Adaptation and Mitigation in Agriculture: A Review of Synergies and Tradeoffs and How EO Could Improve Understanding and Outcomes

NASA Astrophysics Data System (ADS)

Barbieri, L.; Wollenberg, E.

2017-12-01

We present a review of the published literature on agricultural adaptation and mitigation, and report on the current evidence as to whether changes in agricultural practices meant to achieve mitigation or adaptation goals can be dual purpose: simultaneously reducing greenhouse gas (GHG) emissions and helping to facilitate adaptation. We characterize the spatio-temporal and system trends in how adaptation and mitigation outcomes are being achieved, and report on the current technical and knowledge gaps that exist and where Earth observations (EO) could improve our understanding. Agriculture contributes 12% GHG emissions globally, roughly one third from the developing world. Nearly 70% of the technical mitigation potential in agriculture sector occurs in these countries, however, while the mitigation potential is high, agricultural productivity also relies heavily on climate factors. With climate change, agricultural systems already, and will increasingly, need to adapt to extreme events and variability in temperatures and precipitation. This underscores the importance of implementing agricultural practices that can both reduce GHG emissions and help facilitate adaptation. Until recently, these objectives have been treated separately, but policy makers are increasingly calling for a joint approach to improve synergies, and avoid tradeoffs. There remain many complications in considering a joint approach: lack of clear conceptual frameworks, knowledge gaps in scientific understanding and evidence associated with adaptation and mitigation outcomes, and the abilities and motivations of stakeholders to consider both objectives. We review 56 peer-reviewed publications and present results from an in-depth analysis to answer two major concerns: to what extent is evidence provided for claims of synergistic outcomes, and what uncertainty surrounds this evidence. Our results show that only 21% of studies empirically measured both mitigation and adaptation outcomes, and claims of synergies are not well substantiated, and evidence is provided at questionable spatio-temporal scales. We highlight information that could be provided by coordinated, comprehensive and sustained EO which could benefit this critical goal of simultaneously achieving agricultural adaptation and mitigation.

“Lucky Averaging”: Quality improvement on Adaptive Optics Scanning Laser Ophthalmoscope Images

PubMed Central

Huang, Gang; Zhong, Zhangyi; Zou, Weiyao; Burns, Stephen A.

2012-01-01

Adaptive optics(AO) has greatly improved retinal image resolution. However, even with AO, temporal and spatial variations in image quality still occur due to wavefront fluctuations, intra-frame focus shifts and other factors. As a result, aligning and averaging images can produce a mean image that has lower resolution or contrast than the best images within a sequence. To address this, we propose an image post-processing scheme called “lucky averaging”, analogous to lucky imaging (Fried, 1978) based on computing the best local contrast over time. Results from eye data demonstrate improvements in image quality. PMID:21964097

Adaptive OFDM Waveform Design for Spatio-Temporal-Sparsity Exploited STAP Radar

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

Sen, Satyabrata

In this chapter, we describe a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of-freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully adaptive OFDM-STAP, we develop a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain,more » as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we optimally design the transmit OFDM signals by maximizing the output signal-to-interference-plus-noise ratio (SINR) in order to improve the STAP performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity-based technique and adaptive waveform design.« less

Dynamics of resilience of wheat to drought in Australia from 1991-2010.

PubMed

Huai, Jianjun

2017-08-25

Although enhancing resilience is a well-recognized adaptation to climate change, little research has been undertaken on the dynamics of resilience. This occurs because complex relationships exist between adaptive capacity and resilience, and some issues also create challenges related to the construction, operation, and application of resilience. This study identified the dynamics of temporal, spatial changes of resilience found in a sample of wheat-drought resilience in Australia's wheat-sheep production zone during 1991-2010. I estimated resilience using principal component analysis, mapped resilience and its components, distinguished resilient and sensitive regions, and provided recommendations related to improving resilience. I frame that resilience is composed of social resilience including on- and off-site adaptive capacity as well as biophysical resilience including resistance and absorption. I found that resilience and its components have different temporal trends, spatial shifts and growth ratios in each region during different years, which results from complicated interactions, such as complementation and substitution among its components. In wheat-sheep zones, I recommend that identifying regional bottlenecks, science-policy engagement, and managing resilience components are the priorities for improving resilience.

Enhanced Axial Resolution of Wide-Field Two-Photon Excitation Microscopy by Line Scanning Using a Digital Micromirror Device.

PubMed

Park, Jong Kang; Rowlands, Christopher J; So, Peter T C

2017-01-01

Temporal focusing multiphoton microscopy is a technique for performing highly parallelized multiphoton microscopy while still maintaining depth discrimination. While the conventional wide-field configuration for temporal focusing suffers from sub-optimal axial resolution, line scanning temporal focusing, implemented here using a digital micromirror device (DMD), can provide substantial improvement. The DMD-based line scanning temporal focusing technique dynamically trades off the degree of parallelization, and hence imaging speed, for axial resolution, allowing performance parameters to be adapted to the experimental requirements. We demonstrate this new instrument in calibration specimens and in biological specimens, including a mouse kidney slice.

Enhanced Axial Resolution of Wide-Field Two-Photon Excitation Microscopy by Line Scanning Using a Digital Micromirror Device

PubMed Central

Park, Jong Kang; Rowlands, Christopher J.; So, Peter T. C.

2017-01-01

Temporal focusing multiphoton microscopy is a technique for performing highly parallelized multiphoton microscopy while still maintaining depth discrimination. While the conventional wide-field configuration for temporal focusing suffers from sub-optimal axial resolution, line scanning temporal focusing, implemented here using a digital micromirror device (DMD), can provide substantial improvement. The DMD-based line scanning temporal focusing technique dynamically trades off the degree of parallelization, and hence imaging speed, for axial resolution, allowing performance parameters to be adapted to the experimental requirements. We demonstrate this new instrument in calibration specimens and in biological specimens, including a mouse kidney slice. PMID:29387484

Wavefront sensorless adaptive optics temporal focusing-based multiphoton microscopy

PubMed Central

Chang, Chia-Yuan; Cheng, Li-Chung; Su, Hung-Wei; Hu, Yvonne Yuling; Cho, Keng-Chi; Yen, Wei-Chung; Xu, Chris; Dong, Chen Yuan; Chen, Shean-Jen

2014-01-01

Temporal profile distortions reduce excitation efficiency and image quality in temporal focusing-based multiphoton microscopy. In order to compensate the distortions, a wavefront sensorless adaptive optics system (AOS) was integrated into the microscope. The feedback control signal of the AOS was acquired from local image intensity maximization via a hill-climbing algorithm. The control signal was then utilized to drive a deformable mirror in such a way as to eliminate the distortions. With the AOS correction, not only is the axial excitation symmetrically refocused, but the axial resolution with full two-photon excited fluorescence (TPEF) intensity is also maintained. Hence, the contrast of the TPEF image of a R6G-doped PMMA thin film is enhanced along with a 3.7-fold increase in intensity. Furthermore, the TPEF image quality of 1μm fluorescent beads sealed in agarose gel at different depths is improved. PMID:24940539

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

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

Sen, Satyabrata

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratiomore » (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.« less

Coding tools investigation for next generation video coding based on HEVC

NASA Astrophysics Data System (ADS)

Chen, Jianle; Chen, Ying; Karczewicz, Marta; Li, Xiang; Liu, Hongbin; Zhang, Li; Zhao, Xin

2015-09-01

The new state-of-the-art video coding standard, H.265/HEVC, has been finalized in 2013 and it achieves roughly 50% bit rate saving compared to its predecessor, H.264/MPEG-4 AVC. This paper provides the evidence that there is still potential for further coding efficiency improvements. A brief overview of HEVC is firstly given in the paper. Then, our improvements on each main module of HEVC are presented. For instance, the recursive quadtree block structure is extended to support larger coding unit and transform unit. The motion information prediction scheme is improved by advanced temporal motion vector prediction, which inherits the motion information of each small block within a large block from a temporal reference picture. Cross component prediction with linear prediction model improves intra prediction and overlapped block motion compensation improves the efficiency of inter prediction. Furthermore, coding of both intra and inter prediction residual is improved by adaptive multiple transform technique. Finally, in addition to deblocking filter and SAO, adaptive loop filter is applied to further enhance the reconstructed picture quality. This paper describes above-mentioned techniques in detail and evaluates their coding performance benefits based on the common test condition during HEVC development. The simulation results show that significant performance improvement over HEVC standard can be achieved, especially for the high resolution video materials.

Spatio-Temporal Equalizer for a Receiving-Antenna Feed Array

NASA Technical Reports Server (NTRS)

Mukai, Ryan; Lee, Dennis; Vilnrotter, Victor

2010-01-01

A spatio-temporal equalizer has been conceived as an improved means of suppressing multipath effects in the reception of aeronautical telemetry signals, and may be adaptable to radar and aeronautical communication applications as well. This equalizer would be an integral part of a system that would also include a seven-element planar array of receiving feed horns centered at the focal point of a paraboloidal antenna that would be nominally aimed at or near the aircraft that would be the source of the signal that one seeks to receive (see Figure 1). This spatio-temporal equalizer would consist mostly of a bank of seven adaptive finite-impulse-response (FIR) filters one for each element in the array - and the outputs of the filters would be summed (see Figure 2). The combination of the spatial diversity of the feedhorn array and the temporal diversity of the filter bank would afford better multipath-suppression performance than is achievable by means of temporal equalization alone. The seven-element feed array would supplant the single feed horn used in a conventional paraboloidal ground telemetry-receiving antenna. The radio-frequency telemetry signals re ceiv ed by the seven elements of the array would be digitized, converted to complex baseband form, and sent to the FIR filter bank, which would adapt itself in real time to enable reception of telemetry at a low bit error rate, even in the presence of multipath of the type found at many flight test ranges.

Temporal subtraction contrast-enhanced dedicated breast CT

NASA Astrophysics Data System (ADS)

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-09-01

The development of a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, intensity difference adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using normalized cross correlation (NCC), symmetric uncertainty coefficient, normalized mutual information (NMI), mean square error (MSE) and target registration error (TRE). The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE (0-16%), NCC (0-6%), NMI (0-13%) and TRE (0-34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake.

Multireference adaptive noise canceling applied to the EEG.

PubMed

James, C J; Hagan, M T; Jones, R D; Bones, P J; Carroll, G J

1997-08-01

The technique of multireference adaptive noise canceling (MRANC) is applied to enhance transient nonstationarities in the electroeancephalogram (EEG), with the adaptation implemented by means of a multilayer-perception artificial neural network (ANN). The method was applied to recorded EEG segments and the performance on documented nonstationarities recorded. The results show that the neural network (nonlinear) gives an improvement in performance (i.e., signal-to-noise ratio (SNR) of the nonstationarities) compared to a linear implementation of MRANC. In both cases an improvement in the SNR was obtained. The advantage of the spatial filtering aspect of MRANC is highlighted when the performance of MRANC is compared to that of the inverse auto-regressive filtering of the EEG, a purely temporal filter.

Neural Summation in the Hawkmoth Visual System Extends the Limits of Vision in Dim Light.

PubMed

Stöckl, Anna Lisa; O'Carroll, David Charles; Warrant, Eric James

2016-03-21

Most of the world's animals are active in dim light and depend on good vision for the tasks of daily life. Many have evolved visual adaptations that permit a performance superior to that of manmade imaging devices [1]. In insects, a major model visual system, nocturnal species show impressive visual abilities ranging from flight control [2, 3], to color discrimination [4, 5], to navigation using visual landmarks [6-8] or dim celestial compass cues [9, 10]. In addition to optical adaptations that improve their sensitivity in dim light [11], neural summation of light in space and time-which enhances the coarser and slower features of the scene at the expense of noisier finer and faster features-has been suggested to improve sensitivity in theoretical [12-14], anatomical [15-17], and behavioral [18-20] studies. How these summation strategies function neurally is, however, presently unknown. Here, we quantified spatial and temporal summation in the motion vision pathway of a nocturnal hawkmoth. We show that spatial and temporal summation combine supralinearly to substantially increase contrast sensitivity and visual information rate over four decades of light intensity, enabling hawkmoths to see at light levels 100 times dimmer than without summation. Our results reveal how visual motion is calculated neurally in dim light and how spatial and temporal summation improve sensitivity while simultaneously maximizing spatial and temporal resolution, thus extending models of insect motion vision derived predominantly from diurnal flies. Moreover, the summation strategies we have revealed may benefit manmade vision systems optimized for variable light levels [21]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Illusory Reversal of Causality between Touch and Vision has No Effect on Prism Adaptation Rate.

PubMed

Tanaka, Hirokazu; Homma, Kazuhiro; Imamizu, Hiroshi

2012-01-01

Learning, according to Oxford Dictionary, is "to gain knowledge or skill by studying, from experience, from being taught, etc." In order to learn from experience, the central nervous system has to decide what action leads to what consequence, and temporal perception plays a critical role in determining the causality between actions and consequences. In motor adaptation, causality between action and consequence is implicitly assumed so that a subject adapts to a new environment based on the consequence caused by her action. Adaptation to visual displacement induced by prisms is a prime example; the visual error signal associated with the motor output contributes to the recovery of accurate reaching, and a delayed feedback of visual error can decrease the adaptation rate. Subjective feeling of temporal order of action and consequence, however, can be modified or even reversed when her sense of simultaneity is manipulated with an artificially delayed feedback. Our previous study (Tanaka et al., 2011; Exp. Brain Res.) demonstrated that the rate of prism adaptation was unaffected when the subjective delay of visual feedback was shortened. This study asked whether subjects could adapt to prism adaptation and whether the rate of prism adaptation was affected when the subjective temporal order was illusory reversed. Adapting to additional 100 ms delay and its sudden removal caused a positive shift of point of simultaneity in a temporal order judgment experiment, indicating an illusory reversal of action and consequence. We found that, even in this case, the subjects were able to adapt to prism displacement with the learning rate that was statistically indistinguishable to that without temporal adaptation. This result provides further evidence to the dissociation between conscious temporal perception and motor adaptation.

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.

Adaptive prediction of environmental changes by microorganisms.

PubMed

Mitchell, Amir; Romano, Gal H; Groisman, Bella; Yona, Avihu; Dekel, Erez; Kupiec, Martin; Dahan, Orna; Pilpel, Yitzhak

2009-07-09

Natural habitats of some microorganisms may fluctuate erratically, whereas others, which are more predictable, offer the opportunity to prepare in advance for the next environmental change. In analogy to classical Pavlovian conditioning, microorganisms may have evolved to anticipate environmental stimuli by adapting to their temporal order of appearance. Here we present evidence for environmental change anticipation in two model microorganisms, Escherichia coli and Saccharomyces cerevisiae. We show that anticipation is an adaptive trait, because pre-exposure to the stimulus that typically appears early in the ecology improves the organism's fitness when encountered with a second stimulus. Additionally, we observe loss of the conditioned response in E. coli strains that were repeatedly exposed in a laboratory evolution experiment only to the first stimulus. Focusing on the molecular level reveals that the natural temporal order of stimuli is embedded in the wiring of the regulatory network-early stimuli pre-induce genes that would be needed for later ones, yet later stimuli only induce genes needed to cope with them. Our work indicates that environmental anticipation is an adaptive trait that was repeatedly selected for during evolution and thus may be ubiquitous in biology.

Adaptive multiresolution modeling of groundwater flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Malenica, Luka; Gotovac, Hrvoje; Srzic, Veljko; Andric, Ivo

2016-04-01

Proposed methodology was originally developed by our scientific team in Split who designed multiresolution approach for analyzing flow and transport processes in highly heterogeneous porous media. The main properties of the adaptive Fup multi-resolution approach are: 1) computational capabilities of Fup basis functions with compact support capable to resolve all spatial and temporal scales, 2) multi-resolution presentation of heterogeneity as well as all other input and output variables, 3) accurate, adaptive and efficient strategy and 4) semi-analytical properties which increase our understanding of usually complex flow and transport processes in porous media. The main computational idea behind this approach is to separately find the minimum number of basis functions and resolution levels necessary to describe each flow and transport variable with the desired accuracy on a particular adaptive grid. Therefore, each variable is separately analyzed, and the adaptive and multi-scale nature of the methodology enables not only computational efficiency and accuracy, but it also describes subsurface processes closely related to their understood physical interpretation. The methodology inherently supports a mesh-free procedure, avoiding the classical numerical integration, and yields continuous velocity and flux fields, which is vitally important for flow and transport simulations. In this paper, we will show recent improvements within the proposed methodology. Since "state of the art" multiresolution approach usually uses method of lines and only spatial adaptive procedure, temporal approximation was rarely considered as a multiscale. Therefore, novel adaptive implicit Fup integration scheme is developed, resolving all time scales within each global time step. It means that algorithm uses smaller time steps only in lines where solution changes are intensive. Application of Fup basis functions enables continuous time approximation, simple interpolation calculations across different temporal lines and local time stepping control. Critical aspect of time integration accuracy is construction of spatial stencil due to accurate calculation of spatial derivatives. Since common approach applied for wavelets and splines uses a finite difference operator, we developed here collocation one including solution values and differential operator. In this way, new improved algorithm is adaptive in space and time enabling accurate solution for groundwater flow problems, especially in highly heterogeneous porous media with large lnK variances and different correlation length scales. In addition, differences between collocation and finite volume approaches are discussed. Finally, results show application of methodology to the groundwater flow problems in highly heterogeneous confined and unconfined aquifers.

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Temporal partitioning of adaptive responses of the murine heart to fasting.

PubMed

Brewer, Rachel A; Collins, Helen E; Berry, Ryan D; Brahma, Manoja K; Tirado, Brian A; Peliciari-Garcia, Rodrigo A; Stanley, Haley L; Wende, Adam R; Taegtmeyer, Heinrich; Rajasekaran, Namakkal Soorappan; Darley-Usmar, Victor; Zhang, Jianhua; Frank, Stuart J; Chatham, John C; Young, Martin E

2018-03-15

Recent studies suggest that the time of day at which food is consumed dramatically influences clinically-relevant cardiometabolic parameters (e.g., adiposity, insulin sensitivity, and cardiac function). Meal feeding benefits may be the result of daily periods of feeding and/or fasting, highlighting the need for improved understanding of the temporal adaptation of cardiometabolic tissues (e.g., heart) to fasting. Such studies may provide mechanistic insight regarding how time-of-day-dependent feeding/fasting cycles influence cardiac function. We hypothesized that fasting during the sleep period elicits beneficial adaptation of the heart at transcriptional, translational, and metabolic levels. To test this hypothesis, temporal adaptation was investigated in wild-type mice fasted for 24-h, or for either the 12-h light/sleep phase or the 12-h dark/awake phase. Fasting maximally induced fatty acid responsive genes (e.g., Pdk4) during the dark/active phase; transcriptional changes were mirrored at translational (e.g., PDK4) and metabolic flux (e.g., glucose/oleate oxidation) levels. Similarly, maximal repression of myocardial p-mTOR and protein synthesis rates occurred during the dark phase; both parameters remained elevated in the heart of fasted mice during the light phase. In contrast, markers of autophagy (e.g., LC3II) exhibited peak responses to fasting during the light phase. Collectively, these data show that responsiveness of the heart to fasting is temporally partitioned. Autophagy peaks during the light/sleep phase, while repression of glucose utilization and protein synthesis is maximized during the dark/active phase. We speculate that sleep phase fasting may benefit cardiac function through augmentation of protein/cellular constituent turnover. Copyright © 2018 Elsevier Inc. All rights reserved.

Temporal subtraction contrast-enhanced dedicated breast CT

PubMed Central

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-01-01

Purpose To develop a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. Methods An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, Intensity Difference Adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using Normalized Cross Correlation (NCC), Symmetric Uncertainty Coefficient (SUC), Normalized Mutual Information (NMI), Mean Square Error (MSE) and Target Registration Error (TRE). Results The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE(0–16%), NCC (0–6%), NMI (0–13%) and TRE (0–34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Conclusion Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake. PMID:27494376

Adaptation of a Weighted Regression Approach to Evaluate Water Quality Trends in Tampa Bay, Florida

EPA Science Inventory

The increasing availability of long-term monitoring data can improve resolution of temporal and spatial changes in water quality. In many cases, the fact that changes have occurred is no longer a matter of debate. However, the relatively simple methods that have been used to ev...

Widefield compressive multiphoton microscopy.

PubMed

Alemohammad, Milad; Shin, Jaewook; Tran, Dung N; Stroud, Jasper R; Chin, Sang Peter; Tran, Trac D; Foster, Mark A

2018-06-15

A single-pixel compressively sensed architecture is exploited to simultaneously achieve a 10× reduction in acquired data compared with the Nyquist rate, while alleviating limitations faced by conventional widefield temporal focusing microscopes due to scattering of the fluorescence signal. Additionally, we demonstrate an adaptive sampling scheme that further improves the compression and speed of our approach.

Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: II mechanisms.

PubMed

Nikolaev, Anton; Zheng, Lei; Wardill, Trevor J; O'Kane, Cahir J; de Polavieja, Gonzalo G; Juusola, Mikko

2009-01-01

Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

PubMed Central

Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-01-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information. PMID:27304526

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

PubMed

Huang, Chao; Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-06-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

Real-time nutrient monitoring in rivers: adaptive sampling strategies, technological challenges and future directions

NASA Astrophysics Data System (ADS)

Blaen, Phillip; Khamis, Kieran; Lloyd, Charlotte; Bradley, Chris

2016-04-01

Excessive nutrient concentrations in river waters threaten aquatic ecosystem functioning and can pose substantial risks to human health. Robust monitoring strategies are therefore required to generate reliable estimates of river nutrient loads and to improve understanding of the catchment processes that drive spatiotemporal patterns in nutrient fluxes. Furthermore, these data are vital for prediction of future trends under changing environmental conditions and thus the development of appropriate mitigation measures. In recent years, technological developments have led to an increase in the use of continuous in-situ nutrient analysers, which enable measurements at far higher temporal resolutions than can be achieved with discrete sampling and subsequent laboratory analysis. However, such instruments can be costly to run and difficult to maintain (e.g. due to high power consumption and memory requirements), leading to trade-offs between temporal and spatial monitoring resolutions. Here, we highlight how adaptive monitoring strategies, comprising a mixture of temporal sample frequencies controlled by one or more 'trigger variables' (e.g. river stage, turbidity, or nutrient concentration), can advance our understanding of catchment nutrient dynamics while simultaneously overcoming many of the practical and economic challenges encountered in typical in-situ river nutrient monitoring applications. We present examples of short-term variability in river nutrient dynamics, driven by complex catchment behaviour, which support our case for the development of monitoring systems that can adapt in real-time to rapid environmental changes. In addition, we discuss the advantages and disadvantages of current nutrient monitoring techniques, and suggest new research directions based on emerging technologies and highlight how these might improve: 1) monitoring strategies, and 2) understanding of linkages between catchment processes and river nutrient fluxes.

Adapting livestock management to spatio-temporal heterogeneity in semi-arid rangelands.

PubMed

Jakoby, O; Quaas, M F; Baumgärtner, S; Frank, K

2015-10-01

Management strategies in rotational grazing systems differ in their level of complexity and adaptivity. Different components of such grazing strategies are expected to allow for adaptation to environmental heterogeneities in space and time. However, most models investigating general principles of rangeland management strategies neglect spatio-temporal system properties including seasonality and spatial heterogeneity of environmental variables. We developed an ecological-economic rangeland model that combines a spatially explicit farm structure with intra-annual time steps. This allows investigating different management components in rotational grazing systems (including stocking and rotation rules) and evaluating their effect on the ecological and economic states of semi-arid grazing systems. Our results show that adaptive stocking is less sensitive to overstocking compared to a constant stocking strategy. Furthermore, the rotation rule becomes important only at stocking numbers that maximize expected income. Altogether, the best of the tested strategies is adaptive stocking combined with a rotation that adapts to both spatial forage availability and seasonality. This management strategy maximises mean income and at the same time maintains the rangeland in a viable condition. However, we could also show that inappropriate adaptation that neglects seasonality even leads to deterioration. Rangelands characterised by higher inter-annual climate variability show a higher risk of income losses under a non-adaptive stocking rule, and non-adaptive rotation is least able to buffer increasing climate variability. Overall, all important system properties including seasonality and spatial heterogeneity of available resources need to be considered when designing an appropriate rangeland management system. Resulting adaptive rotational grazing strategies can be valuable for improving management and mitigating income risks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of climate change adaptation scenarios on perceived spatio-temporal characteristics of drought events

NASA Astrophysics Data System (ADS)

Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

2012-04-01

Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century under different emissions scenarios? (3) How would perceived drought characteristics evolve under theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective" adaptation) or over a 30-year period centred around the date considered ("prospective" adaptation). These adaptation scenarios are translated into local-scale transient drought thresholds, as opposed to a non-adaptation scenario where the drought threshold remains constant. The perceived spatio-temporal characteristics derived from the theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of local-scale adaptation and global-scale mitigation. This study thus proposes a proof of concept for using standardized drought indices for (1) assessing projections of spatio-temporal drought characteristics and (2) building theoretical adaptation scenarios and associated perceived changes in hydrological impact studies (Vidal et al., submitted). Vidal J.-P., Martin E., Franchistéguy L., Habets F., Soubeyroux J.-M., Blanchard M. & Baillon M. (2010) Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite. Hydrology and Earth System Sciences, 14, 459-478.doi: 10.5194/hess-14-459-2010 Vidal J.-P., Martin E., Kitova N., Najac J. & Soubeyroux, J. M. (submitted) Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios. Submitted to Hydrology and earth System Sciences

High temporal resolution aberrometry in a 50-eye population and implications for adaptive optics error budget.

