distortion in an adaptive optics system is studied and a pre-recognition method for the distortion is devised to prevent low-performance system operation. A confirmation process for a balanced work assignment among deformable mirror (DM) actuators is adopted for the pre-recognition. The corrected experimental results obtained by using a built small scale adaptive optics system are described in this paper.

Adaptive accelerated ReaxFF reactive dynamics with validation from simulating hydrogen combustion.

PubMed

Cheng, Tao; Jaramillo-Botero, Andrés; Goddard, William A; Sun, Huai

2014-07-02

We develop here the methodology for dramatically accelerating the ReaxFF reactive force field based reactive molecular dynamics (RMD) simulations through use of the bond boost concept (BB), which we validate here for describing hydrogen combustion. The bond order, undercoordination, and overcoordination concepts of ReaxFF ensure that the BB correctly adapts to the instantaneous configurations in the reactive system to automatically identify the reactions appropriate to receive the bond boost. We refer to this as adaptive Accelerated ReaxFF Reactive Dynamics or aARRDyn. To validate the aARRDyn methodology, we determined the detailed sequence of reactions for hydrogen combustion with and without the BB. We validate that the kinetics and reaction mechanisms (that is the detailed sequences of reactive intermediates and their subsequent transformation to others) for H2 oxidation obtained from aARRDyn agrees well with the brute force reactive molecular dynamics (BF-RMD) at 2498 K. Using aARRDyn, we then extend our simulations to the whole range of combustion temperatures from ignition (798 K) to flame temperature (2998K), and demonstrate that, over this full temperature range, the reaction rates predicted by aARRDyn agree well with the BF-RMD values, extrapolated to lower temperatures. For the aARRDyn simulation at 798 K we find that the time period for half the H2 to form H2O product is ∼538 s, whereas the computational cost was just 1289 ps, a speed increase of ∼0.42 trillion (10(12)) over BF-RMD. In carrying out these RMD simulations we found that the ReaxFF-COH2008 version of the ReaxFF force field was not accurate for such intermediates as H3O. Consequently we reoptimized the fit to a quantum mechanics (QM) level, leading to the ReaxFF-OH2014 force field that was used in the simulations.

Climate warming is associated with smaller body size and shorter lifespans in moose near their southern range limit.

PubMed

Hoy, Sarah R; Peterson, Rolf O; Vucetich, John A

2018-06-01

Despite the importance of body size for individual fitness, population dynamics and community dynamics, the influence of climate change on growth and body size is inadequately understood, particularly for long-lived vertebrates. Although temporal trends in body size have been documented, it remains unclear whether these changes represent the adverse impact of climate change (environmental stress constraining phenotypes) or its mitigation (via phenotypic plasticity or evolution). Concerns have also been raised about whether climate change is indeed the causal agent of these phenotypic shifts, given the length of time-series analysed and that studies often do not evaluate - and thereby sufficiently rule out - other potential causes. Here, we evaluate evidence for climate-related changes in adult body size (indexed by skull size) over a 4-decade period for a population of moose (Alces alces) near the southern limit of their range whilst also considering changes in density, predation, and human activities. In particular, we document: (i) a trend of increasing winter temperatures and concurrent decline in skull size (decline of 19% for males and 13% for females) and (ii) evidence of a negative relationship between skull size and winter temperatures during the first year of life. These patterns could be plausibly interpreted as an adaptive phenotypic response to climate warming given that latitudinal/temperature clines are often accepted as evidence of adaptation to local climate. However, we also observed: (iii) that moose with smaller skulls had shorter lifespans, (iv) a reduction in lifespan over the 4-decade study period, and (v) a negative relationship between lifespan and winter temperatures during the first year of life. Those observations indicate that this phenotypic change is not an adaptive response to climate change. However, this decline in lifespan was not accompanied by an obvious change in population dynamics, suggesting that climate change may affect population dynamics and life-histories differently. © 2017 John Wiley & Sons Ltd.

Why interdisciplinary research enriches the study of crime. Comment on "Statistical physics of crime: A review" by M.R. D'Orsogna and M. Perc

NASA Astrophysics Data System (ADS)

Donnay, Karsten

2015-03-01

The past several years have seen a rapidly growing interest in the use of advanced quantitative methodologies and formalisms adapted from the natural sciences to study a broad range of social phenomena. The research field of computational social science [1,2], for example, uses digital artifacts of human online activity to cast a new light on social dynamics. Similarly, the studies reviewed by D'Orsogna and Perc showcase a diverse set of advanced quantitative techniques to study the dynamics of crime. Methods used range from partial differential equations and self-exciting point processes to agent-based models, evolutionary game theory and network science [3].

Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms

PubMed Central

Balleza, Enrique; Alvarez-Buylla, Elena R.; Chaos, Alvaro; Kauffman, Stuart; Shmulevich, Ilya; Aldana, Maximino

2008-01-01

The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us. PMID:18560561

Selective host molecules obtained by dynamic adaptive chemistry.

PubMed

Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D

2014-02-17

Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parallel Adaptive Mesh Refinement for High-Order Finite-Volume Schemes in Computational Fluid Dynamics

NASA Astrophysics Data System (ADS)

Schwing, Alan Michael

For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable comparisons across a range of regimes. Unsteady and steady applications are considered in both subsonic and supersonic flows. Inviscid and viscous simulations achieve similar results at a much reduced cost when employing dynamic mesh adaptation. Several techniques for guiding adaptation are compared. Detailed analysis of statistics from the instrumented solver enable understanding of the costs associated with adaptation. Adaptive mesh refinement shows promise for the test cases presented here. It can be considerably faster than using conventional grids and provides accurate results. The procedures for adapting the grid are light-weight enough to not require significant computational time and yield significant reductions in grid size.

Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

NASA Astrophysics Data System (ADS)

Ward, Jonathan A.; Grindrod, Peter

2014-07-01

Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance here, cultural dissemination [47,12,48].Combining the effects of social influence and homophily naturally gives rise to an adaptive network, since social influence causes the states of agents that are strongly connected to become more similar, while homophily strengthens connections between agents whose states are already similar.1

Computational model for behavior shaping as an adaptive health intervention strategy.

PubMed

Berardi, Vincent; Carretero-González, Ricardo; Klepeis, Neil E; Ghanipoor Machiani, Sahar; Jahangiri, Arash; Bellettiere, John; Hovell, Melbourne

2018-03-01

Adaptive behavioral interventions that automatically adjust in real-time to participants' changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared with a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated.

Instantaneous phase mapping deflectometry for dynamic deformable mirror characterization

NASA Astrophysics Data System (ADS)

Trumper, Isaac; Choi, Heejoo

2017-09-01

We present an instantaneous phase mapping deflectometry (PMD) system in the context of measuring a continuous surface deformable mirror (DM). Deflectometry has a high dynamic range, enabling the full range of surfaces generated by the DM to be measured. The recent development of an instantaneous PMD system leverages the simple setup of the PMD system to measure dynamic objects with accuracy similar to an interferometer. To demonstrate the capabilities of this technology, we perform a linearity measurement of the actuator motion in a continuous surface DM, which is critical for closed loop control in adaptive optics applications. We measure the entire set of actuators across the DM as they traverse their full range of motion with a Shack-Hartman wavefront sensor, thereby obtaining the influence function. Given the influence function of each actuator, the DM can produce specific Zernike terms on its surface. We then measure the linearity of the Zernike modes available in the DM software using the instantaneous PMD system. By obtaining the relationship between modes, we can more accurately generate surface profiles composed of Zernike terms. This ability is useful for other dynamic freeform metrology applications that utilize the DM as a null component.

Adaptive infrared-reflecting systems inspired by cephalopods

NASA Astrophysics Data System (ADS)

Xu, Chengyi; Stiubianu, George T.; Gorodetsky, Alon A.

2018-03-01

Materials and systems that statically reflect radiation in the infrared region of the electromagnetic spectrum underpin the performance of many entrenched technologies, including building insulation, energy-conserving windows, spacecraft components, electronics shielding, container packaging, protective clothing, and camouflage platforms. The development of their adaptive variants, in which the infrared-reflecting properties dynamically change in response to external stimuli, has emerged as an important unmet scientific challenge. By drawing inspiration from cephalopod skin, we developed adaptive infrared-reflecting platforms that feature a simple actuation mechanism, low working temperature, tunable spectral range, weak angular dependence, fast response, stability to repeated cycling, amenability to patterning and multiplexing, autonomous operation, robust mechanical properties, and straightforward manufacturability. Our findings may open opportunities for infrared camouflage and other technologies that regulate infrared radiation.

Development of adaptive liquid microlenses and microlens arrays

NASA Astrophysics Data System (ADS)

Berry, Shaun R.; Stewart, Jason B.; Thorsen, Todd A.; Guha, Ingrid

2013-03-01

We report on the development of sub-millimeter size adaptive liquid microlenses and microlens arrays using two immiscible liquids to form individual lenses. Microlenses and microlens arrays having aperture diameters as small as 50 microns were fabricated on a planar quartz substrate using patterned hydrophobic/hydrophilic regions. Liquid lenses were formed by a self-assembled oil dosing process that created well-defined lenses having a high fill factor. Variable focus was achieved by controlling the lens curvature through electrowetting. Greater than 70° of contact angle change was achieved with less than 20 volts, which results in a large optical power dynamic range.

Neural network based adaptive control for nonlinear dynamic regimes

NASA Astrophysics Data System (ADS)

Shin, Yoonghyun

Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

The big and intricate dreams of little organelles: Embracing complexity in the study of membrane traffic.

PubMed

Liu, Allen P; Botelho, Roberto J; Antonescu, Costin N

2017-09-01

Compartmentalization of eukaryotic cells into dynamic organelles that exchange material through regulated membrane traffic governs virtually every aspect of cellular physiology including signal transduction, metabolism and transcription. Much has been revealed about the molecular mechanisms that control organelle dynamics and membrane traffic and how these processes are regulated by metabolic, physical and chemical cues. From this emerges the understanding of the integration of specific organellar phenomena within complex, multiscale and nonlinear regulatory networks. In this review, we discuss systematic approaches that revealed remarkable insight into the complexity of these phenomena, including the use of proximity-based proteomics, high-throughput imaging, transcriptomics and computational modeling. We discuss how these methods offer insights to further understand molecular versatility and organelle heterogeneity, phenomena that allow a single organelle population to serve a range of physiological functions. We also detail on how transcriptional circuits drive organelle adaptation, such that organelles may shift their function to better serve distinct differentiation and stress conditions. Thus, organelle dynamics and membrane traffic are functionally heterogeneous and adaptable processes that coordinate with higher-order system behavior to optimize cell function under a range of contexts. Obtaining a comprehensive understanding of organellar phenomena will increasingly require combined use of reductionist and system-based approaches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Evolutionary dynamics under interactive diversity

NASA Astrophysics Data System (ADS)

Su, Qi; Li, Aming; Wang, Long

2017-10-01

As evidenced by many cases in human societies, individuals often make different behavior decisions in different interactions, and adaptively adjust their behavior in changeable interactive scenarios. However, up to now, how such diverse interactive behavior affects cooperation dynamics has still remained unknown. Here we develop a general framework of interactive diversity, which models individuals’ separated behavior against distinct opponents and their adaptive adjustment in response to opponents’ strategies, to explore the evolution of cooperation. We find that interactive diversity enables individuals to reciprocate every single opponent, and thus sustains large-scale reciprocal interactions. Our work witnesses an impressive boost of cooperation for a notably extensive range of parameters and for all pairwise games. These results are robust against well-mixed and various networked populations, and against degree-normalized and cumulative payoff patterns. From the perspective of network dynamics, distinguished from individuals competing for nodes in most previous work, in this paper, the system evolves in the form of behavior disseminating along edges. We propose a theoretical method based on evolution of edges, which predicts well both the frequency of cooperation and the compact cooperation clusters. Our thorough investigation clarifies the positive role of interactive diversity in resolving social dilemmas and highlights the significance of understanding evolutionary dynamics from the viewpoint of edge dynamics.

Length oscillation mimicking periodic individual deep inspirations during tidal breathing attenuates force recovery and adaptation in airway smooth muscle.

PubMed

Raqeeb, Abdul; Solomon, Dennis; Paré, Peter D; Seow, Chun Y

2010-11-01

Airway smooth muscle (ASM) is able to generate maximal force under static conditions, and this isometric force can be maintained over a large length range due to length adaptation. The increased force at short muscle length could lead to excessive narrowing of the airways. Prolonged exposure of ASM to submaximal stimuli also increases the muscle's ability to generate force in a process called force adaptation. To date, the effects of length and force adaptation have only been demonstrated under static conditions. In the mechanically dynamic environment of the lung, ASM is constantly subjected to periodic stretches by the parenchyma due to tidal breathing and deep inspiration. It is not known whether force recovery due to muscle adaptation to a static environment could occur in a dynamic environment. In this study the effect of length oscillation mimicking tidal breathing and deep inspiration was examined. Force recovery after a length change was attenuated in the presence of length oscillation, except at very short lengths. Force adaptation was abolished by length oscillation. We conclude that in a healthy lung (with intact airway-parenchymal tethering) where airways are not allowed to narrow excessively, large stretches (associated with deep inspiration) may prevent the ability of the muscle to generate maximal force that would occur under static conditions irrespective of changes in mean length; mechanical perturbation on ASM due to tidal breathing and deep inspiration, therefore, is the first line of defense against excessive bronchoconstriction that may result from static length and force adaptation.

An adaptive actuator failure compensation scheme for two linked 2WD mobile robots

NASA Astrophysics Data System (ADS)

Ma, Yajie; Al-Dujaili, Ayad; Cocquempot, Vincent; El Badaoui El Najjar, Maan

2017-01-01

This paper develops a new adaptive compensation control scheme for two linked mobile robots with actuator failurs. A configuration with two linked two-wheel drive (2WD) mobile robots is proposed, and the modelling of its kinematics and dynamics are given. An adaptive failure compensation scheme is developed to compensate actuator failures, consisting of a kinematic controller and a multi-design integration based dynamic controller. The kinematic controller is a virtual one, and based on which, multiple adaptive dynamic control signals are designed which covers all possible failure cases. By combing these dynamic control signals, the dynamic controller is designed, which ensures system stability and asymptotic tracking properties. Simulation results verify the effectiveness of the proposed adaptive failure compensation scheme.

Evaluating sustainable adaptation strategies for vulnerable mega-deltas using system dynamics modelling: Rice agriculture in the Mekong Delta's An Giang Province, Vietnam.

PubMed

Chapman, Alexander; Darby, Stephen

2016-07-15

Challenging dynamics are unfolding in social-ecological systems around the globe as society attempts to mitigate and adapt to climate change while sustaining rapid local development. The IPCC's 5th assessment suggests these changing systems are susceptible to unforeseen and dangerous 'emergent risks'. An archetypal example is the Vietnamese Mekong Delta (VMD) where the river dyke network has been heightened and extended over the last decade with the dual objectives of (1) adapting the delta's 18 million inhabitants and their livelihoods to increasingly intense river-flooding, and (2) developing rice production through a shift from double to triple-cropping. Negative impacts have been associated with this shift, particularly in relation to its exclusion of fluvial sediment deposition from the floodplain. A deficit in our understanding of the dynamics of the rice-sediment system, which involve unintuitive delays, feedbacks, and tipping points, is addressed here, using a system dynamics (SD) approach to inform sustainable adaptation strategies. Specifically, we develop and test a new SD model which simulates the dynamics between the farmers' economic system and their rice agriculture operations, and uniquely, integrates the role of fluvial sediment deposition within their dyke compartment. We use the model to explore a range of alternative rice cultivation strategies. Our results suggest that the current dominant strategy (triple-cropping) is only optimal for wealthier groups within society and over the short-term (ca. 10years post-implementation). The model suggests that the policy of opening sluice gates and leaving paddies fallow during high-flood years, in order to encourage natural sediment deposition and the nutrient replenishment it supplies, is both a more equitable and a more sustainable policy. But, even with this approach, diminished supplies of sediment-bound nutrients and the consequent need to compensate with artificial fertilisers will mean that smaller-scale farmers in the VMD are more vulnerable to accruing debt. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Ultra-Wideband Chaos Life-Detection Radar with Sinusoidal Wave Modulation

NASA Astrophysics Data System (ADS)

Xu, Hang; Li, Ying; Zhang, Jianguo; Han, Hong; Zhang, Bing; Wang, Longsheng; Wang, Yuncai; Wang, Anbang

2017-12-01

We propose and experimentally demonstrate an ultra-wideband (UWB) chaos life-detection radar. The proposed radar transmits a wideband chaotic-pulse-position modulation (CPPM) signal modulated by a single-tone sinusoidal wave. A narrow-band split ring sensor is used to collect the reflected sinusoidal wave, and a lock-in amplifier is utilized to identify frequencies of respiration and heartbeat by detecting the phase change of the sinusoidal echo signal. Meanwhile, human location is realized by correlating the CPPM echo signal with its delayed duplicate and combining the synthetic aperture technology. Experimental results demonstrate that the human target can be located accurately and his vital signs can be detected in a large dynamic range through a 20-cm-thick wall using our radar system. The down-range resolution is 15cm, benefiting from the 1-GHz bandwidth of the CPPM signal. The dynamic range for human location is 50dB, and the dynamic ranges for heartbeat and respiration detection respectively are 20dB and 60dB in our radar system. In addition, the bandwidth of the CPPM signal can be adjusted from 620MHz to 1.56GHz to adapt to different requirements.

Desiccation and Mortality Dynamics in Seedlings of Different European Beech (Fagus sylvatica L.) Populations under Extreme Drought Conditions

PubMed Central

Bolte, Andreas; Czajkowski, Tomasz; Cocozza, Claudia; Tognetti, Roberto; de Miguel, Marina; Pšidová, Eva; Ditmarová, Ĺubica; Dinca, Lucian; Delzon, Sylvain; Cochard, Hervè; Ræbild, Anders; de Luis, Martin; Cvjetkovic, Branislav; Heiri, Caroline; Müller, Jürgen

2016-01-01

European beech (Fagus sylvatica L., hereafter beech), one of the major native tree species in Europe, is known to be drought sensitive. Thus, the identification of critical thresholds of drought impact intensity and duration are of high interest for assessing the adaptive potential of European beech to climate change in its native range. In a common garden experiment with one-year-old seedlings originating from central and marginal origins in six European countries (Denmark, Germany, France, Romania, Bosnia-Herzegovina, and Spain), we applied extreme drought stress and observed desiccation and mortality processes among the different populations and related them to plant water status (predawn water potential, ΨPD) and soil hydraulic traits. For the lethal drought assessment, we used a critical threshold of soil water availability that is reached when 50% mortality in seedling populations occurs (LD50SWA). We found significant population differences in LD50SWA (10.5–17.8%), and mortality dynamics that suggest a genetic difference in drought resistance between populations. The LD50SWA values correlate significantly with the mean growing season precipitation at population origins, but not with the geographic margins of beech range. Thus, beech range marginality may be more due to climatic conditions than to geographic range. The outcome of this study suggests the genetic variation has a major influence on the varying adaptive potential of the investigated populations. PMID:27379105

Statistical Model of Dynamic Markers of the Alzheimer's Pathological Cascade.

PubMed

Balsis, Steve; Geraci, Lisa; Benge, Jared; Lowe, Deborah A; Choudhury, Tabina K; Tirso, Robert; Doody, Rachelle S

2018-05-05

Alzheimer's disease (AD) is a progressive disease reflected in markers across assessment modalities, including neuroimaging, cognitive testing, and evaluation of adaptive function. Identifying a single continuum of decline across assessment modalities in a single sample is statistically challenging because of the multivariate nature of the data. To address this challenge, we implemented advanced statistical analyses designed specifically to model complex data across a single continuum. We analyzed data from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1,056), focusing on indicators from the assessments of magnetic resonance imaging (MRI) volume, fluorodeoxyglucose positron emission tomography (FDG-PET) metabolic activity, cognitive performance, and adaptive function. Item response theory was used to identify the continuum of decline. Then, through a process of statistical scaling, indicators across all modalities were linked to that continuum and analyzed. Findings revealed that measures of MRI volume, FDG-PET metabolic activity, and adaptive function added measurement precision beyond that provided by cognitive measures, particularly in the relatively mild range of disease severity. More specifically, MRI volume, and FDG-PET metabolic activity become compromised in the very mild range of severity, followed by cognitive performance and finally adaptive function. Our statistically derived models of the AD pathological cascade are consistent with existing theoretical models.

The Feasibility of Adaptive Unstructured Computations On Petaflops Systems

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Oliker, Leonid; Heber, Gerd; Gao, Guang; Saini, Subhash (Technical Monitor)

1999-01-01

This viewgraph presentation covers the advantages of mesh adaptation, unstructured grids, and dynamic load balancing. It illustrates parallel adaptive communications, and explains PLUM (Parallel dynamic load balancing for adaptive unstructured meshes), and PSAW (Proper Self Avoiding Walks).

Shack-Hartmann wavefront sensor with large dynamic range.

PubMed

Xia, Mingliang; Li, Chao; Hu, Lifa; Cao, Zhaoliang; Mu, Quanquan; Xuan, Li

2010-01-01

A new spot centroid detection algorithm for a Shack-Hartmann wavefront sensor (SHWFS) is experimentally investigated. The algorithm is a kind of dynamic tracking algorithm that tracks and calculates the corresponding spot centroid of the current spot map based on the spot centroid of the previous spot map, according to the strong correlation of the wavefront slope and the centroid of the corresponding spot between temporally adjacent SHWFS measurements. That is, for adjacent measurements, the spot centroid movement will usually fall within some range. Using the algorithm, the dynamic range of an SHWFS can be expanded by a factor of three in the measurement of tilt aberration compared with the conventional algorithm, more than 1.3 times in the measurement of defocus aberration, and more than 2 times in the measurement of the mixture of spherical aberration plus coma aberration. The algorithm is applied in our SHWFS to measure the distorted wavefront of the human eye. The experimental results of the adaptive optics (AO) system for retina imaging are presented to prove its feasibility for highly aberrated eyes.

Homeostatic enhancement of sensory transduction

PubMed Central

Milewski, Andrew R.; Ó Maoiléidigh, Dáibhid; Salvi, Joshua D.; Hudspeth, A. J.

2017-01-01

Our sense of hearing boasts exquisite sensitivity, precise frequency discrimination, and a broad dynamic range. Experiments and modeling imply, however, that the auditory system achieves this performance for only a narrow range of parameter values. Small changes in these values could compromise hair cells’ ability to detect stimuli. We propose that, rather than exerting tight control over parameters, the auditory system uses a homeostatic mechanism that increases the robustness of its operation to variation in parameter values. To slowly adjust the response to sinusoidal stimulation, the homeostatic mechanism feeds back a rectified version of the hair bundle’s displacement to its adaptation process. When homeostasis is enforced, the range of parameter values for which the sensitivity, tuning sharpness, and dynamic range exceed specified thresholds can increase by more than an order of magnitude. Signatures in the hair cell’s behavior provide a means to determine through experiment whether such a mechanism operates in the auditory system. Robustness of function through homeostasis may be ensured in any system through mechanisms similar to those that we describe here. PMID:28760949

The Dynamics of Learning and the Emergence of Distributed Adaption

DTIC Science & Technology

2006-05-01

regular access to experts in a wide range of disciplines—such as, biology, economics, cognitive science, and sociology—that historically have...organized a successful workshop on “Collective Cognition : Mathemati- cal Foundations of Distributed Intelligence,” bringing together workers in...processing and cognition . (For a complete list of participants, talk titles and abstracts, and other information on the workshop, see http

2009 MICROBIAL POPULATION BIOLOGY GORDON RESEARCH CONFERENCES JULY 19-24,2009

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

ANTHONY DEAN

2009-07-24

The 2009 Gordon Conference on Microbial Population Biology will cover a diverse range of cutting edge issues in the microbial sciences and beyond. Firmly founded in evolutionary biology and with a strongly integrative approach, past Conferences have covered a range of topics from the dynamics and genetics of adaptation to the evolution of mutation rate, community ecology, evolutionary genomics, altruism, and epidemiology. The 2009 Conference is no exception, and will include sessions on the evolution of infectious diseases, social evolution, the evolution of symbioses, experimental evolution, adaptive landscapes, community dynamics, and the evolution of protein structure and function. While genomicmore » approaches continue to make inroads, broadening our knowledge and encompassing new questions, the conference will also emphasize the use of experimental approaches to test hypotheses decisively. As in the past, this Conference provides young scientists and graduate students opportunities to present their work in poster format and exchange ideas with leading investigators from a broad spectrum of disciplines. This meeting is never dull: some of the most significant and contentious issues in biology have been thrashed out here. The 2009 meeting will be no exception.« less

Robust Adaptive Thresholder For Document Scanning Applications

NASA Astrophysics Data System (ADS)

Hsing, To R.

1982-12-01

In document scanning applications, thresholding is used to obtain binary data from a scanner. However, due to: (1) a wide range of different color backgrounds; (2) density variations of printed text information; and (3) the shading effect caused by the optical systems, the use of adaptive thresholding to enhance the useful information is highly desired. This paper describes a new robust adaptive thresholder for obtaining valid binary images. It is basically a memory type algorithm which can dynamically update the black and white reference level to optimize a local adaptive threshold function. The results of high image quality from different types of simulate test patterns can be obtained by this algorithm. The software algorithm is described and experiment results are present to describe the procedures. Results also show that the techniques described here can be used for real-time signal processing in the varied applications.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

Modeling vegetation rooting strategies on a hillslope

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bras, R. L.

2011-12-01

The manner in which water and energy is partitioned and redistributed along a hillslope is the result of complex coupled ecohydrological interactions between the climatic, soils, topography and vegetation operating over a wide range of spatiotemporal scales. Distributed process based modeling creates a framework through which the interaction of vegetation with the subtle differences in the spatial and temporal dynamics of soil moisture that arise under localized abiotic conditions along a hillslope can be simulated and examined. One deficiency in the current dynamic vegetation models is the one sided manner in which vegetation responds to soil moisture dynamics. Above ground, vegetation is given the freedom to dynamically evolve through alterations in fractional vegetation cover and/or canopy height and density; however below ground rooting profiles are simplistically represented and often held constant in time and space. The need to better represent the belowground role of vegetation through dynamic rooting strategies is fundamental in capturing the magnitude and timing of water and energy fluxes between the atmosphere and land surface. In order to allow vegetation to adapt to gradients in soil moisture a dynamic rooting scheme was incorporated into tRIBS+VEGGIE (a physically based distributed ecohydrological model). The dynamic rooting scheme allows vegetation the freedom to adapt their rooting depth and distribution in response abiotic conditions in a way that more closely mimics observed plant behavior. The incorporation of this belowground plasticity results in vegetation employing a suite of rooting strategies based on soil texture, climatic conditions and location on the hillslope.

Older adults learn less, but still reduce metabolic cost, during motor adaptation

PubMed Central

Huang, Helen J.

2013-01-01

The ability to learn new movements and dynamics is important for maintaining independence with advancing age. Age-related sensorimotor changes and increased muscle coactivation likely alter the trial-and-error-based process of adapting to new movement demands (motor adaptation). Here, we asked, to what extent is motor adaptation to novel dynamics maintained in older adults (≥65 yr)? We hypothesized that older adults would adapt to the novel dynamics less well than young adults. Because older adults often use muscle coactivation, we expected older adults to use greater muscle coactivation during motor adaptation than young adults. Nevertheless, we predicted that older adults would reduce muscle activity and metabolic cost with motor adaptation, similar to young adults. Seated older (n = 11, 73.8 ± 5.6 yr) and young (n = 15, 23.8 ± 4.7 yr) adults made targeted reaching movements while grasping a robotic arm. We measured their metabolic rate continuously via expired gas analysis. A force field was used to add novel dynamics. Older adults had greater movement deviations and compensated for just 65% of the novel dynamics compared with 84% in young adults. As expected, older adults used greater muscle coactivation than young adults. Last, older adults reduced muscle activity with motor adaptation and had consistent reductions in metabolic cost later during motor adaptation, similar to young adults. These results suggest that despite increased muscle coactivation, older adults can adapt to the novel dynamics, albeit less accurately. These results also suggest that reductions in metabolic cost may be a fundamental feature of motor adaptation. PMID:24133222

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

An 1.4 ppm/°C bandgap voltage reference with automatic curvature-compensation technique

NASA Astrophysics Data System (ADS)

Zhou, Zekun; Yu, Hongming; Shi, Yue; Zhang, Bo

2017-12-01

A high-precision Bandgap voltage reference (BGR) with a novel curvature-compensation scheme is proposed in this paper. The temperature coefficient (TC) can be automatically optimized with a built-in adaptive curvature-compensation technique, which is realized in a digitization control way. Firstly, an exponential curvature compensation method is adopted to reduce the TC in a certain degree, especially in low temperature range. Then, the temperature drift of BGR in higher temperature range can be further minimized by dynamic zero-temperature-coefficient point tracking with temperature changes. With the help of proposed adaptive signal processing, the output voltage of BGR can approximately maintain zero TC in a wider temperature range. Experiment results of the BGR proposed in this paper, which is implemented in 0.35-μm BCD process, illustrate that the TC of 1.4ppm/°C is realized under the power supply voltage of 3.6V and the power supply rejection of the proposed circuit is -67dB.

A low-noise wide-dynamic-range event-driven detector using SOI pixel technology for high-energy particle imaging

NASA Astrophysics Data System (ADS)

Shrestha, Sumeet; Kamehama, Hiroki; Kawahito, Shoji; Yasutomi, Keita; Kagawa, Keiichiro; Takeda, Ayaki; Tsuru, Takeshi Go; Arai, Yasuo

2015-08-01

This paper presents a low-noise wide-dynamic-range pixel design for a high-energy particle detector in astronomical applications. A silicon on insulator (SOI) based detector is used for the detection of wide energy range of high energy particles (mainly for X-ray). The sensor has a thin layer of SOI CMOS readout circuitry and a thick layer of high-resistivity detector vertically stacked in a single chip. Pixel circuits are divided into two parts; signal sensing circuit and event detection circuit. The event detection circuit consisting of a comparator and logic circuits which detect the incidence of high energy particle categorizes the incident photon it into two energy groups using an appropriate energy threshold and generate a two-bit code for an event and energy level. The code for energy level is then used for selection of the gain of the in-pixel amplifier for the detected signal, providing a function of high-dynamic-range signal measurement. The two-bit code for the event and energy level is scanned in the event scanning block and the signals from the hit pixels only are read out. The variable-gain in-pixel amplifier uses a continuous integrator and integration-time control for the variable gain. The proposed design allows the small signal detection and wide dynamic range due to the adaptive gain technique and capability of correlated double sampling (CDS) technique of kTC noise canceling of the charge detector.

Computerized Dynamic Adaptive Tests with Immediately Individualized Feedback for Primary School Mathematics Learning

ERIC Educational Resources Information Center

Wu, Huey-Min; Kuo, Bor-Chen; Wang, Su-Chen

2017-01-01

In this study, a computerized dynamic assessment test with both immediately individualized feedback and adaptively property was applied to Mathematics learning in primary school. For evaluating the effectiveness of the computerized dynamic adaptive test, the performances of three types of remedial instructions were compared by a pre-test/post-test…

Neural Methods for Imagery, GMTI, and Information Fusion

DTIC Science & Technology

2006-03-15

Dynamic Range Contrast Enhanced Length & Power Normalized JV\\ 0.7 11 2500. No0 00 0.6 :a -30 - i 0.5 1 •4e ,3 ta I. a* 20 4B 60 Be° .0 120 140 160 s e...conditioned profile after length and power normalization. 2 Neural-Based Feature Extraction 2.2 Contrast enhancement and adaptive Rather than directly... power of the signal comprised of HRR range profiles synthesized from the is normalized. This ensures that very weak or very strong MSTAR SAR imagery

Population dynamics and climate change: what are the links?

PubMed

Stephenson, Judith; Newman, Karen; Mayhew, Susannah

2010-06-01

Climate change has been described as the biggest global health threat of the 21(st) century. World population is projected to reach 9.1 billion by 2050, with most of this growth in developing countries. While the principal cause of climate change is high consumption in the developed countries, its impact will be greatest on people in the developing world. Climate change and population can be linked through adaptation (reducing vulnerability to the adverse effects of climate change) and, more controversially, through mitigation (reducing the greenhouse gases that cause climate change). The contribution of low-income, high-fertility countries to global carbon emissions has been negligible to date, but is increasing with the economic development that they need to reduce poverty. Rapid population growth endangers human development, provision of basic services and poverty eradication and weakens the capacity of poor communities to adapt to climate change. Significant mass migration is likely to occur in response to climate change and should be regarded as a legitimate response to the effects of climate change. Linking population dynamics with climate change is a sensitive issue, but family planning programmes that respect and protect human rights can bring a remarkable range of benefits. Population dynamics have not been integrated systematically into climate change science. The contribution of population growth, migration, urbanization, ageing and household composition to mitigation and adaptation programmes needs urgent investigation.

Identification of cascade water tanks using a PWARX model

NASA Astrophysics Data System (ADS)

Mattsson, Per; Zachariah, Dave; Stoica, Petre

2018-06-01

In this paper we consider the identification of a discrete-time nonlinear dynamical model for a cascade water tank process. The proposed method starts with a nominal linear dynamical model of the system, and proceeds to model its prediction errors using a model that is piecewise affine in the data. As data is observed, the nominal model is refined into a piecewise ARX model which can capture a wide range of nonlinearities, such as the saturation in the cascade tanks. The proposed method uses a likelihood-based methodology which adaptively penalizes model complexity and directly leads to a computationally efficient implementation.

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

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

Chai, Tianyou; Jia, Yao; Wang, Hong

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperaturemore » are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.« less

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.

2005-01-01

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

Chameleon Effect, the Range of Values Hypothesis and Reproducing the EPR-Bohm Correlations

NASA Astrophysics Data System (ADS)

Accardi, Luigi; Khrennikov, Andrei

2007-02-01

We present a detailed analysis of assumptions that J. Bell used to show that local realism contradicts QM. We find that Bell's viewpoint on realism is nonphysical, because it implicitly assume that observed physical variables coincides with ontic variables (i.e., these variables before measurement). The real physical process of measurement is a process of dynamical interaction between a system and a measurement device. Therefore one should check the adequacy of QM not to "Bell's realism," but to adaptive realism (chameleon realism). Dropping Bell's assumption we are able to construct a natural representation of the EPR-Bohm correlations in the local (adaptive) realistic approach.

Sensorimotor Adaptations Following Exposure to Ambiguous Inertial Motion Cues

NASA Technical Reports Server (NTRS)

Wood, S. J.; Harm, D. L.; Reschke, M. F.; Rupert, A. H.; Clement, G. R.

2009-01-01

The central nervous system must resolve the ambiguity of inertial motion sensory cues in order to derive accurate spatial orientation awareness. We hypothesize that multi-sensory integration will be adaptively optimized in altered gravity environments based on the dynamics of other sensory information available, with greater changes in otolith-mediated responses in the mid-frequency range where there is a crossover of tilt and translation responses. The primary goals of this ground-based research investigation are to explore physiological mechanisms and operational implications of tilt-translation disturbances during and following re-entry, and to evaluate a tactile prosthesis as a countermeasure for improving control of whole-body orientation.

First benchmark of the Unstructured Grid Adaptation Working Group

NASA Technical Reports Server (NTRS)

Ibanez, Daniel; Barral, Nicolas; Krakos, Joshua; Loseille, Adrien; Michal, Todd; Park, Mike

2017-01-01

Unstructured grid adaptation is a technology that holds the potential to improve the automation and accuracy of computational fluid dynamics and other computational disciplines. Difficulty producing the highly anisotropic elements necessary for simulation on complex curved geometries that satisfies a resolution request has limited this technology's widespread adoption. The Unstructured Grid Adaptation Working Group is an open gathering of researchers working on adapting simplicial meshes to conform to a metric field. Current members span a wide range of institutions including academia, industry, and national laboratories. The purpose of this group is to create a common basis for understanding and improving mesh adaptation. We present our first major contribution: a common set of benchmark cases, including input meshes and analytic metric specifications, that are publicly available to be used for evaluating any mesh adaptation code. We also present the results of several existing codes on these benchmark cases, to illustrate their utility in identifying key challenges common to all codes and important differences between available codes. Future directions are defined to expand this benchmark to mature the technology necessary to impact practical simulation workflows.

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

NASA Astrophysics Data System (ADS)

Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

2016-04-01

Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

Adaptation approaches for conserving ecosystems services and biodiversity in dynamic landscapes caused by climate change

Treesearch

Oswald J. Schmitz; Anne M. Trainor

2014-01-01

Climate change stands to cause animal species to shift their geographic ranges. This will cause ecosystems to become reorganized across landscapes as species migrate into and out of specific locations with attendant impacts on values and services that ecosystems provide to humans. Conservation in an era of climate change needs to ensure that landscapes are resilient by...

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

Quantitative assessment of the effects of 6 months of adapted physical activity on gait in people with multiple sclerosis: a randomized controlled trial.

PubMed

Pau, Massimiliano; Corona, Federica; Coghe, Giancarlo; Marongiu, Elisabetta; Loi, Andrea; Crisafulli, Antonio; Concu, Alberto; Galli, Manuela; Marrosu, Maria Giovanna; Cocco, Eleonora

2018-01-01

The purpose of this study is to quantitatively assess the effect of 6 months of supervised adapted physical activity (APA i.e. physical activity designed for people with special needs) on spatio-temporal and kinematic parameters of gait in persons with Multiple Sclerosis (pwMS). Twenty-two pwMS with Expanded Disability Status Scale scores ranging from 1.5 to 5.5 were randomly assigned either to the intervention group (APA, n = 11) or the control group (CG, n = 11). The former underwent 6 months of APA consisting of 3 weekly 60-min sessions of aerobic and strength training, while CG participants were engaged in no structured PA program. Gait patterns were analyzed before and after the training using three-dimensional gait analysis by calculating spatio-temporal parameters and concise indexes of gait kinematics (Gait Profile Score - GPS and Gait Variable Score - GVS) as well as dynamic Range of Motion (ROM) of hip, knee, and ankle joints. The training originated significant improvements in stride length, gait speed and cadence in the APA group, while GPS and GVS scores remained practically unchanged. A trend of improvement was also observed as regard the dynamic ROM of hip, knee, and ankle joints. No significant changes were observed in the CG for any of the parameters considered. The quantitative analysis of gait supplied mixed evidence about the actual impact of 6 months of APA on pwMS. Although some improvements have been observed, the substantial constancy of kinematic patterns of gait suggests that the full transferability of the administered training on the ambulation function may require more specific exercises. Implications for rehabilitation Adapted Physical Activity (APA) is effective in improving spatio-temporal parameters of gait, but not kinematics, in people with multiple sclerosis. Dynamic range of motion during gait is increased after APA. The full transferability of APA on the ambulation function may require specific exercises rather than generic lower limbs strength/flexibility training.