PubMed

Jarosz, Jessica; Mecê, Pedro; Conan, Jean-Marc; Petit, Cyril; Paques, Michel; Meimon, Serge

2017-04-01

We formed a database gathering the wavefront aberrations of 50 healthy eyes measured with an original custom-built Shack-Hartmann aberrometer at a temporal frequency of 236 Hz, with 22 lenslets across a 7-mm diameter pupil, for a duration of 20 s. With this database, we draw statistics on the spatial and temporal behavior of the dynamic aberrations of the eye. Dynamic aberrations were studied on a 5-mm diameter pupil and on a 3.4 s sequence between blinks. We noted that, on average, temporal wavefront variance exhibits a n -2 power-law with radial order n and temporal spectra follow a f -1.5 power-law with temporal frequency f . From these statistics, we then extract guidelines for designing an adaptive optics system. For instance, we show the residual wavefront error evolution as a function of the number of corrected modes and of the adaptive optics loop frame rate. In particular, we infer that adaptive optics performance rapidly increases with the loop frequency up to 50 Hz, with gain being more limited at higher rates.

High temporal resolution aberrometry in a 50-eye population and implications for adaptive optics error budget

PubMed Central

Jarosz, Jessica; Mecê, Pedro; Conan, Jean-Marc; Petit, Cyril; Paques, Michel; Meimon, Serge

2017-01-01

We formed a database gathering the wavefront aberrations of 50 healthy eyes measured with an original custom-built Shack-Hartmann aberrometer at a temporal frequency of 236 Hz, with 22 lenslets across a 7-mm diameter pupil, for a duration of 20 s. With this database, we draw statistics on the spatial and temporal behavior of the dynamic aberrations of the eye. Dynamic aberrations were studied on a 5-mm diameter pupil and on a 3.4 s sequence between blinks. We noted that, on average, temporal wavefront variance exhibits a n−2 power-law with radial order n and temporal spectra follow a f−1.5 power-law with temporal frequency f. From these statistics, we then extract guidelines for designing an adaptive optics system. For instance, we show the residual wavefront error evolution as a function of the number of corrected modes and of the adaptive optics loop frame rate. In particular, we infer that adaptive optics performance rapidly increases with the loop frequency up to 50 Hz, with gain being more limited at higher rates. PMID:28736657

Heterogeneous water supply affects growth and benefits of clonal integration between co-existing invasive and native Hydrocotyle species.

PubMed

Wang, Yong-Jian; Bai, Yun-Fei; Zeng, Shi-Qi; Yao, Bin; Wang, Wen; Luo, Fang-Li

2016-07-21

Spatial patchiness and temporal variability in water availability are common in nature under global climate change, which can remarkably influence adaptive responses of clonal plants, i.e. clonal integration (translocating resources between connected ramets). However, little is known about the effects of spatial patchiness and temporal heterogeneity in water on growth and clonal integration between congeneric invasive and native Hydrocotyle species. In a greenhouse experiment, we subjected severed or no severed (intact) fragments of Hydrocotyle vulgaris, a highly invasive species in China, and its co-existing, native congener H. sibthorpioides to different spatial patchiness (homogeneous and patchy) and temporal interval (low and high interval) in water supply. Clonal integration had significant positive effects on growth of both species. In the homogeneous water conditions, clonal integration greatly improved the growth in fragments of both species under low interval in water. However, in the patchy water conditions, clonal integration significantly increased growth in both ramets and fragments of H. vulgaris under high interval in water. Therefore, spatial patchiness and temporal interval in water altered the effects of clonal integration of both species, especially for H. vulgaris. The adaptation of H. vulgaris might lead to invasive growth and potential spread under the global water variability.

Emotion-induced trade-offs in spatiotemporal vision.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-05-01

It is generally assumed that emotion facilitates human vision in order to promote adaptive responses to a potential threat in the environment. Surprisingly, we recently found that emotion in some cases impairs the perception of elementary visual features (Bocanegra & Zeelenberg, 2009b). Here, we demonstrate that emotion improves fast temporal vision at the expense of fine-grained spatial vision. We tested participants' threshold resolution with Landolt circles containing a small spatial or brief temporal discontinuity. The prior presentation of a fearful face cue, compared with a neutral face cue, impaired spatial resolution but improved temporal resolution. In addition, we show that these benefits and deficits were triggered selectively by the global configural properties of the faces, which were transmitted only through low spatial frequencies. Critically, the common locus of these opposite effects suggests a trade-off between magno- and parvocellular-type visual channels, which contradicts the common assumption that emotion invariably improves vision. We show that, rather than being a general "boost" for all visual features, affective neural circuits sacrifice the slower processing of small details for a coarser but faster visual signal.

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.

Flicker Adaptation of Low-Level Cortical Visual Neurons Contributes to Temporal Dilation

ERIC Educational Resources Information Center

Ortega, Laura; Guzman-Martinez, Emmanuel; Grabowecky, Marcia; Suzuki, Satoru

2012-01-01

Several seconds of adaptation to a flickered stimulus causes a subsequent brief static stimulus to appear longer in duration. Nonsensory factors, such as increased arousal and attention, have been thought to mediate this flicker-based temporal-dilation aftereffect. In this study, we provide evidence that adaptation of low-level cortical visual…

Rod Electroretinograms Elicited by Silent Substitution Stimuli from the Light-Adapted Human Eye

PubMed Central

Maguire, John; Parry, Neil R. A.; Kremers, Jan; Kommanapalli, Deepika; Murray, Ian J.; McKeefry, Declan J.

2016-01-01

Purpose To demonstrate that silent substitution stimuli can be used to generate electroretinograms (ERGs) that effectively isolate rod photoreceptor function in humans without the need for dark adaptation, and that this approach constitutes a viable alternative to current clinical standard testing protocols. Methods Rod-isolating and non-isolating sinusoidal flicker stimuli were generated on a 4 primary light-emitting diode (LED) Ganzfeld stimulator to elicit ERGs from participants with normal and compromised rod function who had not undergone dark-adaptation. Responses were subjected to Fourier analysis, and the amplitude and phase of the fundamental were used to examine temporal frequency and retinal illuminance response characteristics. Results Electroretinograms elicited by rod-isolating silent substitution stimuli exhibit low-pass temporal frequency response characteristics with an upper response limit of 30 Hz. Responses are optimal between 5 and 8 Hz and between 10 and 100 photopic trolands (Td). There is a significant correlation between the response amplitudes obtained with the silent substitution method and current standard clinical protocols. Analysis of signal-to-noise ratios reveals significant differences between subjects with normal and compromised rod function. Conclusions Silent substitution provides an effective method for the isolation of human rod photoreceptor function in subjects with normal as well as compromised rod function when stimuli are used within appropriate parameter ranges. Translational Relevance This method of generating rod-mediated ERGs can be achieved without time-consuming periods of dark adaptation, provides improved isolation of rod- from cone-based activity, and will lead to the development of faster clinical electrophysiologic testing protocols with improved selectivity. PMID:27617180

Selection, adaptation, and predictive information in changing environments

NASA Astrophysics Data System (ADS)

Feltgen, Quentin; Nemenman, Ilya

2014-03-01

Adaptation by means of natural selection is a key concept in evolutionary biology. Individuals better matched to the surrounding environment outcompete the others. This increases the fraction of the better adapted individuals in the population, and hence increases its collective fitness. Adaptation is also prominent on the physiological scale in neuroscience and cell biology. There each individual infers properties of the environment and changes to become individually better, improving the overall population as well. Traditionally, these two notions of adaption have been considered distinct. Here we argue that both types of adaptation result in the same population growth in a broad class of analytically tractable population dynamics models in temporally changing environments. In particular, both types of adaptation lead to subextensive corrections to the population growth rates. These corrections are nearly universal and are equal to the predictive information in the environment time series, which is also the characterization of the time series complexity. This work has been supported by the James S. McDonnell Foundation.

Sleep to the beat: A nap favours consolidation of timing.

PubMed

Verweij, Ilse M; Onuki, Yoshiyuki; Van Someren, Eus J W; Van der Werf, Ysbrand D

2016-06-01

Growing evidence suggests that sleep is important for procedural learning, but few studies have investigated the effect of sleep on the temporal aspects of motor skill learning. We assessed the effect of a 90-min day-time nap on learning a motor timing task, using 2 adaptations of a serial interception sequence learning (SISL) task. Forty-two right-handed participants performed the task before and after a 90-min period of sleep or wake. Electroencephalography (EEG) was recorded throughout. The motor task consisted of a sequential spatial pattern and was performed according to 2 different timing conditions, that is, either following a sequential or a random temporal pattern. The increase in accuracy was compared between groups using a mixed linear regression model. Within the sleep group, performance improvement was modeled based on sleep characteristics, including spindle- and slow-wave density. The sleep group, but not the wake group, showed improvement in the random temporal, but especially and significantly more strongly in the sequential temporal condition. None of the sleep characteristics predicted improvement on either general of the timing conditions. In conclusion, a daytime nap improves performance on a timing task. We show that performance on the task with a sequential timing sequence benefits more from sleep than motor timing. More important, the temporal sequence did not benefit initial learning, because differences arose only after an offline period and specifically when this period contained sleep. Sleep appears to aid in the extraction of regularities for optimal subsequent performance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient

PubMed Central

Karanth, K. Ullas; Srivathsa, Arjun; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N. Samba

2017-01-01

Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole (Cuon alpinus), leopard (Panthera pardus) and tiger (Panthera tigris) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds. PMID:28179511

Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient.

PubMed

Karanth, K Ullas; Srivathsa, Arjun; Vasudev, Divya; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N Samba

2017-02-08

Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole ( Cuon alpinus ), leopard ( Panthera pardus ) and tiger ( Panthera tigris ) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds. © 2017 The Author(s).

Musical training generalises across modalities and reveals efficient and adaptive mechanisms for reproducing temporal intervals.

PubMed

Aagten-Murphy, David; Cappagli, Giulia; Burr, David

2014-03-01

Expert musicians are able to time their actions accurately and consistently during a musical performance. We investigated how musical expertise influences the ability to reproduce auditory intervals and how this generalises across different techniques and sensory modalities. We first compared various reproduction strategies and interval length, to examine the effects in general and to optimise experimental conditions for testing the effect of music, and found that the effects were robust and consistent across different paradigms. Focussing on a 'ready-set-go' paradigm subjects reproduced time intervals drawn from distributions varying in total length (176, 352 or 704 ms) or in the number of discrete intervals within the total length (3, 5, 11 or 21 discrete intervals). Overall, Musicians performed more veridical than Non-Musicians, and all subjects reproduced auditory-defined intervals more accurately than visually-defined intervals. However, Non-Musicians, particularly with visual stimuli, consistently exhibited a substantial and systematic regression towards the mean interval. When subjects judged intervals from distributions of longer total length they tended to regress more towards the mean, while the ability to discriminate between discrete intervals within the distribution had little influence on subject error. These results are consistent with a Bayesian model that minimizes reproduction errors by incorporating a central tendency prior weighted by the subject's own temporal precision relative to the current distribution of intervals. Finally a strong correlation was observed between all durations of formal musical training and total reproduction errors in both modalities (accounting for 30% of the variance). Taken together these results demonstrate that formal musical training improves temporal reproduction, and that this improvement transfers from audition to vision. They further demonstrate the flexibility of sensorimotor mechanisms in adapting to different task conditions to minimise temporal estimation errors. © 2013.

Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback.

PubMed

Rauter, Georg; Sigrist, Roland; Riener, Robert; Wolf, Peter

2015-01-01

In literature, the effectiveness of haptics for motor learning is controversially discussed. Haptics is believed to be effective for motor learning in general; however, different types of haptic control enhance different movement aspects. Thus, in dependence on the movement aspects of interest, one type of haptic control may be effective whereas another one is not. Therefore, in the current work, it was investigated if and how different types of haptic controllers affect learning of spatial and temporal movement aspects. In particular, haptic controllers that enforce active participation of the participants were expected to improve spatial aspects. Only haptic controllers that provide feedback about the task's velocity profile were expected to improve temporal aspects. In a study on learning a complex trunk-arm rowing task, the effect of training with four different types of haptic control was investigated: position control, path control, adaptive path control, and reactive path control. A fifth group (control) trained with visual concurrent augmented feedback. As hypothesized, the position controller was most effective for learning of temporal movement aspects, while the path controller was most effective in teaching spatial movement aspects of the rowing task. Visual feedback was also effective for learning temporal and spatial movement aspects.

Using a "time machine" to test for local adaptation of aquatic microbes to temporal and spatial environmental variation.

PubMed

Fox, Jeremy W; Harder, Lawrence D

2015-01-01

Local adaptation occurs when different environments are dominated by different specialist genotypes, each of which is relatively fit in its local conditions and relatively unfit under other conditions. Analogously, ecological species sorting occurs when different environments are dominated by different competing species, each of which is relatively fit in its local conditions. The simplest theory predicts that spatial, but not temporal, environmental variation selects for local adaptation (or generates species sorting), but this prediction is difficult to test. Although organisms can be reciprocally transplanted among sites, doing so among times seems implausible. Here, we describe a reciprocal transplant experiment testing for local adaptation or species sorting of lake bacteria in response to both temporal and spatial variation in water chemistry. The experiment used a -80°C freezer as a "time machine." Bacterial isolates and water samples were frozen for later use, allowing transplantation of older isolates "forward in time" and newer isolates "backward in time." Surprisingly, local maladaptation predominated over local adaptation in both space and time. Such local maladaptation may indicate that adaptation, or the analogous species sorting process, fails to keep pace with temporal fluctuations in water chemistry. This hypothesis could be tested with more finely resolved temporal data. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Auditory Stream Segregation Improves Infants' Selective Attention to Target Tones Amid Distracters

ERIC Educational Resources Information Center

Smith, Nicholas A.; Trainor, Laurel J.

2011-01-01

This study examined the role of auditory stream segregation in the selective attention to target tones in infancy. Using a task adapted from Bregman and Rudnicky's 1975 study and implemented in a conditioned head-turn procedure, infant and adult listeners had to discriminate the temporal order of 2,200 and 2,400 Hz target tones presented alone,…

Multiple adaptable mechanisms early in the primate visual pathway

PubMed Central

Dhruv, Neel T.; Tailby, Chris; Sokol, Sach H.; Lennie, Peter

2011-01-01

We describe experiments that isolate and characterize multiple adaptable mechanisms that influence responses of orientation-selective neurons in primary visual cortex (V1) of anesthetized macaque (Macaca fascicularis). The results suggest that three adaptable stages of machinery shape neural responses in V1: a broadly-tuned early stage and a spatio-temporally tuned later stage, both of which provide excitatory input, and a normalization pool that is also broadly tuned. The early stage and the normalization pool are revealed by adapting gratings that themselves fail to evoke a response from the neuron: either low temporal frequency gratings at the null orientation or gratings of any orientation drifting at high temporal frequencies. When effective, adapting stimuli that altered the sensitivity of these two mechanisms caused reductions of contrast gain and often brought about a paradoxical increase in response gain due to a relatively greater desensitization of the normalization pool. The tuned mechanism is desensitized only by stimuli well-matched to a neuron’s receptive field. We could thus infer desensitization of the tuned mechanism by comparing effects obtained with adapting gratings of preferred and null orientation modulated at low temporal frequencies. PMID:22016535

Temporal and spatial adaptations during the acquisition of a reversal movement.

PubMed

van Loon, E M; Buekers, M J; Helsen, W; Magill, R A

1998-03-01

Adjustments of the biphasic movement in a coincidence anticipation task were studied using an erroneous knowledge of results (KR) paradigm. Forty participants received either no KR, correct KR, erroneous (+100 ms) KR, or 100 trials of correct KR followed by 50 trials of erroneous KR. Kinematic analyses revealed that for this 100-50 KR group the extension part of the movement was temporally adjusted under the influence of erroneous KR. Although accompanied by a decrease in movement amplitude, this did not account for the temporal shift in movement outcome, because all groups showed a reduction in amplitude. It is argued that changing external time constraints mainly results in temporal adaptations. However, spatial adaptations do play a role in kinematic changes during acquisition.

Correlation-based discrimination between cardiac tissue and blood for segmentation of 3D echocardiographic images

NASA Astrophysics Data System (ADS)

Saris, Anne E. C. M.; Nillesen, Maartje M.; Lopata, Richard G. P.; de Korte, Chris L.

2013-03-01

Automated segmentation of 3D echocardiographic images in patients with congenital heart disease is challenging, because the boundary between blood and cardiac tissue is poorly defined in some regions. Cardiologists mentally incorporate movement of the heart, using temporal coherence of structures to resolve ambiguities. Therefore, we investigated the merit of temporal cross-correlation for automated segmentation over the entire cardiac cycle. Optimal settings for maximum cross-correlation (MCC) calculation, based on a 3D cross-correlation based displacement estimation algorithm, were determined to obtain the best contrast between blood and myocardial tissue over the entire cardiac cycle. Resulting envelope-based as well as RF-based MCC values were used as additional external force in a deformable model approach, to segment the left-ventricular cavity in entire systolic phase. MCC values were tested against, and combined with, adaptive filtered, demodulated RF-data. Segmentation results were compared with manually segmented volumes using a 3D Dice Similarity Index (3DSI). Results in 3D pediatric echocardiographic images sequences (n = 4) demonstrate that incorporation of temporal information improves segmentation. The use of MCC values, either alone or in combination with adaptive filtered, demodulated RF-data, resulted in an increase of the 3DSI in 75% of the cases (average 3DSI increase: 0.71 to 0.82). Results might be further improved by optimizing MCC-contrast locally, in regions with low blood-tissue contrast. Reducing underestimation of the endocardial volume due to MCC processing scheme (choice of window size) and consequential border-misalignment, could also lead to more accurate segmentations. Furthermore, increasing the frame rate will also increase MCC-contrast and thus improve segmentation.

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.

Cathodal Transcranial Direct Current Stimulation (tDCS) to the Right Cerebellar Hemisphere Affects Motor Adaptation During Gait.

PubMed

Fernandez, Lara; Albein-Urios, Natalia; Kirkovski, Melissa; McGinley, Jennifer L; Murphy, Anna T; Hyde, Christian; Stokes, Mark A; Rinehart, Nicole J; Enticott, Peter G

2017-02-01

The cerebellum appears to play a key role in the development of internal rules that allow fast, predictive adjustments to novel stimuli. This is crucial for adaptive motor processes, such as those involved in walking, where cerebellar dysfunction has been found to increase variability in gait parameters. Motor adaptation is a process that results in a progressive reduction in errors as movements are adjusted to meet demands, and within the cerebellum, this seems to be localised primarily within the right hemisphere. To examine the role of the right cerebellar hemisphere in adaptive gait, cathodal transcranial direct current stimulation (tDCS) was administered to the right cerebellar hemisphere of 14 healthy adults in a randomised, double-blind, crossover study. Adaptation to a series of distinct spatial and temporal templates was assessed across tDCS condition via a pressure-sensitive gait mat (ProtoKinetics Zeno walkway), on which participants walked with an induced 'limp' at a non-preferred pace. Variability was assessed across key spatial-temporal gait parameters. It was hypothesised that cathodal tDCS to the right cerebellar hemisphere would disrupt adaptation to the templates, reflected in a failure to reduce variability following stimulation. In partial support, adaptation was disrupted following tDCS on one of the four spatial-temporal templates used. However, there was no evidence for general effects on either the spatial or temporal domain. This suggests, under specific conditions, a coupling of spatial and temporal processing in the right cerebellar hemisphere and highlights the potential importance of task complexity in cerebellar function.

Synchronizing theta oscillations with direct-current stimulation strengthens adaptive control in the human brain.

PubMed

Reinhart, Robert M G; Zhu, Julia; Park, Sohee; Woodman, Geoffrey F

2015-07-28

Executive control and flexible adjustment of behavior following errors are essential to adaptive functioning. Loss of adaptive control may be a biomarker of a wide range of neuropsychiatric disorders, particularly in the schizophrenia spectrum. Here, we provide support for the view that oscillatory activity in the frontal cortex underlies adaptive adjustments in cognitive processing following errors. Compared with healthy subjects, patients with schizophrenia exhibited low frequency oscillations with abnormal temporal structure and an absence of synchrony over medial-frontal and lateral-prefrontal cortex following errors. To demonstrate that these abnormal oscillations were the origin of the impaired adaptive control in patients with schizophrenia, we applied noninvasive dc electrical stimulation over the medial-frontal cortex. This noninvasive stimulation descrambled the phase of the low-frequency neural oscillations that synchronize activity across cortical regions. Following stimulation, the behavioral index of adaptive control was improved such that patients were indistinguishable from healthy control subjects. These results provide unique causal evidence for theories of executive control and cortical dysconnectivity in schizophrenia.

Language Comprehension in Language-Learning Impaired Children Improved with Acoustically Modified Speech

NASA Astrophysics Data System (ADS)

Tallal, Paula; Miller, Steve L.; Bedi, Gail; Byma, Gary; Wang, Xiaoqin; Nagarajan, Srikantan S.; Schreiner, Christoph; Jenkins, William M.; Merzenich, Michael M.

1996-01-01

A speech processing algorithm was developed to create more salient versions of the rapidly changing elements in the acoustic waveform of speech that have been shown to be deficiently processed by language-learning impaired (LLI) children. LLI children received extensive daily training, over a 4-week period, with listening exercises in which all speech was translated into this synthetic form. They also received daily training with computer "games" designed to adaptively drive improvements in temporal processing thresholds. Significant improvements in speech discrimination and language comprehension abilities were demonstrated in two independent groups of LLI children.

Representation of action in occipito-temporal cortex.

PubMed

Wiggett, Alison J; Downing, Paul E

2011-07-01

A fundamental question for social cognitive neuroscience is how and where in the brain the identities and actions of others are represented. Here we present a replication and extension of a study by Kable and Chatterjee [Kable, J. W., & Chatterjee, A. Specificity of action representations in the lateral occipito-temporal cortex. Journal of Cognitive Neuroscience, 18, 1498-1517, 2006] examining the role of occipito-temporal cortex in these processes. We presented full-cue movies of actors performing whole-body actions and used fMRI to test for action- and identity-specific adaptation effects. We examined a series of functionally defined regions, including the extrastriate and fusiform body areas, the fusiform face area, the parahippocampal place area, the lateral occipital complex, the right posterior superior temporal sulcus, and motion-selective area hMT+. These regions were analyzed with both standard univariate measures as well as multivoxel pattern analyses. Additionally, we performed whole-brain tests for significant adaptation effects. We found significant action-specific adaptation in many areas, but no evidence for identity-specific adaptation. We argue that this finding could be explained by differences in the familiarity of the stimuli presented: The actions shown were familiar but the actors performing the actions were unfamiliar. However, in contrast to previous findings, we found that the action adaptation effect could not be conclusively tied to specific functionally defined regions. Instead, our results suggest that the adaptation to previously seen actions across identities is a widespread effect, evident across lateral and ventral occipito-temporal cortex.

Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing.

PubMed

Wiklund, Urban; Karlsson, Marcus; Ostlund, Nils; Berglin, Lena; Lindecrantz, Kaj; Karlsson, Stefan; Sandsjö, Leif

2007-06-01

Intermittent disturbances are common in ECG signals recorded with smart clothing: this is mainly because of displacement of the electrodes over the skin. We evaluated a novel adaptive method for spatio-temporal filtering for heartbeat detection in noisy multi-channel ECGs including short signal interruptions in single channels. Using multi-channel database recordings (12-channel ECGs from 10 healthy subjects), the results showed that multi-channel spatio-temporal filtering outperformed regular independent component analysis. We also recorded seven channels of ECG using a T-shirt with textile electrodes. Ten healthy subjects performed different sequences during a 10-min recording: resting, standing, flexing breast muscles, walking and pushups. Using adaptive multi-channel filtering, the sensitivity and precision was above 97% in nine subjects. Adaptive multi-channel spatio-temporal filtering can be used to detect heartbeats in ECGs with high noise levels. One application is heartbeat detection in noisy ECG recordings obtained by integrated textile electrodes in smart clothing.

Effect of reservoir zones and hedging factor dynamism on reservoir adaptive capacity for climate change impacts

NASA Astrophysics Data System (ADS)

Adeloye, Adebayo J.; Soundharajan, Bankaru-Swamy

2018-06-01

When based on the zones of available water in storage, hedging has traditionally used a single hedged zone and a constant rationing ratio for constraining supply during droughts. Given the usual seasonality of reservoir inflows, it is also possible that hedging could feature multiple hedged zones and temporally varying rationing ratios but very few studies addressing this have been reported especially in relation to adaptation to projected climate change. This study developed and tested Genetic Algorithms (GA) optimised zone-based operating policies of various configurations using data for the Pong reservoir, Himachal Pradesh, India. The results show that hedging does lessen vulnerability, which dropped from ≥ 60 % without hedging to below 25 % with the single stage hedging. More complex hedging policies, e.g. two stage and/or temporally varying rationing ratios only produced marginal improvements in performance. All this shows that water hedging policies do not have to be overly complex to effectively offset reservoir vulnerability caused by water shortage resulting from e.g. projected climate change.

Sensorimotor synchronization with tempo-changing auditory sequences: Modeling temporal adaptation and anticipation.

PubMed

van der Steen, M C Marieke; Jacoby, Nori; Fairhurst, Merle T; Keller, Peter E

2015-11-11

The current study investigated the human ability to synchronize movements with event sequences containing continuous tempo changes. This capacity is evident, for example, in ensemble musicians who maintain precise interpersonal coordination while modulating the performance tempo for expressive purposes. Here we tested an ADaptation and Anticipation Model (ADAM) that was developed to account for such behavior by combining error correction processes (adaptation) with a predictive temporal extrapolation process (anticipation). While previous computational models of synchronization incorporate error correction, they do not account for prediction during tempo-changing behavior. The fit between behavioral data and computer simulations based on four versions of ADAM was assessed. These versions included a model with adaptation only, one in which adaptation and anticipation act in combination (error correction is applied on the basis of predicted tempo changes), and two models in which adaptation and anticipation were linked in a joint module that corrects for predicted discrepancies between the outcomes of adaptive and anticipatory processes. The behavioral experiment required participants to tap their finger in time with three auditory pacing sequences containing tempo changes that differed in the rate of change and the number of turning points. Behavioral results indicated that sensorimotor synchronization accuracy and precision, while generally high, decreased with increases in the rate of tempo change and number of turning points. Simulations and model-based parameter estimates showed that adaptation mechanisms alone could not fully explain the observed precision of sensorimotor synchronization. Including anticipation in the model increased the precision of simulated sensorimotor synchronization and improved the fit of model to behavioral data, especially when adaptation and anticipation mechanisms were linked via a joint module based on the notion of joint internal models. Overall results suggest that adaptation and anticipation mechanisms both play an important role during sensorimotor synchronization with tempo-changing sequences. This article is part of a Special Issue entitled SI: Prediction and Attention. Copyright © 2015 Elsevier B.V. All rights reserved.

Digital characterization of a neuromorphic IRFPA

NASA Astrophysics Data System (ADS)

Caulfield, John T.; Fisher, John; Zadnik, Jerome A.; Mak, Ernest S.; Scribner, Dean A.

1995-05-01

This paper reports on the performance of the Neuromorphic IRFPA, the first IRFPA designed and fabricated to conduct temporal and spatial processing on the focal plane. The Neuromorphic IRFPA's unique on-chip processing capability can perform retina-like functions such as lateral inhibition and contrast enhancement, spatial and temporal filtering, image compression and edge enhancement, and logarithmic response. Previously, all evaluations of the Neuromorphic IRFPA camera have been performed on the analog video output. In the work leading up to this paper, the Neuromorphic was integrated to a digital recorder to collect quantitative laboratory and field data. This paper describes the operation and characterization of specific on-chip processes such as spatial and temporal kernel size control. The use of Neuromorphic on-chip processing in future IRFPAs is analyzed as applied to improving SNR via adaptive nonuniformity, charge handling, and dynamic range problems.

Evolutionary adaptations for the temporal processing of natural sounds by the anuran peripheral auditory system

PubMed Central

Schrode, Katrina M.; Bee, Mark A.

2015-01-01

ABSTRACT Sensory systems function most efficiently when processing natural stimuli, such as vocalizations, and it is thought that this reflects evolutionary adaptation. Among the best-described examples of evolutionary adaptation in the auditory system are the frequent matches between spectral tuning in both the peripheral and central auditory systems of anurans (frogs and toads) and the frequency spectra of conspecific calls. Tuning to the temporal properties of conspecific calls is less well established, and in anurans has so far been documented only in the central auditory system. Using auditory-evoked potentials, we asked whether there are species-specific or sex-specific adaptations of the auditory systems of gray treefrogs (Hyla chrysoscelis) and green treefrogs (H. cinerea) to the temporal modulations present in conspecific calls. Modulation rate transfer functions (MRTFs) constructed from auditory steady-state responses revealed that each species was more sensitive than the other to the modulation rates typical of conspecific advertisement calls. In addition, auditory brainstem responses (ABRs) to paired clicks indicated relatively better temporal resolution in green treefrogs, which could represent an adaptation to the faster modulation rates present in the calls of this species. MRTFs and recovery of ABRs to paired clicks were generally similar between the sexes, and we found no evidence that males were more sensitive than females to the temporal modulation patterns characteristic of the aggressive calls used in male–male competition. Together, our results suggest that efficient processing of the temporal properties of behaviorally relevant sounds begins at potentially very early stages of the anuran auditory system that include the periphery. PMID:25617467

Channel noise-induced temporal coherence transitions and synchronization transitions in adaptive neuronal networks with time delay

NASA Astrophysics Data System (ADS)

Gong, Yubing; Xie, Huijuan

2017-09-01

Using spike-timing-dependent plasticity (STDP), we study the effect of channel noise on temporal coherence and synchronization of adaptive scale-free Hodgkin-Huxley neuronal networks with time delay. It is found that the spiking regularity and spatial synchronization of the neurons intermittently increase and decrease as channel noise intensity is varied, exhibiting transitions of temporal coherence and synchronization. Moreover, this phenomenon depends on time delay, STDP, and network average degree. As time delay increases, the phenomenon is weakened, however, there are optimal STDP and network average degree by which the phenomenon becomes strongest. These results show that channel noise can intermittently enhance the temporal coherence and synchronization of the delayed adaptive neuronal networks. These findings provide a new insight into channel noise for the information processing and transmission in neural systems.

Exploring the functional impact of adaptive seating on the lives of individual children and their families: a collective case study.

PubMed

Stier, Carly D; Chieu, Ivan B; Howell, Lori; Ryan, Stephen E

2017-07-01

This study examined parent-reported change in the functional performance of four school-aged children with wheeled mobility needs who had used a new adaptive seating system for 6 weeks. The collective case study involved four mothers whose children, ages 6-9 years, received a new adaptive seating system for a manual wheelchair or stroller. Mothers completed the Family Impact of Assistive Technology Scale for Adaptive Seating (FIATS-AS) at the time their child received a new seating system, and then after 6 weeks of daily use. Other questionnaires, health records, and semi-structured interviews provided additional data about the seating interventions and their functional effects on individual children and their families. The FIATS-AS detected overall functional gain in one family, and both gains and losses in 2-7 dimensions for all families. Functional status and change scores showed consistency with measures of seating intervention satisfaction, global functional change, and home participation. Interview themes also suggested consistency with change scores, but provided a deeper understanding of important factors that influenced adaptive seating outcomes. This study supports the need to explore further the complexity, temporality and meaningfulness of adaptive seating outcomes in individual children and their families. Implications for Rehabilitation Assistive technology practitioners need to adopt practical measurement strategies that consider the complexity, temporality, and meaningfulness of outcomes to make evidence-informed decisions about how to improve adaptive seating services and interventions. Health measurement scales that measure adaptive seating outcomes for service applications must have adequate levels of reliability and validity, as well as demonstrate responsive to important change over time for individual children and their families. Needs-specific measurement scales provide a promising avenue for understanding functional outcomes for individual children and youth who use adaptive seating systems.

Quantifying the Adaptive Cycle | Science Inventory | US EPA

EPA Pesticide Factsheets

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

Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

NASA Astrophysics Data System (ADS)

Altuntas, Alper; Baugh, John

2017-07-01

Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

Closed-Loop Adaptive Optics Control in Strong Atmospheric Turbulence

DTIC Science & Technology

2008-09-01

115 7.1.1 Kalman estimation of anisoplanatic Zernike tilt . . . . 115 7.1.2 An improved temporally phase-shifted design . . . . . 115 7.1.3...5 7. Shack-Hartmann lenslet diagram [40] . . . . . . . . . . . . . . . . . . 9 8. Determining phase tilt from a S-H WFS [8...wavefront prior to it encountering the WFS. In this system a non- deformable mirror known as a fast-steering mirror (FSM) corrects the tilt (average phase

Temporal aspects of copper homeostasis and its crosstalk with hormones

PubMed Central

Peñarrubia, Lola; Romero, Paco; Carrió-Seguí, Angela; Andrés-Bordería, Amparo; Moreno, Joaquín; Sanz, Amparo

2015-01-01

To cope with the dual nature of copper as being essential and toxic for cells, plants temporarily adapt the expression of copper homeostasis components to assure its delivery to cuproproteins while avoiding the interference of potential oxidative damage derived from both copper uptake and photosynthetic reactions during light hours. The circadian clock participates in the temporal organization of coordination of plant nutrition adapting metabolic responses to the daily oscillations. This timely control improves plant fitness and reproduction and holds biotechnological potential to drive increased crop yields. Hormonal pathways, including those of abscisic acid, gibberellins, ethylene, auxins, and jasmonates are also under direct clock and light control, both in mono and dicotyledons. In this review, we focus on copper transport in Arabidopsis thaliana and Oryza sativa and the presumable role of hormones in metal homeostasis matching nutrient availability to growth requirements and preventing metal toxicity. The presence of putative hormone-dependent regulatory elements in the promoters of copper transporters genes suggests hormonal regulation to match special copper requirements during plant development. Spatial and temporal processes that can be affected by hormones include the regulation of copper uptake into roots, intracellular trafficking and compartmentalization, and long-distance transport to developing vegetative and reproductive tissues. In turn, hormone biosynthesis and signaling are also influenced by copper availability, which suggests reciprocal regulation subjected to temporal control by the central oscillator of the circadian clock. This transcriptional regulatory network, coordinates environmental and hormonal signaling with developmental pathways to allow enhanced micronutrient acquisition efficiency. PMID:25941529

A marching-walking hybrid induces step length adaptation and transfers to natural walking

PubMed Central

Long, Andrew W.; Finley, James M.

2015-01-01

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not “walk” but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training. PMID:25867742

A marching-walking hybrid induces step length adaptation and transfers to natural walking.

PubMed

Long, Andrew W; Finley, James M; Bastian, Amy J

2015-06-01

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not "walk" but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training. Copyright © 2015 the American Physiological Society.

The ADaptation and Anticipation Model (ADAM) of sensorimotor synchronization

PubMed Central

van der Steen, M. C. (Marieke); Keller, Peter E.

2013-01-01

A constantly changing environment requires precise yet flexible timing of movements. Sensorimotor synchronization (SMS)—the temporal coordination of an action with events in a predictable external rhythm—is a fundamental human skill that contributes to optimal sensory-motor control in daily life. A large body of research related to SMS has focused on adaptive error correction mechanisms that support the synchronization of periodic movements (e.g., finger taps) with events in regular pacing sequences. The results of recent studies additionally highlight the importance of anticipatory mechanisms that support temporal prediction in the context of SMS with sequences that contain tempo changes. To investigate the role of adaptation and anticipatory mechanisms in SMS we introduce ADAM: an ADaptation and Anticipation Model. ADAM combines reactive error correction processes (adaptation) with predictive temporal extrapolation processes (anticipation) inspired by the computational neuroscience concept of internal models. The combination of simulations and experimental manipulations based on ADAM creates a novel and promising approach for exploring adaptation and anticipation in SMS. The current paper describes the conceptual basis and architecture of ADAM. PMID:23772211

Normalized value coding explains dynamic adaptation in the human valuation process.

PubMed

Khaw, Mel W; Glimcher, Paul W; Louie, Kenway

2017-11-28

The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics.

PubMed

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-10-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

PubMed Central

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-01-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation. PMID:27699416

Rapid, generalized adaptation to asynchronous audiovisual speech

PubMed Central

Van der Burg, Erik; Goodbourn, Patrick T.

2015-01-01

The brain is adaptive. The speed of propagation through air, and of low-level sensory processing, differs markedly between auditory and visual stimuli; yet the brain can adapt to compensate for the resulting cross-modal delays. Studies investigating temporal recalibration to audiovisual speech have used prolonged adaptation procedures, suggesting that adaptation is sluggish. Here, we show that adaptation to asynchronous audiovisual speech occurs rapidly. Participants viewed a brief clip of an actor pronouncing a single syllable. The voice was either advanced or delayed relative to the corresponding lip movements, and participants were asked to make a synchrony judgement. Although we did not use an explicit adaptation procedure, we demonstrate rapid recalibration based on a single audiovisual event. We find that the point of subjective simultaneity on each trial is highly contingent upon the modality order of the preceding trial. We find compelling evidence that rapid recalibration generalizes across different stimuli, and different actors. Finally, we demonstrate that rapid recalibration occurs even when auditory and visual events clearly belong to different actors. These results suggest that rapid temporal recalibration to audiovisual speech is primarily mediated by basic temporal factors, rather than higher-order factors such as perceived simultaneity and source identity. PMID:25716790

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Adaptation to delayed auditory feedback induces the temporal recalibration effect in both speech perception and production.

PubMed

Yamamoto, Kosuke; Kawabata, Hideaki

2014-12-01

We ordinarily speak fluently, even though our perceptions of our own voices are disrupted by various environmental acoustic properties. The underlying mechanism of speech is supposed to monitor the temporal relationship between speech production and the perception of auditory feedback, as suggested by a reduction in speech fluency when the speaker is exposed to delayed auditory feedback (DAF). While many studies have reported that DAF influences speech motor processing, its relationship to the temporal tuning effect on multimodal integration, or temporal recalibration, remains unclear. We investigated whether the temporal aspects of both speech perception and production change due to adaptation to the delay between the motor sensation and the auditory feedback. This is a well-used method of inducing temporal recalibration. Participants continually read texts with specific DAF times in order to adapt to the delay. Then, they judged the simultaneity between the motor sensation and the vocal feedback. We measured the rates of speech with which participants read the texts in both the exposure and re-exposure phases. We found that exposure to DAF changed both the rate of speech and the simultaneity judgment, that is, participants' speech gained fluency. Although we also found that a delay of 200 ms appeared to be most effective in decreasing the rates of speech and shifting the distribution on the simultaneity judgment, there was no correlation between these measurements. These findings suggest that both speech motor production and multimodal perception are adaptive to temporal lag but are processed in distinct ways.

Spatial and temporal adaptations that accompany increasing catching performance during learning.

PubMed

Mazyn, Liesbeth I N; Lenoir, Matthieu; Montagne, Gilles; Savelsbergh, Geert J P

2007-11-01

The authors studied changes in performance and kinematics during the acquisition of a 1-handed catch. Participants were 8 women who took an intensive 2-week training program during which they evolved from poor catchers to subexpert catchers. An increased temporal consistency, shift in spatial location of ball-hand contact away from the body, and higher peak velocity of the transport of the hand toward the ball accompanied their improvement in catching performance. Moreover, novice catchers first adjusted spatial characteristics of the catch to the task constraints and fine-tuned temporal features only later during learning. A principal components analysis on a large set of kinematic variables indicated that a successful catch depends on (a) forward displacement of the hand and (b) the dynamics of the hand closure, thereby providing a kinematic underpinning for the traditional transport-manipulation dissociation in the grasping and catching literature.

Evolutionary adaptations for the temporal processing of natural sounds by the anuran peripheral auditory system.

PubMed

Schrode, Katrina M; Bee, Mark A

2015-03-01

Sensory systems function most efficiently when processing natural stimuli, such as vocalizations, and it is thought that this reflects evolutionary adaptation. Among the best-described examples of evolutionary adaptation in the auditory system are the frequent matches between spectral tuning in both the peripheral and central auditory systems of anurans (frogs and toads) and the frequency spectra of conspecific calls. Tuning to the temporal properties of conspecific calls is less well established, and in anurans has so far been documented only in the central auditory system. Using auditory-evoked potentials, we asked whether there are species-specific or sex-specific adaptations of the auditory systems of gray treefrogs (Hyla chrysoscelis) and green treefrogs (H. cinerea) to the temporal modulations present in conspecific calls. Modulation rate transfer functions (MRTFs) constructed from auditory steady-state responses revealed that each species was more sensitive than the other to the modulation rates typical of conspecific advertisement calls. In addition, auditory brainstem responses (ABRs) to paired clicks indicated relatively better temporal resolution in green treefrogs, which could represent an adaptation to the faster modulation rates present in the calls of this species. MRTFs and recovery of ABRs to paired clicks were generally similar between the sexes, and we found no evidence that males were more sensitive than females to the temporal modulation patterns characteristic of the aggressive calls used in male-male competition. Together, our results suggest that efficient processing of the temporal properties of behaviorally relevant sounds begins at potentially very early stages of the anuran auditory system that include the periphery. © 2015. Published by The Company of Biologists Ltd.

fMR-adaptation indicates selectivity to audiovisual content congruency in distributed clusters in human superior temporal cortex.

PubMed

van Atteveldt, Nienke M; Blau, Vera C; Blomert, Leo; Goebel, Rainer

2010-02-02

Efficient multisensory integration is of vital importance for adequate interaction with the environment. In addition to basic binding cues like temporal and spatial coherence, meaningful multisensory information is also bound together by content-based associations. Many functional Magnetic Resonance Imaging (fMRI) studies propose the (posterior) superior temporal cortex (STC) as the key structure for integrating meaningful multisensory information. However, a still unanswered question is how superior temporal cortex encodes content-based associations, especially in light of inconsistent results from studies comparing brain activation to semantically matching (congruent) versus nonmatching (incongruent) multisensory inputs. Here, we used fMR-adaptation (fMR-A) in order to circumvent potential problems with standard fMRI approaches, including spatial averaging and amplitude saturation confounds. We presented repetitions of audiovisual stimuli (letter-speech sound pairs) and manipulated the associative relation between the auditory and visual inputs (congruent/incongruent pairs). We predicted that if multisensory neuronal populations exist in STC and encode audiovisual content relatedness, adaptation should be affected by the manipulated audiovisual relation. The results revealed an occipital-temporal network that adapted independently of the audiovisual relation. Interestingly, several smaller clusters distributed over superior temporal cortex within that network, adapted stronger to congruent than to incongruent audiovisual repetitions, indicating sensitivity to content congruency. These results suggest that the revealed clusters contain multisensory neuronal populations that encode content relatedness by selectively responding to congruent audiovisual inputs, since unisensory neuronal populations are assumed to be insensitive to the audiovisual relation. These findings extend our previously revealed mechanism for the integration of letters and speech sounds and demonstrate that fMR-A is sensitive to multisensory congruency effects that may not be revealed in BOLD amplitude per se.

Prism adaptation improves ego-centered but not allocentric neglect in early rehabilitation patients.

PubMed

Gossmann, Anja; Kastrup, Andreas; Kerkhoff, Georg; López-Herrero, Carmen; Hildebrandt, Helmut

2013-01-01

Unilateral neglect due to parieto-temporo-frontal lesions has a negative impact on the success of rehabilitation, and prism adaptation (PA) enhances recovery from neglect. However, it is unclear if this effect holds also in severely impaired patients and/or in the postacute phase of rehabilitation. Moreover, it is not known whether PA affects all aspects of neglect recovery or ego-centered spatial orientation only. Sixteen patients in a postacute stage (on average 36 days after a large right cerebrovascular stroke) were entered into a series of single case design studies with 4 measurements: 2 before and 2 after 1 week of PA treatment. All patients had severe neglect (showing trunk, head, and eye deviation; canceling less than 20% of targets in a visual cancellation test). Lesions were transferred to a standard brain to analyze size and location. Patients improved in cued body orientation and in the cancellation task, that is, in ego-centered neglect. However, none of the measures used to evaluate neglect of left side of objects irrespective of their position on the right or left side of the patient (allocentric neglect) showed an improvement. Treatment effects were not influenced by total lesion size, but lesions including the postcentral cortex were related to smaller recovery gains. PA is helpful in treating severely impaired patients in the postacute phase, but the effect is restricted to ego-centered neglect. Lesions in the postcentral cortex (middle occipito-temporal, middle temporal, and posterior parietal areas) seem to limit the effect of PA.

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.

Computational Architecture of the Granular Layer of Cerebellum-Like Structures.

PubMed

Bratby, Peter; Sneyd, James; Montgomery, John

2017-02-01

In the adaptive filter model of the cerebellum, the granular layer performs a recoding which expands incoming mossy fibre signals into a temporally diverse set of basis signals. The underlying neural mechanism is not well understood, although various mechanisms have been proposed, including delay lines, spectral timing and echo state networks. Here, we develop a computational simulation based on a network of leaky integrator neurons, and an adaptive filter performance measure, which allows candidate mechanisms to be compared. We demonstrate that increasing the circuit complexity improves adaptive filter performance, and relate this to evolutionary innovations in the cerebellum and cerebellum-like structures in sharks and electric fish. We show how recurrence enables an increase in basis signal duration, which suggest a possible explanation for the explosion in granule cell numbers in the mammalian cerebellum.

Temporal Coding of Volumetric Imagery

NASA Astrophysics Data System (ADS)

Llull, Patrick Ryan

'Image volumes' refer to realizations of images in other dimensions such as time, spectrum, and focus. Recent advances in scientific, medical, and consumer applications demand improvements in image volume capture. Though image volume acquisition continues to advance, it maintains the same sampling mechanisms that have been used for decades; every voxel must be scanned and is presumed independent of its neighbors. Under these conditions, improving performance comes at the cost of increased system complexity, data rates, and power consumption. This dissertation explores systems and methods capable of efficiently improving sensitivity and performance for image volume cameras, and specifically proposes several sampling strategies that utilize temporal coding to improve imaging system performance and enhance our awareness for a variety of dynamic applications. Video cameras and camcorders sample the video volume (x,y,t) at fixed intervals to gain understanding of the volume's temporal evolution. Conventionally, one must reduce the spatial resolution to increase the framerate of such cameras. Using temporal coding via physical translation of an optical element known as a coded aperture, the compressive temporal imaging (CACTI) camera emonstrates a method which which to embed the temporal dimension of the video volume into spatial (x,y) measurements, thereby greatly improving temporal resolution with minimal loss of spatial resolution. This technique, which is among a family of compressive sampling strategies developed at Duke University, temporally codes the exposure readout functions at the pixel level. Since video cameras nominally integrate the remaining image volume dimensions (e.g. spectrum and focus) at capture time, spectral (x,y,t,lambda) and focal (x,y,t,z) image volumes are traditionally captured via sequential changes to the spectral and focal state of the system, respectively. The CACTI camera's ability to embed video volumes into images leads to exploration of other information within that video; namely, focal and spectral information. The next part of the thesis demonstrates derivative works of CACTI: compressive extended depth of field and compressive spectral-temporal imaging. These works successfully show the technique's extension of temporal coding to improve sensing performance in these other dimensions. Geometrical optics-related tradeoffs, such as the classic challenges of wide-field-of-view and high resolution photography, have motivated the development of mulitscale camera arrays. The advent of such designs less than a decade ago heralds a new era of research- and engineering-related challenges. One significant challenge is that of managing the focal volume (x,y,z ) over wide fields of view and resolutions. The fourth chapter shows advances on focus and image quality assessment for a class of multiscale gigapixel cameras developed at Duke. Along the same line of work, we have explored methods for dynamic and adaptive addressing of focus via point spread function engineering. We demonstrate another form of temporal coding in the form of physical translation of the image plane from its nominal focal position. We demonstrate this technique's capability to generate arbitrary point spread functions.

Computer vision elastography: speckle adaptive motion estimation for elastography using ultrasound sequences.