The physical and functional thermal sensitivity of bacterial chemoreceptors.

PubMed

Frank, Vered; Koler, Moriah; Furst, Smadar; Vaknin, Ady

2011-08-19

The bacterium Escherichia coli exhibits chemotactic behavior at temperatures ranging from approximately 20 °C to at least 42 °C. This behavior is controlled by clusters of transmembrane chemoreceptors made from trimers of dimers that are linked together by cross-binding to cytoplasmic components. By detecting fluorescence energy transfer between various components of this system, we studied the underlying molecular behavior of these receptors in vivo and throughout their operating temperature range. We reveal a sharp modulation in the conformation of unclustered and clustered receptor trimers and, consequently, in kinase activity output. These modulations occurred at a characteristic temperature that depended on clustering and were lower for receptors at lower adaptational states. However, in the presence of dynamic adaptation, the response of kinase activity to a stimulus was sustained up to 45 °C, but sensitivity notably decreased. Thus, this molecular system exhibits a clear thermal sensitivity that emerges at the level of receptor trimers, but both receptor clustering and adaptation support the overall robust operation of the system at elevated temperatures. Copyright © 2011 Elsevier Ltd. All rights reserved.

Accurate and general treatment of electrostatic interaction in Hamiltonian adaptive resolution simulations

NASA Astrophysics Data System (ADS)

Heidari, M.; Cortes-Huerto, R.; Donadio, D.; Potestio, R.

2016-10-01

In adaptive resolution simulations the same system is concurrently modeled with different resolution in different subdomains of the simulation box, thereby enabling an accurate description in a small but relevant region, while the rest is treated with a computationally parsimonious model. In this framework, electrostatic interaction, whose accurate treatment is a crucial aspect in the realistic modeling of soft matter and biological systems, represents a particularly acute problem due to the intrinsic long-range nature of Coulomb potential. In the present work we propose and validate the usage of a short-range modification of Coulomb potential, the Damped shifted force (DSF) model, in the context of the Hamiltonian adaptive resolution simulation (H-AdResS) scheme. This approach, which is here validated on bulk water, ensures a reliable reproduction of the structural and dynamical properties of the liquid, and enables a seamless embedding in the H-AdResS framework. The resulting dual-resolution setup is implemented in the LAMMPS simulation package, and its customized version employed in the present work is made publicly available.

Modelling droplet collision outcomes for different substances and viscosities

NASA Astrophysics Data System (ADS)

Sommerfeld, Martin; Kuschel, Matthias

2016-12-01

The main objective of the present study is the derivation of models describing the outcome of binary droplet collisions for a wide range of dynamic viscosities in the well-known collision maps (i.e. normalised lateral droplet displacement at collision, called impact parameter, versus collision Weber number). Previous studies by Kuschel and Sommerfeld (Exp Fluids 54:1440, 2013) for different solution droplets having a range of solids contents and hence dynamic viscosities (here between 1 and 60 mPa s) revealed that the locations of the triple point (i.e. coincidence of bouncing, stretching separation and coalescence) and the critical Weber number (i.e. condition for the transition from coalescence to separation for head-on collisions) show a clear dependence on dynamic viscosity. In order to extend these findings also to pure liquids and to provide a broader data basis for modelling the viscosity effect, additional binary collision experiments were conducted for different alcohols (viscosity range 1.2-15.9 mPa s) and the FVA1 reference oil at different temperatures (viscosity range 3.0-28.2 mPa s). The droplet size for the series of alcohols was around 365 and 385 µm for the FVA1 reference oil, in each case with fixed diameter ratio at Δ= 1. The relative velocity between the droplets was varied in the range 0.5-3.5 m/s, yielding maximum Weber numbers of around 180. Individual binary droplet collisions with defined conditions were generated by two droplet chains each produced by vibrating orifice droplet generators. For recording droplet motion and the binary collision process with good spatial and temporal resolution high-speed shadow imaging was employed. The results for varied relative velocity and impact angle were assembled in impact parameter-Weber number maps. With increasing dynamic viscosity a characteristic displacement of the regimes for the different collision scenarios was also observed for pure liquids similar to that observed for solutions. This displacement could be described on a physical basis using the similarity number and structure parameter K which was obtained through flow process evaluation and optimal proportioning of momentum and energy by Naue and Bärwolff (Transportprozesse in Fluiden. Deutscher Verlag für Grundstoffindustrie GmbH, Leipzig 1992). Two correlations including the structure parameter K could be derived which describe the location of the triple point and the critical We number. All fluids considered, pure liquids and solutions, are very well fitted by these physically based correlations. The boundary model of Jiang et al. (J Fluid Mech 234:171-190, 1992) for distinguishing between coalescence and stretching separation could be adapted to go through the triple point by the two involved model parameters C a and C b, which were correlated with the relaxation velocity u_{{relax}} = {σ/μ}. Based on the predicted critical Weber number, denoting the onset of reflexive separation, the model of Ashgriz and Poo (J Fluid Mech 221:183-204, 1990) was adapted accordingly. The proper performance of the new generalised models was validated based on the present and previous measurements for a wide range of dynamic viscosities (i.e. 1-60 mPa s) and liquid properties. Although the model for the lower boundary of bouncing (Estrade et al. in J Heat Fluid Flow 20:486-491, 1999) could be adapted through the shape factor, it was found not suitable for the entire range of Weber numbers and viscosities.

A fast and automatic fusion algorithm for unregistered multi-exposure image sequence

NASA Astrophysics Data System (ADS)

Liu, Yan; Yu, Feihong

2014-09-01

Human visual system (HVS) can visualize all the brightness levels of the scene through visual adaptation. However, the dynamic range of most commercial digital cameras and display devices are smaller than the dynamic range of human eye. This implies low dynamic range (LDR) images captured by normal digital camera may lose image details. We propose an efficient approach to high dynamic (HDR) image fusion that copes with image displacement and image blur degradation in a computationally efficient manner, which is suitable for implementation on mobile devices. The various image registration algorithms proposed in the previous literatures are unable to meet the efficiency and performance requirements in the application of mobile devices. In this paper, we selected Oriented Brief (ORB) detector to extract local image structures. The descriptor selected in multi-exposure image fusion algorithm has to be fast and robust to illumination variations and geometric deformations. ORB descriptor is the best candidate in our algorithm. Further, we perform an improved RANdom Sample Consensus (RANSAC) algorithm to reject incorrect matches. For the fusion of images, a new approach based on Stationary Wavelet Transform (SWT) is used. The experimental results demonstrate that the proposed algorithm generates high quality images at low computational cost. Comparisons with a number of other feature matching methods show that our method gets better performance.

A Knowledge-Structure-Based Adaptive Dynamic Assessment System for Calculus Learning

ERIC Educational Resources Information Center

Ting, M.-Y.; Kuo, B.-C.

2016-01-01

The purpose of this study was to investigate the effect of a calculus system that was designed using an adaptive dynamic assessment (DA) framework on performance in the "finding an area using an integral". In this study, adaptive testing and dynamic assessment were combined to provide different test items depending on students'…

A limited host immune range facilitates the creation and maintenance of diversity in parasite virulence

PubMed Central

Best, Alex; Hoyle, Andy

2013-01-01

A vast theoretical literature has explored the evolutionary dynamics of parasite virulence. The classic result from this modelling work is that, assuming a saturating transmission–virulence trade-off, there is a single evolutionary optimum where the parasite optimizes the epidemiological R0. However, there are an increasing number of models that have shown how ecological and epidemiological feedbacks to evolution can instead result in the creation and maintenance of multiple parasite strains. Here, we fully explore one such example, where recovered hosts have a limited ‘immune range’ resulting in partial cross-immunity to parasite strains that they have not previously encountered. Taking an adaptive dynamics approach, we show that, provided this immune range is not too wide, high levels of diversity can evolve and be maintained through multiple branching events. We argue that our model provides a more realistic picture of disease dynamics in vertebrate host populations and may be a key explanatory factor in the high levels of parasite diversity seen in natural systems. PMID:24516712

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

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

Song, Hyun-Seob; Cannon, William R.; Beliaev, Alex S.

Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can bemore » potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.« less

Achieving Optimal Self-Adaptivity for Dynamic Tuning of Organic Semiconductors through Resonance Engineering.

PubMed

Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei

2016-08-03

Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.

Integrated Flight/Structural Mode Control for Very Flexible Aircraft Using L1 Adaptive Output Feedback Controller

NASA Technical Reports Server (NTRS)

Che, Jiaxing; Cao, Chengyu; Gregory, Irene M.

2012-01-01

This paper explores application of adaptive control architecture to a light, high-aspect ratio, flexible aircraft configuration that exhibits strong rigid body/flexible mode coupling. Specifically, an L(sub 1) adaptive output feedback controller is developed for a semi-span wind tunnel model capable of motion. The wind tunnel mount allows the semi-span model to translate vertically and pitch at the wing root, resulting in better simulation of an aircraft s rigid body motion. The control objective is to design a pitch control with altitude hold while suppressing body freedom flutter. The controller is an output feedback nominal controller (LQG) augmented by an L(sub 1) adaptive loop. A modification to the L(sub 1) output feedback is proposed to make it more suitable for flexible structures. The new control law relaxes the required bounds on the unmatched uncertainty and allows dependence on the state as well as time, i.e. a more general unmatched nonlinearity. The paper presents controller development and simulated performance responses. Simulation is conducted by using full state flexible wing models derived from test data at 10 different dynamic pressure conditions. An L(sub 1) adaptive output feedback controller is designed for a single test point and is then applied to all the test cases. The simulation results show that the L(sub 1) augmented controller can stabilize and meet the performance requirements for all 10 test conditions ranging from 30 psf to 130 psf dynamic pressure.

Experimental and analytical study of secondary path variations in active engine mounts

NASA Astrophysics Data System (ADS)

Hausberg, Fabian; Scheiblegger, Christian; Pfeffer, Peter; Plöchl, Manfred; Hecker, Simon; Rupp, Markus

2015-03-01

Active engine mounts (AEMs) provide an effective solution to further improve the acoustic and vibrational comfort of passenger cars. Typically, adaptive feedforward control algorithms, e.g., the filtered-x-least-mean-squares (FxLMS) algorithm, are applied to cancel disturbing engine vibrations. These algorithms require an accurate estimate of the AEM active dynamic characteristics, also known as the secondary path, in order to guarantee control performance and stability. This paper focuses on the experimental and theoretical study of secondary path variations in AEMs. The impact of three major influences, namely nonlinearity, change of preload and component temperature, on the AEM active dynamic characteristics is experimentally analyzed. The obtained test results are theoretically investigated with a linear AEM model which incorporates an appropriate description for elastomeric components. A special experimental set-up extends the model validation of the active dynamic characteristics to higher frequencies up to 400 Hz. The theoretical and experimental results show that significant secondary path variations are merely observed in the frequency range of the AEM actuator's resonance frequency. These variations mainly result from the change of the component temperature. As the stability of the algorithm is primarily affected by the actuator's resonance frequency, the findings of this paper facilitate the design of AEMs with simpler adaptive feedforward algorithms. From a practical point of view it may further be concluded that algorithmic countermeasures against instability are only necessary in the frequency range of the AEM actuator's resonance frequency.

Thermal fluctuations of haemoglobin from different species: adaptation to temperature via conformational dynamics

PubMed Central

Stadler, A. M.; Garvey, C. J.; Bocahut, A.; Sacquin-Mora, S.; Digel, I.; Schneider, G. J.; Natali, F.; Artmann, G. M.; Zaccai, G.

2012-01-01

Thermodynamic stability, configurational motions and internal forces of haemoglobin (Hb) of three endotherms (platypus, Ornithorhynchus anatinus; domestic chicken, Gallus gallus domesticus and human, Homo sapiens) and an ectotherm (salt water crocodile, Crocodylus porosus) were investigated using circular dichroism, incoherent elastic neutron scattering and coarse-grained Brownian dynamics simulations. The experimental results from Hb solutions revealed a direct correlation between protein resilience, melting temperature and average body temperature of the different species on the 0.1 ns time scale. Molecular forces appeared to be adapted to permit conformational fluctuations with a root mean square displacement close to 1.2 Å at the corresponding average body temperature of the endotherms. Strong forces within crocodile Hb maintain the amplitudes of motion within a narrow limit over the entire temperature range in which the animal lives. In fully hydrated powder samples of human and chicken, Hb mean square displacements and effective force constants on the 1 ns time scale showed no differences over the whole temperature range from 10 to 300 K, in contrast to the solution case. A complementary result of the study, therefore, is that one hydration layer is not sufficient to activate all conformational fluctuations of Hb in the pico- to nanosecond time scale which might be relevant for biological function. Coarse-grained Brownian dynamics simulations permitted to explore residue-specific effects. They indicated that temperature sensing of human and chicken Hb occurs mainly at residues lining internal cavities in the β-subunits. PMID:22696485

Thermal fluctuations of haemoglobin from different species: adaptation to temperature via conformational dynamics.

PubMed

Stadler, A M; Garvey, C J; Bocahut, A; Sacquin-Mora, S; Digel, I; Schneider, G J; Natali, F; Artmann, G M; Zaccai, G

2012-11-07

Thermodynamic stability, configurational motions and internal forces of haemoglobin (Hb) of three endotherms (platypus, Ornithorhynchus anatinus; domestic chicken, Gallus gallus domesticus and human, Homo sapiens) and an ectotherm (salt water crocodile, Crocodylus porosus) were investigated using circular dichroism, incoherent elastic neutron scattering and coarse-grained Brownian dynamics simulations. The experimental results from Hb solutions revealed a direct correlation between protein resilience, melting temperature and average body temperature of the different species on the 0.1 ns time scale. Molecular forces appeared to be adapted to permit conformational fluctuations with a root mean square displacement close to 1.2 Å at the corresponding average body temperature of the endotherms. Strong forces within crocodile Hb maintain the amplitudes of motion within a narrow limit over the entire temperature range in which the animal lives. In fully hydrated powder samples of human and chicken, Hb mean square displacements and effective force constants on the 1 ns time scale showed no differences over the whole temperature range from 10 to 300 K, in contrast to the solution case. A complementary result of the study, therefore, is that one hydration layer is not sufficient to activate all conformational fluctuations of Hb in the pico- to nanosecond time scale which might be relevant for biological function. Coarse-grained Brownian dynamics simulations permitted to explore residue-specific effects. They indicated that temperature sensing of human and chicken Hb occurs mainly at residues lining internal cavities in the β-subunits.

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

2009-01-01

This paper is devoted to robust, Predictor-based Model Reference Adaptive Control (PMRAC) design. The proposed adaptive system is compared with the now-classical Model Reference Adaptive Control (MRAC) architecture. Simulation examples are presented. Numerical evidence indicates that the proposed PMRAC tracking architecture has better than MRAC transient characteristics. In this paper, we presented a state-predictor based direct adaptive tracking design methodology for multi-input dynamical systems, with partially known dynamics. Efficiency of the design was demonstrated using short period dynamics of an aircraft. Formal proof of the reported PMRAC benefits constitute future research and will be reported elsewhere.

Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

PubMed

Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

2017-07-01

In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

Ribbon synapses compute temporal contrast and encode luminance in retinal rod bipolar cells

PubMed Central

Oesch, Nicholas W.; Diamond, Jeffrey S.

2011-01-01

Contrast is computed throughout the nervous system to encode changing inputs efficiently. The retina encodes luminance and contrast over a wide range of visual conditions and so must adapt its responses to maintain sensitivity and avoid saturation. Here we show how one type of adaptation allows individual synapses to compute contrast and encode luminance in biphasic responses to step changes in light levels. Light-evoked depletion of the readily releasable vesicle pool (RRP) at rod bipolar cell (RBC) ribbon synapses in rat retina limits the dynamic range available to encode transient but not sustained responses, thereby allowing the transient and sustained components of release to compute temporal contrast and encode mean light levels, respectively. A release/replenishment model shows that a single, homogeneous pool of synaptic vesicles is sufficient to generate this behavior and reveals that the dominant mechanism shaping the biphasic contrast/luminance response is the partial depletion of the RRP. PMID:22019730

An adaptive cubature formula for efficient reliability assessment of nonlinear structural dynamic systems

NASA Astrophysics Data System (ADS)

Xu, Jun; Kong, Fan

2018-05-01

Extreme value distribution (EVD) evaluation is a critical topic in reliability analysis of nonlinear structural dynamic systems. In this paper, a new method is proposed to obtain the EVD. The maximum entropy method (MEM) with fractional moments as constraints is employed to derive the entire range of EVD. Then, an adaptive cubature formula is proposed for fractional moments assessment involved in MEM, which is closely related to the efficiency and accuracy for reliability analysis. Three point sets, which include a total of 2d2 + 1 integration points in the dimension d, are generated in the proposed formula. In this regard, the efficiency of the proposed formula is ensured. Besides, a "free" parameter is introduced, which makes the proposed formula adaptive with the dimension. The "free" parameter is determined by arranging one point set adjacent to the boundary of the hyper-sphere which contains the bulk of total probability. In this regard, the tail distribution may be better reproduced and the fractional moments could be evaluated with accuracy. Finally, the proposed method is applied to a ten-storey shear frame structure under seismic excitations, which exhibits strong nonlinearity. The numerical results demonstrate the efficacy of the proposed method.

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

Finite-Size Scaling of a First-Order Dynamical Phase Transition: Adaptive Population Dynamics and an Effective Model

NASA Astrophysics Data System (ADS)

Nemoto, Takahiro; Jack, Robert L.; Lecomte, Vivien

2017-03-01

We analyze large deviations of the time-averaged activity in the one-dimensional Fredrickson-Andersen model, both numerically and analytically. The model exhibits a dynamical phase transition, which appears as a singularity in the large deviation function. We analyze the finite-size scaling of this phase transition numerically, by generalizing an existing cloning algorithm to include a multicanonical feedback control: this significantly improves the computational efficiency. Motivated by these numerical results, we formulate an effective theory for the model in the vicinity of the phase transition, which accounts quantitatively for the observed behavior. We discuss potential applications of the numerical method and the effective theory in a range of more general contexts.

Age-related change in fast adaptation mechanisms measured with the scotopic full-field ERG.

PubMed

Tillman, Megan A; Panorgias, Athanasios; Werner, John S

2016-06-01

To quantify the response dynamics of fast adaptation mechanisms of the scotopic ERG in younger and older adults using full-field m-sequence flash stimulation. Scotopic ERGs were measured for a series of flashes separated by 65 ms over a range of 260 ms in 16 younger (20-26, 22.2 ± 2.1; range mean ±1 SD) and 16 older (65-85, 71.2 ± 7) observers without retinal pathology. A short-wavelength (λ peak = 442 nm) LED was used for scotopic stimulation, and the flashes ranged from 0.0001 to 0.01 cd s m(-2). The complete binary kernel series was derived from the responses to the m-sequence flash stimulation, and the first- and second-order kernel responses were analyzed. The first-order kernel represented the response to a single, isolated flash, while the second-order kernels reflected the adapted flash responses that followed a single flash by one or more base intervals. B-wave amplitudes of the adapted flash responses were measured and plotted as a function of interstimulus interval to describe the recovery of the scotopic ERG. A linear function was fitted to the linear portion of the recovery curve, and the slope of the line was used to estimate the rate of fast adaptation recovery. The amplitudes of the isolated flash responses and rates of scotopic fast adaptation recovery were compared between the younger and older participants using a two-way ANOVA. The isolated flash responses and rates of recovery were found to be significantly lower in the older adults. However, there was no difference between the two age groups in response amplitude or recovery rate after correcting for age-related changes in the density of the ocular media. These results demonstrated that the rate of scotopic fast adaptation recovery of normal younger and older adults is similar when stimuli are equated for retinal illuminance.

Modelling marine community responses to climate-driven species redistribution to guide monitoring and adaptive ecosystem-based management.

PubMed

Marzloff, Martin Pierre; Melbourne-Thomas, Jessica; Hamon, Katell G; Hoshino, Eriko; Jennings, Sarah; van Putten, Ingrid E; Pecl, Gretta T

2016-07-01

As a consequence of global climate-driven changes, marine ecosystems are experiencing polewards redistributions of species - or range shifts - across taxa and throughout latitudes worldwide. Research on these range shifts largely focuses on understanding and predicting changes in the distribution of individual species. The ecological effects of marine range shifts on ecosystem structure and functioning, as well as human coastal communities, can be large, yet remain difficult to anticipate and manage. Here, we use qualitative modelling of system feedback to understand the cumulative impacts of multiple species shifts in south-eastern Australia, a global hotspot for ocean warming. We identify range-shifting species that can induce trophic cascades and affect ecosystem dynamics and productivity, and evaluate the potential effectiveness of alternative management interventions to mitigate these impacts. Our results suggest that the negative ecological impacts of multiple simultaneous range shifts generally add up. Thus, implementing whole-of-ecosystem management strategies and regular monitoring of range-shifting species of ecological concern are necessary to effectively intervene against undesirable consequences of marine range shifts at the regional scale. Our study illustrates how modelling system feedback with only limited qualitative information about ecosystem structure and range-shifting species can predict ecological consequences of multiple co-occurring range shifts, guide ecosystem-based adaptation to climate change and help prioritise future research and monitoring. © 2016 John Wiley & Sons Ltd.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

PubMed

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

Controlling range expansion in habitat networks by adaptively targeting source populations.

PubMed

Hock, Karlo; Wolff, Nicholas H; Beeden, Roger; Hoey, Jessica; Condie, Scott A; Anthony, Kenneth R N; Possingham, Hugh P; Mumby, Peter J

2016-08-01

Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long-term benefit across the ecosystem by restricting species' potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown-of-thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18-fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected. © 2016 Society for Conservation Biology.

Short-Term Adaptive Modification of Dynamic Ocular Accommodation

PubMed Central

Bharadwaj, Shrikant R.; Vedamurthy, Indu; Schor, Clifton M.

2009-01-01

Purpose Indirect observations suggest that the neural control of accommodation may undergo adaptive recalibration in response to age-related biomechanical changes in the accommodative system. However, there has been no direct demonstration of such an adaptive capability. This investigation was conducted to demonstrate short-term adaptation of accommodative step response dynamics to optically induced changes in neuromuscular demands. Methods Repetitive changes in accommodative effort were induced in 15 subjects (18–34 years) with a double-step adaptation paradigm wherein an initial 2-D step change in blur was followed 350 ms later by either a 2-D step increase in blur (increasing-step paradigm) or a 1.75-D step decrease in blur (decreasing-step paradigm). Peak velocity, peak acceleration, and latency of 2-D single-step test responses were assessed before and after 1.5 hours of training with these paradigms. Results Peak velocity and peak acceleration of 2-D step responses increased after adaptation to the increasing-step paradigm (9/12 subjects), and they decreased after adaptation to the decreasing-step paradigm (4/9 subjects). Adaptive changes in peak velocity and peak acceleration generalized to responses that were smaller (1 D) and larger (3 D) than the 2-D adaptation stimulus. The magnitude of adaptation correlated poorly with the subject's age, but it was significantly negatively correlated with the preadaptation dynamics. Response latency decreased after adaptation, irrespective of the direction of adaptation. Conclusions Short-term adaptive changes in accommodative step response dynamics could be induced, at least in some of our subjects between 18 and 34 years, with a directional bias toward increasing rather than decreasing the dynamics. PMID:19255153

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

Bai, Xian-Xu, E-mail: bai@hfut.edu.cn; Wereley, Norman M.

Magnetorheological (MR) energy absorbers (EAs) are an effective adaptive EA technology with which to maximize shock and vibration isolation. However, to realize maximum performance of the semi-active control system, the off-state (i.e., field off) stroking load of the MREA must be minimized at all speeds, and the dynamic range of the MREA must be maximized at high speed. This study presents a fail-safe MREA (MREA-FS) concept that, can produce a greater dynamic range at all piston speeds. A bias damping force is generated in the MREA-FS using permanent magnetic fields, which enables fail-safe behavior in the case of power failure.more » To investigate the feasibility and capability of the MREA-FS in the context of the semi-active control systems, a single-degree-of-freedom base excited rigid payload is mathematically constructed and simulated with skyhook control.« less

Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor

PubMed Central

Simon Chane, Camille; Ieng, Sio-Hoi; Posch, Christoph; Benosman, Ryad B.

2016-01-01

The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (>143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time. PMID:27642275

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Adaptive, dose-finding phase 2 trial evaluating the safety and efficacy of ABT-089 in mild to moderate Alzheimer disease.

PubMed

Lenz, Robert A; Pritchett, Yili L; Berry, Scott M; Llano, Daniel A; Han, Shu; Berry, Donald A; Sadowsky, Carl H; Abi-Saab, Walid M; Saltarelli, Mario D

2015-01-01

ABT-089, an α4β2 neuronal nicotinic receptor partial agonist, was evaluated for efficacy and safety in mild to moderate Alzheimer disease patients receiving stable doses of acetylcholinesterase inhibitors. This phase 2 double-blind, placebo-controlled, proof-of-concept, and dose-finding study adaptively randomized patients to receive ABT-089 (5, 10, 15, 20, 30, or 35 mg once daily) or placebo for 12 weeks. The primary efficacy endpoint was the Alzheimer's Disease Assessment Scale, cognition subscale (ADAS-Cog) total score. A Bayesian response-adaptive randomization algorithm dynamically assigned allocation probabilities based on interim ADAS-Cog total scores. A normal dynamic linear model for dose-response relationships and a longitudinal model for predicting final ADAS-cog score were employed in the algorithm. Stopping criteria for futility or success were defined. The futility stopping criterion was met, terminating the study with 337 patients randomized. No dose-response relationship was observed and no dose demonstrated statistically significant improvement over placebo on ADAS-Cog or any secondary endpoint. ABT-089 was well tolerated at all dose levels. When administered as adjunctive therapy to acetylcholinesterase inhibitors, ABT-089 was not efficacious in mild to moderate Alzheimer disease. The adaptive study design enabled the examination of a broad dose range, enabled rapid determination of futility, and reduced patient exposure to nonefficacious doses of the investigational compound.

Propagule Limitation, Disparate Habitat Quality, and Variation in Phenotypic Selection at a Local Species Range Boundary

PubMed Central

Moore, Kara A.; Stanton, Maureen L.

2014-01-01

Adaptation to novel conditions beyond current range boundaries requires the presence of suitable sites within dispersal range, but may be impeded when emigrants encounter poor habitat and sharply different selection pressures. We investigated fine-scale spatial heterogeneity in ecological dynamics and selection at a local population boundary of the annual plant Gilia tricolor. In two years, we planted G. tricolor seeds in core habitat, margin habitat at the edge of the local range, and exterior habitat in order to measure spatial and temporal variation in habitat quality, opportunity for selection, and selection on phenotypic traits. We found a striking decline in average habitat quality with distance from the population core, yet some migrant seeds were successful in suitable, unoccupied microsites at and beyond the range boundary. Total and direct selection on four out of five measured phenotypic traits varied across habitat zones, as well as between years. Moreover, the margin habitat often exerted unique selection pressures that were not intermediate between core and exterior habitats. This study reveals that a combination of ecological and evolutionary forces, including propagule limitation, variation in habitat quality and spatial heterogeneity in phenotypic selection may reduce opportunities for adaptive range expansion, even across a very local population boundary. PMID:24717472

Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

PubMed

Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

2017-11-27

We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

High-Resolution Detector For X-Ray Diffraction

NASA Technical Reports Server (NTRS)

Carter, Daniel C.; Withrow, William K.; Pusey, Marc L.; Yost, Vaughn H.

1988-01-01

Proposed x-ray-sensitive imaging detector offers superior spatial resolution, counting-rate capacity, and dynamic range. Instrument based on laser-stimulated luminescence and reusable x-ray-sensitive film. Detector scans x-ray film line by line. Extracts latent image in film and simultaneously erases film for reuse. Used primarily for protein crystallography. Principle adapted to imaging detectors for electron microscopy and fluorescence spectroscopy and general use in astronomy, engineering, and medicine.

Benefits of incorporating the adaptive dynamic range optimization amplification scheme into an assistive listening device for people with mild or moderate hearing loss.

PubMed

Chang, Hung-Yue; Luo, Ching-Hsing; Lo, Tun-Shin; Chen, Hsiao-Chuan; Huang, Kuo-You; Liao, Wen-Huei; Su, Mao-Chang; Liu, Shu-Yu; Wang, Nan-Mai

2017-08-28

This study investigated whether a self-designed assistive listening device (ALD) that incorporates an adaptive dynamic range optimization (ADRO) amplification strategy can surpass a commercially available monaurally worn linear ALD, SM100. Both subjective and objective measurements were implemented. Mandarin Hearing-In-Noise Test (MHINT) scores were the objective measurement, whereas participant satisfaction was the subjective measurement. The comparison was performed in a mixed design (i.e., subjects' hearing status being mild or moderate, quiet versus noisy, and linear versus ADRO scheme). The participants were two groups of hearing-impaired subjects, nine mild and eight moderate, respectively. The results of the ADRO system revealed a significant difference in the MHINT sentence reception threshold (SRT) in noisy environments between monaurally aided and unaided conditions, whereas the linear system did not. The benchmark results showed that the ADRO scheme is effectively beneficial to people who experience mild or moderate hearing loss in noisy environments. The satisfaction rating regarding overall speech quality indicated that the participants were satisfied with the speech quality of both ADRO and linear schemes in quiet environments, and they were more satisfied with ADRO than they with the linear scheme in noisy environments.

The social dynamics of healthy food shopping and store choice in an urban environment.

PubMed

Cannuscio, Carolyn C; Hillier, Amy; Karpyn, Allison; Glanz, Karen

2014-12-01

To respond to the high prevalence of obesity and its associated health consequences, recent food research and policy have focused on neighborhood food environments, especially the links between health and retail mix, proximity of food outlets, and types of foods available. In addition, the social environment exerts important influences on food-related behaviors, through mechanisms like role-modeling, social support, and social norms. This study examined the social dynamics of residents' health-related food-shopping behaviors in 2010-11 in urban Philadelphia, where we conducted 25 semi-structured resident interviews-the foundation for this paper-in addition to 514 structured interviews and a food environment audit. In interviews, participants demonstrated adaptability and resourcefulness in their food shopping; they chose to shop at stores that met a range of social needs. Those needs ranged from practical financial considerations, to fundamental issues of safety, to mundane concerns about convenience, and juggling multiple work and family responsibilities. The majority of participants were highly motivated to adapt their shopping patterns to accommodate personal financial constraints. In addition, they selectively shopped at stores frequented by people who shared their race/ethnicity, income and education, and they sought stores where they had positive interactions with personnel and proprietors. In deciding where to shop in this urban context, participants adapted their routines to avoid unsafe places and the threat of violence. Participants also discussed the importance of convenient stores that allowed for easy parking, accommodation of physical disabilities or special needs, and integration of food shopping into other daily activities like meeting children at school. Food research and policies should explicitly attend to the social dynamics that influence food-shopping behavior. In our social relationships, interactions, and responsibilities, there are countless opportunities to influence-and also to improve-health. Copyright © 2014 Elsevier Ltd. All rights reserved.

Stochasticity versus determinism: consequences for realistic gene regulatory network modelling and evolution.

PubMed

Jenkins, Dafyd J; Stekel, Dov J

2010-02-01

Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.

Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Rohrs, C. E.

1982-01-01

Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.

Characterizing Speech Intelligibility in Noise After Wide Dynamic Range Compression.

PubMed

Rhebergen, Koenraad S; Maalderink, Thijs H; Dreschler, Wouter A

The effects of nonlinear signal processing on speech intelligibility in noise are difficult to evaluate. Often, the effects are examined by comparing speech intelligibility scores with and without processing measured at fixed signal to noise ratios (SNRs) or by comparing the adaptive measured speech reception thresholds corresponding to 50% intelligibility (SRT50) with and without processing. These outcome measures might not be optimal. Measuring at fixed SNRs can be affected by ceiling or floor effects, because the range of relevant SNRs is not know in advance. The SRT50 is less time consuming, has a fixed performance level (i.e., 50% correct), but the SRT50 could give a limited view, because we hypothesize that the effect of most nonlinear signal processing algorithms at the SRT50 cannot be generalized to other points of the psychometric function. In this article, we tested the value of estimating the entire psychometric function. We studied the effect of wide dynamic range compression (WDRC) on speech intelligibility in stationary, and interrupted speech-shaped noise in normal-hearing subjects, using a fast method-based local linear fitting approach and by two adaptive procedures. The measured performance differences for conditions with and without WDRC for the psychometric functions in stationary noise and interrupted speech-shaped noise show that the effects of WDRC on speech intelligibility are SNR dependent. We conclude that favorable and unfavorable effects of WDRC on speech intelligibility can be missed if the results are presented in terms of SRT50 values only.

Avoiding the Water-Climate-Poverty Trap: Adaptive Risk Management for Bangladesh's Coastal Embankments

NASA Astrophysics Data System (ADS)

Hall, J. W.

2015-12-01

Our recent research on water security (Sadoff et al., 2015, Dadson et al., 2015) has revealed the dynamic relationship between water security and human well-being. A version of this dynamic is materialising in the coastal polder areas of Khulna, Bangladesh. Repeated coastal floods increase salinity, wipe out agricultural yields for several years and increase out-migration. As a tool to help inform and target future cycles of investment in improvements to the coastal embankments, in this paper we propose a dynamical model of biophysical processes and human well-being, which downscales our previous research to the Khulna region. State variables in the model include agricultural production, population, life expectancy and child mortality. Possible infrastructure interventions include embankment improvements, groundwater wells and drainage infrastructure. Hazard factors include flooding, salinization and drinking water pollution. Our system model can be used to inform adaptation decision making by testing the dynamical response of the system to a range of possible policy interventions, under uncertain future conditions. The analysis is intended to target investment and enable adaptive resource reallocation based on learning about the system response to interventions over the seven years of our research programme. The methodology and paper will demonstrate the complex interplay of factors that determine system vulnerability to climate change. The role of climate change uncertainties (in terms of mean sea level rise and storm surge frequency) will be evaluated alongside multiple other uncertain factors that determine system response. Adaptive management in a 'learning system' will be promoted as a mechanism for coping with climate uncertainties. References:Dadson, S., Hall, J.W., Garrick, D., Sadoff, C. and Grey, D. Water security, risk and economic growth: lessons from a dynamical systems model, Global Environmental Change, in review.Sadoff, C.W., Hall, J.W., Grey, D., Aerts, J.C.J.H., Ait-Kadi, M., Brown, C., Cox, A., Dadson, S., Garrick, D., Kelman, J., McCornick, P., Ringler, C., Rosegrant, M., Whittington, D. and Wiberg, D. Securing Water, Sustaining Growth: Report of the GWP/OECD Task Force on Water Security and Sustainable Growth, University of Oxford, April 2015, 180pp.

Digital PCR Modeling for Maximal Sensitivity, Dynamic Range and Measurement Precision

PubMed Central

Majumdar, Nivedita; Wessel, Thomas; Marks, Jeffrey

2015-01-01

The great promise of digital PCR is the potential for unparalleled precision enabling accurate measurements for genetic quantification. A challenge associated with digital PCR experiments, when testing unknown samples, is to perform experiments at dilutions allowing the detection of one or more targets of interest at a desired level of precision. While theory states that optimal precision (Po) is achieved by targeting ~1.59 mean copies per partition (λ), and that dynamic range (R) includes the space spanning one positive (λL) to one negative (λU) result from the total number of partitions (n), these results are tempered for the practitioner seeking to construct digital PCR experiments in the laboratory. A mathematical framework is presented elucidating the relationships between precision, dynamic range, number of partitions, interrogated volume, and sensitivity in digital PCR. The impact that false reaction calls and volumetric variation have on sensitivity and precision is next considered. The resultant effects on sensitivity and precision are established via Monte Carlo simulations reflecting the real-world likelihood of encountering such scenarios in the laboratory. The simulations provide insight to the practitioner on how to adapt experimental loading concentrations to counteract any one of these conditions. The framework is augmented with a method of extending the dynamic range of digital PCR, with and without increasing n, via the use of dilutions. An example experiment demonstrating the capabilities of the framework is presented enabling detection across 3.33 logs of starting copy concentration. PMID:25806524

A Telescopic Binary Learning Machine for Training Neural Networks.

PubMed

Brunato, Mauro; Battiti, Roberto

2017-03-01

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

Dynamic implicit 3D adaptive mesh refinement for non-equilibrium radiation diffusion

NASA Astrophysics Data System (ADS)

Philip, B.; Wang, Z.; Berrill, M. A.; Birke, M.; Pernice, M.

2014-04-01

The time dependent non-equilibrium radiation diffusion equations are important for solving the transport of energy through radiation in optically thick regimes and find applications in several fields including astrophysics and inertial confinement fusion. The associated initial boundary value problems that are encountered often exhibit a wide range of scales in space and time and are extremely challenging to solve. To efficiently and accurately simulate these systems we describe our research on combining techniques that will also find use more broadly for long term time integration of nonlinear multi-physics systems: implicit time integration for efficient long term time integration of stiff multi-physics systems, local control theory based step size control to minimize the required global number of time steps while controlling 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.

Chikungunya Virus–Vector Interactions

PubMed Central

Coffey, Lark L.; Failloux, Anna-Bella; Weaver, Scott C.

2014-01-01

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes chikungunya fever, a severe, debilitating disease that often produces chronic arthralgia. Since 2004, CHIKV has emerged in Africa, Indian Ocean islands, Asia, Europe, and the Americas, causing millions of human infections. Central to understanding CHIKV emergence is knowledge of the natural ecology of transmission and vector infection dynamics. This review presents current understanding of CHIKV infection dynamics in mosquito vectors and its relationship to human disease emergence. The following topics are reviewed: CHIKV infection and vector life history traits including transmission cycles, genetic origins, distribution, emergence and spread, dispersal, vector competence, vector immunity and microbial interactions, and co-infection by CHIKV and other arboviruses. The genetics of vector susceptibility and host range changes, population heterogeneity and selection for the fittest viral genomes, dual host cycling and its impact on CHIKV adaptation, viral bottlenecks and intrahost diversity, and adaptive constraints on CHIKV evolution are also discussed. The potential for CHIKV re-emergence and expansion into new areas and prospects for prevention via vector control are also briefly reviewed. PMID:25421891

Sucrose in Aqueous Solution Revisited: 2. Adaptively Biased Molecular Dynamics Simulations and Computational Analysis of NMR Relaxation

PubMed Central

Xia, Junchao; Case, David A.