PubMed

Revell, James; Mirmehdi, Majid; McNally, Donal

2005-06-01

We present the development and validation of an image based speckle tracking methodology, for determining temporal two-dimensional (2-D) axial and lateral displacement and strain fields from ultrasound video streams. We refine a multiple scale region matching approach incorporating novel solutions to known speckle tracking problems. Key contributions include automatic similarity measure selection to adapt to varying speckle density, quantifying trajectory fields, and spatiotemporal elastograms. Results are validated using tissue mimicking phantoms and in vitro data, before applying them to in vivo musculoskeletal ultrasound sequences. The method presented has the potential to improve clinical knowledge of tendon pathology from carpel tunnel syndrome, inflammation from implants, sport injuries, and many others.

A video coding scheme based on joint spatiotemporal and adaptive prediction.

PubMed

Jiang, Wenfei; Latecki, Longin Jan; Liu, Wenyu; Liang, Hui; Gorman, Ken

2009-05-01

We propose a video coding scheme that departs from traditional Motion Estimation/DCT frameworks and instead uses Karhunen-Loeve Transform (KLT)/Joint Spatiotemporal Prediction framework. In particular, a novel approach that performs joint spatial and temporal prediction simultaneously is introduced. It bypasses the complex H.26x interframe techniques and it is less computationally intensive. Because of the advantage of the effective joint prediction and the image-dependent color space transformation (KLT), the proposed approach is demonstrated experimentally to consistently lead to improved video quality, and in many cases to better compression rates and improved computational speed.

Locomotor Adaptation to an Asymmetric Force on the Human Pelvis Directed Along the Right Leg.

PubMed

Vashista, Vineet; Martelli, Dario; Agrawal, Sunil

2015-09-11

In this work, we study locomotor adaptation in healthy adults when an asymmetric force vector is applied to the pelvis directed along the right leg. A cable-driven Active Tethered Pelvic Assist Device (A-TPAD) is used to apply an external force on the pelvis, specific to a subject's gait pattern. The force vector is intended to provide external weight bearing during walking and modify the durations of limb supports. The motivation is to use this paradigm to improve weight bearing and stance phase symmetry in individuals with hemiparesis. An experiment with nine healthy subjects was conducted. The results show significant changes in the gait kinematics and kinetics while the healthy subjects developed temporal and spatial asymmetry in gait pattern in response to the applied force vector. This was followed by aftereffects once the applied force vector was removed. The adaptation to the applied force resulted in asymmetry in stance phase timing and lower limb muscle activity. We believe this paradigm, when extended to individuals with hemiparesis, can show improvements in weight bearing capability with positive effects on gait symmetry and walking speed.

Reduced audiovisual recalibration in the elderly.

PubMed

Chan, Yu Man; Pianta, Michael J; McKendrick, Allison M

2014-01-01

Perceived synchrony of visual and auditory signals can be altered by exposure to a stream of temporally offset stimulus pairs. Previous literature suggests that adapting to audiovisual temporal offsets is an important recalibration to correctly combine audiovisual stimuli into a single percept across a range of source distances. Healthy aging results in synchrony perception over a wider range of temporally offset visual and auditory signals, independent of age-related unisensory declines in vision and hearing sensitivities. However, the impact of aging on audiovisual recalibration is unknown. Audiovisual synchrony perception for sound-lead and sound-lag stimuli was measured for 15 younger (22-32 years old) and 15 older (64-74 years old) healthy adults using a method-of-constant-stimuli, after adapting to a stream of visual and auditory pairs. The adaptation pairs were either synchronous or asynchronous (sound-lag of 230 ms). The adaptation effect for each observer was computed as the shift in the mean of the individually fitted psychometric functions after adapting to asynchrony. Post-adaptation to synchrony, the younger and older observers had average window widths (±standard deviation) of 326 (±80) and 448 (±105) ms, respectively. There was no adaptation effect for sound-lead pairs. Both the younger and older observers, however, perceived more sound-lag pairs as synchronous. The magnitude of the adaptation effect in the older observers was not correlated with how often they saw the adapting sound-lag stimuli as asynchronous. Our finding demonstrates that audiovisual synchrony perception adapts less with advancing age.

Reduced audiovisual recalibration in the elderly

PubMed Central

Chan, Yu Man; Pianta, Michael J.; McKendrick, Allison M.

2014-01-01

Perceived synchrony of visual and auditory signals can be altered by exposure to a stream of temporally offset stimulus pairs. Previous literature suggests that adapting to audiovisual temporal offsets is an important recalibration to correctly combine audiovisual stimuli into a single percept across a range of source distances. Healthy aging results in synchrony perception over a wider range of temporally offset visual and auditory signals, independent of age-related unisensory declines in vision and hearing sensitivities. However, the impact of aging on audiovisual recalibration is unknown. Audiovisual synchrony perception for sound-lead and sound-lag stimuli was measured for 15 younger (22–32 years old) and 15 older (64–74 years old) healthy adults using a method-of-constant-stimuli, after adapting to a stream of visual and auditory pairs. The adaptation pairs were either synchronous or asynchronous (sound-lag of 230 ms). The adaptation effect for each observer was computed as the shift in the mean of the individually fitted psychometric functions after adapting to asynchrony. Post-adaptation to synchrony, the younger and older observers had average window widths (±standard deviation) of 326 (±80) and 448 (±105) ms, respectively. There was no adaptation effect for sound-lead pairs. Both the younger and older observers, however, perceived more sound-lag pairs as synchronous. The magnitude of the adaptation effect in the older observers was not correlated with how often they saw the adapting sound-lag stimuli as asynchronous. Our finding demonstrates that audiovisual synchrony perception adapts less with advancing age. PMID:25221508

Rapid, generalized adaptation to asynchronous audiovisual speech.

PubMed

Van der Burg, Erik; Goodbourn, Patrick T

2015-04-07

The brain is adaptive. The speed of propagation through air, and of low-level sensory processing, differs markedly between auditory and visual stimuli; yet the brain can adapt to compensate for the resulting cross-modal delays. Studies investigating temporal recalibration to audiovisual speech have used prolonged adaptation procedures, suggesting that adaptation is sluggish. Here, we show that adaptation to asynchronous audiovisual speech occurs rapidly. Participants viewed a brief clip of an actor pronouncing a single syllable. The voice was either advanced or delayed relative to the corresponding lip movements, and participants were asked to make a synchrony judgement. Although we did not use an explicit adaptation procedure, we demonstrate rapid recalibration based on a single audiovisual event. We find that the point of subjective simultaneity on each trial is highly contingent upon the modality order of the preceding trial. We find compelling evidence that rapid recalibration generalizes across different stimuli, and different actors. Finally, we demonstrate that rapid recalibration occurs even when auditory and visual events clearly belong to different actors. These results suggest that rapid temporal recalibration to audiovisual speech is primarily mediated by basic temporal factors, rather than higher-order factors such as perceived simultaneity and source identity. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Deriving video content type from HEVC bitstream semantics

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio R.

2014-05-01

As network service providers seek to improve customer satisfaction and retention levels, they are increasingly moving from traditional quality of service (QoS) driven delivery models to customer-centred quality of experience (QoE) delivery models. QoS models only consider metrics derived from the network however, QoE models also consider metrics derived from within the video sequence itself. Various spatial and temporal characteristics of a video sequence have been proposed, both individually and in combination, to derive methods of classifying video content either on a continuous scale or as a set of discrete classes. QoE models can be divided into three broad categories, full reference, reduced reference and no-reference models. Due to the need to have the original video available at the client for comparison, full reference metrics are of limited practical value in adaptive real-time video applications. Reduced reference metrics often require metadata to be transmitted with the bitstream, while no-reference metrics typically operate in the decompressed domain at the client side and require significant processing to extract spatial and temporal features. This paper proposes a heuristic, no-reference approach to video content classification which is specific to HEVC encoded bitstreams. The HEVC encoder already makes use of spatial characteristics to determine partitioning of coding units and temporal characteristics to determine the splitting of prediction units. We derive a function which approximates the spatio-temporal characteristics of the video sequence by using the weighted averages of the depth at which the coding unit quadtree is split and the prediction mode decision made by the encoder to estimate spatial and temporal characteristics respectively. Since the video content type of a sequence is determined by using high level information parsed from the video stream, spatio-temporal characteristics are identified without the need for full decoding and can be used in a timely manner to aid decision making in QoE oriented adaptive real time streaming.

Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction

PubMed Central

Kazantsev, Daniil; Guo, Enyu; Kaestner, Anders; Lionheart, William R. B.; Bent, Julian; Withers, Philip J.; Lee, Peter D.

2016-01-01

X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding. PMID:27002902

Grouping and Segregation of Sensory Events by Actions in Temporal Audio-Visual Recalibration.

PubMed

Ikumi, Nara; Soto-Faraco, Salvador

2016-01-01

Perception in multi-sensory environments involves both grouping and segregation of events across sensory modalities. Temporal coincidence between events is considered a strong cue to resolve multisensory perception. However, differences in physical transmission and neural processing times amongst modalities complicate this picture. This is illustrated by cross-modal recalibration, whereby adaptation to audio-visual asynchrony produces shifts in perceived simultaneity. Here, we examined whether voluntary actions might serve as a temporal anchor to cross-modal recalibration in time. Participants were tested on an audio-visual simultaneity judgment task after an adaptation phase where they had to synchronize voluntary actions with audio-visual pairs presented at a fixed asynchrony (vision leading or vision lagging). Our analysis focused on the magnitude of cross-modal recalibration to the adapted audio-visual asynchrony as a function of the nature of the actions during adaptation, putatively fostering cross-modal grouping or, segregation. We found larger temporal adjustments when actions promoted grouping than segregation of sensory events. However, a control experiment suggested that additional factors, such as attention to planning/execution of actions, could have an impact on recalibration effects. Contrary to the view that cross-modal temporal organization is mainly driven by external factors related to the stimulus or environment, our findings add supporting evidence for the idea that perceptual adjustments strongly depend on the observer's inner states induced by motor and cognitive demands.

Grouping and Segregation of Sensory Events by Actions in Temporal Audio-Visual Recalibration

PubMed Central

Ikumi, Nara; Soto-Faraco, Salvador

2017-01-01

Perception in multi-sensory environments involves both grouping and segregation of events across sensory modalities. Temporal coincidence between events is considered a strong cue to resolve multisensory perception. However, differences in physical transmission and neural processing times amongst modalities complicate this picture. This is illustrated by cross-modal recalibration, whereby adaptation to audio-visual asynchrony produces shifts in perceived simultaneity. Here, we examined whether voluntary actions might serve as a temporal anchor to cross-modal recalibration in time. Participants were tested on an audio-visual simultaneity judgment task after an adaptation phase where they had to synchronize voluntary actions with audio-visual pairs presented at a fixed asynchrony (vision leading or vision lagging). Our analysis focused on the magnitude of cross-modal recalibration to the adapted audio-visual asynchrony as a function of the nature of the actions during adaptation, putatively fostering cross-modal grouping or, segregation. We found larger temporal adjustments when actions promoted grouping than segregation of sensory events. However, a control experiment suggested that additional factors, such as attention to planning/execution of actions, could have an impact on recalibration effects. Contrary to the view that cross-modal temporal organization is mainly driven by external factors related to the stimulus or environment, our findings add supporting evidence for the idea that perceptual adjustments strongly depend on the observer's inner states induced by motor and cognitive demands. PMID:28154529

A generalized time-frequency subtraction method for robust speech enhancement based on wavelet filter banks modeling of human auditory system.

PubMed

Shao, Yu; Chang, Chip-Hong

2007-08-01

We present a new speech enhancement scheme for a single-microphone system to meet the demand for quality noise reduction algorithms capable of operating at a very low signal-to-noise ratio. A psychoacoustic model is incorporated into the generalized perceptual wavelet denoising method to reduce the residual noise and improve the intelligibility of speech. The proposed method is a generalized time-frequency subtraction algorithm, which advantageously exploits the wavelet multirate signal representation to preserve the critical transient information. Simultaneous masking and temporal masking of the human auditory system are modeled by the perceptual wavelet packet transform via the frequency and temporal localization of speech components. The wavelet coefficients are used to calculate the Bark spreading energy and temporal spreading energy, from which a time-frequency masking threshold is deduced to adaptively adjust the subtraction parameters of the proposed method. An unvoiced speech enhancement algorithm is also integrated into the system to improve the intelligibility of speech. Through rigorous objective and subjective evaluations, it is shown that the proposed speech enhancement system is capable of reducing noise with little speech degradation in adverse noise environments and the overall performance is superior to several competitive methods.

Infrared fix pattern noise reduction method based on Shearlet Transform

NASA Astrophysics Data System (ADS)

Rong, Shenghui; Zhou, Huixin; Zhao, Dong; Cheng, Kuanhong; Qian, Kun; Qin, Hanlin

2018-06-01

The non-uniformity correction (NUC) is an effective way to reduce fix pattern noise (FPN) and improve infrared image quality. The temporal high-pass NUC method is a kind of practical NUC method because of its simple implementation. However, traditional temporal high-pass NUC methods rely deeply on the scene motion and suffer image ghosting and blurring. Thus, this paper proposes an improved NUC method based on Shearlet Transform (ST). First, the raw infrared image is decomposed into multiscale and multi-orientation subbands by ST and the FPN component mainly exists in some certain high-frequency subbands. Then, high-frequency subbands are processed by the temporal filter to extract the FPN due to its low-frequency characteristics. Besides, each subband has a confidence parameter to determine the degree of FPN, which is estimated by the variance of subbands adaptively. At last, the process of NUC is achieved by subtracting the estimated FPN component from the original subbands and the corrected infrared image can be obtained by the inverse ST. The performance of the proposed method is evaluated with real and synthetic infrared image sequences thoroughly. Experimental results indicate that the proposed method can reduce heavily FPN with less roughness and RMSE.

Noise-induced hearing loss alters the temporal dynamics of auditory-nerve responses

PubMed Central

Scheidt, Ryan E.; Kale, Sushrut; Heinz, Michael G.

2010-01-01

Auditory-nerve fibers demonstrate dynamic response properties in that they adapt to rapid changes in sound level, both at the onset and offset of a sound. These dynamic response properties affect temporal coding of stimulus modulations that are perceptually relevant for many sounds such as speech and music. Temporal dynamics have been well characterized in auditory-nerve fibers from normal-hearing animals, but little is known about the effects of sensorineural hearing loss on these dynamics. This study examined the effects of noise-induced hearing loss on the temporal dynamics in auditory-nerve fiber responses from anesthetized chinchillas. Post-stimulus time histograms were computed from responses to 50-ms tones presented at characteristic frequency and 30 dB above fiber threshold. Several response metrics related to temporal dynamics were computed from post-stimulus-time histograms and were compared between normal-hearing and noise-exposed animals. Results indicate that noise-exposed auditory-nerve fibers show significantly reduced response latency, increased onset response and percent adaptation, faster adaptation after onset, and slower recovery after offset. The decrease in response latency only occurred in noise-exposed fibers with significantly reduced frequency selectivity. These changes in temporal dynamics have important implications for temporal envelope coding in hearing-impaired ears, as well as for the design of dynamic compression algorithms for hearing aids. PMID:20696230

Die Fledermaus: Regarding Optokinetic Contrast Sensitivity and Light-Adaptation, Chicks Are Mice with Wings

PubMed Central

Shi, Qing; Stell, William K.

2013-01-01

Background Through adaptation, animals can function visually under an extremely broad range of light intensities. Light adaptation starts in the retina, through shifts in photoreceptor sensitivity and kinetics plus modulation of visual processing in retinal circuits. Although considerable research has been conducted on retinal adaptation in nocturnal species with rod-dominated retinas, such as the mouse, little is known about how cone-dominated avian retinas adapt to changes in mean light intensity. Methodology/Principal Findings We used the optokinetic response to characterize contrast sensitivity (CS) in the chick retina as a function of spatial frequency and temporal frequency at different mean light intensities. We found that: 1) daytime, cone-driven CS was tuned to spatial frequency; 2) nighttime, presumably rod-driven CS was tuned to temporal frequency and spatial frequency; 3) daytime, presumably cone-driven CS at threshold intensity was invariant with temporal and spatial frequency; and 4) daytime photopic CS was invariant with clock time. Conclusion/Significance Light- and dark-adaptational changes in CS were investigated comprehensively for the first time in the cone-dominated retina of an avian, diurnal species. The chick retina, like the mouse retina, adapts by using a “day/night” or “cone/rod” switch in tuning preference during changes in lighting conditions. The chick optokinetic response is an attractive model for noninvasive, behavioral studies of adaptation in retinal circuitry in health and disease. PMID:24098693

Adaptive Acceleration of Visually Evoked Smooth Eye Movements in Mice

PubMed Central

2016-01-01

The optokinetic response (OKR) consists of smooth eye movements following global motion of the visual surround, which suppress image slip on the retina for visual acuity. The effective performance of the OKR is limited to rather slow and low-frequency visual stimuli, although it can be adaptably improved by cerebellum-dependent mechanisms. To better understand circuit mechanisms constraining OKR performance, we monitored how distinct kinematic features of the OKR change over the course of OKR adaptation, and found that eye acceleration at stimulus onset primarily limited OKR performance but could be dramatically potentiated by visual experience. Eye acceleration in the temporal-to-nasal direction depended more on the ipsilateral floccular complex of the cerebellum than did that in the nasal-to-temporal direction. Gaze-holding following the OKR was also modified in parallel with eye-acceleration potentiation. Optogenetic manipulation revealed that synchronous excitation and inhibition of floccular complex Purkinje cells could effectively accelerate eye movements in the nasotemporal and temporonasal directions, respectively. These results collectively delineate multiple motor pathways subserving distinct aspects of the OKR in mice and constrain hypotheses regarding cellular mechanisms of the cerebellum-dependent tuning of movement acceleration. SIGNIFICANCE STATEMENT Although visually evoked smooth eye movements, known as the optokinetic response (OKR), have been studied in various species for decades, circuit mechanisms of oculomotor control and adaptation remain elusive. In the present study, we assessed kinematics of the mouse OKR through the course of adaptation training. Our analyses revealed that eye acceleration at visual-stimulus onset primarily limited working velocity and frequency range of the OKR, yet could be dramatically potentiated during OKR adaptation. Potentiation of eye acceleration exhibited different properties between the nasotemporal and temporonasal OKRs, indicating distinct visuomotor circuits underlying the two. Lesions and optogenetic manipulation of the cerebellum provide constraints on neural circuits mediating visually driven eye acceleration and its adaptation. PMID:27335412

Mental simulation of routes during navigation involves adaptive temporal compression

PubMed Central

Arnold, Aiden E.G.F.; Iaria, Giuseppe; Ekstrom, Arne D.

2016-01-01

Mental simulation is a hallmark feature of human cognition, allowing features from memories to be flexibly used during prospection. While past studies demonstrate the preservation of real-world features such as size and distance during mental simulation, their temporal dynamics remains unknown. Here, we compare mental simulations to navigation of routes in a large-scale spatial environment to test the hypothesis that such simulations are temporally compressed in an adaptive manner. Our results show that simulations occurred at 2.39x the speed it took to navigate a route, increasing in compression (3.57x) for slower movement speeds. Participant self-reports of vividness and spatial coherence of simulations also correlated strongly with simulation duration, providing an important link between subjective experiences of simulated events and how spatial representations are combined during prospection. These findings suggest that simulation of spatial events involve adaptive temporal mechanisms, mediated partly by the fidelity of memories used to generate the simulation. PMID:27568586

Practical low-cost visual communication using binary images for deaf sign language.

PubMed

Manoranjan, M D; Robinson, J A

2000-03-01

Deaf sign language transmitted by video requires a temporal resolution of 8 to 10 frames/s for effective communication. Conventional videoconferencing applications, when operated over low bandwidth telephone lines, provide very low temporal resolution of pictures, of the order of less than a frame per second, resulting in jerky movement of objects. This paper presents a practical solution for sign language communication, offering adequate temporal resolution of images using moving binary sketches or cartoons, implemented on standard personal computer hardware with low-cost cameras and communicating over telephone lines. To extract cartoon points an efficient feature extraction algorithm adaptive to the global statistics of the image is proposed. To improve the subjective quality of the binary images, irreversible preprocessing techniques, such as isolated point removal and predictive filtering, are used. A simple, efficient and fast recursive temporal prefiltering scheme, using histograms of successive frames, reduces the additive and multiplicative noise from low-cost cameras. An efficient three-dimensional (3-D) compression scheme codes the binary sketches. Subjective tests performed on the system confirm that it can be used for sign language communication over telephone lines.

Are mastery and ability goals both adaptive? Evaluation, initial goal construction and the quality of task engagement.

PubMed

Butler, Ruth

2006-09-01

The aims of this research were to examine the predictions that (a) the kind of evaluation pupils anticipate will influence their initial achievement goals and, as a result, the quality and consequences of task engagement; and (b) initial mastery goals will promote new learning and intrinsic motivation and initial ability goals will promote entity beliefs that ability is fixed. Participants were 312 secondary school pupils at ages 13-15. Pupils expected to receive normative evaluation, temporal evaluation (scores over time) or no evaluation. Mastery and ability goals were measured before pupils worked on challenging problems; intrinsic motivation and entity beliefs were measured after task completion. Anticipation of temporal evaluation enhanced initial mastery goals, anticipation of normative evaluation enhanced ability goals and the no-evaluation condition undermined both. Anticipation of temporal evaluation enhanced new learning (strategy acquisition and performance gains) and intrinsic motivation both directly and by enhancing initial mastery goals; anticipation of normative evaluation enhanced entity beliefs by enhancing ability goals. Results confirmed that evaluation conveys potent cues as to the goals of activity. They also challenged claims that both mastery and ability goals can be adaptive by demonstrating that these were differentially associated with positive versus negative processes and outcomes. Results have theoretical and applied implications for understanding and improving evaluative practices and student motivation.

An Improved STARFM with Help of an Unmixing-Based Method to Generate High Spatial and Temporal Resolution Remote Sensing Data in Complex Heterogeneous Regions.

PubMed

Xie, Dengfeng; Zhang, Jinshui; Zhu, Xiufang; Pan, Yaozhong; Liu, Hongli; Yuan, Zhoumiqi; Yun, Ya

2016-02-05

Remote sensing technology plays an important role in monitoring rapid changes of the Earth's surface. However, sensors that can simultaneously provide satellite images with both high temporal and spatial resolution haven't been designed yet. This paper proposes an improved spatial and temporal adaptive reflectance fusion model (STARFM) with the help of an Unmixing-based method (USTARFM) to generate the high spatial and temporal data needed for the study of heterogeneous areas. The results showed that the USTARFM had higher accuracy than STARFM methods in two aspects of analysis: individual bands and of heterogeneity analysis. Taking the predicted NIR band as an example, the correlation coefficients (r) for the USTARFM, STARFM and unmixing methods were 0.96, 0.95, 0.90, respectively (p-value < 0.001); Root Mean Square Error (RMSE) values were 0.0245, 0.0300, 0.0401, respectively; and ERGAS values were 0.5416, 0.6507, 0.8737, respectively. The USTARM showed consistently higher performance than STARM when the degree of heterogeneity ranged from 2 to 10, highlighting that the use of this method provides the capacity to solve the data fusion problems faced when using STARFM. Additionally, the USTARFM method could help researchers achieve better performance than STARFM at a smaller window size from its heterogeneous land surface quantitative representation.

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

Crimp, Steven; Jin, Huidong; Kokic, Philip; Bakar, Shuvo; Nicholls, Neville

2018-04-01

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation.

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.

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex.

PubMed

McLelland, Douglas; Baker, Pamela M; Ahmed, Bashir; Kohn, Adam; Bair, Wyeth

2015-07-15

A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components. Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales. Copyright © 2015 the authors 0270-6474/15/3510268-13$15.00/0.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Adaptive filtering and maximum entropy spectra with application to changes in atmospheric angular momentum

NASA Technical Reports Server (NTRS)

Penland, Cecile; Ghil, Michael; Weickmann, Klaus M.

1991-01-01

The spectral resolution and statistical significance of a harmonic analysis obtained by low-order MEM can be improved by subjecting the data to an adaptive filter. This adaptive filter consists of projecting the data onto the leading temporal empirical orthogonal functions obtained from singular spectrum analysis (SSA). The combined SSA-MEM method is applied both to a synthetic time series and a time series of AAM data. The procedure is very effective when the background noise is white and less so when the background noise is red. The latter case obtains in the AAM data. Nevertheless, reliable evidence for intraseasonal and interannual oscillations in AAM is detected. The interannual periods include a quasi-biennial one and an LF one, of 5 years, both related to the El Nino/Southern Oscillation. In the intraseasonal band, separate oscillations of about 48.5 and 51 days are ascertained.