2012-01-01

We report 100 ns molecular dynamics simulations, at various temperatures, of sucrose in water (with concentrations of sucrose ranging from 0.02 to 4 M), and in a 7:3 water-DMSO mixture. Convergence of the resulting conformational ensembles was checked using adaptive-biased simulations along the glycosidic φ and ψ torsion angles. NMR relaxation parameters, including longitudinal (R1) and transverse (R2) relaxation rates, nuclear Overhauser enhancements (NOE), and generalized order parameter (S2) were computed from the resulting time-correlation functions. The amplitude and time scales of molecular motions change with temperature and concentration in ways that track closely with experimental results, and are consistent with a model in which sucrose conformational fluctuations are limited (with 80–90% of the conformations having φ – ψ values within 20° of an average conformation), but with some important differences in conformation between pure water and DMSO-water mixtures. PMID:22058066

Understanding Climate Adaptation on Public Lands in the Upper Midwest: Implications for Monitoring and Tracking Progress

NASA Astrophysics Data System (ADS)

Anhalt-Depies, Christine M.; Knoot, Tricia Gorby; Rissman, Adena R.; Sharp, Anthony K.; Martin, Karl J.

2016-05-01

There are limited examples of efforts to systematically monitor and track climate change adaptation progress in the context of natural resource management, despite substantial investments in adaptation initiatives. To better understand the status of adaptation within state natural resource agencies, we utilized and problematized a rational decision-making framework to characterize adaptation at the level of public land managers in the Upper Midwest. We conducted in-depth interviews with 29 biologists and foresters to provide an understanding of managers' experiences with, and perceptions of, climate change impacts, efforts towards planning for climate change, and a full range of actions implemented to address climate change. While the majority of managers identified climate change impacts affecting their region, they expressed significant uncertainty in interpreting those signals. Just under half of managers indicated planning efforts are underway, although most planning is remote from local management. Actions already implemented include both forward-looking measures and those aimed at coping with current impacts. In addition, cross-scale dynamics emerged as an important theme related to the overall adaptation process. The results hold implications for tracking future progress on climate change adaptation. Common definitions or measures of adaptation (e.g., presence of planning documents) may need to be reassessed for applicability at the level of public land managers.

Understanding Climate Adaptation on Public Lands in the Upper Midwest: Implications for Monitoring and Tracking Progress.

PubMed

Anhalt-Depies, Christine M; Knoot, Tricia Gorby; Rissman, Adena R; Sharp, Anthony K; Martin, Karl J

2016-05-01

There are limited examples of efforts to systematically monitor and track climate change adaptation progress in the context of natural resource management, despite substantial investments in adaptation initiatives. To better understand the status of adaptation within state natural resource agencies, we utilized and problematized a rational decision-making framework to characterize adaptation at the level of public land managers in the Upper Midwest. We conducted in-depth interviews with 29 biologists and foresters to provide an understanding of managers' experiences with, and perceptions of, climate change impacts, efforts towards planning for climate change, and a full range of actions implemented to address climate change. While the majority of managers identified climate change impacts affecting their region, they expressed significant uncertainty in interpreting those signals. Just under half of managers indicated planning efforts are underway, although most planning is remote from local management. Actions already implemented include both forward-looking measures and those aimed at coping with current impacts. In addition, cross-scale dynamics emerged as an important theme related to the overall adaptation process. The results hold implications for tracking future progress on climate change adaptation. Common definitions or measures of adaptation (e.g., presence of planning documents) may need to be reassessed for applicability at the level of public land managers.

Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations

NASA Technical Reports Server (NTRS)

Chrisochoides, Nikos

1995-01-01

We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.

Multiphase Fluid Dynamics for Spacecraft Applications

NASA Astrophysics Data System (ADS)

Shyy, W.; Sim, J.

2011-09-01

Multiphase flows involving moving interfaces between different fluids/phases are observed in nature as well as in a wide range of engineering applications. With the recent development of high fidelity computational techniques, a number of challenging multiphase flow problems can now be computed. We introduce the basic notion of the main categories of multiphase flow computation; Lagrangian, Eulerian, and Eulerian-Lagrangian techniques to represent and follow interface, and sharp and continuous interface methods to model interfacial dynamics. The marker-based adaptive Eulerian-Lagrangian method, which is one of the most popular methods, is highlighted with microgravity and space applications including droplet collision and spacecraft liquid fuel tank surface stability.

A WSN-based tool for urban and industrial fire-fighting.

PubMed

De San Bernabe Clemente, Alberto; Martínez-de Dios, José Ramiro; Ollero Baturone, Aníbal

2012-11-06

This paper describes a WSN tool to increase safety in urban and industrial fire-fighting activities. Unlike most approaches, we assume that there is no preexisting WSN in the building, which involves interesting advantages but imposes some constraints. The system integrates the following functionalities: fire monitoring, firefighter monitoring and dynamic escape path guiding. It also includes a robust localization method that employs RSSI-range models dynamically trained to cope with the peculiarities of the environment. The training and application stages of the method are applied simultaneously, resulting in significant adaptability. Besides simulations and laboratory tests, a prototype of the proposed system has been validated in close-to-operational conditions.

Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

NASA Technical Reports Server (NTRS)

Rohrs, C. E.; Valavani, L.; Athans, M.; Stein, G.

1985-01-01

This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.

A heuristic model on the role of plasticity in adaptive evolution: plasticity increases adaptation, population viability and genetic variation.

PubMed

Gomez-Mestre, Ivan; Jovani, Roger

2013-11-22

An ongoing new synthesis in evolutionary theory is expanding our view of the sources of heritable variation beyond point mutations of fixed phenotypic effects to include environmentally sensitive changes in gene regulation. This expansion of the paradigm is necessary given ample evidence for a heritable ability to alter gene expression in response to environmental cues. In consequence, single genotypes are often capable of adaptively expressing different phenotypes in different environments, i.e. are adaptively plastic. We present an individual-based heuristic model to compare the adaptive dynamics of populations composed of plastic or non-plastic genotypes under a wide range of scenarios where we modify environmental variation, mutation rate and costs of plasticity. The model shows that adaptive plasticity contributes to the maintenance of genetic variation within populations, reduces bottlenecks when facing rapid environmental changes and confers an overall faster rate of adaptation. In fluctuating environments, plasticity is favoured by selection and maintained in the population. However, if the environment stabilizes and costs of plasticity are high, plasticity is reduced by selection, leading to genetic assimilation, which could result in species diversification. More broadly, our model shows that adaptive plasticity is a common consequence of selection under environmental heterogeneity, and hence a potentially common phenomenon in nature. Thus, taking adaptive plasticity into account substantially extends our view of adaptive evolution.

Contour detection improved by context-adaptive surround suppression.

PubMed

Sang, Qiang; Cai, Biao; Chen, Hao

2017-01-01

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

Adaptive convergence nonuniformity correction algorithm.

PubMed

Qian, Weixian; Chen, Qian; Bai, Junqi; Gu, Guohua

2011-01-01

Nowadays, convergence and ghosting artifacts are common problems in scene-based nonuniformity correction (NUC) algorithms. In this study, we introduce the idea of space frequency to the scene-based NUC. Then the convergence speed factor is presented, which can adaptively change the convergence speed by a change of the scene dynamic range. In fact, the convergence speed factor role is to decrease the statistical data standard deviation. The nonuniformity space relativity characteristic was summarized by plenty of experimental statistical data. The space relativity characteristic was used to correct the convergence speed factor, which can make it more stable. Finally, real and simulated infrared image sequences were applied to demonstrate the positive effect of our algorithm.

Adaptive texture filtering for defect inspection in ultrasound images

NASA Astrophysics Data System (ADS)

Zmola, Carl; Segal, Andrew C.; Lovewell, Brian; Nash, Charles

1993-05-01

The use of ultrasonic imaging to analyze defects and characterize materials is critical in the development of non-destructive testing and non-destructive evaluation (NDT/NDE) tools for manufacturing. To develop better quality control and reliability in the manufacturing environment advanced image processing techniques are useful. For example, through the use of texture filtering on ultrasound images, we have been able to filter characteristic textures from highly-textured C-scan images of materials. The materials have highly regular characteristic textures which are of the same resolution and dynamic range as other important features within the image. By applying texture filters and adaptively modifying their filter response, we have examined a family of filters for removing these textures.

Climate change and pastoralism: impacts, consequences and adaptation.

PubMed

Herrero, M; Addison, J; Bedelian, C; Carabine, E; Havlík, P; Henderson, B; Van De Steeg, J; Thornton, P K

2016-11-01

The authors discuss the main climate change impacts on pastoralist societies, including those on rangelands, livestock and other natural resources, and their extended repercussions on food security, incomes and vulnerability. The impacts of climate change on the rangelands of the globe and on the vulnerability of the people who inhabit them will be severe and diverse, and will require multiple, simultaneous responses. In higher latitudes, the removal of temperature constraints might increase pasture production and livestock productivity, but in tropical arid lands, the impacts are highly location specific, but mostly negative. The authors outline several adaptation options, ranging from implementing new technical practices and diversifying income sources to finding institutional support and introducing new market mechanisms, all of which are pivotal for enhancing the capacity of pastoralists to adapt to climate variability and change. Due to the dynamism of all the changes affecting pastoral societies, strategies that lock pastoral societies into specified development pathways could be maladaptive. Flexible and evolving combinations of practices and policies are the key to successful pastoral adaptation.

Resolving occlusion and segmentation errors in multiple video object tracking

NASA Astrophysics Data System (ADS)

Cheng, Hsu-Yung; Hwang, Jenq-Neng

2009-02-01

In this work, we propose a method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. The proposed framework is able to detect occlusion and segmentation error cases and perform adaptive particle sampling for accurate measurement selection. Compared with traditional particle filter based tracking methods, the proposed method generates particles only when necessary. With the concept of adaptive particle sampling, we can avoid degeneracy problem because the sampling position and range are dynamically determined by parameters that are updated by Kalman filters. There is no need to spend time on processing particles with very small weights. The adaptive appearance for the occluded object refers to the prediction results of Kalman filters to determine the region that should be updated and avoids the problem of using inadequate information to update the appearance under occlusion cases. The experimental results have shown that a small number of particles are sufficient to achieve high positioning and scaling accuracy. Also, the employment of adaptive appearance substantially improves the positioning and scaling accuracy on the tracking results.

A design of an on-orbit radiometric calibration device for high dynamic range infrared remote sensors

NASA Astrophysics Data System (ADS)

Sheng, Yicheng; Jin, Weiqi; Dun, Xiong; Zhou, Feng; Xiao, Si

2017-10-01

With the demand of quantitative remote sensing technology growing, high reliability as well as high accuracy radiometric calibration technology, especially the on-orbit radiometric calibration device has become an essential orientation in term of quantitative remote sensing technology. In recent years, global launches of remote sensing satellites are equipped with innovative on-orbit radiometric calibration devices. In order to meet the requirements of covering a very wide dynamic range and no-shielding radiometric calibration system, we designed a projection-type radiometric calibration device for high dynamic range sensors based on the Schmidt telescope system. In this internal radiometric calibration device, we select the EF-8530 light source as the calibration blackbody. EF-8530 is a high emittance Nichrome (Ni-Cr) reference source. It can operate in steady or pulsed state mode at a peak temperature of 973K. The irradiance from the source was projected to the IRFPA. The irradiance needs to ensure that the IRFPA can obtain different amplitude of the uniform irradiance through the narrow IR passbands and cover the very wide dynamic range. Combining the internal on-orbit radiometric calibration device with the specially designed adaptive radiometric calibration algorithms, an on-orbit dynamic non-uniformity correction can be accomplished without blocking the optical beam from outside the telescope. The design optimizes optics, source design, and power supply electronics for irradiance accuracy and uniformity. The internal on-orbit radiometric calibration device not only satisfies a series of indexes such as stability, accuracy, large dynamic range and uniformity of irradiance, but also has the advantages of short heating and cooling time, small volume, lightweight, low power consumption and many other features. It can realize the fast and efficient relative radiometric calibration without shielding the field of view. The device can applied to the design and manufacture of the scanning infrared imaging system, the infrared remote sensing system, the infrared early-warning satellite, and so on.

A review of human factors challenges of complex adaptive systems: discovering and understanding chaos in human performance.

PubMed

Karwowski, Waldemar

2012-12-01

In this paper, the author explores a need for a greater understanding of the true nature of human-system interactions from the perspective of the theory of complex adaptive systems, including the essence of complexity, emergent properties of system behavior, nonlinear systems dynamics, and deterministic chaos. Human performance, more often than not, constitutes complex adaptive phenomena with emergent properties that exhibit nonlinear dynamical (chaotic) behaviors. The complexity challenges in the design and management of contemporary work systems, including service systems, are explored. Examples of selected applications of the concepts of nonlinear dynamics to the study of human physical performance are provided. Understanding and applications of the concepts of theory of complex adaptive and dynamical systems should significantly improve the effectiveness of human-centered design efforts of a large system of systems. Performance of many contemporary work systems and environments may be sensitive to the initial conditions and may exhibit dynamic nonlinear properties and chaotic system behaviors. Human-centered design of emergent human-system interactions requires application of the theories of nonlinear dynamics and complex adaptive system. The success of future human-systems integration efforts requires the fusion of paradigms, knowledge, design principles, and methodologies of human factors and ergonomics with those of the science of complex adaptive systems as well as modern systems engineering.

How the Dynamics of a Supramolecular Polymer Determines Its Dynamic Adaptivity and Stimuli-Responsiveness: Structure-Dynamics-Property Relationships From Coarse-Grained Simulations.

PubMed

Torchi, Andrea; Bochicchio, Davide; Pavan, Giovanni M

2018-04-12

The rational design of supramolecular polymers that can adapt or respond in time to specific stimuli in a controlled way is interesting for many applications, but this requires understanding the molecular factors that make the material faster or slower in responding to the stimulus. To this end, it is necessary to study the dynamic adaptive properties at submolecular resolution, which is difficult at an experimental level. Here we show coarse-grained molecular dynamics simulations (<5 Å resolution) demonstrating how the dynamic adaptivity and stimuli responsiveness of a supramolecular polymer is controlled by the intrinsic dynamics of the assembly, which is in turn determined by the structure of the monomers. As a representative case, we focus on a water-soluble 1,3,5-benzenetricarboxamide (BTA) supramolecular polymer incorporating (charged) receptor monomers, experimentally seen to undergo dynamic clustering following the superselective binding to a multivalent recruiter. Our simulations show that the dynamic reorganization of the supramolecular structure proceeds via monomer diffusion on the dynamic fiber surface (exchange within the fiber). Rationally changing the structure of the monomers to make the fiber surface more or less dynamic allows tuning the rate of response to the stimulus and of supramolecular reconfiguration. Simple in silico experiments draw a structure-dynamics-property relationship revealing the key factors underpinning the dynamic adaptivity and stimuli-responsiveness of these supramolecular polymers. We come out with clear evidence that to master the bioinspired properties of these fibers, it is necessary to control their intrinsic dynamics, while the high-resolution of our molecular models permits us to show how.

Cellular plasticity enables adaptation to unforeseen cell-cycle rewiring challenges.

PubMed

Katzir, Yair; Stolovicki, Elad; Stern, Shay; Braun, Erez

2012-01-01

The fundamental dynamics of the cell cycle, underlying cell growth and reproduction, were previously found to be robust under a wide range of environmental and internal perturbations. This property was commonly attributed to its network structure, which enables the coordinated interactions among hundreds of proteins. Despite significant advances in deciphering the components and autonomous interactions of this network, understanding the interfaces of the cell cycle with other major cellular processes is still lacking. To gain insight into these interfaces, we used the process of genome-rewiring in yeast by placing an essential metabolic gene HIS3 from the histidine biosynthesis pathway, under the exclusive regulation of different cell-cycle promoters. In a medium lacking histidine and under partial inhibition of the HIS3p, the rewired cells encountered an unforeseen multitasking challenge; the cell-cycle regulatory genes were required to regulate the essential histidine-pathway gene in concert with the other metabolic demands, while simultaneously driving the cell cycle through its proper temporal phases. We show here that chemostat cell populations with rewired cell-cycle promoters adapted within a short time to accommodate the inhibition of HIS3p and stabilized a new phenotypic state. Furthermore, a significant fraction of the population was able to adapt and grow into mature colonies on plates under such inhibiting conditions. The adapted state was shown to be stably inherited across generations. These adaptation dynamics were accompanied by a non-specific and irreproducible genome-wide transcriptional response. Adaptation of the cell-cycle attests to its multitasking capabilities and flexible interface with cellular metabolic processes and requirements. Similar adaptation features were found in our previous work when rewiring HIS3 to the GAL system and switching cells from galactose to glucose. Thus, at the basis of cellular plasticity is the emergence of a yet-unknown general, non-specific mechanism allowing fast inherited adaptation to unforeseen challenges.

The shape and temporal dynamics of phylogenetic trees arising from geographic speciation.

PubMed

Pigot, Alex L; Phillimore, Albert B; Owens, Ian P F; Orme, C David L

2010-12-01

Phylogenetic trees often depart from the expectations of stochastic models, exhibiting imbalance in diversification among lineages and slowdowns in the rate of lineage accumulation through time. Such departures have led to a widespread perception that ecological differences among species or adaptation and subsequent niche filling are required to explain patterns of diversification. However, a key element missing from models of diversification is the geographical context of speciation and extinction. In this study, we develop a spatially explicit model of geographic range evolution and cladogenesis, where speciation arises via vicariance or peripatry, and explore the effects of these processes on patterns of diversification. We compare the results with those observed in 41 reconstructed avian trees. Our model shows that nonconstant rates of speciation and extinction are emergent properties of the apportioning of geographic ranges that accompanies speciation. The dynamics of diversification exhibit wide variation, depending on the mode of speciation, tendency for range expansion, and rate of range evolution. By varying these parameters, the model is able to capture many, but not all, of the features exhibited by birth-death trees and extant bird clades. Under scenarios with relatively stable geographic ranges, strong slowdowns in diversification rates are produced, with faster rates of range dynamics leading to constant or accelerating rates of apparent diversification. A peripatric model of speciation with stable ranges also generates highly unbalanced trees typical of bird phylogenies but fails to produce realistic range size distributions among the extant species. Results most similar to those of a birth-death process are reached under a peripatric speciation scenario with highly volatile range dynamics. Taken together, our results demonstrate that considering the geographical context of speciation and extinction provides a more conservative null model of diversification and offers a very different perspective on the phylogenetic patterns expected in the absence of ecology.

Structure and dynamics of GeoCyp: a thermophilic cyclophilin with a novel substrate binding mechanism that functions efficiently at low temperatures

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

Holliday, Michael; Camilloni, Carlo; Armstrong, Geoffrey S.

2015-05-26

Thermophilic proteins have found extensive use in research and industrial applications due to their high stability and functionality at elevated temperatures while simultaneously providing valuable insight into our understanding of protein folding, stability, dynamics, and function. Cyclophilins, a ubiquitously expressed family of peptidyl-prolyl isomerases with a range of biological functions and disease associations, have been utilized both for conferring stress tolerances and in exploring the link between conformational dynamics and enzymatic function. To date, however, no active thermophilic cyclophilin has been fully biophysically characterized. Here, we determine the structure of a thermophilic cyclophilin (GeoCyp) from Geobacillus kaustophilus, characterize its dynamicmore » motions over several timescales using an array of methodologies that include chemical shift-based methods and relaxation experiments over a range of temperatures, and measure catalytic activity over a range of temperatures in order to compare structure, dynamics, and function to a mesophilic counterpart, human Cyclophilin A (CypA). Unlike most thermophile/mesophile pairs, GeoCyp catalysis is not substantially impaired at low temperatures as compared to CypA, retaining ~70% of the activity of its mesophilic counterpart. Examination of substrate-bound ensembles reveals a mechanism by which the two cyclophilins may have adapted to their environments through altering dynamic loop motions and a critical residue that acts as a clamp to regulate substrate binding differentially in CypA and GeoCyp. Despite subtle differences in conformational movements, dynamics over fast (ps-ns) and slow (μs) timescales are largely conserved between the two proteins.« less

Dynamic mesh adaption for triangular and tetrahedral grids

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Strawn, Roger

1993-01-01

The following topics are discussed: requirements for dynamic mesh adaption; linked-list data structure; edge-based data structure; adaptive-grid data structure; three types of element subdivision; mesh refinement; mesh coarsening; additional constraints for coarsening; anisotropic error indicator for edges; unstructured-grid Euler solver; inviscid 3-D wing; and mesh quality for solution-adaptive grids. The discussion is presented in viewgraph form.

Nonlinear dynamics of team performance and adaptability in emergency response.

PubMed

Guastello, Stephen J

2010-04-01

The impact of team size and performance feedback on adaptation levels and performance of emergency response (ER) teams was examined to introduce a metric for quantifying adaptation levels based on nonlinear dynamical systems (NDS) theory. NDS principles appear in reports surrounding Hurricane Katrina, earthquakes, floods, a disease epidemic, and the Southeast Asian tsunami. They are also intrinsic to coordination within teams, adaptation levels, and performance in dynamic decision processes. Performance was measured in a dynamic decision task in which ER teams of different sizes worked against an attacker who was trying to destroy a city (total N = 225 undergraduates). The complexity of teams' and attackers' adaptation strategies and the role of the opponents' performance were assessed by nonlinear regression analysis. An optimal group size for team performance was identified. Teams were more readily influenced by the attackers' performance than vice versa. The adaptive capabilities of attackers and teams were impaired by their opponents in some conditions. ER teams should be large enough to contribute a critical mass of ideas but not so large that coordination would be compromised. ER teams used self-organized strategies that could have been more adaptive, whereas attackers used chaotic strategies. The model and results are applicable to ER processes or training maneuvers involving dynamic decisions but could be limited to nonhierarchical groups.

Dynamic accommodation responses following adaptation to defocus.

PubMed

Cufflin, Matthew P; Mallen, Edward A H

2008-10-01

Adaptation to defocus is known to influence the subjective sensitivity to blur in both emmetropes and myopes. Blur is a major contributing factor in the closed-loop dynamic accommodation response. Previous investigations have examined the magnitude of the accommodation response following blur adaptation. We have investigated whether a period of blur adaptation influences the dynamic accommodation response to step and sinusoidal changes in target vergence. Eighteen subjects (six emmetropes, six early onset myopes, and six late onset myopes) underwent 30 min of adaptation to 0.00 D (control), +1.00 D or +3.00 D myopic defocus. Following this adaptation period, accommodation responses to a 2.00 D step change and 2.00 D sinusoidal change (0.2 Hz) in target vergence were recorded continuously using an autorefractor. Adaptation to defocus failed to influence accommodation latency times, but did influence response times to a step change in target vergence. Adaptation to both +1.00 and +3.00 D induced significant increases in response times (p = 0.002 and p = 0.012, respectively) and adaptation to +3.00 D increased the change in accommodation response magnitude (p = 0.014) for a 2.00 D step change in demand. Blur adaptation also significantly increased the peak-to-peak phase lag for accommodation responses to a sinusoidally oscillating target, although failed to influence the accommodation gain. These changes in accommodative response were equivalent across all refractive groups. Adaptation to a degraded stimulus causes an increased level of accommodation for dynamic targets moving towards an observer and increases response times and phase lags. It is suggested that the contrast constancy theory may explain these changes in dynamic behavior.

The Role of Clonal Interference in the Evolutionary Dynamics of Plasmid-Host Adaptation

PubMed Central

Hughes, Julie M.; Lohman, Brian K.; Deckert, Gail E.; Nichols, Eric P.; Settles, Matt; Abdo, Zaid; Top, Eva M.

2012-01-01

ABSTRACT Promiscuous plasmids replicate in a wide range of bacteria and therefore play a key role in the dissemination of various host-beneficial traits, including antibiotic resistance. Despite the medical relevance, little is known about the evolutionary dynamics through which drug resistance plasmids adapt to new hosts and thereby persist in the absence of antibiotics. We previously showed that the incompatibility group P-1 (IncP-1) minireplicon pMS0506 drastically improved its stability in novel host Shewanella oneidensis MR-1 after 1,000 generations under antibiotic selection for the plasmid. The only mutations found were those affecting the N terminus of the plasmid replication initiation protein TrfA1. Our aim in this study was to gain insight into the dynamics of plasmid evolution. Changes in stability and genotype frequencies of pMS0506 were monitored in evolving populations of MR-1 (pMS0506). Genotypes were determined by sequencing trfA1 amplicons from individual clones and by 454 pyrosequencing of whole plasmids from entire populations. Stability of pMS0506 drastically improved by generation 200. Many evolved plasmid genotypes with point mutations as well as in-frame and frameshift deletions and duplications in trfA1 were observed in all lineages with both sequencing methods. Strikingly, multiple genotypes were simultaneously present at high frequencies (>10%) in each population. Their relative abundances changed over time, but after 1,000 generations only one or two genotypes dominated the populations. This suggests that hosts with different plasmid genotypes were competing with each other, thus affecting the evolutionary trajectory. Plasmids can thus rapidly improve their stability, and clonal interference plays a significant role in plasmid-host adaptation dynamics. PMID:22761390

Molecular Mechanisms That Underlie the Dynamic Adaptation of Innate Monocyte Memory to Varying Stimulant Strength of TLR Ligands.

PubMed

Yuan, Ruoxi; Geng, Shuo; Li, Liwu

2016-01-01

In adaptation to rising stimulant strength, innate monocytes can be dynamically programed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programing may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS), the model stimulant of toll-like-receptor 4 (TLR4), we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor, interferon regulatory factor 5 (IRF5), and reduced levels of transcriptional modulator B lymphocyte-induced maturation protein-1 (Blimp-1). Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

Evolution and selection of river networks: Statics, dynamics, and complexity

PubMed Central

Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R.; Maritan, Amos; Rodriguez-Iturbe, Ignacio

2014-01-01

Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics—every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept. PMID:24550264

Combining facial dynamics with appearance for age estimation.

PubMed

Dibeklioglu, Hamdi; Alnajar, Fares; Ali Salah, Albert; Gevers, Theo

2015-06-01

Estimating the age of a human from the captured images of his/her face is a challenging problem. In general, the existing approaches to this problem use appearance features only. In this paper, we show that in addition to appearance information, facial dynamics can be leveraged in age estimation. We propose a method to extract and use dynamic features for age estimation, using a person's smile. Our approach is tested on a large, gender-balanced database with 400 subjects, with an age range between 8 and 76. In addition, we introduce a new database on posed disgust expressions with 324 subjects in the same age range, and evaluate the reliability of the proposed approach when used with another expression. State-of-the-art appearance-based age estimation methods from the literature are implemented as baseline. We demonstrate that for each of these methods, the addition of the proposed dynamic features results in statistically significant improvement. We further propose a novel hierarchical age estimation architecture based on adaptive age grouping. We test our approach extensively, including an exploration of spontaneous versus posed smile dynamics, and gender-specific age estimation. We show that using spontaneity information reduces the mean absolute error by up to 21%, advancing the state of the art for facial age estimation.

Policy tree optimization for adaptive management of water resources systems

NASA Astrophysics Data System (ADS)

Herman, Jonathan; Giuliani, Matteo

2017-04-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points" that suggest the need of updating the policy. However, there remains a need for a general method to optimize the choice of the signposts to be used and their threshold values. This work contributes a general framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. Given a set of feature variables (e.g., reservoir level, inflow observations, inflow forecasts), the resulting policy defines both the optimal reservoir operations and the conditions under which such operations should be triggered. We demonstrate the approach using Folsom Reservoir (California) as a case study, in which operating policies must balance the risk of both floods and droughts. Numerical results show that the tree-based policies outperform the ones designed via Dynamic Programming. In addition, they display good adaptive capacity to the changing climate, successfully adapting the reservoir operations across a large set of uncertain climate scenarios.

Adaptive random walks on the class of Web graphs

NASA Astrophysics Data System (ADS)

Tadić, B.

2001-09-01

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [B. Tadić, Physica A 293, 273 (2001)], and are characterized by a pair of power-law distributions of out- and in-degree for each value of the parameter β, which measures the degree of rewiring in the graph. The walker adapts its move strategy according to locally available information both on out-degree of the visited node and in-degree of target node. A standard random walk, on the other hand, uses the out-degree only. We compute the distribution of connected subgraphs visited by an ensemble of walkers, the average access time and survival probability of the walks. We discuss these properties of the walk dynamics relative to the changes in the global graph structure when the control parameter β is varied. For β≥ 3, corresponding to the world-wide Web, the access time of the walk to a given level of hierarchy on the graph is much shorter compared to the standard random walk on the same graph. By reducing the amount of rewiring towards rigidity limit β↦βc≲ 0.1, corresponding to the range of naturally occurring biochemical networks, the survival probability of adaptive and standard random walk become increasingly similar. The adaptive random walk can be used as an efficient message-passing algorithm on this class of graphs for large degree of rewiring.

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999. Pt. 2

NASA Technical Reports Server (NTRS)

Whitlow, Jr., Woodrow (Editor); Todd, Emily N. (Editor)

1999-01-01

The proceedings of a workshop sponsored by the Confederation of European Aerospace Societies (CEAS), the American Institute of Aeronautics and Astronautics (AIAA), the National Aeronautics and Space Administration (NASA), Washington, D.C., and the Institute for Computer Applications in Science and Engineering (ICASE), Hampton, Virginia, and held in Williamsburg, Virginia June 22-25, 1999 represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

Dynamically Reconfigurable Systolic Array Accelerator

NASA Technical Reports Server (NTRS)

Dasu, Aravind; Barnes, Robert

2012-01-01

A polymorphic systolic array framework has been developed that works in conjunction with an embedded microprocessor on a field-programmable gate array (FPGA), which allows for dynamic and complimentary scaling of acceleration levels of two algorithms active concurrently on the FPGA. Use is made of systolic arrays and a hardware-software co-design to obtain an efficient multi-application acceleration system. The flexible and simple framework allows hosting of a broader range of algorithms, and is extendable to more complex applications in the area of aerospace embedded systems. FPGA chips can be responsive to realtime demands for changing applications needs, but only if the electronic fabric can respond fast enough. This systolic array framework allows for rapid partial and dynamic reconfiguration of the chip in response to the real-time needs of scalability, and adaptability of executables.

Dynamically variable negative stiffness structures.

PubMed

Churchill, Christopher B; Shahan, David W; Smith, Sloan P; Keefe, Andrew C; McKnight, Geoffrey P

2016-02-01

Variable stiffness structures that enable a wide range of efficient load-bearing and dexterous activity are ubiquitous in mammalian musculoskeletal systems but are rare in engineered systems because of their complexity, power, and cost. We present a new negative stiffness-based load-bearing structure with dynamically tunable stiffness. Negative stiffness, traditionally used to achieve novel response from passive structures, is a powerful tool to achieve dynamic stiffness changes when configured with an active component. Using relatively simple hardware and low-power, low-frequency actuation, we show an assembly capable of fast (<10 ms) and useful (>100×) dynamic stiffness control. This approach mitigates limitations of conventional tunable stiffness structures that exhibit either small (<30%) stiffness change, high friction, poor load/torque transmission at low stiffness, or high power active control at the frequencies of interest. We experimentally demonstrate actively tunable vibration isolation and stiffness tuning independent of supported loads, enhancing applications such as humanoid robotic limbs and lightweight adaptive vibration isolators.

Systems and Methods for Derivative-Free Adaptive Control

NASA Technical Reports Server (NTRS)

Calise, Anthony J. (Inventor); Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor)

2015-01-01

An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

Cultural ecologies of adaptive vs. maladaptive traits: A simple nonlinear model

NASA Astrophysics Data System (ADS)

Antoci, Angelo; Russu, Paolo; Sacco, Pier Luigi

2018-05-01

In this paper, we generalize a model by Enquist and Ghirlanda [12] to analyze the "macro" dynamics of cumulative culture in a context where there is a coexistence of adaptive and maladaptive cultural traits. In particular, we introduce a different, nonlinear specification of the main processes at work in the cumulative culture dynamics: imperfect transmission of traits, generation of new traits, and switches from adaptive to maladaptive and vice-versa. We find that the system exhibits a variety of dynamic behaviors where the crucial force is the switching between the adaptive and maladaptive nature of a certain trait, with the other processes playing a modulating role. We identify in particular a number of dynamic regimes with distinctive characteristics.

Neural network based adaptive output feedback control: Applications and improvements

NASA Astrophysics Data System (ADS)

Kutay, Ali Turker

Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in simulation, a fictitious actuator model is developed that fits experimentally observed characteristics of flow control actuators in static flight conditions as well as possible coupling effects between actuation, the dynamics of flow field, and the rigid body dynamics of the vehicle.

Electrically tunable metasurface perfect absorbers for ultrathin mid-infrared optical modulators.

PubMed

Yao, Yu; Shankar, Raji; Kats, Mikhail A; Song, Yi; Kong, Jing; Loncar, Marko; Capasso, Federico

2014-11-12

Dynamically reconfigurable metasurfaces open up unprecedented opportunities in applications such as high capacity communications, dynamic beam shaping, hyperspectral imaging, and adaptive optics. The realization of high performance metasurface-based devices remains a great challenge due to very limited tuning ranges and modulation depths. Here we show that a widely tunable metasurface composed of optical antennas on graphene can be incorporated into a subwavelength-thick optical cavity to create an electrically tunable perfect absorber. By switching the absorber in and out of the critical coupling condition via the gate voltage applied on graphene, a modulation depth of up to 100% can be achieved. In particular, we demonstrated ultrathin (thickness < λ0/10) high speed (up to 20 GHz) optical modulators over a broad wavelength range (5-7 μm). The operating wavelength can be scaled from the near-infrared to the terahertz by simply tailoring the metasurface and cavity dimensions.

The dynamics of mergers and acquisitions: ancestry as the seminal determinant

PubMed Central

Viegas, Eduardo; Cockburn, Stuart P.; Jensen, Henrik J.; West, Geoffrey B.

2014-01-01

Understanding the fundamental mechanisms behind the complex landscape of corporate mergers and acquisitions is of crucial importance to economies across the world. Adapting ideas from the fields of complexity and evolutionary dynamics to analyse business ecosystems, we show here that ancestry, i.e. the cumulative sum of historical mergers across all ancestors, is the key characteristic to company mergers and acquisitions. We verify this by comparing an agent-based model to an extensive range of business data, covering the period from the 1830s to the present day and a range of industries and geographies. This seemingly universal mechanism leads to imbalanced business ecosystems, with the emergence of a few very large, but sluggish ‘too big to fail’ entities, and very small, niche entities, thereby creating a paradigm where a configuration akin to effective oligopoly or monopoly is a likely outcome for free market systems. PMID:25383025

The dynamics of mergers and acquisitions: ancestry as the seminal determinant.

PubMed

Viegas, Eduardo; Cockburn, Stuart P; Jensen, Henrik J; West, Geoffrey B

2014-11-08

Understanding the fundamental mechanisms behind the complex landscape of corporate mergers and acquisitions is of crucial importance to economies across the world. Adapting ideas from the fields of complexity and evolutionary dynamics to analyse business ecosystems, we show here that ancestry, i.e. the cumulative sum of historical mergers across all ancestors, is the key characteristic to company mergers and acquisitions. We verify this by comparing an agent-based model to an extensive range of business data, covering the period from the 1830s to the present day and a range of industries and geographies. This seemingly universal mechanism leads to imbalanced business ecosystems, with the emergence of a few very large, but sluggish 'too big to fail' entities, and very small, niche entities, thereby creating a paradigm where a configuration akin to effective oligopoly or monopoly is a likely outcome for free market systems.

Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2006-12-01

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.

Stress and strain in the contractile and cytoskeletal filaments of airway smooth muscle.

PubMed

Deng, Linhong; Bosse, Ynuk; Brown, Nathan; Chin, Leslie Y M; Connolly, Sarah C; Fairbank, Nigel J; King, Greg G; Maksym, Geoffrey N; Paré, Peter D; Seow, Chun Y; Stephen, Newman L

2009-10-01

Stress and strain are omnipresent in the lung due to constant lung volume fluctuation associated with respiration, and they modulate the phenotype and function of all cells residing in the airways including the airway smooth muscle (ASM) cell. There is ample evidence that the ASM cell is very sensitive to its physical environment, and can alter its structure and/or function accordingly, resulting in either desired or undesired consequences. The forces that are either conferred to the ASM cell due to external stretching or generated inside the cell must be borne and transmitted inside the cytoskeleton (CSK). Thus, maintaining appropriate levels of stress and strain within the CSK is essential for maintaining normal function. Despite the importance, the mechanisms regulating/dysregulating ASM cytoskeletal filaments in response to stress and strain remained poorly understood until only recently. For example, it is now understood that ASM length and force are dynamically regulated, and both can adapt over a wide range of length, rendering ASM one of the most malleable living tissues. The malleability reflects the CSK's dynamic mechanical properties and plasticity, both of which strongly interact with the loading on the CSK, and all together ultimately determines airway narrowing in pathology. Here we review the latest advances in our understanding of stress and strain in ASM cells, including the organization of contractile and cytoskeletal filaments, range and adaptation of functional length, structural and functional changes of the cell in response to mechanical perturbation, ASM tone as a mediator of strain-induced responses, and the novel glassy dynamic behaviors of the CSK in relation to asthma pathophysiology.

A unique charge-coupled device/xenon arc lamp based imaging system for the accurate detection and quantitation of multicolour fluorescence.