Adaptive Hierarchical Voltage Control of a DFIG-Based Wind Power Plant for a Grid Fault

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

Kim, Jinho; Muljadi, Eduard; Park, Jung-Wook

This paper proposes an adaptive hierarchical voltage control scheme of a doubly-fed induction generator (DFIG)-based wind power plant (WPP) that can secure more reserve of reactive power (Q) in the WPP against a grid fault. To achieve this, each DFIG controller employs an adaptive reactive power to voltage (Q-V) characteristic. The proposed adaptive Q-V characteristic is temporally modified depending on the available Q capability of a DFIG; it is dependent on the distance from a DFIG to the point of common coupling (PCC). The proposed characteristic secures more Q reserve in the WPP than the fixed one. Furthermore, it allowsmore » DFIGs to promptly inject up to the Q limit, thereby improving the PCC voltage support. To avert an overvoltage after the fault clearance, washout filters are implemented in the WPP and DFIG controllers; they can prevent a surplus Q injection after the fault clearance by eliminating the accumulated values in the proportional-integral controllers of both controllers during the fault. Test results demonstrate that the scheme can improve the voltage support capability during the fault and suppress transient overvoltage after the fault clearance under scenarios of various system and fault conditions; therefore, it helps ensure grid resilience by supporting the voltage stability.« less

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system

PubMed Central

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902

Stable Short-Term Frequency Support Using Adaptive Gains for a DFIG-Based Wind Power Plant

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

Lee, Jinsik; Jang, Gilsoo; Muljadi, Eduard

For the fixed-gain inertial control of wind power plants (WPPs), a large gain setting provides a large contribution to supporting system frequency control, but it may cause over-deceleration for a wind turbine generator that has a small amount of kinetic energy (KE). Further, if the wind speed decreases during inertial control, even a small gain may cause over-deceleration. This paper proposes a stable inertial control scheme using adaptive gains for a doubly fed induction generator (DFIG)-based WPP. The scheme aims to improve the frequency nadir (FN) while ensuring stable operation of all DFIGs, particularly when the wind speed decreases duringmore » inertial control. In this scheme, adaptive gains are set to be proportional to the KE stored in DFIGs, which is spatially and temporally dependent. To improve the FN, upon detecting an event, large gains are set to be proportional to the KE of DFIGs; to ensure stable operation, the gains decrease with the declining KE. The simulation results demonstrate that the scheme improves the FN while ensuring stable operation of all DFIGs in various wind and system conditions. Further, it prevents over-deceleration even when the wind speed decreases during inertial control.« less

A novel spatial-temporal detection method of dim infrared moving small target

NASA Astrophysics Data System (ADS)

Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

2014-09-01

Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability.

PubMed

Wu, Howard G; Miyamoto, Yohsuke R; Gonzalez Castro, Luis Nicolas; Ölveczky, Bence P; Smith, Maurice A

2014-02-01

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning.

Behavioral demand modulates object category representation in the inferior temporal cortex

PubMed Central

Emadi, Nazli

2014-01-01

Visual object categorization is a critical task in our daily life. Many studies have explored category representation in the inferior temporal (IT) cortex at the level of single neurons and population. However, it is not clear how behavioral demands modulate this category representation. Here, we recorded from the IT single neurons in monkeys performing two different tasks with identical visual stimuli: passive fixation and body/object categorization. We found that category selectivity of the IT neurons was improved in the categorization compared with the passive task where reward was not contingent on image category. The category improvement was the result of larger rate enhancement for the preferred category and smaller response variability for both preferred and nonpreferred categories. These specific modulations in the responses of IT category neurons enhanced signal-to-noise ratio of the neural responses to discriminate better between the preferred and nonpreferred categories. Our results provide new insight into the adaptable category representation in the IT cortex, which depends on behavioral demands. PMID:25080572

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability

PubMed Central

Wu, Howard G; Miyamoto, Yohsuke R; Castro, Luis Nicolas Gonzalez; Ölveczky, Bence P; Smith, Maurice A

2015-01-01

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning. PMID:24413700

A fast BK-type KCa current acts as a postsynaptic modulator of temporal selectivity for communication signals.

PubMed

Kohashi, Tsunehiko; Carlson, Bruce A

2014-01-01

Temporal patterns of spiking often convey behaviorally relevant information. Various synaptic mechanisms and intrinsic membrane properties can influence neuronal selectivity to temporal patterns of input. However, little is known about how synaptic mechanisms and intrinsic properties together determine the temporal selectivity of neuronal output. We tackled this question by recording from midbrain electrosensory neurons in mormyrid fish, in which the processing of temporal intervals between communication signals can be studied in a reduced in vitro preparation. Mormyrids communicate by varying interpulse intervals (IPIs) between electric pulses. Within the midbrain posterior exterolateral nucleus (ELp), the temporal patterns of afferent spike trains are filtered to establish single-neuron IPI tuning. We performed whole-cell recording from ELp neurons in a whole-brain preparation and examined the relationship between intrinsic excitability and IPI tuning. We found that spike frequency adaptation of ELp neurons was highly variable. Postsynaptic potentials (PSPs) of strongly adapting (phasic) neurons were more sharply tuned to IPIs than weakly adapting (tonic) neurons. Further, the synaptic filtering of IPIs by tonic neurons was more faithfully converted into variation in spiking output, particularly at short IPIs. Pharmacological manipulation under current- and voltage-clamp revealed that tonic firing is mediated by a fast, large-conductance Ca(2+)-activated K(+) (KCa) current (BK) that speeds up action potential repolarization. These results suggest that BK currents can shape the temporal filtering of sensory inputs by modifying both synaptic responses and PSP-to-spike conversion. Slow SK-type KCa currents have previously been implicated in temporal processing. Thus, both fast and slow KCa currents can fine-tune temporal selectivity.

Cerebellum, temporal predictability and the updating of a mental model.

PubMed

Kotz, Sonja A; Stockert, Anika; Schwartze, Michael

2014-12-19

We live in a dynamic and changing environment, which necessitates that we adapt to and efficiently respond to changes of stimulus form ('what') and stimulus occurrence ('when'). Consequently, behaviour is optimal when we can anticipate both the 'what' and 'when' dimensions of a stimulus. For example, to perceive a temporally expected stimulus, a listener needs to establish a fairly precise internal representation of its external temporal structure, a function ascribed to classical sensorimotor areas such as the cerebellum. Here we investigated how patients with cerebellar lesions and healthy matched controls exploit temporal regularity during auditory deviance processing. We expected modulations of the N2b and P3b components of the event-related potential in response to deviant tones, and also a stronger P3b response when deviant tones are embedded in temporally regular compared to irregular tone sequences. We further tested to what degree structural damage to the cerebellar temporal processing system affects the N2b and P3b responses associated with voluntary attention to change detection and the predictive adaptation of a mental model of the environment, respectively. Results revealed that healthy controls and cerebellar patients display an increased N2b response to deviant tones independent of temporal context. However, while healthy controls showed the expected enhanced P3b response to deviant tones in temporally regular sequences, the P3b response in cerebellar patients was significantly smaller in these sequences. The current data provide evidence that structural damage to the cerebellum affects the predictive adaptation to the temporal structure of events and the updating of a mental model of the environment under voluntary attention. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Cerebellum, temporal predictability and the updating of a mental model

PubMed Central

Kotz, Sonja A.; Stockert, Anika; Schwartze, Michael

2014-01-01

We live in a dynamic and changing environment, which necessitates that we adapt to and efficiently respond to changes of stimulus form (‘what’) and stimulus occurrence (‘when’). Consequently, behaviour is optimal when we can anticipate both the ‘what’ and ‘when’ dimensions of a stimulus. For example, to perceive a temporally expected stimulus, a listener needs to establish a fairly precise internal representation of its external temporal structure, a function ascribed to classical sensorimotor areas such as the cerebellum. Here we investigated how patients with cerebellar lesions and healthy matched controls exploit temporal regularity during auditory deviance processing. We expected modulations of the N2b and P3b components of the event-related potential in response to deviant tones, and also a stronger P3b response when deviant tones are embedded in temporally regular compared to irregular tone sequences. We further tested to what degree structural damage to the cerebellar temporal processing system affects the N2b and P3b responses associated with voluntary attention to change detection and the predictive adaptation of a mental model of the environment, respectively. Results revealed that healthy controls and cerebellar patients display an increased N2b response to deviant tones independent of temporal context. However, while healthy controls showed the expected enhanced P3b response to deviant tones in temporally regular sequences, the P3b response in cerebellar patients was significantly smaller in these sequences. The current data provide evidence that structural damage to the cerebellum affects the predictive adaptation to the temporal structure of events and the updating of a mental model of the environment under voluntary attention. PMID:25385781

Video quality pooling adaptive to perceptual distortion severity.

PubMed

Park, Jincheol; Seshadrinathan, Kalpana; Lee, Sanghoon; Bovik, Alan Conrad

2013-02-01

It is generally recognized that severe video distortions that are transient in space and/or time have a large effect on overall perceived video quality. In order to understand this phenomena, we study the distribution of spatio-temporally local quality scores obtained from several video quality assessment (VQA) algorithms on videos suffering from compression and lossy transmission over communication channels. We propose a content adaptive spatial and temporal pooling strategy based on the observed distribution. Our method adaptively emphasizes "worst" scores along both the spatial and temporal dimensions of a video sequence and also considers the perceptual effect of large-area cohesive motion flow such as egomotion. We demonstrate the efficacy of the method by testing it using three different VQA algorithms on the LIVE Video Quality database and the EPFL-PoliMI video quality database.

Anomalous brain functional connectivity contributing to poor adaptive behavior in Down syndrome.

PubMed

Pujol, Jesus; del Hoyo, Laura; Blanco-Hinojo, Laura; de Sola, Susana; Macià, Dídac; Martínez-Vilavella, Gerard; Amor, Marta; Deus, Joan; Rodríguez, Joan; Farré, Magí; Dierssen, Mara; de la Torre, Rafael

2015-03-01

Research in Down syndrome has substantially progressed in the understanding of the effect of gene overexpression at the molecular level, but there is a paucity of information on the ultimate consequences on overall brain functional organization. We have assessed the brain functional status in Down syndrome using functional connectivity MRI. Resting-state whole-brain connectivity degree maps were generated in 20 Down syndrome individuals and 20 control subjects to identify sites showing anomalous synchrony with other areas. A subsequent region-of-interest mapping served to detail the anomalies and to assess their potential contribution to poor adaptive behavior. Down syndrome individuals showed higher regional connectivity in a ventral brain system involving the amygdala/anterior temporal region and the ventral aspect of both the anterior cingulate and frontal cortices. By contrast, lower functional connectivity was identified in dorsal executive networks involving dorsal prefrontal and anterior cingulate cortices and posterior insula. Both functional connectivity increases and decreases contributed to account for patient scoring on adaptive behavior related to communication skills. The data overall suggest a distinctive functional organization with system-specific anomalies associated with reduced adaptive efficiency. Opposite effects were identified on distinct frontal and anterior temporal structures and relative sparing of posterior brain areas, which is generally consistent with Down syndrome cognitive profile. Relevantly, measurable connectivity changes, as a marker of the brain functional anomaly, could have a role in the development of therapeutic strategies addressed to improve the quality of life in Down syndrome individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spatial and temporal aspects of chromatic adaptation and their functional significance for colour constancy.

PubMed

Werner, Annette

2014-11-01

Illumination in natural scenes changes at multiple temporal and spatial scales: slow changes in global illumination occur in the course of a day, and we encounter fast and localised illumination changes when visually exploring the non-uniform light field of three-dimensional scenes; in addition, very long-term chromatic variations may come from the environment, like for example seasonal changes. In this context, I consider the temporal and spatial properties of chromatic adaptation and discuss their functional significance for colour constancy in three-dimensional scenes. A process of fast spatial tuning in chromatic adaptation is proposed as a possible sensory mechanism for linking colour constancy to the spatial structure of a scene. The observed middlewavelength selectivity of this process is particularly suitable for adaptation to the mean chromaticity and the compensation of interreflections in natural scenes. Two types of sensory colour constancy are distinguished, based on the functional differences of their temporal and spatial scales: a slow type, operating at a global scale for the compensation of the ambient illumination; and a fast colour constancy, which is locally restricted and well suited to compensate region-specific variations in the light field of three dimensional scenes. Copyright © 2014 Elsevier B.V. All rights reserved.

Temporal dynamics of contrast gain in single cells of the cat striate cortex.

PubMed

Bonds, A B

1991-03-01

The response amplitude of cat striate cortical cells is usually reduced after exposure to high-contrast stimuli. The temporal characteristics and contrast sensitivity of this phenomenon were explored by stimulating cortical cells with drifting gratings in which contrast sequentially incremented and decremented in stepwise fashion over time. All responses showed a clear hysteresis, in which contrast gain dropped on average 0.36 log unit and then returned to baseline values within 60 s. Noticeable gain adjustments were seen in as little as 3 s and with peak contrasts as low as 3%. Contrast adaptation was absent in responses from LGN cells. Adaptation was found to depend on temporal frequency of stimulation, with greater and more rapid adaptation at higher temporal frequencies. Two different tests showed that the mechanism controlling response reduction was influenced primarily by stimulus contrast rather than response amplitude. These results support the existence of a rapid and sensitive cortically based system that normalizes the output of cortical cells as a function of local mean contrast. Control of the adaptation appears to arise at least in part across a population of cells, which is consistent with the idea that the gain control serves to limit the information converging from many cells onto subsequent processing areas.

Light and dark adaptation mechanisms in the compound eyes of Myrmecia ants that occupy discrete temporal niches.

PubMed

Narendra, Ajay; Greiner, Birgit; Ribi, Willi A; Zeil, Jochen

2016-08-15

Ants of the Australian genus Myrmecia partition their foraging niche temporally, allowing them to be sympatric with overlapping foraging requirements. We used histological techniques to study the light and dark adaptation mechanisms in the compound eyes of diurnal (Myrmecia croslandi), crepuscular (M. tarsata, M. nigriceps) and nocturnal ants (M. pyriformis). We found that, except in the day-active species, all ants have a variable primary pigment cell pupil that constricts the crystalline cone in bright light to control for light flux. We show for the nocturnal M. pyriformis that the constriction of the crystalline cone by the primary pigment cells is light dependent whereas the opening of the aperture is regulated by an endogenous rhythm. In addition, in the light-adapted eyes of all species, the retinular cell pigment granules radially migrate towards the rhabdom, a process that in both the day-active M. croslandi and the night-active M. pyriformis is driven by ambient light intensity. Visual system properties thus do not restrict crepuscular and night-active ants to their temporal foraging niche, while day-active ants require high light intensities to operate. We discuss the ecological significance of these adaptation mechanisms and their role in temporal niche partitioning. © 2016. Published by The Company of Biologists Ltd.

Thirty years of use and improvement of remote sensing, applied to epidemiology: from early promises to lasting frustration.

PubMed

Herbreteau, Vincent; Salem, Gérard; Souris, Marc; Hugot, Jean-Pierre; Gonzalez, Jean-Paul

2007-06-01

Remote sensing, referring to the remote study of objects, was originally developed for Earth observation, through the use of sensors on board planes or satellites. Improvements in the use and accessibility of multi-temporal satellite-derived environmental data have, for 30 years, contributed to a growing use in epidemiology. Despite the potential of remote-sensed images and processing techniques for a better knowledge of disease dynamics, an exhaustive analysis of the bibliography shows a generalized use of pre-processed spatial data and low-cost images, resulting in a limited adaptability when addressing biological questions.

An Advanced simulation Code for Modeling Inductive Output Tubes

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

Thuc Bui; R. Lawrence Ives

2012-04-27

During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing currentmore » density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.« less

A high speed multifocal multiphoton fluorescence lifetime imaging microscope for live-cell FRET imaging

PubMed Central

Poland, Simon P.; Krstajić, Nikola; Monypenny, James; Coelho, Simao; Tyndall, David; Walker, Richard J.; Devauges, Viviane; Richardson, Justin; Dutton, Neale; Barber, Paul; Li, David Day-Uei; Suhling, Klaus; Ng, Tony; Henderson, Robert K.; Ameer-Beg, Simon M.

2015-01-01

We demonstrate diffraction limited multiphoton imaging in a massively parallel, fully addressable time-resolved multi-beam multiphoton microscope capable of producing fluorescence lifetime images with sub-50ps temporal resolution. This imaging platform offers a significant improvement in acquisition speed over single-beam laser scanning FLIM by a factor of 64 without compromising in either the temporal or spatial resolutions of the system. We demonstrate FLIM acquisition at 500 ms with live cells expressing green fluorescent protein. The applicability of the technique to imaging protein-protein interactions in live cells is exemplified by observation of time-dependent FRET between the epidermal growth factor receptor (EGFR) and the adapter protein Grb2 following stimulation with the receptor ligand. Furthermore, ligand-dependent association of HER2-HER3 receptor tyrosine kinases was observed on a similar timescale and involved the internalisation and accumulation or receptor heterodimers within endosomes. These data demonstrate the broad applicability of this novel FLIM technique to the spatio-temporal dynamics of protein-protein interaction. PMID:25780724

Time scale matters: genetic analysis does not support adaptation-by-time as the mechanism for adaptive seasonal declines in kokanee reproductive life span

PubMed Central

Morbey, Yolanda E; Jensen, Evelyn L; Russello, Michael A

2014-01-01

Seasonal declines of fitness-related traits are often attributed to environmental effects or individual-level decisions about reproductive timing and effort, but genetic variation may also play a role. In populations of Pacific salmon (Oncorhynchus spp.), seasonal declines in reproductive life span have been attributed to adaptation-by-time, in which divergent selection for different traits occurs among reproductively isolated temporal components of a population. We evaluated this hypothesis in kokanee (freshwater obligate Oncorhynchus nerka) by testing for temporal genetic structure in neutral and circadian-linked loci. We detected no genetic differences in presumably neutral loci among kokanee with different arrival and maturation dates within a spawning season. Similarly, we detected no temporal genetic structure in OtsClock1b, Omy1009uw, or OmyFbxw11, candidate loci associated with circadian function. The genetic evidence from this study and others indicates a lack of support for adaptation-by-time as an important evolutionary mechanism underlying seasonal declines in reproductive life span and a need for greater consideration of other mechanisms such as time-dependent, adaptive adjustment of reproductive effort. PMID:25478160

Adaptive OFDM Radar Waveform Design for Improved Micro-Doppler Estimation

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

Sen, Satyabrata

Here we analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a rotating target having multiple scattering centers. The use of a frequency-diverse OFDM signal enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. We characterize the accuracy of micro-Doppler frequency estimation by computing the Cramer-Rao bound (CRB) on the angular-velocity estimate of the target. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to themore » OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations with respect to the signal-to-noise ratios, number of temporal samples, and number of OFDM subcarriers. We also analysed numerically the improvement in estimation accuracy due to the adaptive waveform design. A grid-based maximum likelihood estimation technique is applied to evaluate the corresponding mean-squared error performance.« less

Trends in measurement of solar vector magnetic fields using the Zeeman effect

NASA Technical Reports Server (NTRS)

Harvey, J. W.

1985-01-01

Trends in spectropolarimetry as applied to the problem of Zeeman effect measurement are discussed. The use of detector arrays to improve observing efficiency is obtained. Which required new polarization modulation schemes that match the time required to read detector arrays. Another significant trend is narrowband filters, to improve angular and temporal coverage, and to Fourier transform spectrometers, to improve spectral coverage and precision. Low-polarization designs and improved methods for compensating instrumental polarization were developed. A requirement for high angular resolution suggests using adaptive optical devices to subdue the effects of bad seeing. The ultimate strategy to beat the seeing is to loft the telescope above the atmosphere such as is planned with a 30-cm telescope in 1985 and a 1250-cm telescope in 1990.

Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO

NASA Astrophysics Data System (ADS)

Gao, Zhen; Dai, Linglong; Wang, Zhaocheng; Chen, Sheng

2015-12-01

This paper proposes a spatially common sparsity based adaptive channel estimation and feedback scheme for frequency division duplex based massive multi-input multi-output (MIMO) systems, which adapts training overhead and pilot design to reliably estimate and feed back the downlink channel state information (CSI) with significantly reduced overhead. Specifically, a non-orthogonal downlink pilot design is first proposed, which is very different from standard orthogonal pilots. By exploiting the spatially common sparsity of massive MIMO channels, a compressive sensing (CS) based adaptive CSI acquisition scheme is proposed, where the consumed time slot overhead only adaptively depends on the sparsity level of the channels. Additionally, a distributed sparsity adaptive matching pursuit algorithm is proposed to jointly estimate the channels of multiple subcarriers. Furthermore, by exploiting the temporal channel correlation, a closed-loop channel tracking scheme is provided, which adaptively designs the non-orthogonal pilot according to the previous channel estimation to achieve an enhanced CSI acquisition. Finally, we generalize the results of the multiple-measurement-vectors case in CS and derive the Cramer-Rao lower bound of the proposed scheme, which enlightens us to design the non-orthogonal pilot signals for the improved performance. Simulation results demonstrate that the proposed scheme outperforms its counterparts, and it is capable of approaching the performance bound.

Spatiotemporal variation in local adaptation of a specialist insect herbivore to its long-lived host plant.

PubMed

Kalske, Aino; Leimu, Roosa; Scheepens, J F; Mutikainen, Pia

2016-09-01

Local adaptation of interacting species to one another indicates geographically variable reciprocal selection. This process of adaptation is central in the organization and maintenance of genetic variation across populations. Given that the strength of selection and responses to it often vary in time and space, the strength of local adaptation should in theory vary between generations and among populations. However, such spatiotemporal variation has rarely been explicitly demonstrated in nature and local adaptation is commonly considered to be relatively static. We report persistent local adaptation of the short-lived herbivore Abrostola asclepiadis to its long-lived host plant Vincetoxicum hirundinaria over three successive generations in two studied populations and considerable temporal variation in local adaptation in six populations supporting the geographic mosaic theory. The observed variation in local adaptation among populations was best explained by geographic distance and population isolation, suggesting that gene flow reduces local adaptation. Changes in herbivore population size did not conclusively explain temporal variation in local adaptation. Our results also imply that short-term studies are likely to capture only a part of the existing variation in local adaptation. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Adaptation, plant evolution, and the fossil record

NASA Technical Reports Server (NTRS)

Knoll, A. H.; Niklas, K. J.

1987-01-01

The importance of adaptation in determining patterns of evolution has become an important focus of debate in evolutionary biology. As it pertains to paleobotany, the issue is whether or not adaptive evolution mediated by natural selection is sufficient to explain the stratigraphic distributions of taxa and character states observed in the plant fossil record. One means of addressing this question is the functional evaluation of stratigraphic series of plant organs set in the context of paleoenvironmental change and temporal patterns of floral composition within environments. For certain organ systems, quantitative estimates of biophysical performance can be made on the basis of structures preserved in the fossil record. Performance estimates for plants separated in time or space can be compared directly. Implicit in different hypotheses of the forces that shape the evolutionary record (e.g. adaptation, mass extinction, rapid environmental change, chance) are predictions about stratigraphic and paleoenvironmental trends in the efficacy of functional performance. Existing data suggest that following the evolution of a significant structural innovation, adaptation for improved functional performance can be a major determinant of evolutionary changes in plants; however, there are structural and development limits to functional improvement, and once these are reached, the structure in question may no longer figure strongly in selection until and unless a new innovation evolves. The Silurian-Devonian paleobotanical record is consistent with the hypothesis that the succession of lowland floodplain dominants preserved in the fossil record of this interval was determined principally by the repeated evolution of new taxa that rose to ecological importance because of competitive advantages conferred by improved biophysical performance. This does not seem to be equally true for Carboniferous-Jurassic dominants of swamp and lowland floodplain environments. In these cases, environmental disruption appears to have been a major factor in shaping the fossil record. This does not mean that continuing adaptation was not important during this interval, but it may indicate that adaptive evolution was strongest in environments other than those best represented in the paleobotanical record.

Adaptation, plant evolution, and the fossil record.

PubMed

Knoll, A H; Niklas, K J

1987-01-01

The importance of adaptation in determining patterns of evolution has become an important focus of debate in evolutionary biology. As it pertains to paleobotany, the issue is whether or not adaptive evolution mediated by natural selection is sufficient to explain the stratigraphic distributions of taxa and character states observed in the plant fossil record. One means of addressing this question is the functional evaluation of stratigraphic series of plant organs set in the context of paleoenvironmental change and temporal patterns of floral composition within environments. For certain organ systems, quantitative estimates of biophysical performance can be made on the basis of structures preserved in the fossil record. Performance estimates for plants separated in time or space can be compared directly. Implicit in different hypotheses of the forces that shape the evolutionary record (e.g. adaptation, mass extinction, rapid environmental change, chance) are predictions about stratigraphic and paleoenvironmental trends in the efficacy of functional performance. Existing data suggest that following the evolution of a significant structural innovation, adaptation for improved functional performance can be a major determinant of evolutionary changes in plants; however, there are structural and development limits to functional improvement, and once these are reached, the structure in question may no longer figure strongly in selection until and unless a new innovation evolves. The Silurian-Devonian paleobotanical record is consistent with the hypothesis that the succession of lowland floodplain dominants preserved in the fossil record of this interval was determined principally by the repeated evolution of new taxa that rose to ecological importance because of competitive advantages conferred by improved biophysical performance. This does not seem to be equally true for Carboniferous-Jurassic dominants of swamp and lowland floodplain environments. In these cases, environmental disruption appears to have been a major factor in shaping the fossil record. This does not mean that continuing adaptation was not important during this interval, but it may indicate that adaptive evolution was strongest in environments other than those best represented in the paleobotanical record.