PubMed

Spibey, C A; Jackson, P; Herick, K

2001-03-01

In recent years the use of fluorescent dyes in biological applications has dramatically increased. The continual improvement in the capabilities of these fluorescent dyes demands increasingly sensitive detection systems that provide accurate quantitation over a wide linear dynamic range. In the field of proteomics, the detection, quantitation and identification of very low abundance proteins are of extreme importance in understanding cellular processes. Therefore, the instrumentation used to acquire an image of such samples, for spot picking and identification by mass spectrometry, must be sensitive enough to be able, not only, to maximise the sensitivity and dynamic range of the staining dyes but, as importantly, adapt to the ever changing portfolio of fluorescent dyes as they become available. Just as the available fluorescent probes are improving and evolving so are the users application requirements. Therefore, the instrumentation chosen must be flexible to address and adapt to those changing needs. As a result, a highly competitive market for the supply and production of such dyes and the instrumentation for their detection and quantitation have emerged. The instrumentation currently available is based on either laser/photomultiplier tube (PMT) scanning or lamp/charge-coupled device (CCD) based mechanisms. This review briefly discusses the advantages and disadvantages of both System types for fluorescence imaging, gives a technical overview of CCD technology and describes in detail a unique xenon/are lamp CCD based instrument, from PerkinElmer Life Sciences. The Wallac-1442 ARTHUR is unique in its ability to scan both large areas at high resolution and give accurate selectable excitation over the whole of the UV/visible range. It operates by filtering both the excitation and emission wavelengths, providing optimal and accurate measurement and quantitation of virtually any available dye and allows excellent spectral resolution between different fluorophores. This flexibility and excitation accuracy is key to multicolour applications and future adaptation of the instrument to address the application requirements and newly emerging dyes.

A model of anuran auditory periphery reveals frequency-dependent adaptation to be a contributing mechanism for two-tone suppression and amplitude modulation coding.

PubMed

Wotton, J M; Ferragamo, M J

2011-10-01

Anuran auditory nerve fibers (ANF) tuned to low frequencies display unusual frequency-dependent adaptation which results in a more phasic response to signals above best frequency (BF) and a more tonic response to signals below. A network model of the first two layers of the anuran auditory system was used to test the contribution of this dynamic peripheral adaptation on two-tone suppression and amplitude modulation (AM) tuning. The model included a peripheral sandwich component, leaky-integrate-and-fire cells and adaptation was implemented by means of a non-linear increase in threshold weighted by the signal frequency. The results of simulations showed that frequency-dependent adaptation was both necessary and sufficient to produce high-frequency-side two-tone suppression for the ANF and cells of the dorsal medullary nucleus (DMN). It seems likely that both suppression and this dynamic adaptation share a common mechanism. The response of ANFs to AM signals was influenced by adaptation and carrier frequency. Vector strength synchronization to an AM signal improved with increased adaptation. The spike rate response to a carrier at BF was the expected flat function with AM rate. However, for non-BF carrier frequencies the response showed a weak band-pass pattern due to the influence of signal sidebands and adaptation. The DMN received inputs from three ANFs and when the frequency tuning of inputs was near the carrier, then the rate response was a low-pass or all-pass shape. When most of the inputs were biased above or below the carrier, then band-pass responses were observed. Frequency-dependent adaptation enhanced the band-pass tuning for AM rate, particularly when the response of the inputs was predominantly phasic for a given carrier. Different combinations of inputs can therefore bias a DMN cell to be especially well suited to detect specific ranges of AM rates for a particular carrier frequency. Such selection of inputs would clearly be advantageous to the frog in recognizing distinct spectral and temporal parameters in communication calls. Copyright © 2011 Elsevier B.V. All rights reserved.

An integration time adaptive control method for atmospheric composition detection of occultation

NASA Astrophysics Data System (ADS)

Ding, Lin; Hou, Shuai; Yu, Fei; Liu, Cheng; Li, Chao; Zhe, Lin

2018-01-01

When sun is used as the light source for atmospheric composition detection, it is necessary to image sun for accurate identification and stable tracking. In the course of 180 second of the occultation, the magnitude of sun light intensity through the atmosphere changes greatly. It is nearly 1100 times illumination change between the maximum atmospheric and the minimum atmospheric. And the process of light change is so severe that 2.9 times per second of light change can be reached. Therefore, it is difficult to control the integration time of sun image camera. In this paper, a novel adaptive integration time control method for occultation is presented. In this method, with the distribution of gray value in the image as the reference variable, and the concepts of speed integral PID control, the integration time adaptive control problem of high frequency imaging. The large dynamic range integration time automatic control in the occultation can be achieved.

A DAFT DL_POLY distributed memory adaptation of the Smoothed Particle Mesh Ewald method

NASA Astrophysics Data System (ADS)

Bush, I. J.; Todorov, I. T.; Smith, W.

2006-09-01

The Smoothed Particle Mesh Ewald method [U. Essmann, L. Perera, M.L. Berkowtz, T. Darden, H. Lee, L.G. Pedersen, J. Chem. Phys. 103 (1995) 8577] for calculating long ranged forces in molecular simulation has been adapted for the parallel molecular dynamics code DL_POLY_3 [I.T. Todorov, W. Smith, Philos. Trans. Roy. Soc. London 362 (2004) 1835], making use of a novel 3D Fast Fourier Transform (DAFT) [I.J. Bush, The Daresbury Advanced Fourier transform, Daresbury Laboratory, 1999] that perfectly matches the Domain Decomposition (DD) parallelisation strategy [W. Smith, Comput. Phys. Comm. 62 (1991) 229; M.R.S. Pinches, D. Tildesley, W. Smith, Mol. Sim. 6 (1991) 51; D. Rapaport, Comput. Phys. Comm. 62 (1991) 217] of the DL_POLY_3 code. In this article we describe software adaptations undertaken to import this functionality and provide a review of its performance.

Moving HAIRS: Towards adaptive, homeostatic materials

NASA Astrophysics Data System (ADS)

Aizenberg, Joanna

Dynamic structures that respond reversibly to changes in their environment are central to self-regulating thermal and lighting systems, targeted drug delivery, sensors, and self-propelled locomotion. Since an adaptive change requires energy input, an ideal strategy would be to design materials that harvest energy directly from the environment and use it to drive an appropriate response. This lecture will present the design of a novel class of reconfigurable materials that use surfaces bearing arrays of nanostructures put in motion by environment-responsive gels. Their unique hybrid architecture, and chemical and mechanical properties can be optimized to confer a wide range of adaptive behaviors. Using both experimental and modeling approaches, we are developing these hydrogel-actuated integrated responsive systems (HAIRS) as new materials with reversible optical and wetting properties, as a multifunctional platform for controlling cell differentiation and function, and as a first homeostatic system with autonomous self-regulation.

Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

NASA Astrophysics Data System (ADS)

Orra, Kashfull; Choudhury, Sounak K.

2016-12-01

The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

Smoothed Biasing Forces Yield Unbiased Free Energies with the Extended-System Adaptive Biasing Force Method

PubMed Central

2016-01-01

We report a theoretical description and numerical tests of the extended-system adaptive biasing force method (eABF), together with an unbiased estimator of the free energy surface from eABF dynamics. Whereas the original ABF approach uses its running estimate of the free energy gradient as the adaptive biasing force, eABF is built on the idea that the exact free energy gradient is not necessary for efficient exploration, and that it is still possible to recover the exact free energy separately with an appropriate estimator. eABF does not directly bias the collective coordinates of interest, but rather fictitious variables that are harmonically coupled to them; therefore is does not require second derivative estimates, making it easily applicable to a wider range of problems than ABF. Furthermore, the extended variables present a smoother, coarse-grain-like sampling problem on a mollified free energy surface, leading to faster exploration and convergence. We also introduce CZAR, a simple, unbiased free energy estimator from eABF trajectories. eABF/CZAR converges to the physical free energy surface faster than standard ABF for a wide range of parameters. PMID:27959559

Dynamic regulation of partner abundance mediates response of reef coral symbioses to environmental change.

PubMed

Cunning, R; Vaughan, N; Gillette, P; Capo, T R; Matté, J L; Baker, A C

2015-05-01

Regulating partner abunclance may allow symmotic organisms to mediate interaction outcomes, facilitating adaptive responses to environmental change. To explore the capacity for-adaptive regulation in an ecologically important endosymbiosis, we studied the population dynamics of symbiotic algae in reef-building corals under different abiotic contexts. We found high natural variability in symbiont abundance in corals across reefs, but this variability converged to different symbiont-specific abundances when colonies were maintained under constant conditions. When conditions changed seasonally, symbiont abundance readjusted to new equilibria. We explain these patterns using an a priori model of symbiotic costs and benefits to the coral host, which shows that the observed changes in symbiont abundance are consistent with the maximization of interaction benefit under different environmental conditions. These results indicate that, while regulating symbiont abundance helps hosts sustain maximum benefit in a dynamic environment, spatiotemporal variation in abiotic factors creates a broad range of symbiont abundances (and interaction outcomes) among corals that may account for observed natural variability in performance (e.g., growth rate) and stress tolerance (e.g., bleaching susceptibility). This cost or benefit framework provides a new perspective on the dynamic regulation of reef coral symbioses and illustrates that the dependence of interaction outcomes on biotic and abiotic contexts may be important in understanding how diverse mutualisms respond to environmental change.

Learning dynamics in social dilemmas

PubMed Central

Macy, Michael W.; Flache, Andreas

2002-01-01

The Nash equilibrium, the main solution concept in analytical game theory, cannot make precise predictions about the outcome of repeated mixed-motive games. Nor can it tell us much about the dynamics by which a population of players moves from one equilibrium to another. These limitations, along with concerns about the cognitive demands of forward-looking rationality, have motivated efforts to explore backward-looking alternatives to analytical game theory. Most of the effort has been invested in evolutionary models of population dynamics. We shift attention to a learning-theoretic alternative. Computational experiments with adaptive agents identify a fundamental solution concept for social dilemmas–−stochastic collusion–−based on a random walk from a self-limiting noncooperative equilibrium into a self-reinforcing cooperative equilibrium. However, we show that this solution is viable only within a narrow range of aspiration levels. Below the lower threshold, agents are pulled into a deficient equilibrium that is a stronger attractor than mutual cooperation. Above the upper threshold, agents are dissatisfied with mutual cooperation. Aspirations that adapt with experience (producing habituation to stimuli) do not gravitate into the window of viability; rather, they are the worst of both worlds. Habituation destabilizes cooperation and stabilizes defection. Results from the two-person problem suggest that applications to multiplex and embedded relationships will yield unexpected insights into the global dynamics of cooperation in social dilemmas. PMID:12011402

Development of a Bayesian response-adaptive trial design for the Dexamethasone for Excessive Menstruation study.

PubMed

Holm Hansen, Christian; Warner, Pamela; Parker, Richard A; Walker, Brian R; Critchley, Hilary Od; Weir, Christopher J

2017-12-01

It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. This article describes the preparatory simulation study for a Bayesian response-adaptive dose-finding trial design. Dexamethasone for Excessive Menstruation aims to assess the efficacy of Dexamethasone in reducing excessive menstrual bleeding and to determine the best dose for further study. To maximise learning about the dose response, patients receive placebo or an active dose with randomisation probabilities adapting based on evidence from patients already recruited. The dose-response relationship is estimated using a flexible Bayesian Normal Dynamic Linear Model. Several competing design options were considered including: number of doses, proportion assigned to placebo, adaptation criterion, and number and timing of adaptations. We performed a fractional factorial study using SAS software to simulate virtual trial data for candidate adaptive designs under a variety of scenarios and to invoke WinBUGS for Bayesian model estimation. We analysed the simulated trial results using Normal linear models to estimate the effects of each design feature on empirical type I error and statistical power. Our readily-implemented approach using widely available statistical software identified a final design which performed robustly across a range of potential trial scenarios.

Thermostatistically approaching living systems: Boltzmann Gibbs or nonextensive statistical mechanics?

NASA Astrophysics Data System (ADS)

Tsallis, Constantino

2006-03-01

Boltzmann-Gibbs ( BG) statistical mechanics is, since well over one century, successfully used for many nonlinear dynamical systems which, in one way or another, exhibit strong chaos. A typical case is a classical many-body short-range-interacting Hamiltonian system (e.g., the Lennard-Jones model for a real gas at moderately high temperature). Its Lyapunov spectrum (which characterizes the sensitivity to initial conditions) includes positive values. This leads to ergodicity, the stationary state being thermal equilibrium, hence standard applicability of the BG theory is verified. The situation appears to be of a different nature for various phenomena occurring in living organisms. Indeed, such systems exhibit a complexity which does not really accommodate with this standard dynamical behavior. Life appears to emerge and evolve in a kind of delicate situation, at the frontier between large order (low adaptability and long memory; typically characterized by regular dynamics, hence only nonpositive Lyapunov exponents) and large disorder (high adaptability and short memory; typically characterized by strong chaos, hence at least one positive Lyapunov exponent). Along this frontier, the maximal relevant Lyapunov exponents are either zero or close to that, characterizing what is currently referred to as weak chaos. This type of situation is shared by a great variety of similar complex phenomena in economics, linguistics, to cite but a few. BG statistical mechanics is built upon the entropy S=-k∑plnp. A generalization of this form, S=k(1-∑piq)/(q-1) (with S=S), has been proposed in 1988 as a basis for formulating what is nowadays currently called nonextensive statistical mechanics. This theory appears to be particularly adapted for nonlinear dynamical systems exhibiting, precisely, weak chaos. Here, we briefly review the theory, its dynamical foundation, its applications in a variety of disciplines (with special emphasis to living systems), and its connections with the ubiquitous scale-free networks.

Mass Conservation of the Unified Continuous and Discontinuous Element-Based Galerkin Methods on Dynamically Adaptive Grids with Application to Atmospheric Simulations

DTIC Science & Technology

2015-09-01

Discontinuous Element-Based Galerkin Methods on Dynamically Adaptive Grids with Application to Atmospheric Simulations 5a. CONTRACT NUMBER 5b. GRANT NUMBER...Discontinuous Element-Based Galerkin Methods on Dynamically Adaptive Grids with Application to Atmospheric Simulations. Michal A. Koperaa,∗, Francis X...mass conservation, as it is an important feature for many atmospheric applications . We believe this is a good metric because, for smooth solutions

An Adaptive Scheme for Robot Localization and Mapping with Dynamically Configurable Inter-Beacon Range Measurements

PubMed Central

Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

2014-01-01

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption. PMID:24776938

An adaptive scheme for robot localization and mapping with dynamically configurable inter-beacon range measurements.

PubMed

Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

2014-04-25

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption.

Self-Induced Switchings between Multiple Space-Time Patterns on Complex Networks of Excitable Units

NASA Astrophysics Data System (ADS)

Ansmann, Gerrit; Lehnertz, Klaus; Feudel, Ulrike

2016-01-01

We report on self-induced switchings between multiple distinct space-time patterns in the dynamics of a spatially extended excitable system. These switchings between low-amplitude oscillations, nonlinear waves, and extreme events strongly resemble a random process, although the system is deterministic. We show that a chaotic saddle—which contains all the patterns as well as channel-like structures that mediate the transitions between them—is the backbone of such a pattern-switching dynamics. Our analyses indicate that essential ingredients for the observed phenomena are that the system behaves like an inhomogeneous oscillatory medium that is capable of self-generating spatially localized excitations and that is dominated by short-range connections but also features long-range connections. With our findings, we present an alternative to the well-known ways to obtain self-induced pattern switching, namely, noise-induced attractor hopping, heteroclinic orbits, and adaptation to an external signal. This alternative way can be expected to improve our understanding of pattern switchings in spatially extended natural dynamical systems like the brain and the heart.

The co-evolutionary dynamics of directed network of spin market agents

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán; Gmitra, Martin

2006-09-01

The spin market model [S. Bornholdt, Int. J. Mod. Phys. C 12 (2001) 667] is generalized by employing co-evolutionary principles, where strategies of the interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak-Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Lett. 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to the instant magnetization. The stationary regime is formed due to the interplay of self-organization and adaptivity effects. The fat tailed distributions of log-price returns are identified numerically. The non-trivial model consequence is the evidence of the long time market memory indicated by the power-law range of the autocorrelation function of volatility with exponent smaller than one. The simulations yield network topology with broad-scale node degree distribution characterized by the range of exponents 1.3<γin<3 coinciding with social networks.

Learning and adaptation: neural and behavioural mechanisms behind behaviour change

NASA Astrophysics Data System (ADS)

Lowe, Robert; Sandamirskaya, Yulia

2018-01-01

This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

Dynamic properties of the adaptive optics system depending on the temporary transformations of mirror control voltages

NASA Astrophysics Data System (ADS)

Lavrinov, V. V.; Lavrinova, L. N.

2017-11-01

The statistically optimal control algorithm for the correcting mirror is formed by constructing a prediction of distortions of the optical signal and improves the time resolution of the adaptive optics system. The prediction of distortions is based on an analysis of the dynamics of changes in the optical inhomogeneities of the turbulent atmosphere or the evolution of phase fluctuations at the input aperture of the adaptive system. Dynamic properties of the system are manifested during the temporary transformation of the stresses controlling the mirror and are determined by the dynamic characteristics of the flexible mirror.

The floristic heterogeneity of the Pantanal and the occurrence of species with different adaptive strategies to water stress.

PubMed

Scremin-Dias, E; Lorenz-Lemke, A P; Oliveira, A K M

2011-04-01

The Pantanal is characterised by a diversity of environments with areas ranging from periodic or permanent heavy flooding to areas with low flood levels, and even environments that never flood. Plant species which inhabit the floodplain are distributed in specific niches, with influence of various phytogeographic domains, including the Seasonal Semi-deciduous Forest, Amazon Rainforest, Cerrado and Chaco, as well rocky remnants, with a wide ecological span in their components. In intensely flooded areas, aquatic macrophytes are widely distributed, with their dynamics closely linked to time, depth and extent of flooding. Although the term "Pantanal" suggests a huge swamp-type wetland, water level variation during a seasonal cycle does not directly reach the root system of many plants. The landscape diversity of the Pantanal wetland is molded by the flood pulse, which interferes with the dynamics of plant communities. Therefore, the retraction and expansion of populations or communities is reflected in important ecological characteristics, considering the variety of morphological, anatomical and ecophysiological features of the species, whose phenotype is the result of a particular genotype. The present study discusses peculiar issues in the adaptation of species distributed in the Pantanal biome and underscores the importance of multidisciplinary approaches to obtain conclusive data on adaptive studies.

Relationships Between Vestibular Measures as Potential Predictors for Spaceflight Sensorimotor Adaptation

NASA Technical Reports Server (NTRS)

Clark, T. K.; Peters, B.; Gadd, N. E.; De Dios, Y. E.; Wood, S.; Bloomberg, J. J.; Mulavara, A. P.

2016-01-01

Introduction: During space exploration missions astronauts are exposed to a series of novel sensorimotor environments, requiring sensorimotor adaptation. Until adaptation is complete, sensorimotor decrements occur, affecting critical tasks such as piloted landing or docking. Of particularly interest are locomotion tasks such as emergency vehicle egress or extra-vehicular activity. While nearly all astronauts eventually adapt sufficiently, it appears there are substantial individual differences in how quickly and effectively this adaptation occurs. These individual differences in capacity for sensorimotor adaptation are poorly understood. Broadly, we aim to identify measures that may serve as pre-flight predictors of and individual's adaptation capacity to spaceflight-induced sensorimotor changes. As a first step, since spaceflight is thought to involve a reinterpretation of graviceptor cues (e.g. otolith cues from the vestibular system) we investigate the relationships between various measures of vestibular function in humans. Methods: In a set of 15 ground-based control subjects, we quantified individual differences in vestibular function using three measures: 1) ocular vestibular evoked myogenic potential (oVEMP), 2) computerized dynamic posturography and 3) vestibular perceptual thresholds. oVEMP responses are elicited using a mechanical stimuli approach. Computerized dynamic posturography was used to quantify Sensory Organization Tests (SOTs), including SOT5M which involved performing pitching head movements while balancing on a sway-reference support surface with eyes closed. We implemented a vestibular perceptual threshold task using the tilt capabilities of the Tilt-Translation Sled (TTS) at JSC. On each trial, the subject was passively roll-tilted left ear down or right ear down in the dark and verbally provided a forced-choice response regarding which direction they felt tilted. The motion profile was a single-cycle sinusoid of angular acceleration with a duration of 5 seconds (frequency of 0.2 Hz), which was selected as it requires sensory integration of otolith and semicircular canal cues. Stimuli direction was randomized and magnitude was determined using an adaptive sampling procedure. One hundred trials were provided and each subject's responses were fit with a psychometric curve to estimate the subject's threshold. Results: Roll tilt perceptual thresholds at 0.2 Hz ranged from 0.5 degrees to 1.82 degrees across the 15 subjects (geometric mean of 1.04 degrees), consistent with previous studies. The inter-individual variability in thresholds may be able to help explain individual differences observed in sensorimotor adaptation to spaceflight. Analysis is ongoing for the oVEMPS and computerized dynamic posturography to identify relationships between the various vestibular measures. Discussion: Predicting individual differences in sensorimotor adaptation is critical both for the development of personalized countermeasures and mission planning. Here we aim to develop a basis of vestibular tests and parameters which may serve as predictors of individual differences in sensorimotor adaptability through studying the relationship between these measures.

Ultra-Low Power Dynamic Knob in Adaptive Compressed Sensing Towards Biosignal Dynamics.

PubMed

Wang, Aosen; Lin, Feng; Jin, Zhanpeng; Xu, Wenyao

2016-06-01

Compressed sensing (CS) is an emerging sampling paradigm in data acquisition. Its integrated analog-to-information structure can perform simultaneous data sensing and compression with low-complexity hardware. To date, most of the existing CS implementations have a fixed architectural setup, which lacks flexibility and adaptivity for efficient dynamic data sensing. In this paper, we propose a dynamic knob (DK) design to effectively reconfigure the CS architecture by recognizing the biosignals. Specifically, the dynamic knob design is a template-based structure that comprises a supervised learning module and a look-up table module. We model the DK performance in a closed analytic form and optimize the design via a dynamic programming formulation. We present the design on a 130 nm process, with a 0.058 mm (2) fingerprint and a 187.88 nJ/event energy-consumption. Furthermore, we benchmark the design performance using a publicly available dataset. Given the energy constraint in wireless sensing, the adaptive CS architecture can consistently improve the signal reconstruction quality by more than 70%, compared with the traditional CS. The experimental results indicate that the ultra-low power dynamic knob can provide an effective adaptivity and improve the signal quality in compressed sensing towards biosignal dynamics.

Dynamical Adaptation in Photoreceptors

PubMed Central

Clark, Damon A.; Benichou, Raphael; Meister, Markus; Azeredo da Silveira, Rava

2013-01-01

Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. PMID:24244119

Contributions of adaptation currents to dynamic spike threshold on slow timescales: Biophysical insights from conductance-based models

NASA Astrophysics Data System (ADS)

Yi, Guosheng; Wang, Jiang; Wei, Xile; Deng, Bin; Li, Huiyan; Che, Yanqiu

2017-06-01

Spike-frequency adaptation (SFA) mediated by various adaptation currents, such as voltage-gated K+ current (IM), Ca2+-gated K+ current (IAHP), or Na+-activated K+ current (IKNa), exists in many types of neurons, which has been shown to effectively shape their information transmission properties on slow timescales. Here we use conductance-based models to investigate how the activation of three adaptation currents regulates the threshold voltage for action potential (AP) initiation during the course of SFA. It is observed that the spike threshold gets depolarized and the rate of membrane depolarization (dV/dt) preceding AP is reduced as adaptation currents reduce firing rate. It is indicated that the presence of inhibitory adaptation currents enables the neuron to generate a dynamic threshold inversely correlated with preceding dV/dt on slower timescales than fast dynamics of AP generation. By analyzing the interactions of ionic currents at subthreshold potentials, we find that the activation of adaptation currents increase the outward level of net membrane current prior to AP initiation, which antagonizes inward Na+ to result in a depolarized threshold and lower dV/dt from one AP to the next. Our simulations demonstrate that the threshold dynamics on slow timescales is a secondary effect caused by the activation of adaptation currents. These findings have provided a biophysical interpretation of the relationship between adaptation currents and spike threshold.

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

2014-01-01

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

Dynamic Courseware Generation on the WWW.

ERIC Educational Resources Information Center

Vassileva, Julita; Deters, Ralph

1998-01-01

The Dynamic Courseware Generator (DCG), which runs on a Web server, was developed for the authoring of adaptive computer-assisted learning courses. It generates an individual course according to the learner's goals and previous knowledge, and dynamically adapts the course according to the learner's success in knowledge acquisition. The tool may be…

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease

NASA Technical Reports Server (NTRS)

Peng, C. K.; Havlin, S.; Hausdorff, J. M.; Mietus, J. E.; Stanley, H. E.; Goldberger, A. L.

1995-01-01

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

A WSN-Based Tool for Urban and Industrial Fire-Fighting

PubMed Central

De San Bernabe Clemente, Alberto; Dios, José Ramiro Martínez-de; Baturone, Aníbal Ollero

2012-01-01

This paper describes a WSN tool to increase safety in urban and industrial fire-fighting activities. Unlike most approaches, we assume that there is no preexisting WSN in the building, which involves interesting advantages but imposes some constraints. The system integrates the following functionalities: fire monitoring, firefighter monitoring and dynamic escape path guiding. It also includes a robust localization method that employs RSSI-range models dynamically trained to cope with the peculiarities of the environment. The training and application stages of the method are applied simultaneously, resulting in significant adaptability. Besides simulations and laboratory tests, a prototype of the proposed system has been validated in close-to-operational conditions. PMID:23202198

Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

NASA Astrophysics Data System (ADS)

Volyanskyy, Kostyantyn Y.

Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance rejection and noise suppression for nonnegative and compartmental dynamical systems with noise and exogenous system disturbances. We then use the developed framework to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of continuing hemorrhage and hemodilution. Critical care patients, whether undergoing surgery or recovering in intensive care units, require drug administration to regulate physiological variables such as blood pressure, cardiac output, heart rate, and degree of consciousness. The rate of infusion of each administered drug is critical, requiring constant monitoring and frequent adjustments. In this dissertation, we develop a neuroadaptive output feedback control framework for nonlinear uncertain nonnegative and compartmental systems with nonnegative control inputs and noisy measurements. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals. In addition, the neuroadaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state space. Finally, the developed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of noisy electroencephalographic (EEG) measurements. Clinical trials demonstrate excellent regulation of unconsciousness allowing for a safe and effective administration of the anesthetic agent propofol. Furthermore, a neuroadaptive output feedback control architecture for nonlinear nonnegative dynamical systems with input amplitude and integral constraints is developed. Specifically, the neuroadaptive controller guarantees that the imposed amplitude and integral input constraints are satisfied and the physical system states remain in the nonnegative orthant of the state space. The proposed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for noncardiac surgery in the face of infusion rate constraints and a drug dosing constraint over a specified period. In addition, the aforementioned control architecture is used to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure- and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multi-compartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient's physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. The effect of spontaneous breathing is incorporated within the lung model and the control framework. Finally, a neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.

Effect of interactions for one-dimensional asymmetric exclusion processes under periodic and bath-adapted coupling environment

NASA Astrophysics Data System (ADS)

Midha, Tripti; Kolomeisky, Anatoly B.; Gupta, Arvind Kumar

2018-04-01

Stimulated by the effect of the nearest neighbor interactions in vehicular traffic and motor proteins, we study a 1D driven lattice gas model, in which the nearest neighbor particle interactions are taken in accordance with the thermodynamic concepts. The non-equilibrium steady-state properties of the system are analyzed under both open and periodic boundary conditions using a combination of cluster mean-field analysis and Monte Carlo simulations. Interestingly, the fundamental diagram of current versus density shows a complex behavior with a unimodal dependence for attractions and weak repulsions that turns into the bimodal behavior for stronger repulsive interactions. Specific details of system-reservoir coupling for the open system have a strong effect on the stationary phases. We produce the steady-state phase diagrams for the bulk-adapted coupling to the reservoir using the minimum and maximum current principles. The strength and nature of interaction energy has a striking influence on the number of stationary phases. We observe that interactions lead to correlations having a strong impact on the system dynamical properties. The correlation between any two sites decays exponentially as the distance between the sites increases. Moreover, they are found to be short-range for repulsions and long-range for attractions. Our results also suggest that repulsions and attractions asymmetrically modify the dynamics of interacting particles in exclusion processes.

Nuclear Potential Clustering As a New Tool to Detect Patterns in High Dimensional Datasets

NASA Astrophysics Data System (ADS)

Tonkova, V.; Paulus, D.; Neeb, H.

2013-02-01

We present a new approach for the clustering of high dimensional data without prior assumptions about the structure of the underlying distribution. The proposed algorithm is based on a concept adapted from nuclear physics. To partition the data, we model the dynamic behaviour of nucleons interacting in an N-dimensional space. An adaptive nuclear potential, comprised of a short-range attractive (strong interaction) and a long-range repulsive term (Coulomb force) is assigned to each data point. By modelling the dynamics, nucleons that are densely distributed in space fuse to build nuclei (clusters) whereas single point clusters repel each other. The formation of clusters is completed when the system reaches the state of minimal potential energy. The data are then grouped according to the particles' final effective potential energy level. The performance of the algorithm is tested with several synthetic datasets showing that the proposed method can robustly identify clusters even when complex configurations are present. Furthermore, quantitative MRI data from 43 multiple sclerosis patients were analyzed, showing a reasonable splitting into subgroups according to the individual patients' disease grade. The good performance of the algorithm on such highly correlated non-spherical datasets, which are typical for MRI derived image features, shows that Nuclear Potential Clustering is a valuable tool for automated data analysis, not only in the MRI domain.

Single-layer HDR video coding with SDR backward compatibility

NASA Astrophysics Data System (ADS)

Lasserre, S.; François, E.; Le Léannec, F.; Touzé, D.

2016-09-01

The migration from High Definition (HD) TV to Ultra High Definition (UHD) is already underway. In addition to an increase of picture spatial resolution, UHD will bring more color and higher contrast by introducing Wide Color Gamut (WCG) and High Dynamic Range (HDR) video. As both Standard Dynamic Range (SDR) and HDR devices will coexist in the ecosystem, the transition from Standard Dynamic Range (SDR) to HDR will require distribution solutions supporting some level of backward compatibility. This paper presents a new HDR content distribution scheme, named SL-HDR1, using a single layer codec design and providing SDR compatibility. The solution is based on a pre-encoding HDR-to-SDR conversion, generating a backward compatible SDR video, with side dynamic metadata. The resulting SDR video is then compressed, distributed and decoded using standard-compliant decoders (e.g. HEVC Main 10 compliant). The decoded SDR video can be directly rendered on SDR displays without adaptation. Dynamic metadata of limited size are generated by the pre-processing and used to reconstruct the HDR signal from the decoded SDR video, using a post-processing that is the functional inverse of the pre-processing. Both HDR quality and artistic intent are preserved. Pre- and post-processing are applied independently per picture, do not involve any inter-pixel dependency, and are codec agnostic. Compression performance, and SDR quality are shown to be solidly improved compared to the non-backward and backward-compatible approaches, respectively using the Perceptual Quantization (PQ) and Hybrid Log Gamma (HLG) Opto-Electronic Transfer Functions (OETF).

Linking Individual and Collective Behavior in Adaptive Social Networks

NASA Astrophysics Data System (ADS)

Pinheiro, Flávio L.; Santos, Francisco C.; Pacheco, Jorge M.

2016-03-01

Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N -person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-10-23

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

Spontaneous scale-free structure in adaptive networks with synchronously dynamical linking

NASA Astrophysics Data System (ADS)

Yuan, Wu-Jie; Zhou, Jian-Fang; Li, Qun; Chen, De-Bao; Wang, Zhen

2013-08-01

Inspired by the anti-Hebbian learning rule in neural systems, we study how the feedback from dynamical synchronization shapes network structure by adding new links. Through extensive numerical simulations, we find that an adaptive network spontaneously forms scale-free structure, as confirmed in many real systems. Moreover, the adaptive process produces two nontrivial power-law behaviors of deviation strength from mean activity of the network and negative degree correlation, which exists widely in technological and biological networks. Importantly, these scalings are robust to variation of the adaptive network parameters, which may have meaningful implications in the scale-free formation and manipulation of dynamical networks. Our study thus suggests an alternative adaptive mechanism for the formation of scale-free structure with negative degree correlation, which means that nodes of high degree tend to connect, on average, with others of low degree and vice versa. The relevance of the results to structure formation and dynamical property in neural networks is briefly discussed as well.

Adaptive critics for dynamic optimization.

PubMed

Kulkarni, Raghavendra V; Venayagamoorthy, Ganesh Kumar

2010-06-01

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. Copyright 2010 Elsevier Ltd. All rights reserved.

Co-occurrence of viruses and mosquitoes at the vectors' optimal climate range: An underestimated risk to temperate regions?

PubMed

Blagrove, Marcus S C; Caminade, Cyril; Waldmann, Elisabeth; Sutton, Elizabeth R; Wardeh, Maya; Baylis, Matthew

2017-06-01

Mosquito-borne viruses have been estimated to cause over 100 million cases of human disease annually. Many methodologies have been developed to help identify areas most at risk from transmission of these viruses. However, generally, these methodologies focus predominantly on the effects of climate on either the vectors or the pathogens they spread, and do not consider the dynamic interaction between the optimal conditions for both vector and virus. Here, we use a new approach that considers the complex interplay between the optimal temperature for virus transmission, and the optimal climate for the mosquito vectors. Using published geolocated data we identified temperature and rainfall ranges in which a number of mosquito vectors have been observed to co-occur with West Nile virus, dengue virus or chikungunya virus. We then investigated whether the optimal climate for co-occurrence of vector and virus varies between "warmer" and "cooler" adapted vectors for the same virus. We found that different mosquito vectors co-occur with the same virus at different temperatures, despite significant overlap in vector temperature ranges. Specifically, we found that co-occurrence correlates with the optimal climatic conditions for the respective vector; cooler-adapted mosquitoes tend to co-occur with the same virus in cooler conditions than their warmer-adapted counterparts. We conclude that mosquitoes appear to be most able to transmit virus in the mosquitoes' optimal climate range, and hypothesise that this may be due to proportionally over-extended vector longevity, and other increased fitness attributes, within this optimal range. These results suggest that the threat posed by vector-competent mosquito species indigenous to temperate regions may have been underestimated, whilst the threat arising from invasive tropical vectors moving to cooler temperate regions may be overestimated.

Invoking adaptation to decipher the genetic legacy of past climate change.

PubMed

de Lafontaine, Guillaume; Napier, Joseph D; Petit, Rémy J; Hu, Feng Sheng

2018-05-05

Persistence of natural populations during periods of climate change is likely to depend on migration (range shifts) or adaptation. These responses were traditionally considered discrete processes and conceptually divided into the realms of ecology and evolution. In a milestone paper, Davis and Shaw (2001) argued that the interplay of adaptation and migration was central to biotic responses to Quaternary climate, but since then there has been no synthesis of efforts made to set up this research program. Here we review some of the salient findings from molecular genetic studies assessing ecological and evolutionary responses to Quaternary climate change. These studies have revolutionized our understanding of population processes associated with past species migration. However, knowledge remains limited about the role of natural selection for local adaptation of populations to Quaternary environmental fluctuations and associated range shifts, and for the footprints this might have left on extant populations. Next-generation sequencing technologies, high-resolution paleoclimate analyses, and advances in population genetic theory offer an unprecedented opportunity to test hypotheses about adaptation through time. Recent population genomics studies have greatly improved our understanding of the role of contemporary adaptation to local environments in shaping spatial patterns of genetic diversity across modern-day landscapes. Advances in this burgeoning field provide important conceptual and methodological bases to decipher the historical role of natural selection and assess adaptation to past environmental variation. We suggest that a process called "temporal conditional neutrality" has taken place: some alleles favored in glacial environments become selectively neutral in modern-day conditions, whereas some alleles that had been neutral during glacial periods become under selection in modern environments. Building on this view, we present a new integrative framework for addressing the interplay of demographic and adaptive evolutionary responses to Quaternary climate dynamics, the research agenda initially envisioned by Davis and Shaw (2001). This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Dynamic Adaptation in Child-Adult Language Interaction

ERIC Educational Resources Information Center

van Dijk, Marijn; van Geert, Paul; Korecky-Kröll, Katharina; Maillochon, Isabelle; Laaha, Sabine; Dressler, Wolfgang U.; Bassano, Dominique

2013-01-01

When speaking to young children, adults adapt their language to that of the child. In this article, we suggest that this child-directed speech (CDS) is the result of a transactional process of dynamic adaptation between the child and the adult. The study compares developmental trajectories of three children to those of the CDS of their caregivers.…

Enhancing Collaborative Learning through Dynamic Forms of Support: The Impact of an Adaptive Domain-Specific Support Strategy

ERIC Educational Resources Information Center

Karakostas, A.; Demetriadis, S.

2011-01-01

Research on computer-supported collaborative learning (CSCL) has strongly emphasized the value of providing student support of either fixed (e.g. collaboration scripts) or dynamic form (e.g. adaptive supportive interventions). Currently, however, there is not sufficient evidence corroborating the potential of adaptive support methods to improve…

Development of force adaptation during childhood.

PubMed

Konczak, Jürgen; Jansen-Osmann, Petra; Kalveram, Karl-Theodor

2003-03-01

Humans learn to make reaching movements in novel dynamic environments by acquiring an internal motor model of their limb dynamics. Here, the authors investigated how 4- to 11-year-old children (N = 39) and adults (N = 7) adapted to changes in arm dynamics, and they examined whether those data support the view that the human brain acquires inverse dynamics models (IDM) during development. While external damping forces were applied, the children learned to perform goal-directed forearm flexion movements. After changes in damping, all children showed kinematic aftereffects indicative of a neural controller that still attempted to compensate the no longer existing damping force. With increasing age, the number of trials toward complete adaptation decreased. When damping was present, forearm paths were most perturbed and most variable in the youngest children but were improved in the older children. The findings indicate that the neural representations of limb dynamics are less precise in children and less stable in time than those of adults. Such controller instability might be a primary cause of the high kinematic variability observed in many motor tasks during childhood. Finally, the young children were not able to update those models at the same rate as the older children, who, in turn, adapted more slowly than adults. In conclusion, the ability to adapt to unknown forces is a developmental achievement. The present results are consistent with the view that the acquisition and modification of internal models of the limb dynamics form the basis of that adaptive process.

Long-range correlations and fractal dynamics in C. elegans: Changes with aging and stress

NASA Astrophysics Data System (ADS)

Alves, Luiz G. A.; Winter, Peter B.; Ferreira, Leonardo N.; Brielmann, Renée M.; Morimoto, Richard I.; Amaral, Luís A. N.

2017-08-01

Reduced motor control is one of the most frequent features associated with aging and disease. Nonlinear and fractal analyses have proved to be useful in investigating human physiological alterations with age and disease. Similar findings have not been established for any of the model organisms typically studied by biologists, though. If the physiology of a simpler model organism displays the same characteristics, this fact would open a new research window on the control mechanisms that organisms use to regulate physiological processes during aging and stress. Here, we use a recently introduced animal-tracking technology to simultaneously follow tens of Caenorhabdits elegans for several hours and use tools from fractal physiology to quantitatively evaluate the effects of aging and temperature stress on nematode motility. Similar to human physiological signals, scaling analysis reveals long-range correlations in numerous motility variables, fractal properties in behavioral shifts, and fluctuation dynamics over a wide range of timescales. These properties change as a result of a superposition of age and stress-related adaptive mechanisms that regulate motility.

Adaptive Control Based Harvesting Strategy for a Predator-Prey Dynamical System.

PubMed

Sen, Moitri; Simha, Ashutosh; Raha, Soumyendu

2018-04-23

This paper deals with designing a harvesting control strategy for a predator-prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.

Adaptation in the auditory midbrain of the barn owl (Tyto alba) induced by tonal double stimulation.

PubMed

Singheiser, Martin; Ferger, Roland; von Campenhausen, Mark; Wagner, Hermann

2012-02-01

During hunting, the barn owl typically listens to several successive sounds as generated, for example, by rustling mice. As auditory cells exhibit adaptive coding, the earlier stimuli may influence the detection of the later stimuli. This situation was mimicked with two double-stimulus paradigms, and adaptation was investigated in neurons of the barn owl's central nucleus of the inferior colliculus. Each double-stimulus paradigm consisted of a first or reference stimulus and a second stimulus (probe). In one paradigm (second level tuning), the probe level was varied, whereas in the other paradigm (inter-stimulus interval tuning), the stimulus interval between the first and second stimulus was changed systematically. Neurons were stimulated with monaural pure tones at the best frequency, while the response was recorded extracellularly. The responses to the probe were significantly reduced when the reference stimulus and probe had the same level and the inter-stimulus interval was short. This indicated response adaptation, which could be compensated for by an increase of the probe level of 5-7 dB over the reference level, if the latter was in the lower half of the dynamic range of a neuron's rate-level function. Recovery from adaptation could be best fitted with a double exponential showing a fast (1.25 ms) and a slow (800 ms) component. These results suggest that neurons in the auditory system show dynamic coding properties to tonal double stimulation that might be relevant for faithful upstream signal propagation. Furthermore, the overall stimulus level of the masker also seems to affect the recovery capabilities of auditory neurons. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Flexible and adaptive water systems operations through more informed and dynamic decisions

NASA Astrophysics Data System (ADS)

Castelletti, A.; Giuliani, M.

2016-12-01

Timely adapting the operations of water systems to be resilient against rapid changes in both hydroclimatic and socioeconomic forcing is generally recommended as a part of planning and managing water resources under uncertain futures. A great opportunity to make the operations more flexible and adaptive is offered by the unprecedented amount of information that is becoming available to water system operators, providing a wide range of data at increasingly higher temporal and spatial resolution. Yet, many water systems are still operated using very simple information systems, typically based on basic statistical analysis and the operator's experience. In this work, we discuss the potential offered by incorporating improved information to enhance water systems operation and increase their ability of adapting to different external conditions and resolving potential conflicts across sectors. In particular, we focus on the use of different variables associated to different dynamics of the system (slow and fast) diversely impacting the operating objectives on the short-, medium- and long-term. The multi-purpose operations of the Hoa Binh reservoir in the Red River Basin (Vietnam) is used to demonstrate our approach. Numerical results show that our procedure is able to automatically select the most valuable information for improving the Hoa Binh operations and mitigating the conflict between short-term objectives, i.e. hydropower production and flood control. Moreover, we also successfully identify low-frequency climate information associated to El-Nino Southern Oscillation for improving the performance in terms of long-term objectives, i.e. water supply. Finally, we assess the value of better informing operational decisions for adapting the system operations to changing conditions by considering different climate change projections.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Adaptive Detection and ISI Mitigation for Mobile Molecular Communication.

PubMed

Chang, Ge; Lin, Lin; Yan, Hao

2018-03-01

Current studies on modulation and detection schemes in molecular communication mainly focus on the scenarios with static transmitters and receivers. However, mobile molecular communication is needed in many envisioned applications, such as target tracking and drug delivery. Until now, investigations about mobile molecular communication have been limited. In this paper, a static transmitter and a mobile bacterium-based receiver performing random walk are considered. In this mobile scenario, the channel impulse response changes due to the dynamic change of the distance between the transmitter and the receiver. Detection schemes based on fixed distance fail in signal detection in such a scenario. Furthermore, the intersymbol interference (ISI) effect becomes more complex due to the dynamic character of the signal which makes the estimation and mitigation of the ISI even more difficult. In this paper, an adaptive ISI mitigation method and two adaptive detection schemes are proposed for this mobile scenario. In the proposed scheme, adaptive ISI mitigation, estimation of dynamic distance, and the corresponding impulse response reconstruction are performed in each symbol interval. Based on the dynamic channel impulse response in each interval, two adaptive detection schemes, concentration-based adaptive threshold detection and peak-time-based adaptive detection, are proposed for signal detection. Simulations demonstrate that the ISI effect is significantly reduced and the adaptive detection schemes are reliable and robust for mobile molecular communication.

Recruitment dynamics in adaptive social networks

NASA Astrophysics Data System (ADS)

Shkarayev, Maxim; Shaw, Leah; Schwartz, Ira

2011-03-01

We model recruitment in social networks in the presence of birth and death processes. The recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. The recruiting nodes may adapt their connections in order to improve recruitment capabilities, thus changing the network structure. We develop a mean-field theory describing the system dynamics. Using mean-field theory we characterize the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment dynamics, as well as on network topology. The theoretical predictions are confirmed by the direct simulations of the full system.

Adaptive Impact-Driven Detection of Silent Data Corruption for HPC Applications

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

Di, Sheng; Cappello, Franck

For exascale HPC applications, silent data corruption (SDC) is one of the most dangerous problems because there is no indication that there are errors during the execution. We propose an adaptive impact-driven method that can detect SDCs dynamically. The key contributions are threefold. (1) We carefully characterize 18 real-world HPC applications and discuss the runtime data features, as well as the impact of the SDCs on their execution results. (2) We propose an impact-driven detection model that does not blindly improve the prediction accuracy, but instead detects only influential SDCs to guarantee user-acceptable execution results. (3) Our solution can adaptmore » to dynamic prediction errors based on local runtime data and can automatically tune detection ranges for guaranteeing low false alarms. Experiments show that our detector can detect 80-99.99% of SDCs with a false alarm rate less that 1% of iterations for most cases. The memory cost and detection overhead are reduced to 15% and 6.3%, respectively, for a large majority of applications.« less

A continually online-trained neural network controller for brushless DC motor drives

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

Rubaai, A.; Kotaru, R.; Kankam, M.D.

2000-04-01

In this paper, a high-performance controller with simultaneous online identification and control is designed for brushless dc motor drives. The dynamics of the motor/load are modeled online, and controlled using two different neural network based identification and control schemes, as the system is in operation. In the first scheme, an attempt is made to control the rotor angular speed, utilizing a single three-hidden-layer network. The second scheme attempts to control the stator currents, using a predetermined control law as a function of the estimated states. This schemes incorporates three multilayered feedforward neural networks that are online trained, using the Levenburg-Marquadtmore » training algorithm. The control of the direct and quadrature components of the stator current successfully tracked a wide variety of trajectories after relatively short online training periods. The control strategy adapts to the uncertainties of the motor/load dynamics and, in addition, learns their inherent nonlinearities. Simulation results illustrated that a neurocontroller used in conjunction with adaptive control schemes can result in a flexible control device which may be utilized in a wide range of environments.« less

DyNAvectors: dynamic constitutional vectors for adaptive DNA transfection.

PubMed

Clima, Lilia; Peptanariu, Dragos; Pinteala, Mariana; Salic, Adrian; Barboiu, Mihail

2015-12-25

Dynamic constitutional frameworks, based on squalene, PEG and PEI components, reversibly connected to core centers, allow the efficient identification of adaptive vectors for good DNA transfection efficiency and are well tolerated by mammalian cells.

Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting

NASA Technical Reports Server (NTRS)

Trujillo, Anna; Gregory, Irene

2013-01-01

Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.

Effects of high-heeled footwear on static and dynamic pelvis position and lumbar lordosis in experienced younger and middle-aged women.

PubMed

Schroeder, Jan; Hollander, Karsten

2018-01-01

There is still conflicting evidence about the effect of high-heeled footwear on posture, especially if methodological confounders are taken into account. The purpose of this study was to investigate the effect of high-heeled footwear on lumbopelvic parameters in experienced younger and middle-aged women while standing and walking. Thirty-seven experienced younger (n=19:18-25 years) and middle-aged (n=18:26-56 years) women were included in this randomized crossover study. Using a non-invasive back shape reconstruction device (rasterstereography), static (pelvic tilt and lumbar lordosis angle) and dynamic (pelvic rotation, median lumbar lordosis angle and range of motion) parameters representing pelvis position and lumbar curvature were measured. In order to analyse standing and walking on a treadmill (0.83m/s), the effects of high-heels (7-11cm) were compared to standard control shoes. There were no effects on the lumbar lordosis angle or range of motion under static or dynamic conditions (p>0.05, d≤0.06). But there was a small effect for a reduced pelvic tilt (p=0.003, d=0.24) and a moderate effect for an increased transversal pelvic rotation (p=0.001, d=0.63) due to high heel shoed standing or walking, respectively. There were no significant age-group or interaction effects (p>0.05). Altered pelvic parameters may be interpreted as compensatory adaptations to high-heeled footwear rather than lumbar lordosis adaptations in experienced wearers. The impact of these findings on back complaints should be revisited carefully, because muscular overuse as well as postural load relieving may contribute to chronic consequences. Further research is necessary to examine clinically relevant outcomes corresponding to postural alterations. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the resilience of urban water supply using the capital portfolio approach

NASA Astrophysics Data System (ADS)

Krueger, E. H.; Klammler, H.; Borchardt, D.; Frank, K.; Jawitz, J. W.; Rao, P. S.

2017-12-01

The dynamics of global change challenge the resilience of cities in a multitude of ways, including pressures resulting from population and consumption changes, production patterns, climate and landuse change, as well as environmental hazards. Responses to these challenges aim to improve urban resilience, but lack an adequate understanding of 1) the elements and processes that lead to the resilience of coupled natural-human-engineered systems, 2) the complex dynamics emerging from the interaction of these elements, including the availability of natural resources, infrastructure, and social capital, which may lead to 3) unintended consequences resulting from management responses. We propose a new model that simulates the coupled dynamics of five types of capitals (water resources, infrastructure, finances, political capital /management, and social adaptive capacity) that are necessary for the provision of water supply to urban residents. We parameterize the model based on data for a case study city, which is limited by constraints in water availability, financial resources, and faced with degrading infrastructure, as well as population increase, which challenge the urban management institutions. Our model analyzes the stability of the coupled system, and produces time series of the capital dynamics to quantify its resilience as a result of the portfolio of capitals available to usher adaptive capacity and to secure water supply subjected to multiple recurring shocks. We apply our model to one real urban water supply system located in an arid environment, as well as a wide range of hypothetical case studies, which demonstrates its applicability to various types of cities, and its ability to quantify and compare water supply resilience. The analysis of a range of urban water systems provides valuable insights into guiding more sustainable responses for maintaining the resilience of urban water supply around the globe, by showing how unsustainable responses risk the loss of resilience. We suggest that the same model can be generalized to represent other types of urban infrastructure service systems with different parameterizations.

Anthropogenically induced adaptation to invade (AIAI): contemporary adaptation to human-altered habitats within the native range can promote invasions

PubMed Central

Hufbauer, Ruth A; Facon, Benoît; Ravigné, Virginie; Turgeon, Julie; Foucaud, Julien; Lee, Carol E; Rey, Olivier; Estoup, Arnaud

2012-01-01

Adaptive evolution is currently accepted as playing a significant role in biological invasions. Adaptations relevant to invasions are typically thought to occur either recently within the introduced range, as an evolutionary response to novel selection regimes, or within the native range, because of long-term adaptation to the local environment. We propose that recent adaptation within the native range, in particular adaptations to human-altered habitat, could also contribute to the evolution of invasive populations. Populations adapted to human-altered habitats in the native range are likely to increase in abundance within areas frequented by humans and associated with human transport mechanisms, thus enhancing the likelihood of transport to a novel range. Given that habitats are altered by humans in similar ways worldwide, as evidenced by global environmental homogenization, propagules from populations adapted to human-altered habitats in the native range should perform well within similarly human-altered habitats in the novel range. We label this scenario ‘Anthropogenically Induced Adaptation to Invade’. We illustrate how it differs from other evolutionary processes that may occur during invasions, and how it can help explain accelerating rates of invasions. PMID:25568032

The Use of Complex Adaptive Systems as a Generative Metaphor in an Action Research Study of an Organisation

ERIC Educational Resources Information Center

Brown, Callum

2008-01-01

Understanding the dynamic behaviour of organisations is challenging and this study uses a model of complex adaptive systems as a generative metaphor to address this challenge. The research question addressed is: How might a conceptual model of complex adaptive systems be used to assist in understanding the dynamic nature of organisations? Using an…

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

NASA Astrophysics Data System (ADS)

Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

2018-05-01

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation

PubMed Central

Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si

2018-01-01

Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural encoding. We believe that our study shed lights on the mechanism underlying the efficient neural information processing via adaptation. PMID:29636675

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Kobezhicov, V.

2015-10-01

This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

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

Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.

2015-01-01

Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combiningmore » the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.« less

Selection history and epistatic interactions impact dynamics of adaptation to novel environmental stresses.

PubMed

Lagator, Mato; Colegrave, Nick; Neve, Paul

2014-11-07

In rapidly changing environments, selection history may impact the dynamics of adaptation. Mutations selected in one environment may result in pleiotropic fitness trade-offs in subsequent novel environments, slowing the rates of adaptation. Epistatic interactions between mutations selected in sequential stressful environments may slow or accelerate subsequent rates of adaptation, depending on the nature of that interaction. We explored the dynamics of adaptation during sequential exposure to herbicides with different modes of action in Chlamydomonas reinhardtii. Evolution of resistance to two of the herbicides was largely independent of selection history. For carbetamide, previous adaptation to other herbicide modes of action positively impacted the likelihood of adaptation to this herbicide. Furthermore, while adaptation to all individual herbicides was associated with pleiotropic fitness costs in stress-free environments, we observed that accumulation of resistance mechanisms was accompanied by a reduction in overall fitness costs. We suggest that antagonistic epistasis may be a driving mechanism that enables populations to more readily adapt in novel environments. These findings highlight the potential for sequences of xenobiotics to facilitate the rapid evolution of multiple-drug and -pesticide resistance, as well as the potential for epistatic interactions between adaptive mutations to facilitate evolutionary rescue in rapidly changing environments. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

PubMed

Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

2014-03-01

In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Applying Parallel Adaptive Methods with GeoFEST/PYRAMID to Simulate Earth Surface Crustal Dynamics

NASA Technical Reports Server (NTRS)

Norton, Charles D.; Lyzenga, Greg; Parker, Jay; Glasscoe, Margaret; Donnellan, Andrea; Li, Peggy

2006-01-01

This viewgraph presentation reviews the use Adaptive Mesh Refinement (AMR) in simulating the Crustal Dynamics of Earth's Surface. AMR simultaneously improves solution quality, time to solution, and computer memory requirements when compared to generating/running on a globally fine mesh. The use of AMR in simulating the dynamics of the Earth's Surface is spurred by future proposed NASA missions, such as InSAR for Earth surface deformation and other measurements. These missions will require support for large-scale adaptive numerical methods using AMR to model observations. AMR was chosen because it has been successful in computation fluid dynamics for predictive simulation of complex flows around complex structures.

Quantitative Modeling of Virus Evolutionary Dynamics and Adaptation in Serial Passages Using Empirically Inferred Fitness Landscapes

DTIC Science & Technology

2014-01-01

decrease in virus count. This overall behavior of total species count (uninfected cells and viruses of all genotypes) shown in Fig. 1 was qualitatively...respiratory syndrome corona - virus host range expansion in human airway epithelium. J. Virol. 82: 2274 –2285. http://dx.doi.org/10.1128/JVI.02041-07...2008.12.014. 44. Bouvier NM, Lowen AC. 2010. Animal models for influenza virus patho- genesis and transmission. Viruses 2:1530 –1563. http

Adapting agriculture to climate change.

PubMed

Howden, S Mark; Soussana, Jean-François; Tubiello, Francesco N; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

2007-12-11

The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.

Regional Approach for Linking Ecosystem Services and Livelihood Strategies Under Climate Change of Pastoral Communities in the Mongolian Steppe Ecosystem

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Galvin, K.; Togtohyn, C.

2012-12-01

Dramatic changes due to climate and land use dynamics in the Mongolian Plateau affecting ecosystem services and agro-pastoral systems in Mongolia. Recently, market forces and development strategies are affecting land and water resources of the pastoral communities which are being further stressed due to climatic changes. Evaluation of pastoral systems, where humans depend on livestock and grassland ecosystem services, have demonstrated the vulnerability of the social-ecological system to climate change. Current social-ecological changes in ecosystem services are affecting land productivity and carrying capacity, land-atmosphere interactions, water resources, and livelihood strategies. The general trend involves greater intensification of resource exploitation at the expense of traditional patterns of extensive range utilization. Thus we expect climate-land use-land cover relationships to be crucially modified by the social-economic forces. The analysis incorporates information about the social-economic transitions taking place in the region which affect land-use, food security, and ecosystem dynamics. The region of study extends from the Mongolian plateau in Mongolia. Our research indicate that sustainability of pastoral systems in the region needs to integrate the impact of climate change on ecosystem services with socio-economic changes shaping the livelihood strategies of pastoral systems in the region. Adaptation strategies which incorporate integrated analysis of landscape management and livelihood strategies provides a framework which links ecosystem services to critical resource assets. Analysis of the available livelihood assets provides insights to the adaptive capacity of various agents in a region or in a community. Sustainable development pathways which enable the development of these adaptive capacity elements will lead to more effective adaptive management strategies for pastoral land use and herder's living standards. Pastoralists will have the opportunity to utilize seasonal resources and enhance their ability to process and manufacture products from the available ecosystem services in these dynamic social-ecological systems.

Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

PubMed Central

Garrido, Jesús A.; Luque, Niceto R.; D'Angelo, Egidio; Ros, Eduardo

2013-01-01

Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario. PMID:24130518

Eco-evolutionary dynamics in a coevolving host-virus system.

PubMed

Frickel, Jens; Sieber, Michael; Becks, Lutz

2016-04-01

Eco-evolutionary dynamics have been shown to be important for understanding population and community stability and their adaptive potential. However, coevolution in the framework of eco-evolutionary theory has not been addressed directly. Combining experiments with an algal host and its viral parasite, and mathematical model analyses we show eco-evolutionary dynamics in antagonistic coevolving populations. The interaction between antagonists initially resulted in arms race dynamics (ARD) with selective sweeps, causing oscillating host-virus population dynamics. However, ARD ended and populations stabilised after the evolution of a general resistant host, whereas a trade-off between host resistance and growth then maintained host diversity over time (trade-off driven dynamics). Most importantly, our study shows that the interaction between ecology and evolution had important consequences for the predictability of the mode and tempo of adaptive change and for the stability and adaptive potential of populations. © 2016 John Wiley & Sons Ltd/CNRS.

Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics

NASA Technical Reports Server (NTRS)

Iyengar, N.; Peng, C. K.; Morin, R.; Goldberger, A. L.; Lipsitz, L. A.

1996-01-01

We postulated that aging is associated with disruption in the fractallike long-range correlations that characterize healthy sinus rhythm cardiac interval dynamics. Ten young (21-34 yr) and 10 elderly (68-81 yr) rigorously screened healthy subjects underwent 120 min of continuous supine resting electrocardiographic recording. We analyzed the interbeat interval time series using standard time and frequency domain statistics and using a fractal measure, detrended fluctuation analysis, to quantify long-range correlation properties. In healthy young subjects, interbeat intervals demonstrated fractal scaling, with scaling exponents (alpha) from the fluctuation analysis close to a value of 1.0. In the group of healthy elderly subjects, the interbeat interval time series had two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, alpha = 1.5), whereas over the longer range they resembled white noise (alpha = 0.5). Short (alpha s)- and long-range (alpha 1) scaling exponents were significantly different in the elderly subjects compared with young (alpha s = 1.12 +/- 0.19 vs. 0.90 +/- 0.14, respectively, P = 0.009; alpha 1 = 0.75 +/- 0.17 vs. 0.99 +/- 0.10, respectively, P = 0.002). The crossover behavior from one scaling region to another could be modeled as a first-order autoregressive process, which closely fit the data from four elderly subjects. This implies that a single characteristic time scale may be dominating heartbeat control in these subjects. The age-related loss of fractal organization in heartbeat dynamics may reflect the degradation of integrated physiological regulatory systems and may impair an individual's ability to adapt to stress.

Trajectory optimization study of a lifting body re-entry vehicle for medium to intermediate range applications

NASA Astrophysics Data System (ADS)

Rizvi, S. Tauqeer ul Islam; Linshu, He; ur Rehman, Tawfiq; Rafique, Amer Farhan

2012-11-01

A numerical optimization study of lifting body re-entry vehicles is presented for nominal as well as shallow entry conditions for Medium and Intermediate Range applications. Due to the stringent requirement of a high degree of accuracy for conventional vehicles, lifting re-entry can be used to attain the impact at the desired terminal flight path angle and speed and thus can potentially improve accuracy of the re-entry vehicle. The re-entry of a medium range and intermediate range vehicles is characterized by very high negative flight path angle and low re-entry speed as compared to a maneuverable re-entry vehicle or a common aero vehicle intended for an intercontinental range. Highly negative flight path angles at the re-entry impose high dynamic pressure as well as heat loads on the vehicle. The trajectory studies are carried out to maximize the cross range of the re-entry vehicle while imposing a maximum dynamic pressure constraint of 350 KPa with a 3 MW/m2 heat rate limit. The maximum normal acceleration and the total heat load experienced by the vehicle at the stagnation point during the maneuver have been computed for the vehicle for possible future conceptual design studies. It has been found that cross range capability of up to 35 km can be achieved with a lifting-body design within the heat rate and the dynamic pressure boundary at normal entry conditions. For shallow entry angle of -20 degree and intermediate ranges a cross range capability of up to 250 km can be attained for a lifting body design with less than 10 percent loss in overall range. The normal acceleration also remains within limits. The lifting-body results have also been compared with wing-body results at shallow entry condition. An hp-adaptive pseudo-spectral method has been used for constrained trajectory optimization.

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

2002-01-01

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Dynamically variable negative stiffness structures

PubMed Central

Churchill, Christopher B.; Shahan, David W.; Smith, Sloan P.; Keefe, Andrew C.; McKnight, Geoffrey P.

2016-01-01

Variable stiffness structures that enable a wide range of efficient load-bearing and dexterous activity are ubiquitous in mammalian musculoskeletal systems but are rare in engineered systems because of their complexity, power, and cost. We present a new negative stiffness–based load-bearing structure with dynamically tunable stiffness. Negative stiffness, traditionally used to achieve novel response from passive structures, is a powerful tool to achieve dynamic stiffness changes when configured with an active component. Using relatively simple hardware and low-power, low-frequency actuation, we show an assembly capable of fast (<10 ms) and useful (>100×) dynamic stiffness control. This approach mitigates limitations of conventional tunable stiffness structures that exhibit either small (<30%) stiffness change, high friction, poor load/torque transmission at low stiffness, or high power active control at the frequencies of interest. We experimentally demonstrate actively tunable vibration isolation and stiffness tuning independent of supported loads, enhancing applications such as humanoid robotic limbs and lightweight adaptive vibration isolators. PMID:26989771

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

PubMed

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

NASA Technical Reports Server (NTRS)

Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

2010-01-01

This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

Optimal structure of metaplasticity for adaptive learning

PubMed Central

2017-01-01

Learning from reward feedback in a changing environment requires a high degree of adaptability, yet the precise estimation of reward information demands slow updates. In the framework of estimating reward probability, here we investigated how this tradeoff between adaptability and precision can be mitigated via metaplasticity, i.e. synaptic changes that do not always alter synaptic efficacy. Using the mean-field and Monte Carlo simulations we identified ‘superior’ metaplastic models that can substantially overcome the adaptability-precision tradeoff. These models can achieve both adaptability and precision by forming two separate sets of meta-states: reservoirs and buffers. Synapses in reservoir meta-states do not change their efficacy upon reward feedback, whereas those in buffer meta-states can change their efficacy. Rapid changes in efficacy are limited to synapses occupying buffers, creating a bottleneck that reduces noise without significantly decreasing adaptability. In contrast, more-populated reservoirs can generate a strong signal without manifesting any observable plasticity. By comparing the behavior of our model and a few competing models during a dynamic probability estimation task, we found that superior metaplastic models perform close to optimally for a wider range of model parameters. Finally, we found that metaplastic models are robust to changes in model parameters and that metaplastic transitions are crucial for adaptive learning since replacing them with graded plastic transitions (transitions that change synaptic efficacy) reduces the ability to overcome the adaptability-precision tradeoff. Overall, our results suggest that ubiquitous unreliability of synaptic changes evinces metaplasticity that can provide a robust mechanism for mitigating the tradeoff between adaptability and precision and thus adaptive learning. PMID:28658247

Association between stride time fractality and gait adaptability during unperturbed and asymmetric walking.

PubMed

Ducharme, Scott W; Liddy, Joshua J; Haddad, Jeffrey M; Busa, Michael A; Claxton, Laura J; van Emmerik, Richard E A

2018-04-01

Human locomotion is an inherently complex activity that requires the coordination and control of neurophysiological and biomechanical degrees of freedom across various spatiotemporal scales. Locomotor patterns must constantly be altered in the face of changing environmental or task demands, such as heterogeneous terrains or obstacles. Variability in stride times occurring at short time scales (e.g., 5-10 strides) is statistically correlated to larger fluctuations occurring over longer time scales (e.g., 50-100 strides). This relationship, known as fractal dynamics, is thought to represent the adaptive capacity of the locomotor system. However, this has not been tested empirically. Thus, the purpose of this study was to determine if stride time fractality during steady state walking associated with the ability of individuals to adapt their gait patterns when locomotor speed and symmetry are altered. Fifteen healthy adults walked on a split-belt treadmill at preferred speed, half of preferred speed, and with one leg at preferred speed and the other at half speed (2:1 ratio asymmetric walking). The asymmetric belt speed condition induced gait asymmetries that required adaptation of locomotor patterns. The slow speed manipulation was chosen in order to determine the impact of gait speed on stride time fractal dynamics. Detrended fluctuation analysis was used to quantify the correlation structure, i.e., fractality, of stride times. Cross-correlation analysis was used to measure the deviation from intended anti-phasing between legs as a measure of gait adaptation. Results revealed no association between unperturbed walking fractal dynamics and gait adaptability performance. However, there was a quadratic relationship between perturbed, asymmetric walking fractal dynamics and adaptive performance during split-belt walking, whereby individuals who exhibited fractal scaling exponents that deviated from 1/f performed the poorest. Compared to steady state preferred walking speed, fractal dynamics increased closer to 1/f when participants were exposed to asymmetric walking. These findings suggest there may not be a relationship between unperturbed preferred or slow speed walking fractal dynamics and gait adaptability. However, the emergent relationship between asymmetric walking fractal dynamics and limb phase adaptation may represent a functional reorganization of the locomotor system (i.e., improved interactivity between degrees of freedom within the system) to be better suited to attenuate externally generated perturbations at various spatiotemporal scales. Copyright © 2018 Elsevier B.V. All rights reserved.

Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.

PubMed

Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David

2014-08-01

In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.

Behavioural adaptations of two sympatric sandhoppers living on a mesotidal European Atlantic sandy beach

NASA Astrophysics Data System (ADS)

Bessa, Filipa; Marques, João Carlos; Scapini, Felicita

2014-06-01

Behavioural adaptations of supralittoral species on sandy beaches are expressed as responses to environmental changes and constitute a key factor in their survival and evolution. Two sympatric talitrid amphipods (Talitrus saltator and Britorchestia brito) from a mesotidal exposed sandy beach on the European Atlantic coast (Portugal) were compared as regards orientation and littoral zonation patterns under natural conditions. Orientation experiments were carried out during spring and summer 2011 and 2012 at Quiaios beach, a highly dynamic exposed sandy beach. Multiple regression models were fitted to the angular data and the environmental effects on orientation were investigated for each species. Both talitrids were shown to be well orientated towards the shoreline and finely adapted to the mesotidal environment but a different use of local cues and climatic features between the two species was apparent. T. saltator showed a lower precision in the orientation performance (with a bimodal distribution sea- and land-wards), with less dependence on the sun cues and higher dependence on climatic features. In addition, the zonation of T. saltator was across the land-sea axis during both seasons. For B. brito the landscape vision, sun visibility and the tidal range enhanced the orientation to the shoreline. On this mesotidal Atlantic beach, T. saltator appeared to have a more flexible orientation with respect to B. brito, which appeared to be more dependent on the conditions offered by the intertidal zone, a behaviour confirmed by its restricted zonation below the high tide mark. Consequently, T. saltator showed a more flexible behaviour that may be considered an important evolutionary adaptation to dynamic and mesotidal sandy beaches.

Homeostatic Scaling of Excitability in Recurrent Neural Networks

PubMed Central

Remme, Michiel W. H.; Wadman, Wytse J.

2012-01-01

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity. PMID:22570604

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

NASA Astrophysics Data System (ADS)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

Rethinking climate change adaptation and place through a situated pathways framework: A case study from the Big Hole Valley, USA

Treesearch

Daniel J. Murphy; Laurie Yung; Carina Wyborn; Daniel R. Williams

2017-01-01

This paper critically examines the temporal and spatial dynamics of adaptation in climate change science and explores how dynamic notions of 'place' elucidate novel ways of understanding community vulnerability and adaptation. Using data gathered from a narrative scenario-building process carried out among communities of the Big Hole Valley in Montana, the...

3D level set methods for evolving fronts on tetrahedral meshes with adaptive mesh refinement

DOE PAGES

Morgan, Nathaniel Ray; Waltz, Jacob I.

2017-03-02

The level set method is commonly used to model dynamically evolving fronts and interfaces. In this work, we present new methods for evolving fronts with a specified velocity field or in the surface normal direction on 3D unstructured tetrahedral meshes with adaptive mesh refinement (AMR). The level set field is located at the nodes of the tetrahedral cells and is evolved using new upwind discretizations of Hamilton–Jacobi equations combined with a Runge–Kutta method for temporal integration. The level set field is periodically reinitialized to a signed distance function using an iterative approach with a new upwind gradient. We discuss themore » details of these level set and reinitialization methods. Results from a range of numerical test problems are presented.« less

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature.

PubMed

Li, Yuankun; Xu, Tingfa; Deng, Honggao; Shi, Guokai; Guo, Jie

2018-02-23

Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.

On the dynamics of some grid adaption schemes

NASA Technical Reports Server (NTRS)

Sweby, Peter K.; Yee, Helen C.

1994-01-01

The dynamics of a one-parameter family of mesh equidistribution schemes coupled with finite difference discretisations of linear and nonlinear convection-diffusion model equations is studied numerically. It is shown that, when time marched to steady state, the grid adaption not only influences the stability and convergence rate of the overall scheme, but can also introduce spurious dynamics to the numerical solution procedure.

Dynamic nanoplatforms in biosensor and membrane constitutional systems.

PubMed

Mahon, Eugene; Aastrup, Teodor; Barboiu, Mihail

2012-01-01

Molecular recognition in biological systems occurs mainly at interfacial environments such as membrane surfaces, enzyme active sites, or the interior of the DNA double helix. At the cell membrane surface, carbohydrate-protein recognition principles apply to a range of specific non-covalent interactions including immune response, cell proliferation, adhesion and death, cell-cell interaction and communication. Protein-protein recognition meanwhile accounts for signalling processes and ion channel structure. In this chapter we aim to describe such constitutional dynamic interfaces for biosensing and membrane transport applications. Constitutionally adaptive interfaces may mimic the recognition capabilities intrinsic to natural recognition processes. We present some recent examples of 2D and 3D constructed sensors and membranes of this type and describe their sensing and transport capabilities.

Conservation and adaptation to climate change.

PubMed

Brooke, Cassandra

2008-12-01

The need to adapt to climate change has become increasingly apparent, and many believe the practice of biodiversity conservation will need to alter to face this challenge. Conservation organizations are eager to determine how they should adapt their practices to climate change. This involves asking the fundamental question of what adaptation to climate change means. Most studies on climate change and conservation, if they consider adaptation at all, assume it is equivalent to the ability of species to adapt naturally to climate change as stated in Article 2 of the United Nations Framework Convention on Climate Change. Adaptation, however, can refer to an array of activities that range from natural adaptation, at one end of the spectrum, to sustainability science in coupled human and natural systems at the other. Most conservation organizations deal with complex systems in which adaptation to climate change involves making decisions on priorities for biodiversity conservation in the face of dynamic risks and involving the public in these decisions. Discursive methods such as analytic deliberation are useful for integrating scientific knowledge with public perceptions and values, particularly when large uncertainties and risks are involved. The use of scenarios in conservation planning is a useful way to build shared understanding at the science-policy interface. Similarly, boundary organizations-organizations or institutions that bridge different scales or mediate the relationship between science and policy-could prove useful for managing the transdisciplinary nature of adaptation to climate change, providing communication and brokerage services and helping to build adaptive capacity. The fact that some nongovernmental organizations (NGOs) are active across the areas of science, policy, and practice makes them well placed to fulfill this role in integrated assessments of biodiversity conservation and adaptation to climate change.

Mesoscale simulation of concrete spall failure

NASA Astrophysics Data System (ADS)

Knell, S.; Sauer, M.; Millon, O.; Riedel, W.

2012-05-01

Although intensively studied, it is still being debated which physical mechanisms are responsible for the increase of dynamic strength and fracture energy of concrete observed at high loading rates, and to what extent structural inertia forces on different scales contribute to the observation. We present a new approach for the three dimensional mesoscale modelling of dynamic damage and cracking in concrete. Concrete is approximated as a composite of spherical elastic aggregates of mm to cm size embedded in an elastic cement stone matrix. Cracking within the matrix and at aggregate interfaces in the μm range are modelled with adaptively inserted—initially rigid—cohesive interface elements. The model is applied to analyse the dynamic tensile failure observed in Hopkinson-Bar spallation experiments with strain rates up to 100/s. The influence of the key mesoscale failure parameters of strength, fracture energy and relative weakening of the ITZ on macromechanic strength, momentum and energy conservation is numerically investigated.

Agreement dynamics on interaction networks with diverse topologies

NASA Astrophysics Data System (ADS)

Barrat, Alain; Baronchelli, Andrea; Dall'Asta, Luca; Loreto, Vittorio

2007-06-01

We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence.

Epitaxial Ge2Sb2Te5 probed by single cycle THz pulses of coherent synchrotron radiation

NASA Astrophysics Data System (ADS)

Bragaglia, V.; Schnegg, A.; Calarco, R.; Holldack, K.

2016-10-01

A THz-probe spectroscopy scheme with laser-induced single cycle pulses of coherent synchrotron radiation is devised and adapted to reveal the dynamic THz transmittance response in epitaxially grown phase change materials upon 800 nm fs-laser excitation. Amorphous (a-) and crystalline (c-) films of the prototypical Ge2Sb2Te5 (GST) alloy are probed with single cycle THz pulses tuned to the spectral range of the highest absorption contrast at 2 THz. After an initial instantaneous sub-picosecond (ps) dynamic THz transmittance drop, the response of a-GST in that range is dominated only by a short recovery time τshort = 2 ps of the excited carriers. On the contrary, the behavior of the c-GST response displays a short decay of 0.85 ps followed by a long one τlong = 90 ps, suggesting that vacancy layers in an ordered c-GST play a role as dissipation channel for photo-induced free carriers.

Theta dynamics reveal domain-specific control over stimulus and response conflict.

PubMed

Nigbur, Roland; Cohen, Michael X; Ridderinkhof, K Richard; Stürmer, Birgit

2012-05-01

Cognitive control allows us to adjust to environmental changes. The medial frontal cortex (MFC) is thought to detect conflicts and recruit additional resources from other brain areas including the lateral prefrontal cortices. Here we investigated how the MFC acts in concert with visual, motor, and lateral prefrontal cortices to support adaptations of goal-directed behavior. Physiologically, these interactions may occur through local and long-range synchronized oscillation dynamics, particularly in the theta range (4-8 Hz). A speeded flanker task allowed us to investigate conflict-type-specific control networks for perceptual and response conflicts. Theta power over MFC was sensitive to both perceptual and response conflict. Interareal theta phase synchrony, however, indicated a selective enhancement specific for response conflicts between MFC and left frontal cortex as well as between MFC and the presumed motor cortex contralateral to the response hand. These findings suggest that MFC theta-band activity is both generally involved in conflict processing and specifically involved in linking a neural network controlling response conflict.

Brain-wide neuronal dynamics during motor adaptation in zebrafish.

PubMed

Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

2012-05-09

A fundamental question in neuroscience is how entire neural circuits generate behaviour and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record the activity of large populations of neurons at the cellular level, throughout the brain of larval zebrafish expressing a genetically encoded calcium sensor, while the paralysed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neuronal response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioural adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behaviour.

Brain-wide neuronal dynamics during motor adaptation in zebrafish

PubMed Central

Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

2013-01-01

A fundamental question in neuroscience is how entire neural circuits generate behavior and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record activity of large populations of neurons at the cellular level throughout the brain of larval zebrafish expressing a genetically-encoded calcium sensor, while the paralyzed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neural response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioral adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behavior. PMID:22622571

Optimal region of latching activity in an adaptive Potts model for networks of neurons

NASA Astrophysics Data System (ADS)

Abdollah-nia, Mohammad-Farshad; Saeedghalati, Mohammadkarim; Abbassian, Abdolhossein

2012-02-01

In statistical mechanics, the Potts model is a model for interacting spins with more than two discrete states. Neural networks which exhibit features of learning and associative memory can also be modeled by a system of Potts spins. A spontaneous behavior of hopping from one discrete attractor state to another (referred to as latching) has been proposed to be associated with higher cognitive functions. Here we propose a model in which both the stochastic dynamics of Potts models and an adaptive potential function are present. A latching dynamics is observed in a limited region of the noise(temperature)-adaptation parameter space. We hence suggest noise as a fundamental factor in such alternations alongside adaptation. From a dynamical systems point of view, the noise-adaptation alternations may be the underlying mechanism for multi-stability in attractor-based models. An optimality criterion for realistic models is finally inferred.