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

NASA Astrophysics Data System (ADS)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2017-06-01

The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

Intercepting moving targets: does memory from practice in a specific condition of target displacement affect movement timing?

PubMed

de Azevedo Neto, Raymundo Machado; Teixeira, Luis Augusto

2011-05-01

This investigation aimed at assessing the extent to which memory from practice in a specific condition of target displacement modulates temporal errors and movement timing of interceptive movements. We compared two groups practicing with certainty of future target velocity either in unchanged target velocity or in target velocity decrease. Following practice, both experimental groups were probed in the situations of unchanged target velocity and target velocity decrease either under the context of certainty or uncertainty about target velocity. Results from practice showed similar improvement of temporal accuracy between groups, revealing that target velocity decrease did not disturb temporal movement organization when fully predictable. Analysis of temporal errors in the probing trials indicated that both groups had higher timing accuracy in velocity decrease in comparison with unchanged velocity. Effect of practice was detected by increased temporal accuracy of the velocity decrease group in situations of decreased velocity; a trend consistent with the expected effect of practice was observed for temporal errors in the unchanged velocity group and in movement initiation at a descriptive level. An additional point of theoretical interest was the fast adaptation in both groups to a target velocity pattern different from that practiced. These points are discussed under the perspective of integration of vision and motor control by means of an internal forward model of external motion.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

In-situ Chemical Exploration and Mapping using an Autonomous Underwater Vehicle

NASA Astrophysics Data System (ADS)

Camilli, R.; Bingham, B. S.; Jakuba, M.; Whelan, J.; Singh, H.; Whiticar, M.

2004-12-01

Recent advances in in-situ chemical sensing have emphasized several issues associated with making reliable chemical measurements in the ocean. Such measurements are often aliased temporally and or spatially, and may suffer from instrumentation artifacts, such as slow response time, limited dynamic range, hysteresis, and environmental sensitivities (eg., temperature and pressure). We focus on the in-situ measurement of light hydrocarbons. Specifically we examine data collected using a number of methods including: a vertical profiler, autonomous underwater vehicles (AUV) surveys, and adaptive spatio-temporal survey techniques. We present data collected using a commercial METS sensor on a vertical profiler to identify and map structures associated with ocean bottom methane sources in the Saanich inlet off Vancouver, Canada. This sensor was deployed in parallel with a submersible mass spectrometer and a shipboard equilibrator-gas chromatograph. Our results illustrate that spatial offsets as small as centimeters can produce significant differences in measured concentration. In addition, differences in response times between instruments can also alias the measurements. The results of this preliminary experiment underscore the challenges of quantifying ocean chemical processes with small-scale spatial variability and temporal variability that is often faster than the response times of many available instruments. We explore the capabilities and current limitations of autonomous underwater vehicles for extending the spatial coverage of new in-situ sensor technologies. We present data collected from deployments of Seabed, a passively stable, hover capable AUV, at large-scale gas blowout features located along the U.S. Atlantic margin. Although these deployments successfully revealed previously unobservable oceanographic processes, temporal aliasing caused by sensor response as well as tidal variability manifests itself, illustrating the possibilities for misinterpretation of localized periodic anomalies. Finally we present results of recent experimental chemical plume mapping surveys that were conducted off the coast of Massachusetts using adaptive behaviors that allow the AUV to optimize its mission plan to autonomously search for chemical anomalies. This adaptive operation is based on coupling the chemical sensor payload within a closed-loop architecture with the vehicle's navigation control system for real-time autonomous data assimilation and decision making processes. This allows the vehicle to autonomously refine the search strategy, thereby improving feature localization capabilities and enabling surveys at an appropriate temporal and spatial resolution.

A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng

2016-05-01

Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a range of plant development stages. Overall, STEM-LAI represents an effective downscaling and temporal enhancement mechanism that predicts in-situ measured LAI better than estimates derived through linear interpolation between Landsat acquisitions. This is particularly true when the in-situ measurement date is greater than 10 days from the nearest Landsat acquisition, with prediction errors reduced by up to 50%. With a streamlined and completely automated processing interface, STEM-LAI represents a flexible tool for LAI disaggregation in space and time that is adaptable to different land cover types, landscape heterogeneities, and cloud cover conditions.

Temporal Coordination and Adaptation to Rate Change in Music Performance

ERIC Educational Resources Information Center

Loehr, Janeen D.; Large, Edward W.; Palmer, Caroline

2011-01-01

People often coordinate their actions with sequences that exhibit temporal variability and unfold at multiple periodicities. We compared oscillator- and timekeeper-based accounts of temporal coordination by examining musicians' coordination of rhythmic musical sequences with a metronome that gradually changed rate at the end of a musical phrase…

Temporal Effects of Alignment in Text-Based, Task-Oriented Discourse

ERIC Educational Resources Information Center

Foltz, Anouschka; Gaspers, Judith; Meyer, Carolin; Thiele, Kristina; Cimiano, Philipp; Stenneken, Prisca

2015-01-01

Communicative alignment refers to adaptation to one's communication partner. Temporal aspects of such alignment have been little explored. This article examines temporal aspects of lexical and syntactic alignment (i.e., tendencies to use the interlocutor's lexical items and syntactic structures) in task-oriented discourse. In particular, we…

Temporal Effects on Monaural Amplitude-Modulation Sensitivity in Ipsilateral, Contralateral and Bilateral Noise.

PubMed

Marrufo-Pérez, Miriam I; Eustaquio-Martín, Almudena; López-Bascuas, Luis E; Lopez-Poveda, Enrique A

2018-04-01

The amplitude modulations (AMs) in speech signals are useful cues for speech recognition. Several adaptation mechanisms may make the detection of AM in noisy backgrounds easier when the AM carrier is presented later rather than earlier in the noise. The aim of the present study was to characterize temporal adaptation to noise in AM detection. AM detection thresholds were measured for monaural (50 ms, 1.5 kHz) pure-tone carriers presented at the onset ('early' condition) and 300 ms after the onset ('late' condition) of ipsilateral, contralateral, and bilateral (diotic) broadband noise, as well as in quiet. Thresholds were 2-4 dB better in the late than in the early condition for the three noise lateralities. The temporal effect held for carriers at equal sensation levels, confirming that it was not due to overshoot on carrier audibility. The temporal effect was larger for broadband than for low-band contralateral noises. Many aspects in the results were consistent with the noise activating the medial olivocochlear reflex (MOCR) and enhancing AM depth in the peripheral auditory response. Other aspects, however, indicate that central masking and adaptation unrelated to the MOCR also affect both carrier-tone and AM detection and are involved in the temporal effects.

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

The role of multisensory interplay in enabling temporal expectations.

PubMed

Ball, Felix; Michels, Lara E; Thiele, Carsten; Noesselt, Toemme

2018-01-01

Temporal regularities can guide our attention to focus on a particular moment in time and to be especially vigilant just then. Previous research provided evidence for the influence of temporal expectation on perceptual processing in unisensory auditory, visual, and tactile contexts. However, in real life we are often exposed to a complex and continuous stream of multisensory events. Here we tested - in a series of experiments - whether temporal expectations can enhance perception in multisensory contexts and whether this enhancement differs from enhancements in unisensory contexts. Our discrimination paradigm contained near-threshold targets (subject-specific 75% discrimination accuracy) embedded in a sequence of distractors. The likelihood of target occurrence (early or late) was manipulated block-wise. Furthermore, we tested whether spatial and modality-specific target uncertainty (i.e. predictable vs. unpredictable target position or modality) would affect temporal expectation (TE) measured with perceptual sensitivity (d ' ) and response times (RT). In all our experiments, hidden temporal regularities improved performance for expected multisensory targets. Moreover, multisensory performance was unaffected by spatial and modality-specific uncertainty, whereas unisensory TE effects on d ' but not RT were modulated by spatial and modality-specific uncertainty. Additionally, the size of the temporal expectation effect, i.e. the increase in perceptual sensitivity and decrease of RT, scaled linearly with the likelihood of expected targets. Finally, temporal expectation effects were unaffected by varying target position within the stream. Together, our results strongly suggest that participants quickly adapt to novel temporal contexts, that they benefit from multisensory (relative to unisensory) stimulation and that multisensory benefits are maximal if the stimulus-driven uncertainty is highest. We propose that enhanced informational content (i.e. multisensory stimulation) enables the robust extraction of temporal regularities which in turn boost (uni-)sensory representations. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Adaptation of gastrointestinal nematode parasites to host genotype: single locus simulation models

PubMed Central

2013-01-01

Background Breeding livestock for improved resistance to disease is an increasingly important selection goal. However, the risk of pathogens adapting to livestock bred for improved disease resistance is difficult to quantify. Here, we explore the possibility of gastrointestinal worms adapting to sheep bred for low faecal worm egg count using computer simulation. Our model assumes sheep and worm genotypes interact at a single locus, such that the effect of an A allele in sheep is dependent on worm genotype, and the B allele in worms is favourable for parasitizing the A allele sheep but may increase mortality on pasture. We describe the requirements for adaptation and test if worm adaptation (1) is slowed by non-genetic features of worm infections and (2) can occur with little observable change in faecal worm egg count. Results Adaptation in worms was found to be primarily influenced by overall worm fitness, viz. the balance between the advantage of the B allele during the parasitic stage in sheep and its disadvantage on pasture. Genetic variation at the interacting locus in worms could be from de novo or segregating mutations, but de novo mutations are rare and segregating mutations are likely constrained to have (near) neutral effects on worm fitness. Most other aspects of the worm infection we modelled did not affect the outcomes. However, the host-controlled mechanism to reduce faecal worm egg count by lowering worm fecundity reduced the selection pressure on worms to adapt compared to other mechanisms, such as increasing worm mortality. Temporal changes in worm egg count were unreliable for detecting adaptation, despite the steady environment assumed in the simulations. Conclusions Adaptation of worms to sheep selected for low faecal worm egg count requires an allele segregating in worms that is favourable in animals with improved resistance but less favourable in other animals. Obtaining alleles with this specific property seems unlikely. With support from experimental data, we conclude that selection for low faecal worm egg count should be stable over a short time frame (e.g. 20 years). We are further exploring model outcomes with multiple loci and comparing outcomes to other control strategies. PMID:23714384

Reward: commentary. Temporal discounting in conduct disorder: toward an experience-adaptation hypothesis of the role of psychosocial insecurity.

PubMed

Sonuga-Barke, Edmund J S

2014-02-01

Young people with conduct disorder often experience histories of psychosocial adversity and socioeconomic insecurity. For these individuals, real-world future outcomes are not only delayed in their delivery but also highly uncertain. Under such circumstances, accentuated time preference (extreme favoring of the present over the future) is a rational response to the everyday reality of social and economic transactions. Building on this observation, the author sets out the hypothesis that the exaggerated temporal discounting displayed by individuals with conduct disorder reported by White et al. (2014) is an adaptation to chronic exposure to psychosocial insecurity during development. The author postulates that this adaptation leads to (a) a decision-making bias whereby delay and uncertainty are coded as inseparable characteristics of choice outcomes and/or (b) reprogramming of the brain networks regulating intertemporal decision making. Future research could explore the putative role of environmental exposures to adversity in the development of exaggerated temporal discounting in conduct disorder as well as the mediating role of putative cognitive and neurobiological adaptations.

Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas.

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.

Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke.

PubMed

Hope, Thomas M H; Leff, Alex P; Prejawa, Susan; Bruce, Rachel; Haigh, Zula; Lim, Louise; Ramsden, Sue; Oberhuber, Marion; Ludersdorfer, Philipp; Crinion, Jenny; Seghier, Mohamed L; Price, Cathy J

2017-06-01

Stroke survivors with acquired language deficits are commonly thought to reach a 'plateau' within a year of stroke onset, after which their residual language skills will remain stable. Nevertheless, there have been reports of patients who appear to recover over years. Here, we analysed longitudinal change in 28 left-hemisphere stroke patients, each more than a year post-stroke when first assessed-testing each patient's spoken object naming skills and acquiring structural brain scans twice. Some of the patients appeared to improve over time while others declined; both directions of change were associated with, and predictable given, structural adaptation in the intact right hemisphere of the brain. Contrary to the prevailing view that these patients' language skills are stable, these results imply that real change continues over years. The strongest brain-behaviour associations (the 'peak clusters') were in the anterior temporal lobe and the precentral gyrus. Using functional magnetic resonance imaging, we confirmed that both regions are actively involved when neurologically normal control subjects name visually presented objects, but neither appeared to be involved when the same participants used a finger press to make semantic association decisions on the same stimuli. This suggests that these regions serve word-retrieval or articulatory functions in the undamaged brain. We teased these interpretations apart by reference to change in other tasks. Consistent with the claim that the real change is occurring here, change in spoken object naming was correlated with change in two other similar tasks, spoken action naming and written object naming, each of which was independently associated with structural adaptation in similar (overlapping) right hemisphere regions. Change in written object naming, which requires word-retrieval but not articulation, was also significantly more correlated with both (i) change in spoken object naming; and (ii) structural adaptation in the two peak clusters, than was change in another task-auditory word repetition-which requires articulation but not word retrieval. This suggests that the changes in spoken object naming reflected variation at the level of word-retrieval processes. Surprisingly, given their qualitatively similar activation profiles, hypertrophy in the anterior temporal region was associated with improving behaviour, while hypertrophy in the precentral gyrus was associated with declining behaviour. We predict that either or both of these regions might be fruitful targets for neural stimulation studies (suppressing the precentral region and/or enhancing the anterior temporal region), aiming to encourage recovery or arrest decline even years after stroke occurs. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke

PubMed Central

Leff, Alex P.; Prejawa, Susan; Bruce, Rachel; Haigh, Zula; Lim, Louise; Ramsden, Sue; Oberhuber, Marion; Ludersdorfer, Philipp; Crinion, Jenny; Seghier, Mohamed L.; Price, Cathy J.

2017-01-01

Abstract Stroke survivors with acquired language deficits are commonly thought to reach a ‘plateau’ within a year of stroke onset, after which their residual language skills will remain stable. Nevertheless, there have been reports of patients who appear to recover over years. Here, we analysed longitudinal change in 28 left-hemisphere stroke patients, each more than a year post-stroke when first assessed—testing each patient’s spoken object naming skills and acquiring structural brain scans twice. Some of the patients appeared to improve over time while others declined; both directions of change were associated with, and predictable given, structural adaptation in the intact right hemisphere of the brain. Contrary to the prevailing view that these patients’ language skills are stable, these results imply that real change continues over years. The strongest brain–behaviour associations (the ‘peak clusters’) were in the anterior temporal lobe and the precentral gyrus. Using functional magnetic resonance imaging, we confirmed that both regions are actively involved when neurologically normal control subjects name visually presented objects, but neither appeared to be involved when the same participants used a finger press to make semantic association decisions on the same stimuli. This suggests that these regions serve word-retrieval or articulatory functions in the undamaged brain. We teased these interpretations apart by reference to change in other tasks. Consistent with the claim that the real change is occurring here, change in spoken object naming was correlated with change in two other similar tasks, spoken action naming and written object naming, each of which was independently associated with structural adaptation in similar (overlapping) right hemisphere regions. Change in written object naming, which requires word-retrieval but not articulation, was also significantly more correlated with both (i) change in spoken object naming; and (ii) structural adaptation in the two peak clusters, than was change in another task—auditory word repetition—which requires articulation but not word retrieval. This suggests that the changes in spoken object naming reflected variation at the level of word-retrieval processes. Surprisingly, given their qualitatively similar activation profiles, hypertrophy in the anterior temporal region was associated with improving behaviour, while hypertrophy in the precentral gyrus was associated with declining behaviour. We predict that either or both of these regions might be fruitful targets for neural stimulation studies (suppressing the precentral region and/or enhancing the anterior temporal region), aiming to encourage recovery or arrest decline even years after stroke occurs. PMID:28444235

Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data

NASA Astrophysics Data System (ADS)

Correia, Carlos M.; Bond, Charlotte Z.; Sauvage, Jean-François; Fusco, Thierry; Conan, Rodolphe; Wizinowich, Peter L.

2017-10-01

We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $\\sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${\\lambda}/D$ separations ($\\sim1-5{\\lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater

NASA Astrophysics Data System (ADS)

Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.

2015-12-01

The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.

Biweekly disturbance capture and attribution: case study in western Alberta grizzly bear habitat

NASA Astrophysics Data System (ADS)

Hilker, Thomas; Coops, Nicholas C.; Gaulton, Rachel; Wulder, Michael A.; Cranston, Jerome; Stenhouse, Gordon

2011-01-01

An increasing number of studies have demonstrated the impact of landscape disturbance on ecosystems. Satellite remote sensing can be used for mapping disturbances, and fusion techniques of sensors with complimentary characteristics can help to improve the spatial and temporal resolution of satellite-based mapping techniques. Classification of different disturbance types from satellite observations is difficult, yet important, especially in an ecological context as different disturbance types might have different impacts on vegetation recovery, wildlife habitats, and food resources. We demonstrate a possible approach for classifying common disturbance types by means of their spatial characteristics. First, landscape level change is characterized on a near biweekly basis through application of a data fusion model (spatial temporal adaptive algorithm for mapping reflectance change) and a number of spatial and temporal characteristics of the predicted disturbance patches are inferred. A regression tree approach is then used to classify disturbance events. Our results show that spatial and temporal disturbance characteristics can be used to classify disturbance events with an overall accuracy of 86% of the disturbed area observed. The date of disturbance was identified as the most powerful predictor of the disturbance type, together with the patch core area, patch size, and contiguity.

Speak on time! Effects of a musical rhythmic training on children with hearing loss.

PubMed

Hidalgo, Céline; Falk, Simone; Schön, Daniele

2017-08-01

This study investigates temporal adaptation in speech interaction in children with normal hearing and in children with cochlear implants (CIs) and/or hearing aids (HAs). We also address the question of whether musical rhythmic training can improve these skills in children with hearing loss (HL). Children named pictures presented on the screen in alternation with a virtual partner. Alternation rate (fast or slow) and the temporal predictability (match vs mismatch of stress occurrences) were manipulated. One group of children with normal hearing (NH) and one with HL were tested. The latter group was tested twice: once after 30 min of speech therapy and once after 30 min of musical rhythmic training. Both groups of children (NH and with HL) can adjust their speech production to the rate of alternation of the virtual partner. Moreover, while children with normal hearing benefit from the temporal regularity of stress occurrences, children with HL become sensitive to this manipulation only after rhythmic training. Rhythmic training may help children with HL to structure the temporal flow of their verbal interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

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

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient formore » the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.« less

Projecting coral reef futures under global warming and ocean acidification.

PubMed

Pandolfi, John M; Connolly, Sean R; Marshall, Dustin J; Cohen, Anne L

2011-07-22

Many physiological responses in present-day coral reefs to climate change are interpreted as consistent with the imminent disappearance of modern reefs globally because of annual mass bleaching events, carbonate dissolution, and insufficient time for substantial evolutionary responses. Emerging evidence for variability in the coral calcification response to acidification, geographical variation in bleaching susceptibility and recovery, responses to past climate change, and potential rates of adaptation to rapid warming supports an alternative scenario in which reef degradation occurs with greater temporal and spatial heterogeneity than current projections suggest. Reducing uncertainty in projecting coral reef futures requires improved understanding of past responses to rapid climate change; physiological responses to interacting factors, such as temperature, acidification, and nutrients; and the costs and constraints imposed by acclimation and adaptation.

An adaptive spatio-temporal Gaussian filter for processing cardiac optical mapping data.

PubMed

Pollnow, S; Pilia, N; Schwaderlapp, G; Loewe, A; Dössel, O; Lenis, G

2018-06-04

Optical mapping is widely used as a tool to investigate cardiac electrophysiology in ex vivo preparations. Digital filtering of fluorescence-optical data is an important requirement for robust subsequent data analysis and still a challenge when processing data acquired from thin mammalian myocardium. Therefore, we propose and investigate the use of an adaptive spatio-temporal Gaussian filter for processing optical mapping signals from these kinds of tissue usually having low signal-to-noise ratio (SNR). We demonstrate how filtering parameters can be chosen automatically without additional user input. For systematic comparison of this filter with standard filtering methods from the literature, we generated synthetic signals representing optical recordings from atrial myocardium of a rat heart with varying SNR. Furthermore, all filter methods were applied to experimental data from an ex vivo setup. Our developed filter outperformed the other filter methods regarding local activation time detection at SNRs smaller than 3 dB which are typical noise ratios expected in these signals. At higher SNRs, the proposed filter performed slightly worse than the methods from literature. In conclusion, the proposed adaptive spatio-temporal Gaussian filter is an appropriate tool for investigating fluorescence-optical data with low SNR. The spatio-temporal filter parameters were automatically adapted in contrast to the other investigated filters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Phase-aberration correction with a 3-D ultrasound scanner: feasibility study.

PubMed

Ivancevich, Nikolas M; Dahl, Jeremy J; Trahey, Gregg E; Smith, Stephen W

2006-08-01

We tested the feasibility of using adaptive imaging, namely phase-aberration correction, with two-dimensional (2-D) arrays and real-time, 3-D ultrasound. Because of the high spatial frequency content of aberrators, 2-D arrays, which generally have smaller pitch and thus higher spatial sampling frequency, and 3-D imaging show potential to improve the performance of adaptive imaging. Phase-correction algorithms improve image quality by compensating for tissue-induced errors in beamforming. Using the illustrative example of transcranial ultrasound, we have evaluated our ability to perform adaptive imaging with a real-time, 3-D scanner. We have used a polymer casting of a human temporal bone, root-mean-square (RMS) phase variation of 45.0 ns, full-width-half-maximum (FWHM) correlation length of 3.35 mm, and an electronic aberrator, 100 ns RMS, 3.76 mm correlation, with tissue phantoms as illustrative examples of near-field, phase-screen aberrators. Using the multilag, least-squares, cross-correlation method, we have shown the ability of 3-D adaptive imaging to increase anechoic cyst identification, image brightness, contrast-to-speckle ratio (CSR), and, in 3-D color Doppler experiments, the ability to visualize flow. For a physical aberrator skull casting we saw CSR increase by 13% from 1.01 to 1.14, while the number of detectable cysts increased from 4.3 to 7.7.

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

Increases in the autistic trait of attention to detail are associated with decreased multisensory temporal adaptation.

PubMed

Stevenson, Ryan A; Toulmin, Jennifer K; Youm, Ariana; Besney, Richard M A; Schulz, Samantha E; Barense, Morgan D; Ferber, Susanne

2017-10-30

Recent empirical evidence suggests that autistic individuals perceive the world differently than their typically-developed peers. One theoretical account, the predictive coding hypothesis, posits that autistic individuals show a decreased reliance on previous perceptual experiences, which may relate to autism symptomatology. We tested this through a well-characterized, audiovisual statistical-learning paradigm in which typically-developed participants were first adapted to consistent temporal relationships between audiovisual stimulus pairs (audio-leading, synchronous, visual-leading) and then performed a simultaneity judgement task with audiovisual stimulus pairs varying in temporal offset from auditory-leading to visual-leading. Following exposure to the visual-leading adaptation phase, participants' perception of synchrony was biased towards visual-leading presentations, reflecting the statistical regularities of their previously experienced environment. Importantly, the strength of adaptation was significantly related to the level of autistic traits that the participant exhibited, measured by the Autism Quotient (AQ). This was specific to the Attention to Detail subscale of the AQ that assesses the perceptual propensity to focus on fine-grain aspects of sensory input at the expense of more integrative perceptions. More severe Attention to Detail was related to weaker adaptation. These results support the predictive coding framework, and suggest that changes in sensory perception commonly reported in autism may contribute to autistic symptomatology.

Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction

PubMed Central

Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong

2015-01-01

In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991

Face adaptation aftereffects reveal anterior medial temporal cortex role in high level category representation.