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

NASA Technical Reports Server (NTRS)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

Workload-Matched Adaptive Automation Support of Air Traffic Controller Information Processing Stages

NASA Technical Reports Server (NTRS)

Kaber, David B.; Prinzel, Lawrence J., III; Wright, Melanie C.; Clamann, Michael P.

2002-01-01

Adaptive automation (AA) has been explored as a solution to the problems associated with human-automation interaction in supervisory control environments. However, research has focused on the performance effects of dynamic control allocations of early stage sensory and information acquisition functions. The present research compares the effects of AA to the entire range of information processing stages of human operators, such as air traffic controllers. The results provide evidence that the effectiveness of AA is dependent on the stage of task performance (human-machine system information processing) that is flexibly automated. The results suggest that humans are better able to adapt to AA when applied to lower-level sensory and psychomotor functions, such as information acquisition and action implementation, as compared to AA applied to cognitive (analysis and decision-making) tasks. The results also provide support for the use of AA, as compared to completely manual control. These results are discussed in terms of implications for AA design for aviation.

Unbalance vibration suppression for AMBs system using adaptive notch filter

NASA Astrophysics Data System (ADS)

Chen, Qi; Liu, Gang; Han, Bangcheng

2017-09-01

The unbalance of rotor levitated by active magnetic bearings (AMBs) will cause synchronous vibration which greatly degrade the performance at high speeds in the rotating machinery. To suppress the unbalance vibration without angular velocity information, a novel modified adaptive notch filter (ANF) with phase shift in the AMBs system is presented in this study. Firstly, a 4-degree-of-freedom (DOF) radial unbalanced AMB rotor system is described and analyzed, and the solution of rotor vibration displacement is compared with the experimental data to verify the preciseness of the dynamic model. Then the principle and structure of the proposed notch filter used for the frequency estimation and online identification of synchronous component are presented. As well, the convergence property of the algorithm is investigated. In addition, the stability analysis of the closed-loop AMB system with the proposed ANF is conducted. Simulation and experiments on an AMB driveline system demonstrate the effectiveness and the adaptive characteristics of the proposed ANF on the elimination of synchronous controlled current in a widely operating speed range.

Evolutionary advantages of adaptive rewarding

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2012-09-01

Our well-being depends on both our personal success and the success of our society. The realization of this fact makes cooperation an essential trait. Experiments have shown that rewards can elevate our readiness to cooperate, but since giving a reward inevitably entails paying a cost for it, the emergence and stability of such behavior remains elusive. Here we show that allowing for the act of rewarding to self-organize in dependence on the success of cooperation creates several evolutionary advantages that instill new ways through which collaborative efforts are promoted. Ranging from indirect territorial battle to the spontaneous emergence and destruction of coexistence, phase diagrams and the underlying spatial patterns reveal fascinatingly rich social dynamics that explain why this costly behavior has evolved and persevered. Comparisons with adaptive punishment, however, uncover an Achilles heel of adaptive rewarding, coming from over-aggression, which in turn hinders optimal utilization of network reciprocity. This may explain why, despite its success, rewarding is not as firmly embedded into our societal organization as punishment.

A comparison between the first-fit settings of two multichannel digital signal-processing strategies: music quality ratings and speech-in-noise scores.

PubMed

Higgins, Paul; Searchfield, Grant; Coad, Gavin

2012-06-01

The aim of this study was to determine which level-dependent hearing aid digital signal-processing strategy (DSP) participants preferred when listening to music and/or performing a speech-in-noise task. Two receiver-in-the-ear hearing aids were compared: one using 32-channel adaptive dynamic range optimization (ADRO) and the other wide dynamic range compression (WDRC) incorporating dual fast (4 channel) and slow (15 channel) processing. The manufacturers' first-fit settings based on participants' audiograms were used in both cases. Results were obtained from 18 participants on a quick speech-in-noise (QuickSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) task and for 3 music listening conditions (classical, jazz, and rock). Participants preferred the quality of music and performed better at the QuickSIN task using the hearing aids with ADRO processing. A potential reason for the better performance of the ADRO hearing aids was less fluctuation in output with change in sound dynamics. ADRO processing has advantages for both music quality and speech recognition in noise over the multichannel WDRC processing that was used in the study. Further evaluations of which DSP aspects contribute to listener preference are required.

Nanostructural self-organization and dynamic adaptation of metal-polymer tribosystems

NASA Astrophysics Data System (ADS)

Mashkov, Yu. K.

2017-02-01

The results of investigating the effect of nanosize modifiers of a polymer matrix on the nanostructural self-organization of polymer composites and dynamic adaptation of metal-polymer tribosystems, which considerably affect the wear resistance of polymer composite materials, have been analyzed. It has been shown that the physicochemical nanostructural self-organization processes are developed in metal-polymer tribosystems with the formation of thermotropic liquid-crystal structures of the polymer matrix, followed by the transition of the system to the stationary state with a negative feedback that ensures dynamic adaptation of the tribosystem to given operating conditions.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling

PubMed Central

Jacobs, Matthieu; Grégoire, Nicolas; Couet, William; Bulitta, Jurgen B.

2016-01-01

Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS) were performed for models with one susceptible bacterial population without (M1) or with a resting stage (M2), a one population model with adaptive resistance (M5), models with pre-existing susceptible and resistant populations without (M3) or with (M4) inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6). For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range) or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h). Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions) were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10%) and had good imprecision (<30%). However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and ultimately patients. PMID:26967893

Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

NASA Technical Reports Server (NTRS)

Luong, Phu Vinh; Thompson, J. F.; Gatlin, B.; Mastin, C. W.; Kim, H. J.

1992-01-01

In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code.

Modelling the dynamics of traits involved in fighting-predators-prey system.

PubMed

Kooi, B W

2015-12-01

We study the dynamics of a predator-prey system where predators fight for captured prey besides searching for and handling (and digestion) of the prey. Fighting for prey is modelled by a continuous time hawk-dove game dynamics where the gain depends on the amount of disputed prey while the costs for fighting is constant per fighting event. The strategy of the predator-population is quantified by a trait being the proportion of the number of predator-individuals playing hawk tactics. The dynamics of the trait is described by two models of adaptation: the replicator dynamics (RD) and the adaptive dynamics (AD). In the RD-approach a variant individual with an adapted trait value changes the population's strategy, and consequently its trait value, only when its payoff is larger than the population average. In the AD-approach successful replacement of the resident population after invasion of a rare variant population with an adapted trait value is a step in a sequence changing the population's strategy, and hence its trait value. The main aim is to compare the consequences of the two adaptation models. In an equilibrium predator-prey system this will lead to convergence to a neutral singular strategy, while in the oscillatory system to a continuous singular strategy where in this endpoint the resident population is not invasible by any variant population. In equilibrium (low prey carrying capacity) RD and AD-approach give the same results, however not always in a periodically oscillating system (high prey carrying-capacity) where the trait is density-dependent. For low costs the predator population is monomorphic (only hawks) while for high costs dimorphic (hawks and doves). These results illustrate that intra-specific trait dynamics matters in predator-prey dynamics.

Dynamic optimization of metabolic networks coupled with gene expression.

PubMed

Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

2015-01-21

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright © 2014 Elsevier Ltd. All rights reserved.

Population Dynamics of Genetic Regulatory Networks

NASA Astrophysics Data System (ADS)

Braun, Erez

2005-03-01

Unlike common objects in physics, a biological cell processes information. The cell interprets its genome and transforms the genomic information content, through the action of genetic regulatory networks, into proteins which in turn dictate its metabolism, functionality and morphology. Understanding the dynamics of a population of biological cells presents a unique challenge. It requires to link the intracellular dynamics of gene regulation, through the mechanism of cell division, to the level of the population. We present experiments studying adaptive dynamics of populations of genetically homogeneous microorganisms (yeast), grown for long durations under steady conditions. We focus on population dynamics that do not involve random genetic mutations. Our experiments follow the long-term dynamics of the population distributions and allow to quantify the correlations among generations. We focus on three interconnected issues: adaptation of genetically homogeneous populations following environmental changes, selection processes on the population and population variability and expression distributions. We show that while the population exhibits specific short-term responses to environmental inputs, it eventually adapts to a robust steady-state, largely independent of external conditions. Cycles of medium-switch show that the adapted state is imprinted in the population and that this memory is maintained for many generations. To further study population adaptation, we utilize the process of gene recruitment whereby a gene naturally regulated by a specific promoter is placed under a different regulatory system. This naturally occurring process has been recognized as a major driving force in evolution. We have recruited an essential gene to a foreign regulatory network and followed the population long-term dynamics. Rewiring of the regulatory network allows us to expose their complex dynamics and phase space structure.

Design of high-performance adaptive objective lens with large optical depth scanning range for ultrabroad near infrared microscopic imaging

PubMed Central

Lan, Gongpu; Mauger, Thomas F.; Li, Guoqiang

2015-01-01

We report on the theory and design of adaptive objective lens for ultra broadband near infrared light imaging with large dynamic optical depth scanning range by using an embedded tunable lens, which can find wide applications in deep tissue biomedical imaging systems, such as confocal microscope, optical coherence tomography (OCT), two-photon microscopy, etc., both in vivo and ex vivo. This design is based on, but not limited to, a home-made prototype of liquid-filled membrane lens with a clear aperture of 8mm and the thickness of 2.55mm ~3.18mm. It is beneficial to have an adaptive objective lens which allows an extended depth scanning range larger than the focal length zoom range, since this will keep the magnification of the whole system, numerical aperture (NA), field of view (FOV), and resolution more consistent. To achieve this goal, a systematic theory is presented, for the first time to our acknowledgment, by inserting the varifocal lens in between a front and a back solid lens group. The designed objective has a compact size (10mm-diameter and 15mm-length), ultrabroad working bandwidth (760nm - 920nm), a large depth scanning range (7.36mm in air) — 1.533 times of focal length zoom range (4.8mm in air), and a FOV around 1mm × 1mm. Diffraction-limited performance can be achieved within this ultrabroad bandwidth through all the scanning depth (the resolution is 2.22 μm - 2.81 μm, calculated at the wavelength of 800nm with the NA of 0.214 - 0.171). The chromatic focal shift value is within the depth of focus (field). The chromatic difference in distortion is nearly zero and the maximum distortion is less than 0.05%. PMID:26417508

The influence of leaf size and shape on leaf thermal dynamics: does theory hold up under natural conditions?

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

Leigh, A.; Sevanto, Sanna Annika; Close, J. D.

Laboratory studies on artificial leaves suggest that leaf thermal dynamics are strongly influenced by the two-dimensional size and shape of leaves and associated boundary layer thickness. Hot environments are therefore said to favour selection for small, narrow or dissected leaves. Empirical evidence from real leaves under field conditions is scant and traditionally based on point measurements that do not capture spatial variation in heat load. Here in this study, we used thermal imagery under field conditions to measure the leaf thermal time constant (τ) in summer and the leaf-to-air temperature difference (ΔT) and temperature range across laminae (T range) duringmore » winter, autumn and summer for 68 Proteaceae species. We investigated the influence of leaf area and margin complexity relative to effective leaf width (w e), the latter being a more direct indicator of boundary layer thickness. Normalized difference of margin complexity had no or weak effects on thermal dynamics, but w e strongly predicted τ and ΔT, whereas leaf area influenced T range. Unlike artificial leaves, however, spatial temperature distribution in large leaves appeared to be governed largely by structural variation. Therefore, we agree that small size, specifically we, has adaptive value in hot environments but not with the idea that thermal regulation is the primary evolutionary driver of leaf dissection.« less

The influence of leaf size and shape on leaf thermal dynamics: does theory hold up under natural conditions?

DOE PAGES

Leigh, A.; Sevanto, Sanna Annika; Close, J. D.; ...

2016-11-05

Laboratory studies on artificial leaves suggest that leaf thermal dynamics are strongly influenced by the two-dimensional size and shape of leaves and associated boundary layer thickness. Hot environments are therefore said to favour selection for small, narrow or dissected leaves. Empirical evidence from real leaves under field conditions is scant and traditionally based on point measurements that do not capture spatial variation in heat load. Here in this study, we used thermal imagery under field conditions to measure the leaf thermal time constant (τ) in summer and the leaf-to-air temperature difference (ΔT) and temperature range across laminae (T range) duringmore » winter, autumn and summer for 68 Proteaceae species. We investigated the influence of leaf area and margin complexity relative to effective leaf width (w e), the latter being a more direct indicator of boundary layer thickness. Normalized difference of margin complexity had no or weak effects on thermal dynamics, but w e strongly predicted τ and ΔT, whereas leaf area influenced T range. Unlike artificial leaves, however, spatial temperature distribution in large leaves appeared to be governed largely by structural variation. Therefore, we agree that small size, specifically we, has adaptive value in hot environments but not with the idea that thermal regulation is the primary evolutionary driver of leaf dissection.« less

Dynamic Reconstruction and Multivariable Control for Force-Actuated, Thin Facesheet Adaptive Optics

NASA Technical Reports Server (NTRS)

Grocott, Simon C. O.; Miller, David W.

1997-01-01

The Multiple Mirror Telescope (MMT) under development at the University of Arizona takes a new approach in adaptive optics placing a large (0.65 m) force-actuated, thin facesheet deformable mirror at the secondary of an astronomical telescope, thus reducing the effects of emissivity which are important in IR astronomy. However, The large size of the mirror and low stiffness actuators used drive the natural frequencies of the mirror down into the bandwidth of the atmospheric distortion. Conventional adaptive optics takes a quasi-static approach to controlling the, deformable mirror. However, flexibility within the control bandwidth calls for a new approach to adaptive optics. Dynamic influence functions are used to characterize the influence of each actuator on the surface of the deformable mirror. A linearized model of atmospheric distortion is combined with dynamic influence functions to produce a dynamic reconstructor. This dynamic reconstructor is recognized as an optimal control problem. Solving the optimal control problem for a system with hundreds of actuators and sensors is formidable. Exploiting the circularly symmetric geometry of the mirror, and a suitable model of atmospheric distortion, the control problem is divided into a number of smaller decoupled control problems using circulant matrix theory. A hierarchic control scheme which seeks to emulate the quasi-static control approach that is generally used in adaptive optics is compared to the proposed dynamic reconstruction technique. Although dynamic reconstruction requires somewhat more computational power to implement, it achieves better performance with less power usage, and is less sensitive than the hierarchic technique.

Some design guidelines for discrete-time adaptive controllers

NASA Technical Reports Server (NTRS)

Rohrs, C. E.; Athans, M.; Valavani, L.; Stein, G.

1985-01-01

There have been many algorithms proposed for adaptive control which will provide globally asymptotically stable controllers if some stringent conditions on the plant are met. The conditions on the plant cannot be met in practice as all plants will contain high frequency unmolded dynamics therefore, blind implementation of the published algorithms can lead to disastrous results. This paper uses a linearization analysis of a non-linear adaptive controller to demonstrate analytically design guidelines which aleviate some of the problems associated with adaptive control in the presence of unmodeled dynamics.

Effect of dispersal at range edges on the structure of species ranges

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Range edges are of particular interest to ecology because they hold key insights into the limits of the realized niche and associated population dynamics. A recent feature of Oikos summarized the state of the art on range edge ecology. While the typical question is what causes range edges, another important question is how range edges influence the distribution of abundances across a species geographic range when dispersal is present. We used a single species population dynamics model on a coupled-lattice to determine the effects of dispersal on peripheral populations as compared to populations at the core of the range. In the absence of resource gradients, the reduced neighborhood and thus lower connectivity or higher isolation among populations at the range edge alone led to significantly lower population sizes in the periphery of the range than in the core. Lower population sizes mean higher extinction risks and lower adaptability at the range edge, which could inhibit or slow range expansions, and thus effectively stabilize range edges. The strength of this effect depended on the potential population growth rate and the maximum dispersal distance. Lower potential population growth rates led to a stronger effect of dispersal resulting in a higher difference in population sizes between the two areas. The differential effect of dispersal on population sizes at the core and periphery of the range in the absence of resource gradients implies that traditional, habitat-based distribution models could result in misleading conclusions about the habitat quality in the periphery. Lower population sizes at the periphery are also relevant to conservation, because habitat removal not only eliminates populations but also creates new edges. Populations bordering these new edges may experience declines, due to their increased isolation. ?? OIKOS.

Ion-optical studies for a range adaptation method in ion beam therapy using a static wedge degrader combined with magnetic beam deflection.

PubMed

Chaudhri, Naved; Saito, Nami; Bert, Christoph; Franczak, Bernhard; Steidl, Peter; Durante, Marco; Rietzel, Eike; Schardt, Dieter

2010-06-21

Fast radiological range adaptation of the ion beam is essential when target motion is mitigated by beam tracking using scanned ion beams for dose delivery. Electromagnetically controlled deflection of a well-focused ion beam on a small static wedge degrader positioned between two dipole magnets, inside the beam delivery system, has been considered as a fast range adaptation method. The principle of the range adaptation method was tested in experiments and Monte Carlo simulations for the therapy beam line at the GSI Helmholtz Centre for Heavy Ions Research. Based on the simulations, ion optical settings of beam deflection and realignment of the adapted beam were experimentally applied to the beam line, and additional tuning was manually performed. Different degrader shapes were employed for the energy adaptation. Measured and simulated beam profiles, i.e. lateral distribution and range in water at isocentre, were analysed and compared with the therapy beam values for beam scanning. Deflected beam positions of up to +/-28 mm on degrader were performed which resulted in a range adaptation of up to +/-15 mm water equivalence (WE). The maximum deviation between the measured adapted range from the nominal range adaptation was below 0.4 mm WE. In experiments, the width of the adapted beam at the isocentre was adjustable between 5 and 11 mm full width at half maximum. The results demonstrate the feasibility/proof of the proposed range adaptation method for beam tracking from the beam quality point of view.

Modularization and Response Curve Engineering of a Naringenin-Responsive Transcriptional Biosensor.

PubMed

De Paepe, Brecht; Maertens, Jo; Vanholme, Bartel; De Mey, Marjan

2018-05-18

To monitor the intra- and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LacI-, TetR- and AraC-based inducible circuits.

A New Approach to Interference Excision in Radio Astronomy: Real-Time Adaptive Cancellation

NASA Astrophysics Data System (ADS)

Barnbaum, Cecilia; Bradley, Richard F.

1998-11-01

Every year, an increasing amount of radio-frequency (RF) spectrum in the VHF, UHF, and microwave bands is being utilized to support new commercial and military ventures, and all have the potential to interfere with radio astronomy observations. Such services already cause problems for radio astronomy even in very remote observing sites, and the potential for this form of light pollution to grow is alarming. Preventive measures to eliminate interference through FCC legislation and ITU agreements can be effective; however, many times this approach is inadequate and interference excision at the receiver is necessary. Conventional techniques such as RF filters, RF shielding, and postprocessing of data have been only somewhat successful, but none has been sufficient. Adaptive interference cancellation is a real-time approach to interference excision that has not been used before in radio astronomy. We describe here, for the first time, adaptive interference cancellation in the context of radio astronomy instrumentation, and we present initial results for our prototype receiver. In the 1960s, analog adaptive interference cancelers were developed that obtain a high degree of cancellation in problems of radio communications and radar. However, analog systems lack the dynamic range, noised performance, and versatility required by radio astronomy. The concept of digital adaptive interference cancellation was introduced in the mid-1960s as a way to reduce unwanted noise in low-frequency (audio) systems. Examples of such systems include the canceling of maternal ECG in fetal electrocardiography and the reduction of engine noise in the passenger compartments of automobiles. These audio-frequency applications require bandwidths of only a few tens of kilohertz. Only recently has high-speed digital filter technology made high dynamic range adaptive canceling possible in a bandwidth as large as a few megahertz, finally opening the door to application in radio astronomy. We have built a prototype adaptive canceler that consists of two receivers: the primary channel (input from the main beam of the telescope) and a separate reference channel. The primary channel receives the desired astronomical signal corrupted by RFI (radio-frequency interference) coming in the sidelobes of the main beam. A separate reference antenna is designed to receive only the RFI. The reference channel input is processed using a digital adaptive filter and then subtracted from the primary channel input, producing the system output. The weighting coefficients of the digital filter are adjusted by way of an algorithm that minimizes, in a least-squares sense, the power output of the system. Through an adaptive-iterative process, the canceler locks onto the RFI, and the filter adjusts itself to minimize the effect of the RFI at the system output. We have designed the adaptive canceler with an intermediate frequency (IF) of 40 MHz. This prototype system will ultimately be functional with a variety of radio astronomy receivers in the microwave band. We have also built a prototype receiver centered at 100 MHz (in the FM broadcast band) to test the adaptive canceler with actual interferers, which are well characterized. The initial laboratory tests of the adaptive canceler are encouraging, with attenuation of strong frequency-modulated (FM) interference to 72 dB (a factor of more than 10 million), which is at the performance limit of our measurements. We also consider requirements of the system and the RFI environment for effective adaptive canceling.

Adaptive relative pose control for autonomous spacecraft rendezvous and proximity operations with thrust misalignment and model uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2017-04-01

An adaptive relative pose control strategy is proposed for a pursue spacecraft in proximity operations on a tumbling target. Relative position vector between two spacecraft is required to direct towards the docking port of the target while the attitude of them must be synchronized. With considering the thrust misalignment of pursuer, an integrated controller for relative translational and relative rotational dynamics is developed by using norm-wise adaptive estimations. Parametric uncertainties, unknown coupled dynamics, and bounded external disturbances are compensated online by adaptive update laws. It is proved via Lyapunov stability theory that the tracking errors of relative pose converge to zero asymptotically. Numerical simulations including six degrees-of-freedom rigid body dynamics are performed to demonstrate the effectiveness of the proposed controller.

Adaptive shaping of cortical response selectivity in the vibrissa pathway

PubMed Central

Zheng, He J. V.; Wang, Qi

2015-01-01

One embodiment of context-dependent sensory processing is bottom-up adaptation, where persistent stimuli decrease neuronal firing rate over hundreds of milliseconds. Adaptation is not, however, simply the fatigue of the sensory pathway, but shapes the information flow and selectivity to stimulus features. Adaptation enhances spatial discriminability (distinguishing stimulus location) while degrading detectability (reporting presence of the stimulus), for both the ideal observer of the cortex and awake, behaving animals. However, how the dynamics of the adaptation shape the cortical response and this detection and discrimination tradeoff is unknown, as is to what degree this phenomenon occurs on a continuum as opposed to a switching of processing modes. Using voltage-sensitive dye imaging in anesthetized rats to capture the temporal and spatial characteristics of the cortical response to tactile inputs, we showed that the suppression of the cortical response, in both magnitude and spatial spread, is continuously modulated by the increasing amount of energy in the adapting stimulus, which is nonuniquely determined by its frequency and velocity. Single-trial ideal observer analysis demonstrated a tradeoff between detectability and spatial discriminability up to a moderate amount of adaptation, which corresponds to the frequency range in natural whisking. This was accompanied by a decrease in both detectability and discriminability with high-energy adaptation, which indicates a more complex coupling between detection and discrimination than a simple switching of modes. Taken together, the results suggest that adaptation operates on a continuum and modulates the tradeoff between detectability and discriminability that has implications for information processing in ethological contexts. PMID:25787959

Implications of introducing realistic fire response traits in a Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Kelley, D.; Harrison, S. P.; Prentice, I. C.

2013-12-01

Bark thickness is a key trait protecting woody plants against fire damage, while the ability to resprout is a trait that confers competitive advantage over non-resprouting individuals in fire-prone landscapes. Neither trait is well represented in fire-enabled dynamic global vegetation models (DGVMs). Here we describe a version of the Land Processes and eXchanges (LPX-Mv1) DGVM that incorporates both of these traits in a realistic way. From a synthesis of a large number of field studies, we show there is considerable innate variability in bark thickness between species within a plant-functional type (PFT). Furthermore, bark thickness is an adaptive trait at ecosystem level, increasing with fire frequency. We use the data to specify the range of bark thicknesses characteristic of each model PFT. We allow this distribution to change dynamically: thinner-barked trees are killed preferentially by fire, shifting the distribution of bark thicknesses represented in a model grid cell. We use the PFT-specific bark-thickness probability range for saplings during re-establishment. Since it is rare to destroy all trees in a grid cell, this treatment results in average bark thickness increasing with fire frequency and intensity. Resprouting is a prominent adaptation of temperate and tropical trees in fire-prone areas. The ability to resprout from above-ground tissue (apical or epicormic resprouting) results in the fastest recovery of total biomass after disturbance; resprouting from basal or below-ground meristems results in slower recovery, while non-resprouting species must regenerate from seed and therefore take the longest time to recover. Our analyses show that resprouting species have thicker bark than non-resprouting species. Investment in resprouting is accompanied by reduced efficacy of regeneration from seed. We introduce resprouting PFTs in LPX-Mv1 by specifying an appropriate range of bark thickness, allowing resprouters to survive fire and regenerate vegetatively in the next growing season, while regenerating from seed at 10% the rate of non-resprouters. Tests of LPX-Mv1 for Australia - a continent with a wide range of fire-adapted ecosystems - show that it produces a 33% improvement in the simulation of vegetation composition compared to the previous version of the model, with more realistic vegetation transitions from forests to woodland/savanna. It also produces a 19% improvement in the simulation of burnt area compared to the original model. Resprouting PFTs dominate tropical and temperate areas where the climate is semi-humid but are not common in very dry or very wet areas. Comparison with site-based observations of the abundance of resprouters indicate this is realistic. Ecosystems dominated by resprouters in the simulations recover to pre-fire levels of biomass within 5-7 years, much faster than ecosystems dominated by non-resprouters; again this is confirmed by our analyses of the observations. Simulations of the response to projected future climate change show that the incorporation of adaptive bark thickness and of resprouting has a significant effect on terrestrial carbon stocks in fire-affected areas.

Development of a High Dynamic Range Pixel Array Detector for Synchrotrons and XFELs

NASA Astrophysics Data System (ADS)

Weiss, Joel Todd

Advances in synchrotron radiation light source technology have opened new lines of inquiry in material science, biology, and everything in between. However, x-ray detector capabilities must advance in concert with light source technology to fully realize experimental possibilities. X-ray free electron lasers (XFELs) place particularly large demands on the capabilities of detectors, and developments towards diffraction-limited storage ring sources also necessitate detectors capable of measuring very high flux [1-3]. The detector described herein builds on the Mixed Mode Pixel Array Detector (MM-PAD) framework, developed previously by our group to perform high dynamic range imaging, and the Adaptive Gain Integrating Pixel Detector (AGIPD) developed for the European XFEL by a collaboration between Deustsches Elektronen-Synchrotron (DESY), the Paul-Scherrer-Institute (PSI), the University of Hamburg, and the University of Bonn, led by Heinz Graafsma [4, 5]. The feasibility of combining adaptive gain with charge removal techniques to increase dynamic range in XFEL experiments is assessed by simulating XFEL scatter with a pulsed infrared laser. The strategy is incorporated into pixel prototypes which are evaluated with direct current injection to simulate very high incident x-ray flux. A fully functional 16x16 pixel hybrid integrating x-ray detector featuring several different pixel architectures based on the prototypes was developed. This dissertation describes its operation and characterization. To extend dynamic range, charge is removed from the integration node of the front-end amplifier without interrupting integration. The number of times this process occurs is recorded by a digital counter in the pixel. The parameter limiting full well is thereby shifted from the size of an integration capacitor to the depth of a digital counter. The result is similar to that achieved by counting pixel array detectors, but the integrators presented here are designed to tolerate a sustained flux >1011 x-rays/pixel/second. In addition, digitization of residual analog signals allows sensitivity for single x-rays or low flux signals. Pixel high flux linearity is evaluated by direct exposure to an unattenuated synchrotron source x-ray beam and flux measurements of more than 1010 9.52 keV x-rays/pixel/s are made. Detector sensitivity to small signals is evaluated and dominant sources of error are identified. These new pixels boast multiple orders of magnitude improvement in maximum sustained flux over the MM-PAD, which is capable of measuring a sustained flux in excess of 108 x-rays/pixel/second while maintaining sensitivity to smaller signals, down to single x-rays.

Experimental studies of adaptation in Clarkia xantiana. II. Fitness variation across a subspecies border.

PubMed

Geber, Monica A; Eckhart, Vincent M

2005-03-01

Because the range boundary is the locale beyond which a taxon fails to persist, it provides a unique opportunity for studying the limits on adaptive evolution. Adaptive constraints on range expansion are perplexing in view of widespread ecotypic differentiation by habitat and region within a species' range (regional adaptation) and rapid evolutionary response to novel environments. In this study of two parapatric subspecies, Clarkia xantiana ssp. xantiana and C. x. ssp. parviflora, we compared the fitness of population transplants within their native region, in a non-native region within the native range, and in the non-native range to assess whether range expansion might be limited by a greater intensity of selection on colonists of a new range versus a new region within the range. The combined range of the two subspecies spans a west-to-east gradient of declining precipitation in the Sierra Nevada of California, with ssp. xantiana in the west being replaced by ssp. parviflora in the east. Both subspecies had significantly higher fitness in the native range (range adaptation), whereas regional adaptation was weak and was found only in the predominantly outcrossing ssp. xantiana but was absent in the inbreeding ssp. parvifilora. Because selection intensity on transplants was much stronger in the non-native range relative to non-native regions, there is a larger adaptive barrier to range versus regional expansion. Three of five sequential fitness components accounted for regional and range adaptation, but only one of them, survivorship from germination to flowering, contributed to both. Flower number contributed to regional adaptation in ssp. xantiana and fruit set (number of fruits per flower) to range adaptation. Differential survivorship of the two taxa or regional populations of ssp. xantiana in non-native environments was attributable, in part, to biotic interactions, including competition, herbivory, and pollination. For example, low fruit set in ssp. xantiana in the east was likely due to the absence of its principal specialist bee pollinators in ssp. parviflora's range. Thus, convergence on self-fertilization may be necessary for ssp. xantiana to invade ssp. parviflora's range, but the evolution of outcrossing would not be required for ssp. parviflora to invade ssp. xantiana's range.

Heating and Large Scale Dynamics of the Solar Corona

NASA Technical Reports Server (NTRS)

Schnack, Dalton D.

2000-01-01

The effort was concentrated in the areas: coronal heating mechanism, unstructured adaptive grid algorithms, numerical modeling of magnetic reconnection in the MRX experiment: effect of toroidal magnetic field and finite pressure, effect of OHMIC heating and vertical magnetic field, effect of dynamic MESH adaption.

Dynamic adaptive chemistry for turbulent flame simulations

NASA Astrophysics Data System (ADS)

Yang, Hongtao; Ren, Zhuyin; Lu, Tianfeng; Goldin, Graham M.

2013-02-01

The use of large chemical mechanisms in flame simulations is computationally expensive due to the large number of chemical species and the wide range of chemical time scales involved. This study investigates the use of dynamic adaptive chemistry (DAC) for efficient chemistry calculations in turbulent flame simulations. DAC is achieved through the directed relation graph (DRG) method, which is invoked for each computational fluid dynamics cell/particle to obtain a small skeletal mechanism that is valid for the local thermochemical condition. Consequently, during reaction fractional steps, one needs to solve a smaller set of ordinary differential equations governing chemical kinetics. Test calculations are performed in a partially-stirred reactor (PaSR) involving both methane/air premixed and non-premixed combustion with chemistry described by the 53-species GRI-Mech 3.0 mechanism and the 129-species USC-Mech II mechanism augmented with recently updated NO x pathways, respectively. Results show that, in the DAC approach, the DRG reduction threshold effectively controls the incurred errors in the predicted temperature and species concentrations. The computational saving achieved by DAC increases with the size of chemical kinetic mechanisms. For the PaSR simulations, DAC achieves a speedup factor of up to three for GRI-Mech 3.0 and up to six for USC-Mech II in simulation time, while at the same time maintaining good accuracy in temperature and species concentration predictions.

Adaptive contact networks change effective disease infectiousness and dynamics.

PubMed

Van Segbroeck, Sven; Santos, Francisco C; Pacheco, Jorge M

2010-08-19

Human societies are organized in complex webs that are constantly reshaped by a social dynamic which is influenced by the information individuals have about others. Similarly, epidemic spreading may be affected by local information that makes individuals aware of the health status of their social contacts, allowing them to avoid contact with those infected and to remain in touch with the healthy. Here we study disease dynamics in finite populations in which infection occurs along the links of a dynamical contact network whose reshaping may be biased based on each individual's health status. We adopt some of the most widely used epidemiological models, investigating the impact of the reshaping of the contact network on the disease dynamics. We derive analytical results in the limit where network reshaping occurs much faster than disease spreading and demonstrate numerically that this limit extends to a much wider range of time scales than one might anticipate. Specifically, we show that from a population-level description, disease propagation in a quickly adapting network can be formulated equivalently as disease spreading on a well-mixed population but with a rescaled infectiousness. We find that for all models studied here--SI, SIS and SIR--the effective infectiousness of a disease depends on the population size, the number of infected in the population, and the capacity of healthy individuals to sever contacts with the infected. Importantly, we indicate how the use of available information hinders disease progression, either by reducing the average time required to eradicate a disease (in case recovery is possible), or by increasing the average time needed for a disease to spread to the entire population (in case recovery or immunity is impossible).

Thermal and Cycle-Life Behavior of Commercial Li-ion and Li-Polymer Cells

NASA Technical Reports Server (NTRS)

Zimmerman, Albert H.; Quinzio, M. V.

2001-01-01

Accelerated and real-time LEO cycle-life test data will be presented for a range of commercial Li-ion and Li-polymer (gel type) cells indicating the ranges of performance that can be obtained, and the performance screening tests that must be done to assure long life. The data show large performance variability between cells, as well as a highly variable degradation signature during non-cycling periods within the life tests. High-resolution Dynamic Calorimetry data will be presented showing the complex series of reactions occurring within these Li cells as they are cycled. Data will also be presented for cells being tested using an Adaptive Charge Control Algorithm (ACCA) that continuously adapts itself to changes in cell performance, operation, or environment to both find and maintain the optimum recharge over life. The ACCA has been used to prevent all unneeded overcharge for Li cells, NiCd cells and NiH2 cells. While this is important for all these cell types, it is most critical for Li-ion cells, which are not designed with electrochemical tolerance for overcharge.

Characterising a holographic modal phase mask for the detection of ocular aberrations

NASA Astrophysics Data System (ADS)

Corbett, A. D.; Leyva, D. Gil; Diaz-Santana, L.; Wilkinson, T. D.; Zhong, J. J.

2005-12-01

The accurate measurement of the double-pass ocular wave front has been shown to have a broad range of applications from LASIK surgery to adaptively corrected retinal imaging. The ocular wave front can be accurately described by a small number of Zernike circle polynomials. The modal wave front sensor was first proposed by Neil et al. and allows the coefficients of the individual Zernike modes to be measured directly. Typically the aberrations measured with the modal sensor are smaller than those seen in the ocular wave front. In this work, we investigated a technique for adapting a modal phase mask for the sensing of the ocular wave front. This involved extending the dynamic range of the sensor by increasing the pinhole size to 2.4mm and optimising the mask bias to 0.75λ. This was found to decrease the RMS error by up to a factor of three for eye-like aberrations with amplitudes up to 0.2μm. For aberrations taken from a sample of real-eye measurements a 20% decrease in the RMS error was observed.

Automated adaptive inference of phenomenological dynamical models.

PubMed

Daniels, Bryan C; Nemenman, Ilya

2015-08-21

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

Automated adaptive inference of phenomenological dynamical models

PubMed Central

Daniels, Bryan C.; Nemenman, Ilya

2015-01-01

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications

PubMed Central

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O.

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n2 memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach. PMID:26578867

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

PubMed

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

Adaptation to changes in higher-order stimulus statistics in the salamander retina.

PubMed

Tkačik, Gašper; Ghosh, Anandamohan; Schneidman, Elad; Segev, Ronen

2014-01-01

Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution.

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior.

PubMed

Hansen, Sofie Therese; Hansen, Lars Kai

2017-03-01

Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging connections exist in the brain than long ranging, arguing for spatially focal sources. Additionally, recent work (Delorme et al., 2012) argues that EEG can be decomposed into components having sparse source distributions. On the temporal side both short and long term stationarity of brain activation are seen. We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

Toward Hamiltonian Adaptive QM/MM: Accurate Solvent Structures Using Many-Body Potentials.

PubMed

Boereboom, Jelle M; Potestio, Raffaello; Donadio, Davide; Bulo, Rosa E

2016-08-09

Adaptive quantum mechanical (QM)/molecular mechanical (MM) methods enable efficient molecular simulations of chemistry in solution. Reactive subregions are modeled with an accurate QM potential energy expression while the rest of the system is described in a more approximate manner (MM). As solvent molecules diffuse in and out of the reactive region, they are gradually included into (and excluded from) the QM expression. It would be desirable to model such a system with a single adaptive Hamiltonian, but thus far this has resulted in distorted structures at the boundary between the two regions. Solving this long outstanding problem will allow microcanonical adaptive QM/MM simulations that can be used to obtain vibrational spectra and dynamical properties. The difficulty lies in the complex QM potential energy expression, with a many-body expansion that contains higher order terms. Here, we outline a Hamiltonian adaptive multiscale scheme within the framework of many-body potentials. The adaptive expressions are entirely general, and complementary to all standard (nonadaptive) QM/MM embedding schemes available. We demonstrate the merit of our approach on a molecular system defined by two different MM potentials (MM/MM'). For the long-range interactions a numerical scheme is used (particle mesh Ewald), which yields energy expressions that are many-body in nature. Our Hamiltonian approach is the first to provide both energy conservation and the correct solvent structure everywhere in this system.

Visualizing the dynamic structure of the plant photosynthetic membrane.

PubMed

Ruban, Alexander V; Johnson, Matthew P

2015-11-03

The chloroplast thylakoid membrane is the site for the initial steps of photosynthesis that convert solar energy into chemical energy, ultimately powering almost all life on earth. The heterogeneous distribution of protein complexes within the membrane gives rise to an intricate three-dimensional structure that is nonetheless extremely dynamic on a timescale of seconds to minutes. These dynamics form the basis for the regulation of photosynthesis, and therefore the adaptability of plants to different environments. High-resolution microscopy has in recent years begun to provide new insights into the structural dynamics underlying a number of regulatory processes such as membrane stacking, photosystem II repair, photoprotective energy dissipation, state transitions and alternative electron transfer. Here we provide an overview of the essentials of thylakoid membrane structure in plants, and consider how recent advances, using a range of microscopies, have substantially increased our knowledge of the thylakoid dynamic structure. We discuss both the successes and limitations of the currently available techniques and highlight newly emerging microscopic methods that promise to move the field beyond the current 'static' view of membrane organization based on frozen snapshots to a 'live' view of functional membranes imaged under native aqueous conditions at ambient temperature and responding dynamically to external stimuli.

Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

PubMed Central

Ferriere, Regis; Legendre, Stéphane

2013-01-01

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163

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

Koniges, A.E.; Craddock, G.G.; Schnack, D.D.

The purpose of the workshop was to assemble workers, both within and outside of the fusion-related computations areas, for discussion regarding the issues of dynamically adaptive gridding. There were three invited talks related to adaptive gridding application experiences in various related fields of computational fluid dynamics (CFD), and nine short talks reporting on the progress of adaptive techniques in the specific areas of scrape-off-layer (SOL) modeling and magnetohydrodynamic (MHD) stability. Adaptive mesh methods have been successful in a number of diverse fields of CFD for over a decade. The method involves dynamic refinement of computed field profiles in a waymore » that disperses uniformly the numerical errors associated with discrete approximations. Because the process optimizes computational effort, adaptive mesh methods can be used to study otherwise the intractable physical problems that involve complex boundary shapes or multiple spatial/temporal scales. Recent results indicate that these adaptive techniques will be required for tokamak fluid-based simulations involving the diverted tokamak SOL modeling and MHD simulations problems related to the highest priority ITER relevant issues.Individual papers are indexed separately on the energy data bases.« less

A Quasiphysics Intelligent Model for a Long Range Fast Tool Servo

PubMed Central

Liu, Qiang; Zhou, Xiaoqin; Lin, Jieqiong; Xu, Pengzi; Zhu, Zhiwei

2013-01-01

Accurately modeling the dynamic behaviors of fast tool servo (FTS) is one of the key issues in the ultraprecision positioning of the cutting tool. Herein, a quasiphysics intelligent model (QPIM) integrating a linear physics model (LPM) and a radial basis function (RBF) based neural model (NM) is developed to accurately describe the dynamic behaviors of a voice coil motor (VCM) actuated long range fast tool servo (LFTS). To identify the parameters of the LPM, a novel Opposition-based Self-adaptive Replacement Differential Evolution (OSaRDE) algorithm is proposed which has been proved to have a faster convergence mechanism without compromising with the quality of solution and outperform than similar evolution algorithms taken for consideration. The modeling errors of the LPM and the QPIM are investigated by experiments. The modeling error of the LPM presents an obvious trend component which is about ±1.15% of the full span range verifying the efficiency of the proposed OSaRDE algorithm for system identification. As for the QPIM, the trend component in the residual error of LPM can be well suppressed, and the error of the QPIM maintains noise level. All the results verify the efficiency and superiority of the proposed modeling and identification approaches. PMID:24163627

Stochastic Models of Emerging Infectious Disease Transmission on Adaptive Random Networks

PubMed Central

Pipatsart, Navavat; Triampo, Wannapong

2017-01-01

We presented adaptive random network models to describe human behavioral change during epidemics and performed stochastic simulations of SIR (susceptible-infectious-recovered) epidemic models on adaptive random networks. The interplay between infectious disease dynamics and network adaptation dynamics was investigated in regard to the disease transmission and the cumulative number of infection cases. We found that the cumulative case was reduced and associated with an increasing network adaptation probability but was increased with an increasing disease transmission probability. It was found that the topological changes of the adaptive random networks were able to reduce the cumulative number of infections and also to delay the epidemic peak. Our results also suggest the existence of a critical value for the ratio of disease transmission and adaptation probabilities below which the epidemic cannot occur. PMID:29075314

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Evolution of Gustatory Receptor Gene Family Provides Insights into Adaptation to Diverse Host Plants in Nymphalid Butterflies.

PubMed

Suzuki, Hiromu C; Ozaki, Katsuhisa; Makino, Takashi; Uchiyama, Hironobu; Yajima, Shunsuke; Kawata, Masakado

2018-06-01

The host plant range of herbivorous insects is a major aspect of insect-plant interaction, but the genetic basis of host range expansion in insects is poorly understood. In butterflies, gustatory receptor genes (GRs) play important roles in host plant selection by ovipositing females. Since several studies have shown associations between the repertoire sizes of chemosensory gene families and the diversity of resource use, we hypothesized that the increase in the number of genes in the GR family is associated with host range expansion in butterflies. Here, we analyzed the evolutionary dynamics of GRs among related species, including the host generalist Vanessa cardui and three specialists. Although the increase of the GR repertoire itself was not observed, we found that the gene birth rate of GRs was the highest in the lineage leading to V. cardui compared with other specialist lineages. We also identified two taxon-specific subfamilies of GRs, characterized by frequent lineage-specific duplications and higher non-synonymous substitution rates. Together, our results suggest that frequent gene duplications in GRs, which might be involved in the detection of plant secondary metabolites, were associated with host range expansion in the V. cardui lineage. These evolutionary patterns imply that the capability to perceive various compounds during host selection was favored during adaptation to diverse host plants.

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adaptive governance of riverine and wetland ecosystem goods and services

EPA Science Inventory

Adaptive governance and adaptive management have developed over the past quarter century in response to institutional and organizational failures, and unforeseen changes in natural resource dynamics. Adaptive governance provides a context for managing known and unknown consequenc...

An adaptive compensation algorithm for temperature drift of micro-electro-mechanical systems gyroscopes using a strong tracking Kalman filter.

PubMed

Feng, Yibo; Li, Xisheng; Zhang, Xiaojuan

2015-05-13

We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF), the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to -2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation.

Connectivity-Preserving Approach for Distributed Adaptive Synchronized Tracking of Networked Uncertain Nonholonomic Mobile Robots.

PubMed

Yoo, Sung Jin; Park, Bong Seok

2017-09-06

This paper addresses a distributed connectivity-preserving synchronized tracking problem of multiple uncertain nonholonomic mobile robots with limited communication ranges. The information of the time-varying leader robot is assumed to be accessible to only a small fraction of follower robots. The main contribution of this paper is to introduce a new distributed nonlinear error surface for dealing with both the synchronized tracking and the preservation of the initial connectivity patterns among nonholonomic robots. Based on this nonlinear error surface, the recursive design methodology is presented to construct the approximation-based local adaptive tracking scheme at the robot dynamic level. Furthermore, a technical lemma is established to analyze the stability and the connectivity preservation of the total closed-loop control system in the Lyapunov sense. An example is provided to illustrate the effectiveness of the proposed methodology.

Genomic composition and dynamics among Methanomicrobiales predict adaptation to contrasting environments.

PubMed

Browne, Patrick; Tamaki, Hideyuki; Kyrpides, Nikos; Woyke, Tanja; Goodwin, Lynne; Imachi, Hiroyuki; Bräuer, Suzanna; Yavitt, Joseph B; Liu, Wen-Tso; Zinder, Stephen; Cadillo-Quiroz, Hinsby

2017-01-01

Members of the order Methanomicrobiales are abundant, and sometimes dominant, hydrogenotrophic (H 2 -CO 2 utilizing) methanoarchaea in a broad range of anoxic habitats. Despite their key roles in greenhouse gas emissions and waste conversion to methane, little is known about the physiological and genomic bases for their widespread distribution and abundance. In this study, we compared the genomes of nine diverse Methanomicrobiales strains, examined their pangenomes, reconstructed gene flow and identified genes putatively mediating their success across different habitats. Most strains slowly increased gene content whereas one, Methanocorpusculum labreanum, evidenced genome downsizing. Peat-dwelling Methanomicrobiales showed adaptations centered on improved transport of scarce inorganic nutrients and likely use H + rather than Na + transmembrane chemiosmotic gradients during energy conservation. In contrast, other Methanomicrobiales show the potential to concurrently use Na + and H + chemiosmotic gradients. Analyses also revealed that the Methanomicrobiales lack a canonical electron bifurcation system (MvhABGD) known to produce low potential electrons in other orders of hydrogenotrophic methanogens. Additional putative differences in anabolic metabolism suggest that the dynamics of interspecies electron transfer from Methanomicrobiales syntrophic partners can also differ considerably. Altogether, these findings suggest profound differences in electron trafficking in the Methanomicrobiales compared with other hydrogenotrophs, and warrant further functional evaluations.

Quantifying the adaptive cycle

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Quantifying the Adaptive Cycle.

PubMed

Angeler, David G; Allen, Craig R; Garmestani, Ahjond S; Gunderson, Lance H; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

A Framework for Speech Activity Detection Using Adaptive Auditory Receptive Fields.

PubMed

Carlin, Michael A; Elhilali, Mounya

2015-12-01

One of the hallmarks of sound processing in the brain is the ability of the nervous system to adapt to changing behavioral demands and surrounding soundscapes. It can dynamically shift sensory and cognitive resources to focus on relevant sounds. Neurophysiological studies indicate that this ability is supported by adaptively retuning the shapes of cortical spectro-temporal receptive fields (STRFs) to enhance features of target sounds while suppressing those of task-irrelevant distractors. Because an important component of human communication is the ability of a listener to dynamically track speech in noisy environments, the solution obtained by auditory neurophysiology implies a useful adaptation strategy for speech activity detection (SAD). SAD is an important first step in a number of automated speech processing systems, and performance is often reduced in highly noisy environments. In this paper, we describe how task-driven adaptation is induced in an ensemble of neurophysiological STRFs, and show how speech-adapted STRFs reorient themselves to enhance spectro-temporal modulations of speech while suppressing those associated with a variety of nonspeech sounds. We then show how an adapted ensemble of STRFs can better detect speech in unseen noisy environments compared to an unadapted ensemble and a noise-robust baseline. Finally, we use a stimulus reconstruction task to demonstrate how the adapted STRF ensemble better captures the spectrotemporal modulations of attended speech in clean and noisy conditions. Our results suggest that a biologically plausible adaptation framework can be applied to speech processing systems to dynamically adapt feature representations for improving noise robustness.

An adaptive Cartesian control scheme for manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

Geographic and temporal dynamics of a global radiation and diversification in the killer whale.

PubMed

Morin, Phillip A; Parsons, Kim M; Archer, Frederick I; Ávila-Arcos, María C; Barrett-Lennard, Lance G; Dalla Rosa, Luciano; Duchêne, Sebastián; Durban, John W; Ellis, Graeme M; Ferguson, Steven H; Ford, John K; Ford, Michael J; Garilao, Cristina; Gilbert, M Thomas P; Kaschner, Kristin; Matkin, Craig O; Petersen, Stephen D; Robertson, Kelly M; Visser, Ingrid N; Wade, Paul R; Ho, Simon Y W; Foote, Andrew D

2015-08-01

Global climate change during the Late Pleistocene periodically encroached and then released habitat during the glacial cycles, causing range expansions and contractions in some species. These dynamics have played a major role in geographic radiations, diversification and speciation. We investigate these dynamics in the most widely distributed of marine mammals, the killer whale (Orcinus orca), using a global data set of over 450 samples. This marine top predator inhabits coastal and pelagic ecosystems ranging from the ice edge to the tropics, often exhibiting ecological, behavioural and morphological variation suggestive of local adaptation accompanied by reproductive isolation. Results suggest a rapid global radiation occurred over the last 350 000 years. Based on habitat models, we estimated there was only a 15% global contraction of core suitable habitat during the last glacial maximum, and the resources appeared to sustain a constant global effective female population size throughout the Late Pleistocene. Reconstruction of the ancestral phylogeography highlighted the high mobility of this species, identifying 22 strongly supported long-range dispersal events including interoceanic and interhemispheric movement. Despite this propensity for geographic dispersal, the increased sampling of this study uncovered very few potential examples of ancestral dispersal among ecotypes. Concordance of nuclear and mitochondrial data further confirms genetic cohesiveness, with little or no current gene flow among sympatric ecotypes. Taken as a whole, our data suggest that the glacial cycles influenced local populations in different ways, with no clear global pattern, but with secondary contact among lineages following long-range dispersal as a potential mechanism driving ecological diversification. © 2015 John Wiley & Sons Ltd.

Acousto-Optic Applications for Multichannel Adaptive Optical Processor

DTIC Science & Technology

1992-06-01

AO cell and the two- channel line-scan camera system described in Subsection 4.1. The AO material for this IntraAction AOD-70 device was flint glass (n...Single-Channel 1.68 (flint glass ) 60,.0 AO Cell Multichannel 2.26 (TeO 2) 20.0 AO Cell Beam splitter 1.515 ( glass ) 50.8 Multichannel correlation was...Tone Intermodulation Dynamic Ranges of Longitudinal TeO2 Bragg Cells for Several Acoustic Power Densities 4-92 f f2 f 3 1 t SOURCE: Reference 21 TR-92

Plant toxicity, adaptive herbivory, and plant community dynamics

Treesearch

Zhilan Feng; Rongsong Liu; Donald L. DeAngelis; John P. Bryant; Knut Kielland; F. Stuart Chapin; Robert K. Swihart

2009-01-01

We model effects of interspecific plant competition, herbivory, and a plant's toxic defenses against herbivores on vegetation dynamics. The model predicts that, when a generalist herbivore feeds in the absence of plant toxins, adaptive foraging generally increases the probability of coexistence of plant species populations, because the herbivore switches more of...

Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation

NASA Astrophysics Data System (ADS)

Shankar, Praveen

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network based adaptive controller. While the fixed RBF network based controller which is tuned to compensate for control surface failures fails to achieve the same performance under modeling uncertainty and disturbances, the SORBFN is able to achieve good tracking convergence under all error conditions.

Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

NASA Astrophysics Data System (ADS)

Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2016-07-01

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

Study of the long-time dynamics of a viscous vortex sheet with a fully adaptive nonstiff method

NASA Astrophysics Data System (ADS)

Ceniceros, Hector D.; Roma, Alexandre M.

2004-12-01

A numerical investigation of the long-time dynamics of two immiscible two-dimensional fluids shearing past one another is presented. The fluids are incompressible and the interface between the bulk phases is subjected to surface tension. The simple case of density and viscosity matched fluids is considered. The two-dimensional Navier-Stokes equations are solved numerically with a fully adaptive nonstiff strategy based on the immersed boundary method. Dynamically adaptive mesh refinements are used to cover at all times the separately tracked fluid interface at the finest grid level. In addition, by combining adaptive front tracking, in the form of continuous interface marker equidistribution, with a predictor-corrector discretization an efficient method is introduced to successfully treat the well-known numerical difficulties associated with surface tension. The resulting numerical method can be used to compute stably and with high resolution the flow for wide-ranging Weber numbers but this study focuses on the computationally challenging cases for which elongated fingering and interface roll-up are observed. To assess the importance of the viscous and vortical effects in the interfacial dynamics the full viscous flow simulations are compared with inviscid counterparts computed with a state-of-the-art boundary integral method. In the examined cases of roll-up, it is found that in contrast to the inviscid flow in which the interface undergoes a topological reconfiguration, the viscous interface remarkably escapes self-intersection and rich long-time dynamics due to separation, transport, and diffusion of vorticity is observed. An even more striking motion occurs at an intermediate Weber number for which elongated interpenetrating fingers of fluid develop. In this case, it is found that the Kelvin-Helmholtz instability weakens due to shedding of vorticity and unlike the inviscid counterpart in which there is indefinite finger growth the viscous interface is pulled back by surface tension. As the interface recedes, thin necks connecting pockets of fluid with the rest of the fingers form. Narrow jets are observed at the necking regions but the vorticity there ultimately appears to be insufficient to drain all the fluid and cause reconnection. However, at another point, two disparate portions of the interface come in close proximity as the interface continues to contract. Large curvature points and an intense concentration of vorticity are observed in this region and then the motion is abruptly terminated by the collapse of the interface.

A new portable generator to dynamically produce SI-traceable reference gas mixtures for VOCs and water vapour at atmospheric concentration

NASA Astrophysics Data System (ADS)

Guillevic, Myriam; Pascale, Céline; Ackermann, Andreas; Leuenberger, Daiana; Niederhauser, Bernhard

2016-04-01

In the framework of the KEY-VOCs and AtmoChem-ECV projects, we are currently developing new facilities to dynamically generate reference gas mixtures for a variety of reactive compounds, at concentrations measured in the atmosphere and in a SI-traceable way (i.e. the amount of substance fraction in mole per mole is traceable to SI-units). Here we present the realisation of such standards for water vapour in the range 1-10 μmol/mol and for volatile organic compounds (VOCs) such as limonene, alpha-pinene, MVK, MEK, in the nmol/mol range. The matrix gas can be nitrogen or synthetic air. Further development in gas purification techniques could make possible to use purified atmospheric air as carrier gas. The method is based on permeation and dynamic dilution: one permeator containing a pure substance (either water, limonene, MVK, MEK or α-pinene) is kept into a permeation chamber with a constant gas flow. The mass loss is precisely calibrated using a magnetic suspension balance. The carrier gas is purified beforehand from the compounds of interest to the required level, using commercially available purification cartridges. This primary mixture is then diluted to reach the required amount of substance fraction. All flows are piloted by mass flow controllers which makes the production process flexible and easily adaptable to generate the required concentration. All parts in contact with the gas mixture are passivated using coated surfaces, to reduce adsorption/desorption processes as much as possible. Two setups are currently developed: one already built and fixed in our laboratory in Bern as well as a portable generator that is still under construction and that could be used anywhere in the field. The permeation chamber of the portable generator has multiple individual cells allowing the generation of mixtures up to 5 different components if needed. Moreover the presented technique can be adapted and applied to a large variety of molecules (e.g., NO2, BTEX, CFCs, HCFCs, HFCs and other refrigerants) and is particularly suitable for gas species and/or concentration ranges that are not stable in cylinders.

Local adaptation at the range peripheries of Sitka spruce.

PubMed

Mimura, M; Aitken, S N

2010-02-01

High-dispersal rates in heterogeneous environments and historical rapid range expansion can hamper local adaptation; however, we often see clinal variation in high-dispersal tree species. To understand the mechanisms of the species' distribution, we investigated local adaptation and adaptive plasticity in a range-wide context in Sitka spruce, a wind-pollinated tree species that has recently expanded its range after glaciations. Phenotypic traits were observed using growth chamber experiments that mimicked temperature and photoperiodic regimes from the limits of the species realized niche. Bud phenology exhibited parallel reaction norms among populations; however, putatively adaptive plasticity and strong divergent selection were seen in bud burst and bud set timing respectively. Natural selection appears to have favoured genotypes that maximize growth rate during available frost-free periods in each environment. We conclude that Sitka spruce has developed local adaptation and adaptive plasticity throughout its range in response to current climatic conditions despite generally high pollen flow and recent range expansion.

Development of fault tolerant adaptive control laws for aerospace systems

NASA Astrophysics Data System (ADS)

Perez Rocha, Andres E.

The main topic of this dissertation is the design, development and implementation of intelligent adaptive control techniques designed to maintain healthy performance of aerospace systems subjected to malfunctions, external parameter changes and/or unmodeled dynamics. The dissertation is focused on the development of novel adaptive control configurations that rely on non-linear functions that appear in the immune system of living organisms as main source of adaptation. One of the main goals of this dissertation is to demonstrate that these novel adaptive control architectures are able to improve overall performance and protect the system while reducing control effort and maintaining adequate operation outside bounds of nominal design. This research effort explores several phases, ranging from theoretical stability analysis, simulation and hardware implementation on different types of aerospace systems including spacecraft, aircraft and quadrotor vehicles. The results presented in this dissertation are focused on two main adaptivity approaches, the first one is intended for aerospace systems that do not attain large angles and use exact feedback linearization of Euler angle kinematics. A proof of stability is presented by means of the circle Criterion and Lyapunov's direct method. The second approach is intended for aerospace systems that can attain large attitude angles (e.g. space systems in gravity-less environments), the adaptation is incorporated on a baseline architecture that uses partial feedback linearization of quaternions kinematics. In this case, the closed loop stability was analyzed using Lyapunov's direct method and Barbalat's Lemma. It is expected that some results presented in this dissertation can contribute towards the validation and certification of direct adaptive controllers.

Phase Adaptation and Correction by Adaptive Optics

NASA Astrophysics Data System (ADS)

Tiziani, Hans J.

2010-04-01

Adaptive optical elements and systems for imaging or laser beam propagation are used for some time in particular in astronomy, where the image quality is degraded by atmospheric turbulence. In astronomical telescopes a deformable mirror is frequently used to compensate wavefront-errors due to deformations of the large mirror, vibrations as well as turbulence and hence to increase the image quality. In the last few years interesting elements like Spatial Light Modulators, SLM's, such as photorefractive crystals, liquid crystals and micro mirrors and membrane mirrors were introduced. The development of liquid crystals and micro mirrors was driven by data projectors as consumer products. They contain typically a matrix of individually addressable pixels of liquid crystals and flip mirrors respectively or more recently piston mirrors for special applications. Pixel sizes are in the order of a few microns and therefore also appropriate as active diffractive elements in digital holography or miniature masks. Although liquid crystals are mainly optimized for intensity modulation; they can be used for phase modulation. Adaptive optics is a technology for beam shaping and wavefront adaptation. The application of spatial light modulators for wavefront adaptation and correction and defect analysis as well as sensing will be discussed. Dynamic digital holograms are generated with liquid crystal devices (LCD) and used for wavefront correction as well as for beam shaping and phase manipulation, for instance. Furthermore, adaptive optics is very useful to extend the measuring range of wavefront sensors and for the wavefront adaptation in order to measure and compare the shape of high precision aspherical surfaces.

GMTIFS: the adaptive optics beam steering mirror for the GMT integral-field spectrograph

NASA Astrophysics Data System (ADS)

Davies, J.; Bloxham, G.; Boz, R.; Bundy, D.; Espeland, B.; Fordham, B.; Hart, J.; Herrald, N.; Nielsen, J.; Sharp, R.; Vaccarella, A.; Vest, C.; Young, P. J.

2016-07-01

To achieve the high adaptive optics sky coverage necessary to allow the GMT Integral-Field Spectrograph (GMTIFS) to access key scientific targets, the on-instrument adaptive-optics wavefront-sensing (OIWFS) system must patrol the full 180 arcsecond diameter guide field passed to the instrument. The OIWFS uses a diffraction limited guide star as the fundamental pointing reference for the instrument. During an observation the offset between the science target and the guide star will change due to sources such as flexure, differential refraction and non-sidereal tracking rates. GMTIFS uses a beam steering mirror to set the initial offset between science target and guide star and also to correct for changes in offset. In order to reduce image motion from beam steering errors to those comparable to the AO system in the most stringent case, the beam steering mirror is set a requirement of less than 1 milliarcsecond RMS. This corresponds to a dynamic range for both actuators and sensors of better than 1/180,000. The GMTIFS beam steering mirror uses piezo-walk actuators and a combination of eddy current sensors and interferometric sensors to achieve this dynamic range and control. While the sensors are rated for cryogenic operation, the actuators are not. We report on the results of prototype testing of single actuators, with the sensors, on the bench and in a cryogenic environment. Specific failures of the system are explained and suspected reasons for them. A modified test jig is used to investigate the option of heating the actuator and we report the improved results. In addition to individual component testing, we built and tested a complete beam steering mirror assembly. Testing was conducted with a point source microscope, however controlling environmental conditions to less than 1 micron was challenging. The assembly testing investigated acquisition accuracy and if there was any un-sensed hysteresis in the system. Finally we present the revised beam steering mirror design based on the outcomes and lessons learnt from this prototyping.

Adaptation in Coding by Large Populations of Neurons in the Retina

NASA Astrophysics Data System (ADS)

Ioffe, Mark L.

A comprehensive theory of neural computation requires an understanding of the statistical properties of the neural population code. The focus of this work is the experimental study and theoretical analysis of the statistical properties of neural activity in the tiger salamander retina. This is an accessible yet complex system, for which we control the visual input and record from a substantial portion--greater than a half--of the ganglion cell population generating the spiking output. Our experiments probe adaptation of the retina to visual statistics: a central feature of sensory systems which have to adjust their limited dynamic range to a far larger space of possible inputs. In Chapter 1 we place our work in context with a brief overview of the relevant background. In Chapter 2 we describe the experimental methodology of recording from 100+ ganglion cells in the tiger salamander retina. In Chapter 3 we first present the measurements of adaptation of individual cells to changes in stimulation statistics and then investigate whether pairwise correlations in fluctuations of ganglion cell activity change across different stimulation conditions. We then transition to a study of the population-level probability distribution of the retinal response captured with maximum-entropy models. Convergence of the model inference is presented in Chapter 4. In Chapter 5 we first test the empirical presence of a phase transition in such models fitting the retinal response to different experimental conditions, and then proceed to develop other characterizations which are sensitive to complexity in the interaction matrix. This includes an analysis of the dynamics of sampling at finite temperature, which demonstrates a range of subtle attractor-like properties in the energy landscape. These are largely conserved when ambient illumination is varied 1000-fold, a result not necessarily apparent from the measured low-order statistics of the distribution. Our results form a consistent picture which is discussed at the end of Chapter 5. We conclude with a few future directions related to this thesis.

A range of newly developed mobile generators to dynamically produce SI-traceable reference gas mixtures for reactive compounds at atmospheric concentrations

NASA Astrophysics Data System (ADS)

Leuenberger, Daiana; Pascale, Céline; Guillevic, Myriam; Ackermann, Andreas; Niederhauser, Bernhard

2017-04-01

Three new mobile facilities have been developed at METAS to dynamically generate SI-traceable reference gas mixtures for a variety of reactive compounds at atmospheric amount of substance fractions and at very low levels of uncertainty (Ux < 3%). We present three new portable "Reactive Gas Standard ReGaS" reference gas generators for the realisation of the following substances: ReGaS1: Ammonia and nitrogen dioxide in the nmol/mol (ppb) range ReGaS2: Volatile organic compounds (VOCs), e.g. limonene, alpha-pinene, MVK, MEK in the nmol/mol (ppb) range ReGaS-3: Fluorinated gases (F-gases, i.e. containing fluorine atoms) in the pmol/mol (ppt) range These three mobile generators have been designed and manufactured at METAS in the framework of the three EMRP projects MetNH3, KEY-VOCs and HIGHGAS. The method is based on permeation and subsequent dynamic dilution: A permeation tube containing the pure substance (e.g. NH3) is stored in the permeation chamber at constant temperature, pressure and matrix gas flow (N2, purified air, synthetic air). Under such conditions the pure substance permeates at constant rate into the matrix gas and can be diluted thereafter to the desired amount fractions in one or two subsequent steps. The permeation rate (mass loss over time) of the permeation tube is precisely calibrated in a fully traceable magnetic suspension balance. The carrier gas is previously purified from the compounds of interest using commercially available purification cartridges. The permeation chambers of ReGaS2 and ReGaS3 have multiple individual cells allowing for the generation of mixtures containing up to 5 different components if required. ReGaS1 allows for the generation of one-component mixtures only. These primary mixtures are then diluted to the required amount of substance fractions using thermal mass flow controllers for full flexibility and adaptability of the generation process over the entire range of possible concentrations. In order to considerably reduce adsorption/desorption processes and thus stabilisation time, all electro-polished stainless steel parts of ReGaS1 and ReGaS2 in contact with the reference gas mixtures are passivated with SilcoNert2000® surface coating. These three state-of-the-art mobile reference gas generators are applicable under both, laboratory and field conditions. Moreover the dynamic generation method can be adapted and applied to a large variety of molecules (e.g. BTEX, CFCs, HCFCs, HFCs and other refrigerants) and is particularly suitable for reactive gas species and/or at concentration ranges which are unstable when stored in pressurised cylinders. Acknowledgement: This work was supported by the European Metrology Research Programme (EMRP). The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union

A Fluid Structure Interaction Strategy with Application to Low Reynolds Number Flapping Flight

DTIC Science & Technology

2010-01-01

using a predictor - corrector strategy. Dynamic fluid grid adaptation is implemented to reduce the number of grid points and computation costs...governing the dynamics of the ow and the structure are simultaneously advanced in time by using a predictor - corrector strategy. Dynamic uid grid...colleague Patrick Rabenold, the math-guy, who provided the seminal work on adaptive mesh refine- ment for incompressible flow using the Paramesh c

A New Approach to Parallel Dynamic Partitioning for Adaptive Unstructured Meshes

NASA Technical Reports Server (NTRS)

Heber, Gerd; Biswas, Rupak; Gao, Guang R.

1999-01-01

Classical mesh partitioning algorithms were designed for rather static situations, and their straightforward application in a dynamical framework may lead to unsatisfactory results, e.g., excessive data migration among processors. Furthermore, special attention should be paid to their amenability to parallelization. In this paper, a novel parallel method for the dynamic partitioning of adaptive unstructured meshes is described. It is based on a linear representation of the mesh using self-avoiding walks.

Adaptive Calibration of Dynamic Accommodation—Implications for Accommodating Intraocular Lenses

PubMed Central

Schor, Clifton M.; Bharadwaj, Shrikant R.

2009-01-01

PURPOSE When the aging lens is replaced with prosthetic accommodating intraocular lenses (IOLs), with effective viscoelasticities different from those of the natural lens, mismatches could arise between the neural control of accommodation and the biomechanical properties of the new lens. These mismatches could lead to either unstable oscillations or sluggishness of dynamic accommodation. Using computer simulations, we investigated whether optimal accommodative responses could be restored through recalibration of the neural control of accommodation. Using human experiments, we also investigated whether the accommodative system has the capacity for adaptive recalibration in response to changes in lens biomechanics. METHODS Dynamic performance of two accommodating IOL prototypes was simulated for a 45-year-old accommodative system, before and after neural recalibration, using a dynamic model of accommodation. Accommodating IOL I, a prototype for an injectable accommodating IOL, was less stiff and less viscous than the natural 45-year-old lens. Accommodating IOL II, a prototype for a translating accommodating IOL, was less stiff and more viscous than the natural 45-year-old lens. Short-term adaptive recalibration of dynamic accommodation was stimulated using a double-step adaptation paradigm that optically induced changes in neuromuscular effort mimicking responses to changes in lens biomechanics. RESULTS Model simulations indicate that the unstable oscillations or sluggishness of dynamic accommodation resulting from mismatches between neural control and lens biomechanics might be restored through neural recalibration. CONCLUSIONS Empirical measures reveal that the accommodative system is capable of adaptive recalibration in response to optical loads that simulate effects of changing lens biomechanics. PMID:19044245

Translational studies of goal-directed action as a framework for classifying deficits across psychiatric disorders

PubMed Central

Griffiths, Kristi R.; Morris, Richard W.; Balleine, Bernard W.

2014-01-01

The ability to learn contingencies between actions and outcomes in a dynamic environment is critical for flexible, adaptive behavior. Goal-directed actions adapt to changes in action-outcome contingencies as well as to changes in the reward-value of the outcome. When networks involved in reward processing and contingency learning are maladaptive, this fundamental ability can be lost, with detrimental consequences for decision-making. Impaired decision-making is a core feature in a number of psychiatric disorders, ranging from depression to schizophrenia. The argument can be developed, therefore, that seemingly disparate symptoms across psychiatric disorders can be explained by dysfunction within common decision-making circuitry. From this perspective, gaining a better understanding of the neural processes involved in goal-directed action, will allow a comparison of deficits observed across traditional diagnostic boundaries within a unified theoretical framework. This review describes the key processes and neural circuits involved in goal-directed decision-making using evidence from animal studies and human neuroimaging. Select studies are discussed to outline what we currently know about causal judgments regarding actions and their consequences, action-related reward evaluation, and, most importantly, how these processes are integrated in goal-directed learning and performance. Finally, we look at how adaptive decision-making is impaired across a range of psychiatric disorders and how deepening our understanding of this circuitry may offer insights into phenotypes and more targeted interventions. PMID:24904322

The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics.

PubMed

McKenna, Erin; Bray, Laurence C Jayet; Zhou, Weiwei; Joiner, Wilsaan M

2017-10-01

Delays in transmitting and processing sensory information require correctly associating delayed feedback to issued motor commands for accurate error compensation. The flexibility of this alignment between motor signals and feedback has been demonstrated for movement recalibration to visual manipulations, but the alignment dependence for adapting movement dynamics is largely unknown. Here we examined the effect of visual feedback manipulations on force-field adaptation. Three subject groups used a manipulandum while experiencing a lag in the corresponding cursor motion (0, 75, or 150 ms). When the offset was applied at the start of the session (continuous condition), adaptation was not significantly different between groups. However, these similarities may be due to acclimation to the offset before motor adaptation. We tested additional subjects who experienced the same delays concurrent with the introduction of the perturbation (abrupt condition). In this case adaptation was statistically indistinguishable from the continuous condition, indicating that acclimation to feedback delay was not a factor. In addition, end-point errors were not significantly different across the delay or onset conditions, but end-point correction (e.g., deceleration duration) was influenced by the temporal offset. As an additional control, we tested a group of subjects who performed without visual feedback and found comparable movement adaptation results. These results suggest that visual feedback manipulation (absence or temporal misalignment) does not affect adaptation to novel dynamics, independent of both acclimation and perceptual awareness. These findings could have implications for modeling how the motor system adjusts to errors despite concurrent delays in sensory feedback information. NEW & NOTEWORTHY A temporal offset between movement and distorted visual feedback (e.g., visuomotor rotation) influences the subsequent motor recalibration, but the effects of this offset for altered movement dynamics are largely unknown. Here we examined the influence of 1 ) delayed and 2 ) removed visual feedback on the adaptation to novel movement dynamics. These results contribute to understanding of the control strategies that compensate for movement errors when there is a temporal separation between motion state and sensory information. Copyright © 2017 the American Physiological Society.

Complexity and network dynamics in physiological adaptation: an integrated view.

PubMed

Baffy, György; Loscalzo, Joseph

2014-05-28

Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. Published by Elsevier Inc.

Direct adaptive control of manipulators in Cartesian space

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

How much can history constrain adaptive evolution? A real-time evolutionary approach of inversion polymorphisms in Drosophila subobscura.

PubMed

Fragata, I; Lopes-Cunha, M; Bárbaro, M; Kellen, B; Lima, M; Santos, M A; Faria, G S; Santos, M; Matos, M; Simões, P

2014-12-01

Chromosomal inversions are present in a wide range of animals and plants, having an important role in adaptation and speciation. Although empirical evidence of their adaptive value is abundant, the role of different processes underlying evolution of chromosomal polymorphisms is not fully understood. History and selection are likely to shape inversion polymorphism variation to an extent yet largely unknown. Here, we perform a real-time evolution study addressing the role of historical constraints and selection in the evolution of these polymorphisms. We founded laboratory populations of Drosophila subobscura derived from three locations along the European cline and followed the evolutionary dynamics of inversion polymorphisms throughout the first 40 generations. At the beginning, populations were highly differentiated and remained so throughout generations. We report evidence of positive selection for some inversions, variable between foundations. Signs of negative selection were more frequent, in particular for most cold-climate standard inversions across the three foundations. We found that previously observed convergence at the phenotypic level in these populations was not associated with convergence in inversion frequencies. In conclusion, our study shows that selection has shaped the evolutionary dynamics of inversion frequencies, but doing so within the constraints imposed by previous history. Both history and selection are therefore fundamental to predict the evolutionary potential of different populations to respond to global environmental changes. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Coevolution of dynamical states and interactions in dynamic networks

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi

2004-06-01

We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.

Fixed gain and adaptive techniques for rotorcraft vibration control

NASA Technical Reports Server (NTRS)

Roy, R. H.; Saberi, H. A.; Walker, R. A.

1985-01-01

The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

Structural self-assembly and avalanchelike dynamics in locally adaptive networks

NASA Astrophysics Data System (ADS)

Gräwer, Johannes; Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni

2015-07-01

Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. In addition, we find that the long term equilibration dynamics exhibit behavior reminiscent of glassy systems characterized by long periods of slow changes punctuated by bursts of reorganization events.

Recent Developments in Smart Adaptive Structures for Solar Sailcraft

NASA Technical Reports Server (NTRS)

Whorton, M. S.; Kim, Y. K.; Oakley, J.; Adetona, O.; Keel, L. H.

2007-01-01

The "Smart Adaptive Structures for Solar Sailcraft" development activity at MSFC has investigated issues associated with understanding how to model and scale the subsystem and multi-body system dynamics of a gossamer solar sailcraft with the objective of designing sailcraft attitude control systems. This research and development activity addressed three key tasks that leveraged existing facilities and core competencies of MSFC to investigate dynamics and control issues of solar sails. Key aspects of this effort included modeling and testing of a 30 m deployable boom; modeling of the multi-body system dynamics of a gossamer sailcraft; investigation of control-structures interaction for gossamer sailcraft; and development and experimental demonstration of adaptive control technologies to mitigate control-structures interaction.

Sliding Mode Control of Dynamic Voltage Restorer by Using a New Adaptive Reaching Law

NASA Astrophysics Data System (ADS)

Pandey, Achala; Agrawal, Rekha; Mandloi, Ravindra S.; Sarkar, Biswaroop

2017-12-01

This paper presents a new kind of adaptive reaching law for sliding mode control of Dynamic Voltage Restorer (DVR). Such an adaptive reaching law follows under-damped sinusoidal nature that causes the initial state to reach the sliding regime in extremely less time with negligible chattering. Moreover, it is robust in the sense the trajectory does not deviate from the sliding surface. This new approach is developed and successfully applied to DVR. The simulation results are presented that show its robustness.

An Evaluation of Controller and Pilot Performance, Workload and Acceptability under a NextGen Concept for Dynamic Weather Adapted Arrival Routing

NASA Technical Reports Server (NTRS)

Johnson, Walter W.; Lachter, Joel; Brandt, Summer; Koteskey, Robert; Dao, Arik-Quang; Kraut, Josh; Ligda, Sarah; Battiste, Vernol

2012-01-01

In todays terminal operations, controller workload increases and throughput decreases when fixed standard terminal arrival routes (STARs) are impacted by storms. To circumvent this operational constraint, Prete, Krozel, Mitchell, Kim and Zou (2008) proposed to use automation to dynamically adapt arrival and departure routing based on weather predictions. The present study examined this proposal in the context of a NextGen trajectory-based operation concept, focusing on the acceptability and its effect on the controllers ability to manage traffic flows. Six controllers and twelve transport pilots participated in a human-in-the-loop simulation of arrival operations into Louisville International Airport with interval management requirements. Three types of routing structures were used: Static STARs (similar to current routing, which require the trajectories of individual aircraft to be modified to avoid the weather), Dynamic routing (automated adaptive routing around weather), and Dynamic Adjusted routing (automated adaptive routing around weather with aircraft entry time adjusted to account for differences in route length). Spacing Responsibility, whether responsibility for interval management resided with the controllers (as today), or resided with the pilot (who used a flight deck based automated spacing algorithm), was also manipulated. Dynamic routing as a whole was rated superior to static routing, especially by pilots, both in terms of workload reduction and flight path safety. A downside of using dynamic routing was that the paths flown in the dynamic conditions tended to be somewhat longer than the paths flown in the static condition.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

PLUM: Parallel Load Balancing for Unstructured Adaptive Meshes. Degree awarded by Colorado Univ.