PubMed

Furl, N; van Rijsbergen, N J; Treves, A; Dolan, R J

2007-08-01

Previous studies have shown reductions of the functional magnetic resonance imaging (fMRI) signal in response to repetition of specific visual stimuli. We examined how adaptation affects the neural responses associated with categorization behavior, using face adaptation aftereffects. Adaptation to a given facial category biases categorization towards non-adapted facial categories in response to presentation of ambiguous morphs. We explored a hypothesis, posed by recent psychophysical studies, that these adaptation-induced categorizations are mediated by activity in relatively advanced stages within the occipitotemporal visual processing stream. Replicating these studies, we find that adaptation to a facial expression heightens perception of non-adapted expressions. Using comparable behavioral methods, we also show that adaptation to a specific identity heightens perception of a second identity in morph faces. We show both expression and identity effects to be associated with heightened anterior medial temporal lobe activity, specifically when perceiving the non-adapted category. These regions, incorporating bilateral anterior ventral rhinal cortices, perirhinal cortex and left anterior hippocampus are regions previously implicated in high-level visual perception. These categorization effects were not evident in fusiform or occipital gyri, although activity in these regions was reduced to repeated faces. The findings suggest that adaptation-induced perception is mediated by activity in regions downstream to those showing reductions due to stimulus repetition.

Adaptive semantic tag mining from heterogeneous clinical research texts.

PubMed

Hao, T; Weng, C

2015-01-01

To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts. We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts. Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed. This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.

Improved Simulation of Electrodiffusion in the Node of Ranvier by Mesh Adaptation.

PubMed

Dione, Ibrahima; Deteix, Jean; Briffard, Thomas; Chamberland, Eric; Doyon, Nicolas

2016-01-01

In neural structures with complex geometries, numerical resolution of the Poisson-Nernst-Planck (PNP) equations is necessary to accurately model electrodiffusion. This formalism allows one to describe ionic concentrations and the electric field (even away from the membrane) with arbitrary spatial and temporal resolution which is impossible to achieve with models relying on cable theory. However, solving the PNP equations on complex geometries involves handling intricate numerical difficulties related either to the spatial discretization, temporal discretization or the resolution of the linearized systems, often requiring large computational resources which have limited the use of this approach. In the present paper, we investigate the best ways to use the finite elements method (FEM) to solve the PNP equations on domains with discontinuous properties (such as occur at the membrane-cytoplasm interface). 1) Using a simple 2D geometry to allow comparison with analytical solution, we show that mesh adaptation is a very (if not the most) efficient way to obtain accurate solutions while limiting the computational efforts, 2) We use mesh adaptation in a 3D model of a node of Ranvier to reveal details of the solution which are nearly impossible to resolve with other modelling techniques. For instance, we exhibit a non linear distribution of the electric potential within the membrane due to the non uniform width of the myelin and investigate its impact on the spatial profile of the electric field in the Debye layer.

Impact of climate change on human infectious diseases: Empirical evidence and human adaptation.

PubMed

Wu, Xiaoxu; Lu, Yongmei; Zhou, Sen; Chen, Lifan; Xu, Bing

2016-01-01

Climate change refers to long-term shifts in weather conditions and patterns of extreme weather events. It may lead to changes in health threat to human beings, multiplying existing health problems. This review examines the scientific evidences on the impact of climate change on human infectious diseases. It identifies research progress and gaps on how human society may respond to, adapt to, and prepare for the related changes. Based on a survey of related publications between 1990 and 2015, the terms used for literature selection reflect three aspects--the components of infectious diseases, climate variables, and selected infectious diseases. Humans' vulnerability to the potential health impacts by climate change is evident in literature. As an active agent, human beings may control the related health effects that may be effectively controlled through adopting proactive measures, including better understanding of the climate change patterns and of the compound disease-specific health effects, and effective allocation of technologies and resources to promote healthy lifestyles and public awareness. The following adaptation measures are recommended: 1) to go beyond empirical observations of the association between climate change and infectious diseases and develop more scientific explanations, 2) to improve the prediction of spatial-temporal process of climate change and the associated shifts in infectious diseases at various spatial and temporal scales, and 3) to establish locally effective early warning systems for the health effects of predicated climate change. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adaptive evolution of Escherichia coli to Ciprofloxacin in controlled stress environments: emergence of tolerance in spatial and temporal gradients

NASA Astrophysics Data System (ADS)

Deng, J.; Sanford, R. A.; Dong, Y.; Shechtman, L. A.; Zhou, L.; Alcalde, R.; Werth, C. J.; Fouke, B. W.

2016-12-01

Microorganisms in nature have evolved in response to a variety of environmental stresses, including gradients of temperature, pH, substrate availability and aqueous chemistry. While environmental stresses are considered to be the driving forces of adaptive evolution, the impact and extent of any specific stress needed to drive such changes has not been well characterized. In this study, the antibiotic Ciprofloxacin was used as a stressor and systematically applied to E. coli st. 307 cells via a spatial gradient in a microfluidic pore network and a temporal gradient in batch cultures. The microfluidic device facilitated in vitro real-time tracking of bacterial abundances and dynamic spatial distributions in response to the gradients of both the antibiotic and nutrients. Cells collected from the microfluidic device showed growth on plates containing up to 10-times the original minimum inhibition concentration (MIC). In batch systems, Ciprofloxacin was used to evaluate adaptive responses via temporal gradients, in which the stressor concentration was incrementally increased over time with each transfer of the culture after 24 hours of growth. Responses of E. coli 307 to these stress patterns were measured by quantifying changes in the MIC for Ciprofloxacin. Over a period of 18 days of step-wise concentration increments, bacterial cells were observed to acquire tolerance gradually and eventually adapt to a 28-fold increase in the original MIC. Samples at different stages within the temporal Ciprofloxacin gradient treatment show different extents of resistance. All samples exhibited resistance exceeding the highest exposure stress concentration. In combination with the spatial and temporal gradient systems, this work provides the first comprehensive measure of the dynamic resistance of E. coli in response to Ciprofloxacin concentration gradients. These will provide invaluable insights to understand the effects of antibiotic stresses on bacterial adaptive evolution in medical settings and shed light on understanding the mechanics of microbial evolution.

Rapid Motion Adaptation Reveals the Temporal Dynamics of Spatiotemporal Correlation between ON and OFF Pathways

PubMed Central

Oluk, Can; Pavan, Andrea; Kafaligonul, Hulusi

2016-01-01

At the early stages of visual processing, information is processed by two major thalamic pathways encoding brightness increments (ON) and decrements (OFF). Accumulating evidence suggests that these pathways interact and merge as early as in primary visual cortex. Using regular and reverse-phi motion in a rapid adaptation paradigm, we investigated the temporal dynamics of within and across pathway mechanisms for motion processing. When the adaptation duration was short (188 ms), reverse-phi and regular motion led to similar adaptation effects, suggesting that the information from the two pathways are combined efficiently at early-stages of motion processing. However, as the adaption duration was increased to 752 ms, reverse-phi and regular motion showed distinct adaptation effects depending on the test pattern used, either engaging spatiotemporal correlation between the same or opposite contrast polarities. Overall, these findings indicate that spatiotemporal correlation within and across ON-OFF pathways for motion processing can be selectively adapted, and support those models that integrate within and across pathway mechanisms for motion processing. PMID:27667401

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

Piecing together the puzzle: Improving event content coverage for real-time sub-event detection using adaptive microblog crawling

PubMed Central

Tokarchuk, Laurissa; Wang, Xinyue; Poslad, Stefan

2017-01-01

In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM) framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The novel combination of our proposed adaptive crawler and our stream division/recombination technique provides significant gains in event recall (44.44%) and event precision (9.57%). The addition of these sub-events or pieces, allows us to get closer to solving the event puzzle. PMID:29107976

Piecing together the puzzle: Improving event content coverage for real-time sub-event detection using adaptive microblog crawling.

PubMed

Tokarchuk, Laurissa; Wang, Xinyue; Poslad, Stefan

2017-01-01

In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM) framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The novel combination of our proposed adaptive crawler and our stream division/recombination technique provides significant gains in event recall (44.44%) and event precision (9.57%). The addition of these sub-events or pieces, allows us to get closer to solving the event puzzle.

A Neural Model for Temporal Order Judgments and Their Active Recalibration: A Common Mechanism for Space and Time?

PubMed Central

Cai, Mingbo; Stetson, Chess; Eagleman, David M.

2012-01-01

When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006). We present here a novel neural model that can explain temporal order judgments (TOJs) and their recalibration. Our model employs three ubiquitous features of neural systems: (1) information pooling, (2) opponent processing, and (3) synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding “before” and “after”), and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analog to the motion aftereffect (MAE). In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the MAE. PMID:23130010

Temporal change in genetic integrity suggests loss of local adaptation in a wild Atlantic salmon (Salmo salar) population following introgression by farmed escapees.

PubMed

Bourret, V; O'Reilly, P T; Carr, J W; Berg, P R; Bernatchez, L

2011-03-01

In some wild Atlantic salmon populations, rapid declines in numbers of wild returning adults has been associated with an increase in the prevalence of farmed salmon. Studies of phenotypic variation have shown that interbreeding between farmed and wild salmon may lead to loss of local adaptation. Yet, few studies have attempted to assess the impact of interbreeding at the genome level, especially among North American populations. Here, we document temporal changes in the genetic makeup of the severely threatened Magaguadavic River salmon population (Bay of Fundy, Canada), a population that might have been impacted by interbreeding with farmed salmon for nearly 20 years. Wild and farmed individuals caught entering the river from 1980 to 2005 were genotyped at 112 single-nucleotide polymorphisms (SNPs), and/or eight microsatellite loci, to scan for potential shifts in adaptive genetic variation. No significant temporal change in microsatellite-based estimates of allele richness or gene diversity was detected in the wild population, despite its precipitous decline in numbers over the last two decades. This might reflect the effect of introgression from farmed salmon, which was corroborated by temporal change in linkage-disequilibrium. Moreover, SNP genome scans identified a temporal decrease in candidate loci potentially under directional selection. Of particular interest was a SNP previously shown to be strongly associated with an important quantitative trait locus for parr mark number, which retained its genetic distinctiveness between farmed and wild fish longer than other outliers. Overall, these results indicate that farmed escapees have introgressed with wild Magaguadavic salmon resulting in significant alteration of the genetic integrity of the native population, including possible loss of adaptation to wild conditions.

Temporal change in genetic integrity suggests loss of local adaptation in a wild Atlantic salmon (Salmo salar) population following introgression by farmed escapees

PubMed Central

Bourret, V; O'Reilly, P T; Carr, J W; Berg, P R; Bernatchez, L

2011-01-01

In some wild Atlantic salmon populations, rapid declines in numbers of wild returning adults has been associated with an increase in the prevalence of farmed salmon. Studies of phenotypic variation have shown that interbreeding between farmed and wild salmon may lead to loss of local adaptation. Yet, few studies have attempted to assess the impact of interbreeding at the genome level, especially among North American populations. Here, we document temporal changes in the genetic makeup of the severely threatened Magaguadavic River salmon population (Bay of Fundy, Canada), a population that might have been impacted by interbreeding with farmed salmon for nearly 20 years. Wild and farmed individuals caught entering the river from 1980 to 2005 were genotyped at 112 single-nucleotide polymorphisms (SNPs), and/or eight microsatellite loci, to scan for potential shifts in adaptive genetic variation. No significant temporal change in microsatellite-based estimates of allele richness or gene diversity was detected in the wild population, despite its precipitous decline in numbers over the last two decades. This might reflect the effect of introgression from farmed salmon, which was corroborated by temporal change in linkage-disequilibrium. Moreover, SNP genome scans identified a temporal decrease in candidate loci potentially under directional selection. Of particular interest was a SNP previously shown to be strongly associated with an important quantitative trait locus for parr mark number, which retained its genetic distinctiveness between farmed and wild fish longer than other outliers. Overall, these results indicate that farmed escapees have introgressed with wild Magaguadavic salmon resulting in significant alteration of the genetic integrity of the native population, including possible loss of adaptation to wild conditions. PMID:21224876

Determinants of Autobiographical Memory in Patients with Unilateral Temporal Lobe Epilepsy or Excisions

ERIC Educational Resources Information Center

St-Laurent, Marie; Moscovitch, Morris; Levine, Brian; McAndrews, Mary Pat

2009-01-01

Patients with unilateral temporal lobe epilepsy from hippocampal origin and patients with unilateral surgical excision of an epileptic focus located in the medial temporal lobe were compared to healthy controls on a version of the Autobiographical Interview (AI) adapted to assess memory for event-specific and generic personal episodes. For both…

Object-Driven and Temporal Action Rules Mining

ERIC Educational Resources Information Center

Hajja, Ayman

2013-01-01

In this thesis, I present my complete research work in the field of action rules, more precisely object-driven and temporal action rules. The drive behind the introduction of object-driven and temporally based action rules is to bring forth an adapted approach to extract action rules from a subclass of systems that have a specific nature, in which…

A framework of connections between soil and people can help improve sustainability of the food system and soil functions.

PubMed

Ball, Bruce C; Hargreaves, Paul R; Watson, Christine A

2018-04-01

Globally soil quality and food security continue to decrease indicating that agriculture and the food system need to adapt. Improving connection to the soil by knowledge exchange can help achieve this. We propose a framework of three types of connections that allow the targeting of appropriate messages to different groups of people. Direct connection by, for example, handling soil develops soil awareness for management that can be fostered by farmers joining groups on soil-focused farming such as organic farming or no-till. Indirect connections between soil, food and ecosystem services can inform food choices and environmental awareness in the public and can be promoted by, for example, gardening, education and art. Temporal connection revealed from past usage of soil helps to bring awareness to policy workers of the need for the long-term preservation of soil quality for environmental conservation. The understanding of indirect and temporal connections can be helped by comparing them with the operations of the networks of soil organisms and porosity that sustain soil fertility and soil functions.

Efficient Prediction Structures for H.264 Multi View Coding Using Temporal Scalability

NASA Astrophysics Data System (ADS)

Guruvareddiar, Palanivel; Joseph, Biju K.

2014-03-01

Prediction structures with "disposable view components based" hierarchical coding have been proven to be efficient for H.264 multi view coding. Though these prediction structures along with the QP cascading schemes provide superior compression efficiency when compared to the traditional IBBP coding scheme, the temporal scalability requirements of the bit stream could not be met to the fullest. On the other hand, a fully scalable bit stream, obtained by "temporal identifier based" hierarchical coding, provides a number of advantages including bit rate adaptations and improved error resilience, but lacks in compression efficiency when compared to the former scheme. In this paper it is proposed to combine the two approaches such that a fully scalable bit stream could be realized with minimal reduction in compression efficiency when compared to state-of-the-art "disposable view components based" hierarchical coding. Simulation results shows that the proposed method enables full temporal scalability with maximum BDPSNR reduction of only 0.34 dB. A novel method also has been proposed for the identification of temporal identifier for the legacy H.264/AVC base layer packets. Simulation results also show that this enables the scenario where the enhancement views could be extracted at a lower frame rate (1/2nd or 1/4th of base view) with average extraction time for a view component of only 0.38 ms.

The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations

NASA Astrophysics Data System (ADS)

Miyoshi, Takemasa; Kunii, Masaru

2012-03-01

The local ensemble transform Kalman filter (LETKF) is implemented with the Weather Research and Forecasting (WRF) model, and real observations are assimilated to assess the newly-developed WRF-LETKF system. The WRF model is a widely-used mesoscale numerical weather prediction model, and the LETKF is an ensemble Kalman filter (EnKF) algorithm particularly efficient in parallel computer architecture. This study aims to provide the basis of future research on mesoscale data assimilation using the WRF-LETKF system, an additional testbed to the existing EnKF systems with the WRF model used in the previous studies. The particular LETKF system adopted in this study is based on the system initially developed in 2004 and has been continuously improved through theoretical studies and wide applications to many kinds of dynamical models including realistic geophysical models. Most recent and important improvements include an adaptive covariance inflation scheme which considers the spatial and temporal inhomogeneity of inflation parameters. Experiments show that the LETKF successfully assimilates real observations and that adaptive inflation is advantageous. Additional experiments with various ensemble sizes show that using more ensemble members improves the analyses consistently.

Policy improvement by a model-free Dyna architecture.

PubMed

Hwang, Kao-Shing; Lo, Chia-Yue

2013-05-01

The objective of this paper is to accelerate the process of policy improvement in reinforcement learning. The proposed Dyna-style system combines two learning schemes, one of which utilizes a temporal difference method for direct learning; the other uses relative values for indirect learning in planning between two successive direct learning cycles. Instead of establishing a complicated world model, the approach introduces a simple predictor of average rewards to actor-critic architecture in the simulation (planning) mode. The relative value of a state, defined as the accumulated differences between immediate reward and average reward, is used to steer the improvement process in the right direction. The proposed learning scheme is applied to control a pendulum system for tracking a desired trajectory to demonstrate its adaptability and robustness. Through reinforcement signals from the environment, the system takes the appropriate action to drive an unknown dynamic to track desired outputs in few learning cycles. Comparisons are made between the proposed model-free method, a connectionist adaptive heuristic critic, and an advanced method of Dyna-Q learning in the experiments of labyrinth exploration. The proposed method outperforms its counterparts in terms of elapsed time and convergence rate.

Temporal Sensitivity Measured Shortly After Cochlear Implantation Predicts 6-Month Speech Recognition Outcome.

PubMed

Erb, Julia; Ludwig, Alexandra Annemarie; Kunke, Dunja; Fuchs, Michael; Obleser, Jonas

2018-04-24

Psychoacoustic tests assessed shortly after cochlear implantation are useful predictors of the rehabilitative speech outcome. While largely independent, both spectral and temporal resolution tests are important to provide an accurate prediction of speech recognition. However, rapid tests of temporal sensitivity are currently lacking. Here, we propose a simple amplitude modulation rate discrimination (AMRD) paradigm that is validated by predicting future speech recognition in adult cochlear implant (CI) patients. In 34 newly implanted patients, we used an adaptive AMRD paradigm, where broadband noise was modulated at the speech-relevant rate of ~4 Hz. In a longitudinal study, speech recognition in quiet was assessed using the closed-set Freiburger number test shortly after cochlear implantation (t0) as well as the open-set Freiburger monosyllabic word test 6 months later (t6). Both AMRD thresholds at t0 (r = -0.51) and speech recognition scores at t0 (r = 0.56) predicted speech recognition scores at t6. However, AMRD and speech recognition at t0 were uncorrelated, suggesting that those measures capture partially distinct perceptual abilities. A multiple regression model predicting 6-month speech recognition outcome with deafness duration and speech recognition at t0 improved from adjusted R = 0.30 to adjusted R = 0.44 when AMRD threshold was added as a predictor. These findings identify AMRD thresholds as a reliable, nonredundant predictor above and beyond established speech tests for CI outcome. This AMRD test could potentially be developed into a rapid clinical temporal-resolution test to be integrated into the postoperative test battery to improve the reliability of speech outcome prognosis.

Strategies for Choosing Descent Flight-Path Angles for Small Jets

NASA Technical Reports Server (NTRS)

Wu, Minghong Gilbert; Green, Steven M.

2012-01-01

Three candidate strategies for choosing the descent flight path angle (FPA) for small jets are proposed, analyzed, and compared for fuel efficiency under arrival metering conditions. The strategies vary in operational complexity from a universally fixed FPA, or FPA function that varies with descent speed for improved fuel efficiency, to the minimum-fuel FPA computed for each flight based on winds, route, and speed profile. Methodologies for selecting the parameter for the first two strategies are described. The differences in fuel burn are analyzed over a year s worth of arrival traffic and atmospheric conditions recorded for the Dallas/Fort Worth (DFW) Airport during 2011. The results show that the universally fixed FPA strategy (same FPA for all flights, all year) burns on average 26 lbs more fuel per flight as compared to the minimum-fuel solution. This FPA is adapted to the arrival gate (direction of entry to the terminal) and various timespans (season, month and day) to improve fuel efficiency. Compared to a typical FPA of approximately 3 degrees the adapted FPAs vary significantly, up to 1.3 from one arrival gate to another or up to 1.4 from one day to another. Adapting the universally fixed FPA strategy to the arrival gate or to each day reduces the extra fuel burn relative to the minimum-fuel solution by 27% and 34%, respectively. The adaptations to gate and time combined shows up to 57% reduction of the extra fuel burn. The second strategy, an FPA function, contributes a 17% reduction in the 26 lbs of extra fuel burn over the universally fixed FPA strategy. Compared to the corresponding adaptations of the universally fixed FPA, adaptations of the FPA function reduce the extra fuel burn anywhere from 15-23% depending on the extent of adaptation. The combined effect of the FPA function strategy with both directional and temporal adaptation recovers 67% of the extra fuel relative to the minimum-fuel solution.

An Efficient Adaptive Window Size Selection Method for Improving Spectrogram Visualization.

PubMed

Nisar, Shibli; Khan, Omar Usman; Tariq, Muhammad

2016-01-01

Short Time Fourier Transform (STFT) is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves the application of a Fast Fourier Transform (FFT) to a signal multiplied with an appropriate window function with fixed resolution. The selection of an appropriate window size is difficult when no background information about the input signal is known. In this paper, a novel empirical model is proposed that adaptively adjusts the window size for a narrow band-signal using spectrum sensing technique. For wide-band signals, where a fixed time-frequency resolution is undesirable, the approach adapts the constant Q transform (CQT). Unlike the STFT, the CQT provides a varying time-frequency resolution. This results in a high spectral resolution at low frequencies and high temporal resolution at high frequencies. In this paper, a simple but effective switching framework is provided between both STFT and CQT. The proposed method also allows for the dynamic construction of a filter bank according to user-defined parameters. This helps in reducing redundant entries in the filter bank. Results obtained from the proposed method not only improve the spectrogram visualization but also reduce the computation cost and achieves 87.71% of the appropriate window length selection.

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Assessing fit, interplay, and scale: Aligning governance and information for improved water management in a changing climate

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Dilling, L.

2011-12-01

Water managers have long experienced the challenges of managing water resources in a variable climate. However, climate change has the potential to reshape the experiential landscape by, for example, increasing the intensity and duration of droughts, shifting precipitation timing and amounts, and changing sea levels. Given the uncertainty in evaluating potential climate risks as well as future water availability and water demands, scholars suggest water managers employ more flexible and adaptive science-based management to manage uncertainty (NRC 2009). While such an approach is appropriate, for adaptive science-based management to be effective both governance and information must be concordant across three measures: fit, interplay and scale (Young 2002)(Note 1). Our research relies on interviews of state water managers and related experts (n=50) and documentary analysis in five U.S. states to understand the drivers and constraints to improving water resource planning and decision-making in a changing climate using an assessment of fit, interplay and scale as an evaluative framework. We apply this framework to assess and compare how water managers plan and respond to current or anticipated water resource challenges within each state. We hypothesize that better alignment between the data and management framework and the water resource problem improves water managers' facility to understand (via available, relevant, timely information) and respond appropriately (through institutional response mechanisms). In addition, better alignment between governance mechanisms (between the scope of the problem and identified appropriate responses) improves water management. Moreover, because many of the management challenges analyzed in this study concern present day issues with scarcity brought on by a combination of growth and drought, better alignment of fit, interplay, and scale today will enable and prepare water managers to be more successful in adapting to climate change impacts in the long-term. Note 1: For the purposes of this research, the problem of fit deals with the level of concordance between the natural and human systems while interplay involves how institutional arrangements interact both horizontally and vertically. Lastly, scale considers both spatial and temporal alignment of the physical systems and management structure. For example, to manage water resources effectively in a changing climate suggests having information that informs short-term and long-term changes and having institutional arrangements that seek understanding across temporal scales and facilitate responses based on information available (Young 2002).

Comparison between two time-resolved approaches for prostate cancer diagnosis: high rate imager vs. photon counting system

NASA Astrophysics Data System (ADS)

Boutet, J.; Debourdeau, M.; Laidevant, A.; Hervé, L.; Dinten, J.-M.

2010-02-01

Finding a way to combine ultrasound and fluorescence optical imaging on an endorectal probe may improve early detection of prostate cancer. A trans-rectal probe adapted to fluorescence diffuse optical tomography measurements was developed by our team. This probe is based on a pulsed NIR laser source, an optical fiber network and a time-resolved detection system. A reconstruction algorithm was used to help locate and quantify fluorescent prostate tumors. In this study, two different kinds of time-resolved detectors are compared: High Rate Imaging system (HRI) and a photon counting system. The HRI is based on an intensified multichannel plate and a CCD Camera. The temporal resolution is obtained through a gating of the HRI. Despite a low temporal resolution (300ps), this system allows a simultaneous acquisition of the signal from a large number of detection fibers. In the photon counting setup, 4 photomultipliers are connected to a Time Correlated Single Photon Counting (TCSPC) board, providing a better temporal resolution (0.1 ps) at the expense of a limited number of detection fibers (4). At last, we show that the limited number of detection fibers of the photon counting setup is enough for a good localization and dramatically improves the overall acquisition time. The photon counting approach is then validated through the localization of fluorescent inclusions in a prostate-mimicking phantom.