NASA Technical Reports Server (NTRS)

Oliker, Leonid

1998-01-01

Dynamic mesh adaption on unstructured grids is a powerful tool for computing large-scale problems that require grid modifications to efficiently resolve solution features. By locally refining and coarsening the mesh to capture physical phenomena of interest, such procedures make standard computational methods more cost effective. Unfortunately, an efficient parallel implementation of these adaptive methods is rather difficult to achieve, primarily due to the load imbalance created by the dynamically-changing nonuniform grid. This requires significant communication at runtime, leading to idle processors and adversely affecting the total execution time. Nonetheless, it is generally thought that unstructured adaptive- grid techniques will constitute a significant fraction of future high-performance supercomputing. Various dynamic load balancing methods have been reported to date; however, most of them either lack a global view of loads across processors or do not apply their techniques to realistic large-scale applications.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights.

PubMed

Luo, Shaohua; Wu, Songli; Gao, Ruizhen

2015-07-01

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Evolutionary branching under multi-dimensional evolutionary constraints.

PubMed

Ito, Hiroshi; Sasaki, Akira

2016-10-21

The fitness of an existing phenotype and of a potential mutant should generally depend on the frequencies of other existing phenotypes. Adaptive evolution driven by such frequency-dependent fitness functions can be analyzed effectively using adaptive dynamics theory, assuming rare mutation and asexual reproduction. When possible mutations are restricted to certain directions due to developmental, physiological, or physical constraints, the resulting adaptive evolution may be restricted to subspaces (constraint surfaces) with fewer dimensionalities than the original trait spaces. To analyze such dynamics along constraint surfaces efficiently, we develop a Lagrange multiplier method in the framework of adaptive dynamics theory. On constraint surfaces of arbitrary dimensionalities described with equality constraints, our method efficiently finds local evolutionarily stable strategies, convergence stable points, and evolutionary branching points. We also derive the conditions for the existence of evolutionary branching points on constraint surfaces when the shapes of the surfaces can be chosen freely. Copyright © 2016 Elsevier Ltd. All rights reserved.

Static and Dynamic Behaviour Assessment of the Trajan Arch by Means of New Monitoring Technologies

NASA Astrophysics Data System (ADS)

Petti, L.; Barone, F.; Mammone, A.; Giordano, G.

2017-08-01

An effective assessment of the static and dynamic structural behavior of historical monuments requires the development and validation of suitable adaptive structural models using high-quality experimental data acquired with an effectively continuous and distributed monitoring. Furthermore, the adaptive strategy allows an efficient evaluation of the health status and of the evolution along the time of a historical monument, providing relevant information to plan appropriate actions for its long-term preservation. The Trajan Arch in Benevento chosen as a case of study to develop and apply this new adaptive strategy in cultural heritage conservation. The paper, after a description of the innovative monitoring system, based on state-of-the-art mechanical sensors, presents and discusses the results of two tests, comparing the measurements with the predictions of an adaptive structural FEM model developed for the dynamical simulation of the Trajan Arch.

An emergency-adaptive routing scheme for wireless sensor networks for building fire hazard monitoring.

PubMed

Zeng, Yuanyuan; Sreenan, Cormac J; Sitanayah, Lanny; Xiong, Naixue; Park, Jong Hyuk; Zheng, Guilin

2011-01-01

Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work.

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

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

Luo, Shaohua; Department of Mechanical Engineering, Chongqing Aerospace Polytechnic, Chongqing, 400021; Wu, Songli

2015-07-15

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in themore » closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.« less

An Emergency-Adaptive Routing Scheme for Wireless Sensor Networks for Building Fire Hazard Monitoring

PubMed Central

Zeng, Yuanyuan; Sreenan, Cormac J.; Sitanayah, Lanny; Xiong, Naixue; Park, Jong Hyuk; Zheng, Guilin

2011-01-01

Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work. PMID:22163774

Complexity, Chaos, and Nonlinear Dynamics: A New Perspective on Career Development Theory

ERIC Educational Resources Information Center

Bloch, Deborah P.

2005-01-01

The author presents a theory of career development drawing on nonlinear dynamics and chaos and complexity theories. Career is presented as a complex adaptive entity, a fractal of the human entity. Characteristics of complex adaptive entities, including (a) autopiesis, or self-regeneration; (b) open exchange; (c) participation in networks; (d)…

Flatness-based embedded adaptive fuzzy control of turbocharged diesel engines

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan

2014-10-01

In this paper nonlinear embedded control for turbocharged Diesel engines is developed with the use of Differential flatness theory and adaptive fuzzy control. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances an adaptive fuzzy control scheme is implemanted making use of the transformed dynamical system of the diesel engine that is obtained through the application of differential flatness theory. Since only the system's output is measurable the complete state vector has to be reconstructed with the use of a state observer. It is shown that a suitable learning law can be defined for neuro-fuzzy approximators, which are part of the controller, so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed observer-based adaptive fuzzy control scheme results in H∞ tracking performance.

Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

PubMed

Bagheri, Pedram; Sun, Qiao

2016-07-01

In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

PubMed

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Wavefront aberrations of x-ray dynamical diffraction beams.

PubMed

Liao, Keliang; Hong, Youli; Sheng, Weifan

2014-10-01

The effects of dynamical diffraction in x-ray diffractive optics with large numerical aperture render the wavefront aberrations difficult to describe using the aberration polynomials, yet knowledge of them plays an important role in a vast variety of scientific problems ranging from optical testing to adaptive optics. Although the diffraction theory of optical aberrations was established decades ago, its application in the area of x-ray dynamical diffraction theory (DDT) is still lacking. Here, we conduct a theoretical study on the aberration properties of x-ray dynamical diffraction beams. By treating the modulus of the complex envelope as the amplitude weight function in the orthogonalization procedure, we generalize the nonrecursive matrix method for the determination of orthonormal aberration polynomials, wherein Zernike DDT and Legendre DDT polynomials are proposed. As an example, we investigate the aberration evolution inside a tilted multilayer Laue lens. The corresponding Legendre DDT polynomials are obtained numerically, which represent balanced aberrations yielding minimum variance of the classical aberrations of an anamorphic optical system. The balancing of classical aberrations and their standard deviations are discussed. We also present the Strehl ratio of the primary and secondary balanced aberrations.

Markets on Networks

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

2003-03-01

The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE)

PubMed Central

Sharif, Behzad; Derbyshire, J. Andrew; Faranesh, Anthony Z.; Bresler, Yoram

2010-01-01

MR imaging of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional non-gated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly-accelerated non-gated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically-driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient-adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject’s heart-rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high resolution non-gated cardiac MRI during a short breath-hold. PMID:20665794

A reduced adaptive observer for multivariable systems. [using reduced dynamic ordering

NASA Technical Reports Server (NTRS)

Carroll, R. L.; Lindorff, D. P.

1973-01-01

An adaptive observer for multivariable systems is presented for which the dynamic order of the observer is reduced, subject to mild restrictions. The observer structure depends directly upon the multivariable structure of the system rather than a transformation to a single-output system. The number of adaptive gains is at most the sum of the order of the system and the number of input parameters being adapted. Moreover, for the relatively frequent specific cases for which the number of required adaptive gains is less than the sum of system order and input parameters, the number of these gains is easily determined by inspection of the system structure. This adaptive observer possesses all the properties ascribed to the single-input single-output adpative observer. Like the other adaptive observers some restriction is required of the allowable system command input to guarantee convergence of the adaptive algorithm, but the restriction is more lenient than that required by the full-order multivariable observer. This reduced observer is not restricted to cycle systems.

Analysis of Thermo-Diffusive Cellular Instabilities in Continuum Combustion Fronts

NASA Astrophysics Data System (ADS)

Azizi, Hossein; Gurevich, Sebastian; Provatas, Nikolas; Department of Physics, Centre Physics of Materials Team

We explore numerically the morphological patterns of thermo-diffusive instabilities in combustion fronts with a continuum solid fuel source, within a range of Lewis numbers, focusing on the cellular regime. Cellular and dendritic instabilities are found at low Lewis numbers. These are studied using a dynamic adaptive mesh refinement technique that allows very large computational domains, thus allowing us to reduce finite size effects that can affect or even preclude the emergence of these patterns. The distinct types of dynamics found in the vicinity of the critical Lewis number. These types of dynamics are classified as ``quasi-linear'' and characterized by low amplitude cells that may be strongly affected by the mode selection mechanism and growth prescribed by the linear theory. Below this range of Lewis number, highly non-linear effects become prominent and large amplitude, complex cellular and seaweed dendritic morphologies emerge. The cellular patterns simulated in this work are similar to those observed in experiments of flame propagation over a bed of nano-aluminum powder burning with a counter-flowing oxidizer conducted by Malchi et al. It is noteworthy that the physical dimension of our computational domain is roughly close to their experimental setup. This work was supported by a Canadian Space Agency Class Grant ''Percolating Reactive Waves in Particulate Suspensions''. We thank Compute Canada for computing resources.

Host and parasite thermal ecology jointly determine the effect of climate warming on epidemic dynamics.

PubMed

Gehman, Alyssa-Lois M; Hall, Richard J; Byers, James E

2018-01-23

Host-parasite systems have intricately coupled life cycles, but each interactor can respond differently to changes in environmental variables like temperature. Although vital to predicting how parasitism will respond to climate change, thermal responses of both host and parasite in key traits affecting infection dynamics have rarely been quantified. Through temperature-controlled experiments on an ectothermic host-parasite system, we demonstrate an offset in the thermal optima for survival of infected and uninfected hosts and parasite production. We combine experimentally derived thermal performance curves with field data on seasonal host abundance and parasite prevalence to parameterize an epidemiological model and forecast the dynamical responses to plausible future climate-warming scenarios. In warming scenarios within the coastal southeastern United States, the model predicts sharp declines in parasite prevalence, with local parasite extinction occurring with as little as 2 °C warming. The northern portion of the parasite's current range could experience local increases in transmission, but assuming no thermal adaptation of the parasite, we find no evidence that the parasite will expand its range northward under warming. This work exemplifies that some host populations may experience reduced parasitism in a warming world and highlights the need to measure host and parasite thermal performance to predict infection responses to climate change.

Criticality of Adaptive Control Dynamics

NASA Astrophysics Data System (ADS)

Patzelt, Felix; Pawelzik, Klaus

2011-12-01

We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.

Iterative-Transform Phase Retrieval Using Adaptive Diversity

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak; Gabow, Harold N.

1999-01-01

The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.

Dynamical information encoding in neural adaptation.

PubMed

Luozheng Li; Wenhao Zhang; Yuanyuan Mi; Dahui Wang; Xiaohan Lin; Si Wu

2016-08-01

Adaptation refers to the general phenomenon that a neural system dynamically adjusts its response property according to the statistics of external inputs. In response to a prolonged constant stimulation, neuronal firing rates always first increase dramatically at the onset of the stimulation; and afterwards, they decrease rapidly to a low level close to background activity. This attenuation of neural activity seems to be contradictory to our experience that we can still sense the stimulus after the neural system is adapted. Thus, it prompts a question: where is the stimulus information encoded during the adaptation? Here, we investigate a computational model in which the neural system employs a dynamical encoding strategy during the neural adaptation: at the early stage of the adaptation, the stimulus information is mainly encoded in the strong independent firings; and as time goes on, the information is shifted into the weak but concerted responses of neurons. We find that short-term plasticity, a general feature of synapses, provides a natural mechanism to achieve this goal. Furthermore, we demonstrate that with balanced excitatory and inhibitory inputs, this correlation-based information can be read out efficiently. The implications of this study on our understanding of neural information encoding are discussed.

Performance assessment of dynamic spiral scan modes with variable pitch for quantitative perfusion computed tomography.

PubMed

Haberland, Ulrike; Klotz, Ernst; Abolmaali, Nasreddin

2010-07-01

Perfusion computed tomography is increasingly being used in diagnostic radiology. Axial coverage of the traditional approach is limited to the width of the detector. Using continuous periodic table movement coverage can be increased beyond this limit. In this study, we compared tissue flow values determined from scans with a periodic spiral implementation with variable pitch with ones determined from standard dynamic scan modes. A flow phantom (preserved porcine kidney) was scanned with 2 settings of a periodic spiral (Adaptive 4D Spiral) with a range of 100 and 148 mm and a temporal sampling of 1.5 seconds. Additionally, the whole phantom was scanned with the standard dynamic mode (detector width 38.4 mm, temporal sampling 1.0 seconds) at various overlapping positions as a reference. Scan parameters (80 kV, 140 mAs, 40s scan time) were selected similar to a typical brain perfusion study. All scans were repeated 5 times. Tissue flow was calculated with a dedicated deconvolution algorithm. In a center slice and 3 additional slices at various off center positions flow values were recorded in a total of 126 regions of interest (ROI). Reproducibility was determined from the variation of the repeat scans. Agreement between periodic spirals and standard mode was determined by Bland Altman plots and correlation analysis. The reproducibility of the tissue flow determination ranged from 2.7 to 4.4 mL/100 mL/min and was similar for all scan modes. The coefficient of variation ranged from 3.9% to 6.1%. Mean tissue flow in the 126 ROIs ranged from 35 to 121 mL/100 mL/min. There was excellent correlation between both periodic spiral ranges and the standard dynamic mode with a Pearson correlation coefficient of r = 0.97. The regression slope (intercept 0) for the 100 mm range was 1.01, for the 148 mm range it was 0.97. The absolute differences per ROI varied between 1.5 and 4.1 mL/100 mL/min, the relative differences between 1.9% and 6.5%. Differences did not depend on the slice location. Periodic spiral scan modes with variable pitch and a sampling rate of 1.5 seconds can be used for the quantitative determination of tissue flow. Their performance is equivalent to equidistant sampling with standard dynamic scan modes. The ranges of 100 and 148 mm investigated allow coverage of the whole brain or an entire organ for perfusion imaging.

A High Performance Piezoelectric Sensor for Dynamic Force Monitoring of Landslide.

PubMed

Li, Ming; Cheng, Wei; Chen, Jiangpan; Xie, Ruili; Li, Xiongfei

2017-02-17

Due to the increasing influence of human engineering activities, it is important to monitor the transient disturbance during the evolution process of landslide. For this purpose, a high-performance piezoelectric sensor is presented in this paper. To adapt the high static and dynamic stress environment in slope engineering, two key techniques, namely, the self-structure pressure distribution method (SSPDM) and the capacitive circuit voltage distribution method (CCVDM) are employed in the design of the sensor. The SSPDM can greatly improve the compressive capacity and the CCVDM can quantitatively decrease the high direct response voltage. Then, the calibration experiments are conducted via the independently invented static and transient mechanism since the conventional testing machines cannot match the calibration requirements. The sensitivity coefficient is obtained and the results reveal that the sensor has the characteristics of high compressive capacity, stable sensitivities under different static preload levels and wide-range dynamic measuring linearity. Finally, to reduce the measuring error caused by charge leakage of the piezoelectric element, a low-frequency correction method is proposed and experimental verified. Therefore, with the satisfactory static and dynamic properties and the improving low-frequency measuring reliability, the sensor can complement dynamic monitoring capability of the existing landslide monitoring and forecasting system.

Investigating the social behavioral dynamics and differentiation of skill in a martial arts technique.

PubMed

Caron, Robert R; Coey, Charles A; Dhaim, Ashley N; Schmidt, R C

2017-08-01

Coordinating interpersonal motor activity is crucial in martial arts, where managing spatiotemporal parameters is emphasized to produce effective techniques. Modeling arm movements in an Aikido technique as coupled oscillators, we investigated whether more-skilled participants would adapt to the perturbation of weighted arms in different and predictable ways compared to less-skilled participants. Thirty-four participants ranging from complete novice to veterans of more than twenty years were asked to perform an Aikido exercise with a repeated attack and response, resulting in a period of steady-state coordination, followed by a take down. We used mean relative phase and its variability to measure the steady-state dynamics of both the inter- and intrapersonal coordination. Our findings suggest that interpersonal coordination of less-skilled participants is disrupted in highly predictable ways based on oscillatory dynamics; however, more-skilled participants overcome these natural dynamics to maintain critical performance variables. Interestingly, the more-skilled participants exhibited more variability in their intrapersonal dynamics while meeting these interpersonal demands. This work lends insight to the development of skill in competitive social motor activities. Copyright © 2017 Elsevier B.V. All rights reserved.

Analytically Sensitive Protein Detection in Microtiter Plates by Proximity Ligation with Rolling Circle Amplification.

PubMed

Ebai, Tonge; Souza de Oliveira, Felipe Marques; Löf, Liza; Wik, Lotta; Schweiger, Caroline; Larsson, Anders; Keilholtz, Ulrich; Haybaeck, Johannes; Landegren, Ulf; Kamali-Moghaddam, Masood

2017-09-01

Detecting proteins at low concentrations in plasma is crucial for early diagnosis. Current techniques in clinical routine, such as sandwich ELISA, provide sensitive protein detection because of a dependence on target recognition by pairs of antibodies, but detection of still lower protein concentrations is often called for. Proximity ligation assay with rolling circle amplification (PLARCA) is a modified proximity ligation assay (PLA) for analytically specific and sensitive protein detection via binding of target proteins by 3 antibodies, and signal amplification via rolling circle amplification (RCA) in microtiter wells, easily adapted to instrumentation in use in hospitals. Proteins captured by immobilized antibodies were detected using a pair of oligonucleotide-conjugated antibodies. Upon target recognition these PLA probes guided oligonucleotide ligation, followed by amplification via RCA of circular DNA strands that formed in the reaction. The RCA products were detected by horseradish peroxidase-labeled oligonucleotides to generate colorimetric reaction products with readout in an absorbance microplate reader. We compared detection of interleukin (IL)-4, IL-6, IL-8, p53, and growth differentiation factor 15 (GDF-15) by PLARCA and conventional sandwich ELISA or immuno-RCA. PLARCA detected lower concentrations of proteins and exhibited a broader dynamic range compared to ELISA and iRCA using the same antibodies. IL-4 and IL-6 were detected in clinical samples at femtomolar concentrations, considerably lower than for ELISA. PLARCA offers detection of lower protein levels and increased dynamic ranges compared to ELISA. The PLARCA procedure may be adapted to routine instrumentation available in hospitals and research laboratories. © 2017 American Association for Clinical Chemistry.

Neural network adaptive control of wing-rock motion of aircraft model mounted on three-degree-of-freedom dynamic rig in wind tunnel

NASA Astrophysics Data System (ADS)

Ignatyev, D. I.

2018-06-01

High-angles-of-attack dynamics of aircraft are complicated with dangerous phenomena such as wing rock, stall, and spin. Autonomous dynamically scaled aircraft model mounted in three-degree-of-freedom (3DoF) dynamic rig is proposed for studying aircraft dynamics and prototyping of control laws in wind tunnel. Dynamics of the scaled aircraft model in 3DoF manoeuvre rig in wind tunnel is considered. The model limit-cycle oscillations are obtained at high angles of attack. A neural network (NN) adaptive control suppressing wing rock motion is designed. The wing rock suppression with the proposed control law is validated using nonlinear time-domain simulations.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation.

PubMed

Augustin, Moritz; Ladenbauer, Josef; Baumann, Fabian; Obermayer, Klaus

2017-06-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

PubMed Central

Baumann, Fabian; Obermayer, Klaus

2017-01-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models. PMID:28644841

Paradoxical enhancement of chemoreceptor detection sensitivity by a sensory adaptation enzyme

PubMed Central

Han, Xue-Sheng; Dahlquist, Frederick W.; Parkinson, John S.

2017-01-01

A sensory adaptation system that tunes chemoreceptor sensitivity enables motile Escherichia coli cells to track chemical gradients with high sensitivity over a wide dynamic range. Sensory adaptation involves feedback control of covalent receptor modifications by two enzymes: CheR, a methyltransferase, and CheB, a methylesterase. This study describes a CheR function that opposes the signaling consequences of its catalytic activity. In the presence of CheR, a variety of mutant serine chemoreceptors displayed up to 40-fold enhanced detection sensitivity to chemoeffector stimuli. This response enhancement effect did not require the known catalytic activity of CheR, but did involve a binding interaction between CheR and receptor molecules. Response enhancement was maximal at low CheR:receptor stoichiometry and quantitative analyses argued against a reversible binding interaction that simply shifts the ON–OFF equilibrium of receptor signaling complexes. Rather, a short-lived CheR binding interaction appears to promote a long-lasting change in receptor molecules, either a covalent modification or conformation that enhances their response to attractant ligands. PMID:28827352

Adaptations of indigenous bacteria to fuel contamination in karst aquifers in south-central Kentucky

USGS Publications Warehouse

Byl, Thomas D.; Metge, David W.; Agymang, Daniel T.; Bradley, Michael W.; Hileman, Gregg; Harvey, Ronald W.

2014-01-01

The karst aquifer systems in southern Kentucky can be dynamic and quick to change. Microorganisms that live in these unpredictable aquifers are constantly faced with environmental changes. Their survival depends upon adaptations to changes in water chemistry, taking advantage of positive stimuli and avoiding negative environmental conditions. The U.S. Geological Survey conducted a study in 2001 to determine the capability of bacteria to adapt in two distinct regions of water quality in a karst aquifer, an area of clean, oxygenated groundwater and an area where the groundwater was oxygen depleted and contaminated by jet fuel. Water samples containing bacteria were collected from one clean well and two jet fuel contaminated wells in a conduit-dominated karst aquifer. Bacterial concentrations, enumerated through direct count, ranged from 500,000 to 2.7 million bacteria per mL in the clean portion of the aquifer, and 200,000 to 3.2 million bacteria per mL in the contaminated portion of the aquifer over a twelve month period. Bacteria from the clean well ranged in size from 0.2 to 2.5 mm, whereas bacteria from one fuel-contaminated well were generally larger, ranging in size from 0.2 to 3.9 mm. Also, bacteria collected from the clean well had a higher density and, consequently, were more inclined to sink than bacteria collected from contaminated wells. Bacteria collected from the clean portion of the karst aquifer were predominantly (,95%) Gram-negative and more likely to have flagella present than bacteria collected from the contaminated wells, which included a substantial fraction (,30%) of Gram-positive varieties. The ability of the bacteria from the clean portion of the karst aquifer to biodegrade benzene and toluene was studied under aerobic and anaerobic conditions in laboratory microcosms. The rate of fuel biodegradation in laboratory studies was approximately 50 times faster under aerobic conditions as compared to anaerobic, sulfur-reducing conditions. The optimum pH for fuel biodegradation ranged from 6 to 7. These findings suggest that bacteria have adapted to water-saturated karst systems with a variety of active and passive transport mechanisms.

High Dynamic Range Pixel Array Detector for Scanning Transmission Electron Microscopy.

PubMed

Tate, Mark W; Purohit, Prafull; Chamberlain, Darol; Nguyen, Kayla X; Hovden, Robert; Chang, Celesta S; Deb, Pratiti; Turgut, Emrah; Heron, John T; Schlom, Darrell G; Ralph, Daniel C; Fuchs, Gregory D; Shanks, Katherine S; Philipp, Hugh T; Muller, David A; Gruner, Sol M

2016-02-01

We describe a hybrid pixel array detector (electron microscope pixel array detector, or EMPAD) adapted for use in electron microscope applications, especially as a universal detector for scanning transmission electron microscopy. The 128×128 pixel detector consists of a 500 µm thick silicon diode array bump-bonded pixel-by-pixel to an application-specific integrated circuit. The in-pixel circuitry provides a 1,000,000:1 dynamic range within a single frame, allowing the direct electron beam to be imaged while still maintaining single electron sensitivity. A 1.1 kHz framing rate enables rapid data collection and minimizes sample drift distortions while scanning. By capturing the entire unsaturated diffraction pattern in scanning mode, one can simultaneously capture bright field, dark field, and phase contrast information, as well as being able to analyze the full scattering distribution, allowing true center of mass imaging. The scattering is recorded on an absolute scale, so that information such as local sample thickness can be directly determined. This paper describes the detector architecture, data acquisition system, and preliminary results from experiments with 80-200 keV electron beams.

2.5 Gbit/s Optical Receiver Front-End Circuit with High Sensitivity and Wide Dynamic Range

NASA Astrophysics Data System (ADS)

Zhu, Tiezhu; Mo, Taishan; Ye, Tianchun

2017-12-01

An optical receiver front-end circuit is designed for passive optical network and fabricated in a 0.18 um CMOS technology. The whole circuit consists of a transimpedance amplifier (TIA), a single-ended to differential amplifier and an output driver. The TIA employs a cascode stage as the input stage and auxiliary amplifier to reduce the miller effect. Current injecting technique is employed to enlarge the input transistor's transconductance, optimize the noise performance and overcome the lack of voltage headroom. To achieve a wide dynamic range, an automatic gain control circuit with self-adaptive function is proposed. Experiment results show an optical sensitivity of -28 dBm for a bit error rate of 10-10 at 2.5 Gbit/s and a maxim input optical power of 2 dBm using an external photodiode. The chip occupies an area of 1×0.9 mm2 and consumes around 30 mW from single 1.8 V supply. The front-end circuit can be used in various optical receivers.

Objective quality assessment of tone-mapped images.

PubMed

Yeganeh, Hojatollah; Wang, Zhou

2013-02-01

Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. Different TMOs create different tone-mapped images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-mapped images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural images. Validations using independent subject-rated image databases show good correlations between subjective ranking score and the proposed tone-mapped image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples-parameter tuning for TMOs and adaptive fusion of multiple tone-mapped images.

Entrainment to a real time fractal visual stimulus modulates fractal gait dynamics.

PubMed

Rhea, Christopher K; Kiefer, Adam W; D'Andrea, Susan E; Warren, William H; Aaron, Roy K

2014-08-01

Fractal patterns characterize healthy biological systems and are considered to reflect the ability of the system to adapt to varying environmental conditions. Previous research has shown that fractal patterns in gait are altered following natural aging or disease, and this has potential negative consequences for gait adaptability that can lead to increased risk of injury. However, the flexibility of a healthy neurological system to exhibit different fractal patterns in gait has yet to be explored, and this is a necessary step toward understanding human locomotor control. Fifteen participants walked for 15min on a treadmill, either in the absence of a visual stimulus or while they attempted to couple the timing of their gait with a visual metronome that exhibited a persistent fractal pattern (contained long-range correlations) or a random pattern (contained no long-range correlations). The stride-to-stride intervals of the participants were recorded via analog foot pressure switches and submitted to detrended fluctuation analysis (DFA) to determine if the fractal patterns during the visual metronome conditions differed from the baseline (no metronome) condition. DFA α in the baseline condition was 0.77±0.09. The fractal patterns in the stride-to-stride intervals were significantly altered when walking to the fractal metronome (DFA α=0.87±0.06) and to the random metronome (DFA α=0.61±0.10) (both p<.05 when compared to the baseline condition), indicating that a global change in gait dynamics was observed. A variety of strategies were identified at the local level with a cross-correlation analysis, indicating that local behavior did not account for the consistent global changes. Collectively, the results show that a gait dynamics can be shifted in a prescribed manner using a visual stimulus and the shift appears to be a global phenomenon. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling Of Spontaneous Multiscale Roughening And Branching of Ruptures Propagating On A Slip-Weakening Frictional Fault

NASA Astrophysics Data System (ADS)

Elbanna, A. E.

2013-12-01

Numerous field and experimental observations suggest that faults surfaces are rough at multiple scales and tend to produce a wide range of branch sizes ranging from micro-branching to large scale secondary faults. The development and evolution of fault roughness and branching is believed to play an important role in rupture dynamics and energy partitioning. Previous work by several groups has succeeded in determining conditions under which a main rupture may branch into a secondary fault. Recently, there great progress has been made in investigating rupture propagation on rough faults with and without off-fault plasticity. Nonetheless, in most of these models the heterogeneity, whether the roughness profile or the secondary faults orientation, was built into the system from the beginning and consequently the final outcome depends strongly on the initial conditions. Here we introduce an adaptive mesh technique for modeling mode-II crack propagation on slip weakening frictional interfaces. We use a Finite Element Framework with random mesh topology that adapts to crack dynamics through element splitting and sequential insertion of frictional interfaces dictated by the failure criterion. This allows the crack path to explore non-planar paths and develop the roughness profile that is most compatible with the dynamical constraints. It also enables crack branching at different scales. We quantify energy dissipation due to the roughening process and small scale branching. We compare the results of our model to a reference case for propagation on a planar fault. We show that the small scale processes of roughening and branching influence many characteristics of the rupture propagation including the energy partitioning, rupture speed and peak slip rates. We also estimate the fracture energy required for propagating a crack on a planar fault that will be required to produce comparable results. We anticipate that this modeling approach provides an attractive methodology that complements the current efforts in modeling off-fault plasticity and damage.

Cell fate determination dynamics in bacteria

NASA Astrophysics Data System (ADS)

Kuchina, Anna; Espinar, Lorena; Cagatay, Tolga; Garcia-Ojalvo, Jordi; Suel, Gurol

2010-03-01

The fitness of an organism depends on many processes that serve the purpose to adapt to changing environment in a robust and coordinated fashion. One example of such process is cellular fate determination. In the presence of a variety of alternative responses each cell adopting a particular fate represents a ``choice'' that must be tightly regulated to ensure the best survival strategy for the population taking into account the broad range of possible environmental challenges. We investigated this problem in the model organism B.Subtilis which under stress conditions differentiates terminally into highly resistant spores or initiates an alternative transient state of competence. The dynamics underlying cell fate choice remains largely unknown. We utilize quantitative fluorescent microscopy to track the activities of genes involved in these responses on a single-cell level. We explored the importance of temporal interactions between competing cell fates by re- engineering the differentiation programs. I will discuss how the precise dynamics of cellular ``decision-making'' governed by the corresponding biological circuits may enable cells to adjust to diverse environments and determine survival.

Band excitation method applicable to scanning probe microscopy

DOEpatents

Jesse, Stephen [Knoxville, TN; Kalinin, Sergei V [Knoxville, TN

2010-08-17

Methods and apparatus are described for scanning probe microscopy. A method includes generating a band excitation (BE) signal having finite and predefined amplitude and phase spectrum in at least a first predefined frequency band; exciting a probe using the band excitation signal; obtaining data by measuring a response of the probe in at least a second predefined frequency band; and extracting at least one relevant dynamic parameter of the response of the probe in a predefined range including analyzing the obtained data. The BE signal can be synthesized prior to imaging (static band excitation), or adjusted at each pixel or spectroscopy step to accommodate changes in sample properties (adaptive band excitation). An apparatus includes a band excitation signal generator; a probe coupled to the band excitation signal generator; a detector coupled to the probe; and a relevant dynamic parameter extractor component coupled to the detector, the relevant dynamic parameter extractor including a processor that performs a mathematical transform selected from the group consisting of an integral transform and a discrete transform.

Band excitation method applicable to scanning probe microscopy

DOEpatents

Jesse, Stephen; Kalinin, Sergei V

2013-05-28

Methods and apparatus are described for scanning probe microscopy. A method includes generating a band excitation (BE) signal having finite and predefined amplitude and phase spectrum in at least a first predefined frequency band; exciting a probe using the band excitation signal; obtaining data by measuring a response of the probe in at least a second predefined frequency band; and extracting at least one relevant dynamic parameter of the response of the probe in a predefined range including analyzing the obtained data. The BE signal can be synthesized prior to imaging (static band excitation), or adjusted at each pixel or spectroscopy step to accommodate changes in sample properties (adaptive band excitation). An apparatus includes a band excitation signal generator; a probe coupled to the band excitation signal generator; a detector coupled to the probe; and a relevant dynamic parameter extractor component coupled to the detector, the relevant dynamic parameter extractor including a processor that performs a mathematical transform selected from the group consisting of an integral transform and a discrete transform.

A New Powered Lower Limb Prosthesis Control Framework Based on Adaptive Dynamic Programming.

PubMed

Wen, Yue; Si, Jennie; Gao, Xiang; Huang, Stephanie; Huang, He Helen

2017-09-01

This brief presents a novel application of adaptive dynamic programming (ADP) for optimal adaptive control of powered lower limb prostheses, a type of wearable robots to assist the motor function of the limb amputees. Current control of these robotic devices typically relies on finite state impedance control (FS-IC), which lacks adaptability to the user's physical condition. As a result, joint impedance settings are often customized manually and heuristically in clinics, which greatly hinder the wide use of these advanced medical devices. This simulation study aimed at demonstrating the feasibility of ADP for automatic tuning of the twelve knee joint impedance parameters during a complete gait cycle to achieve balanced walking. Given that the accurate models of human walking dynamics are difficult to obtain, the model-free ADP control algorithms were considered. First, direct heuristic dynamic programming (dHDP) was applied to the control problem, and its performance was evaluated on OpenSim, an often-used dynamic walking simulator. For the comparison purposes, we selected another established ADP algorithm, the neural fitted Q with continuous action (NFQCA). In both cases, the ADP controllers learned to control the right knee joint and achieved balanced walking, but dHDP outperformed NFQCA in this application during a 200 gait cycle-based testing.

Salinity fluctuation influencing biological adaptation: growth dynamics and Na+ /K+ -ATPase activity in a euryhaline bacterium.

PubMed

Yang, Hao; Meng, Yang; Song, Youxin; Tan, Yalin; Warren, Alan; Li, Jiqiu; Lin, Xiaofeng

2017-07-01

Although salinity fluctuation is a prominent characteristic of many coastal ecosystems, its effects on biological adaptation have not yet been fully recognized. To test the salinity fluctuations on biological adaptation, population growth dynamics and Na + /K + -ATPase activity were investigated in the euryhaline bacterium Idiomarina sp. DYB, which was acclimated at different salinity exposure levels, exposure times, and shifts in direction of salinity. Results showed: (1) bacterial population growth dynamics and Na + /K + -ATPase activity changed significantly in response to salinity fluctuation; (2) patterns of variation in bacterial growth dynamics were related to exposure times, levels of salinity, and shifts in direction of salinity change; (3) significant tradeoffs were detected between growth rate (r) and carrying capacity (K) on the one hand, and Na + /K + -ATPase activity on the other; and (4) beneficial acclimation was confirmed in Idiomarina sp. DYB. In brief, this study demonstrated that salinity fluctuation can change the population growth dynamics, Na + /K + -ATPase activity, and tradeoffs between r, K, and Na + /K + -ATPase activity, thus facilitating bacterial adaption in a changing environment. These findings provide constructive information for determining biological response patterns to environmental change. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic imaging of adaptive stress response pathway activation for prediction of drug induced liver injury.

PubMed

Wink, Steven; Hiemstra, Steven W; Huppelschoten, Suzanne; Klip, Janna E; van de Water, Bob

2018-05-01

Drug-induced liver injury remains a concern during drug treatment and development. There is an urgent need for improved mechanistic understanding and prediction of DILI liabilities using in vitro approaches. We have established and characterized a panel of liver cell models containing mechanism-based fluorescent protein toxicity pathway reporters to quantitatively assess the dynamics of cellular stress response pathway activation at the single cell level using automated live cell imaging. We have systematically evaluated the application of four key adaptive stress pathway reporters for the prediction of DILI liability: SRXN1-GFP (oxidative stress), CHOP-GFP (ER stress/UPR response), p21 (p53-mediated DNA damage-related response) and ICAM1 (NF-κB-mediated inflammatory signaling). 118 FDA-labeled drugs in five human exposure relevant concentrations were evaluated for reporter activation using live cell confocal imaging. Quantitative data analysis revealed activation of single or multiple reporters by most drugs in a concentration and time dependent manner. Hierarchical clustering of time course dynamics and refined single cell analysis allowed the allusion of key events in DILI liability. Concentration response modeling was performed to calculate benchmark concentrations (BMCs). Extracted temporal dynamic parameters and BMCs were used to assess the predictive power of sub-lethal adaptive stress pathway activation. Although cellular adaptive responses were activated by non-DILI and severe-DILI compounds alike, dynamic behavior and lower BMCs of pathway activation were sufficiently distinct between these compound classes. The high-level detailed temporal- and concentration-dependent evaluation of the dynamics of adaptive stress pathway activation adds to the overall understanding and prediction of drug-induced liver liabilities.

Force adaptation transfers to untrained workspace regions in children: evidence for developing inverse dynamic motor models.

PubMed

Jansen-Osmann, Petra; Richter, Stefanie; Konczak, Jürgen; Kalveram, Karl-Theodor

2002-03-01

When humans perform goal-directed arm movements under the influence of an external damping force, they learn to adapt to these external dynamics. After removal of the external force field, they reveal kinematic aftereffects that are indicative of a neural controller that still compensates the no longer existing force. Such behavior suggests that the adult human nervous system uses a neural representation of inverse arm dynamics to control upper-extremity motion. Central to the notion of an inverse dynamic model (IDM) is that learning generalizes. Consequently, aftereffects should be observable even in untrained workspace regions. Adults have shown such behavior, but the ontogenetic development of this process remains unclear. This study examines the adaptive behavior of children and investigates whether learning a force field in one hemifield of the right arm workspace has an effect on force adaptation in the other hemifield. Thirty children (aged 6-10 years) and ten adults performed 30 degrees elbow flexion movements under two conditions of external damping (negative and null). We found that learning to compensate an external damping force transferred to the opposite hemifield, which indicates that a model of the limb dynamics rather than an association of visited space and experienced force was acquired. Aftereffects were more pronounced in the younger children and readaptation to a null-force condition was prolonged. This finding is consistent with the view that IDMs in children are imprecise neural representations of the actual arm dynamics. It indicates that the acquisition of IDMs is a developmental achievement and that the human motor system is inherently flexible enough to adapt to any novel force within the limits of the organism's biomechanics.

Cooperative Adaptive Responses in Gene Regulatory Networks with Many Degrees of Freedom

PubMed Central

Inoue, Masayo; Kaneko, Kunihiko

2013-01-01

Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components. PMID:23592959