Object size determines the spatial spread of visual time

PubMed Central

McGraw, Paul V.; Roach, Neil W.; Whitaker, David

2016-01-01

A key question for temporal processing research is how the nervous system extracts event duration, despite a notable lack of neural structures dedicated to duration encoding. This is in stark contrast with the orderly arrangement of neurons tasked with spatial processing. In this study, we examine the linkage between the spatial and temporal domains. We use sensory adaptation techniques to generate after-effects where perceived duration is either compressed or expanded in the opposite direction to the adapting stimulus' duration. Our results indicate that these after-effects are broadly tuned, extending over an area approximately five times the size of the stimulus. This region is directly related to the size of the adapting stimulus—the larger the adapting stimulus the greater the spatial spread of the after-effect. We construct a simple model to test predictions based on overlapping adapted versus non-adapted neuronal populations and show that our effects cannot be explained by any single, fixed-scale neural filtering. Rather, our effects are best explained by a self-scaled mechanism underpinned by duration selective neurons that also pool spatial information across earlier stages of visual processing. PMID:27466452

The influence of an uncertain force environment on reshaping trial-to-trial motor variability.

PubMed

Izawa, Jun; Yoshioka, Toshinori; Osu, Rieko

2014-09-10

Motor memory is updated to generate ideal movements in a novel environment. When the environment changes every trial randomly, how does the brain incorporate this uncertainty into motor memory? To investigate how the brain adapts to an uncertain environment, we considered a reach adaptation protocol where individuals practiced moving in a force field where a noise was injected. After they had adapted, we measured the trial-to-trial variability in the temporal profiles of the produced hand force. We found that the motor variability was significantly magnified by the adaptation to the random force field. Temporal profiles of the motor variance were significantly dissociable between two different types of random force fields experienced. A model-based analysis suggests that the variability is generated by noise in the gains of the internal model. It further suggests that the trial-to-trial motor variability magnified by the adaptation in a random force field is generated by the uncertainty of the internal model formed in the brain as a result of the adaptation.

Advanced platform technologies for Earth science

NASA Astrophysics Data System (ADS)

Lemmerman, Loren; Raymond, Carol; Shotwell, Robert; Chase, James; Bhasin, Kul; Connerton, Robert

2005-01-01

Historically, Earth science investigations have been independent and highly focused. However, the Earth's environment is a very dynamic and interrelated system and to understand it, significant improvements in spatial and temporal observations will be required. Science needs to document the need for constellations to achieve desired spatial and temporal observations. A key element envisioned for accomplishing these difficult challenges is the idea of a distributed, heterogeneous, and adaptive observing system or sensor web. This paper focuses on one possible approach based on a LEO constellation composed of 100 spacecraft. A cost analysis has been done to indicate the financial pressures of each mission phase and conclusions are drawn suggesting that new technology investments are needed, directed toward lowering production costs; that operations costs will need to be reduced through autonomy; and that, of the on-board subsystems considered, advanced power generation and management may be the most enabling of new technologies.

Evaluation of Ecotoxicological Risks Related to the Discharge of Combined Sewer Overflows (CSOs) in a Periurban River

PubMed Central

Angerville, Ruth; Perrodin, Yves; Bazin, Christine; Emmanuel, Evens

2013-01-01

Discharges of Combined Sewer Overflows (CSOs) into periurban rivers present risks for the concerned aquatic ecosystems. In this work, a specific ecotoxicological risk assessment methodology has been developed as management tool to municipalities equipped with CSOs. This methodology comprises a detailed description of the spatio-temporal system involved, the choice of ecological targets to be preserved, and carrying out bioassays adapted to each compartment of the river receiving CSOs. Once formulated, this methodology was applied to a river flowing through the outskirts of the city of Lyon in France. The results obtained for the scenario studied showed a moderate risk for organisms of the water column and a major risk for organisms of the benthic and hyporheic zones of the river. The methodology enabled identifying the critical points of the spatio-temporal systems studied, and then making proposals for improving the management of CSOs. PMID:23812025

Constructing Temporally Extended Actions through Incremental Community Detection

PubMed Central

Li, Ge

2018-01-01

Hierarchical reinforcement learning works on temporally extended actions or skills to facilitate learning. How to automatically form such abstraction is challenging, and many efforts tackle this issue in the options framework. While various approaches exist to construct options from different perspectives, few of them concentrate on options' adaptability during learning. This paper presents an algorithm to create options and enhance their quality online. Both aspects operate on detected communities of the learning environment's state transition graph. We first construct options from initial samples as the basis of online learning. Then a rule-based community revision algorithm is proposed to update graph partitions, based on which existing options can be continuously tuned. Experimental results in two problems indicate that options from initial samples may perform poorly in more complex environments, and our presented strategy can effectively improve options and get better results compared with flat reinforcement learning. PMID:29849543

Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

PubMed

Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

2017-03-01

Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Advanced Atmospheric Ensemble Modeling Techniques

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

Buckley, R.; Chiswell, S.; Kurzeja, R.

Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two releasemore » times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.« less

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI.

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2017-04-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

NASA Astrophysics Data System (ADS)

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

2017-04-01

Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved

Can the black box be cracked? The augmentation of microbial ecology by high-resolution, automated sensing technologies.

PubMed

Shade, Ashley; Carey, Cayelan C; Kara, Emily; Bertilsson, Stefan; McMahon, Katherine D; Smith, Matthew C

2009-08-01

Automated sensing technologies, 'ASTs,' are tools that can monitor environmental or microbial-related variables at increasingly high temporal resolution. Microbial ecologists are poised to use AST data to couple microbial structure, function and associated environmental observations on temporal scales pertinent to microbial processes. In the context of aquatic microbiology, we discuss three applications of ASTs: windows on the microbial world, adaptive sampling and adaptive management. We challenge microbial ecologists to push AST potential in helping to reveal relationships between microbial structure and function.

Temporal variability in chlorophyll fluorescence of back-reef corals in Ofu, American Samoa

USGS Publications Warehouse

Piniak, G.A.; Brown, E.K.

2009-01-01

Change in the yield of chlorophyll a fluorescence is a common indicator of thermal stress in corals. The present study reports temporal variability in quantum yield measurements for 10 coral species in Ofu, American Samoa - a place known to experience elevated and variable seawater temperatures. In winter, the zooxanthellae generally had higher dark-adapted maximum quantum yield (F v/Fm), higher light- adapted effective quantum yield (??F/F'm), and lower relative electron transport rates (rETR) than in the summer. Temporal changes appeared unrelated to the expected bleaching sensitivity of corals. All species surveyed, with the exception of Montipora grisea, demonstrated significant temporal changes in the three fluorescence parameters. Fluorescence responses were influenced by the microhabitat - temporal differences in fluorescence parameters were usually observed in the habitat with a more variable temperature regime (pool 300), while differences in Fv/Fm between species were observed only in the more environmentally stable habitat (pool 400). Such species-specific responses and microhabitat variability should be considered when attempting to determine whether observed in situ changes are normal seasonal changes or early signs of bleaching. ?? 2009 Marine Biological Laboratory.

Higher-order neural processing tunes motion neurons to visual ecology in three species of hawkmoths.

PubMed

Stöckl, A L; O'Carroll, D; Warrant, E J

2017-06-28

To sample information optimally, sensory systems must adapt to the ecological demands of each animal species. These adaptations can occur peripherally, in the anatomical structures of sensory organs and their receptors; and centrally, as higher-order neural processing in the brain. While a rich body of investigations has focused on peripheral adaptations, our understanding is sparse when it comes to central mechanisms. We quantified how peripheral adaptations in the eyes, and central adaptations in the wide-field motion vision system, set the trade-off between resolution and sensitivity in three species of hawkmoths active at very different light levels: nocturnal Deilephila elpenor, crepuscular Manduca sexta , and diurnal Macroglossum stellatarum. Using optical measurements and physiological recordings from the photoreceptors and wide-field motion neurons in the lobula complex, we demonstrate that all three species use spatial and temporal summation to improve visual performance in dim light. The diurnal Macroglossum relies least on summation, but can only see at brighter intensities. Manduca, with large sensitive eyes, relies less on neural summation than the smaller eyed Deilephila , but both species attain similar visual performance at nocturnal light levels. Our results reveal how the visual systems of these three hawkmoth species are intimately matched to their visual ecologies. © 2017 The Author(s).

Developmental improvements in dynamic control of fingertip forces last throughout childhood and into adolescence

PubMed Central

Dayanidhi, Sudarshan; Hedberg, Åsa; Forssberg, Hans

2013-01-01

While it is clear that the development of dexterous manipulation in children exhibits dramatic improvements over an extended period, it is difficult to separate musculoskeletal from neural contributors to these important functional gains. This is in part due to the inability of current methods to disambiguate improvements in hand strength from gains in finger dexterity (i.e., the dynamic control of fingertip force vectors at low magnitudes). We adapted our novel instrumentation to evaluate finger dexterity in 130 typically developing children between the ages of 4 and 16 yr. We find that finger dexterity continues to develop well into late adolescence and musculoskeletal growth and strength are poorly correlated with the improvements in dexterity. Importantly, because these behavioral results seem to mirror the known timelines of neuroanatomical development up to adolescence, we speculate that they reflect the functional benefits of such continual neural maturation. This novel perspective now enables the systematic study of the functional roles of specific neuroanatomical structures and their connectivity, maturity, and plasticity. Moreover, the temporal dynamics of the fingertip force vectors shows improvements in stability that provide a novel way to look at the maturation of finger control. From a clinical perspective, our results provide a practical means to chart functional development of dexterous manipulation in typically developing children and could be adapted for clinical use and for use in children with developmental disorders. PMID:23864371

Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

An adaptive framework to differentiate receiving water quality impacts on a multi-scale level.

PubMed

Blumensaat, F; Tränckner, J; Helm, B; Kroll, S; Dirckx, G; Krebs, P

2013-01-01

The paradigm shift in recent years towards sustainable and coherent water resources management on a river basin scale has changed the subject of investigations to a multi-scale problem representing a great challenge for all actors participating in the management process. In this regard, planning engineers often face an inherent conflict to provide reliable decision support for complex questions with a minimum of effort. This trend inevitably increases the risk to base decisions upon uncertain and unverified conclusions. This paper proposes an adaptive framework for integral planning that combines several concepts (flow balancing, water quality monitoring, process modelling, multi-objective assessment) to systematically evaluate management strategies for water quality improvement. As key element, an S/P matrix is introduced to structure the differentiation of relevant 'pressures' in affected regions, i.e. 'spatial units', which helps in handling complexity. The framework is applied to a small, but typical, catchment in Flanders, Belgium. The application to the real-life case shows: (1) the proposed approach is adaptive, covers problems of different spatial and temporal scale, efficiently reduces complexity and finally leads to a transparent solution; and (2) water quality and emission-based performance evaluation must be done jointly as an emission-based performance improvement does not necessarily lead to an improved water quality status, and an assessment solely focusing on water quality criteria may mask non-compliance with emission-based standards. Recommendations derived from the theoretical analysis have been put into practice.

Numerical simulation of electrophoresis separation processes

NASA Technical Reports Server (NTRS)

Ganjoo, D. K.; Tezduyar, T. E.

1986-01-01

A new Petrov-Galerkin finite element formulation has been proposed for transient convection-diffusion problems. Most Petrov-Galerkin formulations take into account the spatial discretization, and the weighting functions so developed give satisfactory solutions for steady state problems. Though these schemes can be used for transient problems, there is scope for improvement. The schemes proposed here, which consider temporal as well as spatial discretization, provide improved solutions. Electrophoresis, which involves the motion of charged entities under the influence of an applied electric field, is governed by equations similiar to those encountered in fluid flow problems, i.e., transient convection-diffusion equations. Test problems are solved in electrophoresis and fluid flow. The results obtained are satisfactory. It is also expected that these schemes, suitably adapted, will improve the numerical solutions of the compressible Euler and the Navier-Stokes equations.

Multiple Scales in Fluid Dynamics and Meteorology: The DFG Priority Programme 1276 MetStröm

NASA Astrophysics Data System (ADS)

von Larcher, Th; Klein, R.

2012-04-01

Geophysical fluid motions are characterized by a very wide range of length and time scales, and by a rich collection of varying physical phenomena. The mathematical description of these motions reflects this multitude of scales and mechanisms in that it involves strong non-linearities and various scale-dependent singular limit regimes. Considerable progress has been made in recent years in the mathematical modelling and numerical simulation of such flows in detailed process studies, numerical weather forecasting, and climate research. One task of outstanding importance in this context has been and will remain for the foreseeable future the subgrid scale parameterization of the net effects of non-resolved processes that take place on spacio-temporal scales not resolvable even by the largest most recent supercomputers. Since the advent of numerical weather forecasting some 60 years ago, one simple but efficient means to achieve improved forecasting skills has been increased spacio-temporal resolution. This seems quite consistent with the concept of convergence of numerical methods in Applied Mathematics and Computational Fluid Dynamics (CFD) at a first glance. Yet, the very notion of increased resolution in atmosphere-ocean science is very different from the one used in Applied Mathematics: For the mathematician, increased resolution provides the benefit of getting closer to the ideal of a converged solution of some given partial differential equations. On the other hand, the atmosphere-ocean scientist would naturally refine the computational grid and adjust his mathematical model, such that it better represents the relevant physical processes that occur at smaller scales. This conceptual contradiction remains largely irrelevant as long as geophysical flow models operate with fixed computational grids and time steps and with subgrid scale parameterizations being optimized accordingly. The picture changes fundamentally when modern techniques from CFD involving spacio-temporal grid adaptivity get invoked in order to further improve the net efficiency in exploiting the given computational resources. In the setting of geophysical flow simulation one must then employ subgrid scale parameterizations that dynamically adapt to the changing grid sizes and time steps, implement ways to judiciously control and steer the newly available flexibility of resolution, and invent novel ways of quantifying the remaining errors. The DFG priority program MetStröm covers the expertise of Meteorology, Fluid Dynamics, and Applied Mathematics to develop model- as well as grid-adaptive numerical simulation concepts in multidisciplinary projects. The goal of this priority programme is to provide simulation models which combine scale-dependent (mathematical) descriptions of key physical processes with adaptive flow discretization schemes. Deterministic continuous approaches and discrete and/or stochastic closures and their possible interplay are taken into consideration. Research focuses on the theory and methodology of multiscale meteorological-fluid mechanics modelling. Accompanying reference experiments support model validation.

Individual Differences in Sentence Comprehension: A Functional Magnetic Resonance Imaging Investigation of Syntactic and Lexical Processing Demands

PubMed Central

Prat, Chantel S.; Keller, Timothy A.; Just, Marcel Adam

2008-01-01

Language comprehension is neurally underpinned by a network of collaborating cortical processing centers; individual differences in comprehension must be related to some set of this network’s properties. This study investigated the neural bases of individual differences during sentence comprehension by examining the network’s response to two variations in processing demands: reading sentences containing words of high versus low lexical frequency and having simpler versus more complex syntax. In a functional magnetic resonance imaging study, readers who were independently identified as having high or low working memory capacity for language exhibited three differentiating properties of their language network, namely, neural efficiency, adaptability, and synchronization. First, greater efficiency (defined as a reduction in activation associated with improved performance) was manifested as less activation in the bilateral middle frontal and right lingual gyri in high-capacity readers. Second, increased adaptability was indexed by larger lexical frequency effects in high-capacity readers across bilateral middle frontal, bilateral inferior occipital, and right temporal regions. Third, greater synchronization was observed in high-capacity readers between left temporal and left inferior frontal, left parietal, and right occipital regions. Synchronization interacted with adaptability, such that functional connectivity remained constant or increased with increasing lexical and syntactic demands in high-capacity readers, whereas low-capacity readers either showed no reliable differentiation or a decrease in functional connectivity with increasing demands. These results are among the first to relate multiple cortical network properties to individual differences in reading capacity and suggest a more general framework for understanding the relation between neural function and individual differences in cognitive performance. PMID:17892384

Individual differences in sentence comprehension: a functional magnetic resonance imaging investigation of syntactic and lexical processing demands.

PubMed

Prat, Chantel S; Keller, Timothy A; Just, Marcel Adam

2007-12-01

Language comprehension is neurally underpinned by a network of collaborating cortical processing centers; individual differences in comprehension must be related to some set of this network's properties. This study investigated the neural bases of individual differences during sentence comprehension by examining the network's response to two variations in processing demands: reading sentences containing words of high versus low lexical frequency and having simpler versus more complex syntax. In a functional magnetic resonance imaging study, readers who were independently identified as having high or low working memory capacity for language exhibited three differentiating properties of their language network, namely, neural efficiency, adaptability, and synchronization. First, greater efficiency (defined as a reduction in activation associated with improved performance) was manifested as less activation in the bilateral middle frontal and right lingual gyri in high-capacity readers. Second, increased adaptability was indexed by larger lexical frequency effects in high-capacity readers across bilateral middle frontal, bilateral inferior occipital, and right temporal regions. Third, greater synchronization was observed in high-capacity readers between left temporal and left inferior frontal, left parietal, and right occipital regions. Synchronization interacted with adaptability, such that functional connectivity remained constant or increased with increasing lexical and syntactic demands in high-capacity readers, whereas low-capacity readers either showed no reliable differentiation or a decrease in functional connectivity with increasing demands. These results are among the first to relate multiple cortical network properties to individual differences in reading capacity and suggest a more general framework for understanding the relation between neural function and individual differences in cognitive performance.

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

[Temporal perspective and other psychological factors making it difficult to adapt to requirements of treatment in chronic dialysis patients].

PubMed

Zawadzka, Barbara; Byrczek, Magdalena; Zawadzka, Sara

2014-01-01

The study analyzed the relationship between temporal perspective, selected personal resources, and unhealthy behavior, manifesting in problems with adherence to fluid intake restrictions, in chronic.hemodialyzis patients. The authors tried to answer the question whether there is temporal perspective and other psychological factors increasing the risk of non-adaptive behaviors. Sixty-one patients, aged 23-81 years (m = 59; SD = 13,9) on chronic hemodialysis at the Department of Nephrology University Hospital were qualified to the study. The study group consisted of 30 patients with poorer fluid regimen adherence and 31 con- trols, who maintained fluid regimen. The patients were qualified on the bases of the average interdialysis weight gains measured nine times during three weeks. The following research tools were used: P. Zimbardo and J. Boyd ZTPI test; P.T. Costa and R.R. McCrae NEO-FFI Inventory; J. Strelau Temperament Inventory, R. Schwarzer GSES; M. F. Scheier; C. S. Carver and M. W. Bridges LOT-R; M. Watson and S. Greer CECS; BJ. Felton, TA. Revenson, GA. Hinrichsen AIS. Difficulties in adapting to the fluid intake restrictions are significantly associated with temporal orientation towards negative aspects of the present and the past. Non-adaptive health behaviors are typical for patients with temperamental lack of balance between agitation and inhibition processes and are characterized by high agreeableness and low conscientious- ness. The association between excessive anger control and the risk of non-adherence medical recommendations. Time perception and other personality factors form mechanisms regulating health behaviors in chronically treatment patients.

Separate channels for the analysis of the shape and the movement of moving visual stimulus.

PubMed

Tolhurst, D J

1973-06-01

1. The effects of temporal modulation on the properties of spatial frequency channels have been investigated using adaptation.2. Adapting to drifting sinusoidal gratings caused threshold elevation that was both spatial frequency and direction specific. Little systematic difference was found between the band widths of the elevation curves for drifting and stationary gratings.3. It was confirmed that adaptation fails to reveal channels at low spatial frequencies when stationary gratings are used. However, channels were revealed at frequencies at least as low as 0.66 c/deg when the test gratings were made to move. These channels are adapted only a little by stationary gratings, confirming their dependence on movement.4. The existence of movement-sensitive channels at low spatial frequencies explains the well known observation that temporal modulation greatly increases the sensitivity of the visual system to low spatial frequencies.5. Temporal modulation was effective at revealing these channels only when the flicker or movement of the test patterns was apparent to the observer; only at low spatial frequencies did patterns, modulated at low rates, actually appear to be temporarily modulated at threshold. At higher spatial frequencies, they were indistinguishable from stationary patterns until the contrast was some way above the detection threshold.6. It is suggested, therefore, that the movement-sensitive channels are responsible for signalling the occurrence of movement; the channels at higher spatial frequencies give no information about temporal changes. These two systems of channels are compared to the Y- and X-cells respectively of the cat.

Concurrent validity of Zimbardo Time Perspective Inventory profiles: A secondary analysis of data from the United Kingdom.

PubMed

Worrell, Frank C; McKay, Michael T; Andretta, James R

2015-07-01

This paper examined the association between membership in profiles based on a shortened form of the Zimbardo Time Perspective Inventory (ZTPI-S; McKay, Andretta, McGee, & Worrell, 2014) and other temporal and psychosocial variables. Participants consisted of 1620 adolescents attending high school in Northern Ireland. ZTPI-S scores had correlations with other temporal and psychosocial variables that were similar to those reported for ZTPI scores in previous studies. Four ZTPI-S profiles were identified-Balanced, Past Negative, Present Hedonistic, and Future-and results indicated that these profiles had theoretically meaningful relationships with self-esteem, self-efficacy, aggression, parental attachment, consideration of future consequences, and future temporal focus. Unlike studies of college students where the Balanced profile was related to more adaptive functioning, the Future profile was related to more adaptive functioning. Future studies are needed to establish the generalizability of these profiles and to determine if there are developmental differences in which profiles are more adaptive. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. All rights reserved.

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Temporal sampling, resetting, and adaptation orchestrate gradient sensing in sperm

PubMed Central

Alvarez, Luis; Seifert, Reinhard; Gregor, Ingo; Jäckle, Oliver; Beyermann, Michael; Krause, Eberhard

2012-01-01

Sperm, navigating in a chemical gradient, are exposed to a periodic stream of chemoattractant molecules. The periodic stimulation entrains Ca2+ oscillations that control looping steering responses. It is not known how sperm sample chemoattractant molecules during periodic stimulation and adjust their sensitivity. We report that sea urchin sperm sampled molecules for 0.2–0.6 s before a Ca2+ response was produced. Additional molecules delivered during a Ca2+ response reset the cell by causing a pronounced Ca2+ drop that terminated the response; this reset was followed by a new Ca2+ rise. After stimulation, sperm adapted their sensitivity following the Weber–Fechner law. Taking into account the single-molecule sensitivity, we estimate that sperm can register a minimal gradient of 0.8 fM/µm and be attracted from as far away as 4.7 mm. Many microorganisms sense stimulus gradients along periodic paths to translate a spatial distribution of the stimulus into a temporal pattern of the cell response. Orchestration of temporal sampling, resetting, and adaptation might control gradient sensing in such organisms as well. PMID:22986497

Temporal sampling, resetting, and adaptation orchestrate gradient sensing in sperm.

PubMed

Kashikar, Nachiket D; Alvarez, Luis; Seifert, Reinhard; Gregor, Ingo; Jäckle, Oliver; Beyermann, Michael; Krause, Eberhard; Kaupp, U Benjamin

2012-09-17

Sperm, navigating in a chemical gradient, are exposed to a periodic stream of chemoattractant molecules. The periodic stimulation entrains Ca(2+) oscillations that control looping steering responses. It is not known how sperm sample chemoattractant molecules during periodic stimulation and adjust their sensitivity. We report that sea urchin sperm sampled molecules for 0.2-0.6 s before a Ca(2+) response was produced. Additional molecules delivered during a Ca(2+) response reset the cell by causing a pronounced Ca(2+) drop that terminated the response; this reset was followed by a new Ca(2+) rise. After stimulation, sperm adapted their sensitivity following the Weber-Fechner law. Taking into account the single-molecule sensitivity, we estimate that sperm can register a minimal gradient of 0.8 fM/µm and be attracted from as far away as 4.7 mm. Many microorganisms sense stimulus gradients along periodic paths to translate a spatial distribution of the stimulus into a temporal pattern of the cell response. Orchestration of temporal sampling, resetting, and adaptation might control gradient sensing in such organisms as well.

Prismatic Adaptation Induces Plastic Changes onto Spatial and Temporal Domains in Near and Far Space.

PubMed

Patané, Ivan; Farnè, Alessandro; Frassinetti, Francesca

2016-01-01

A large literature has documented interactions between space and time suggesting that the two experiential domains may share a common format in a generalized magnitude system (ATOM theory). To further explore this hypothesis, here we measured the extent to which time and space are sensitive to the same sensorimotor plasticity processes, as induced by classical prismatic adaptation procedures (PA). We also exanimated whether spatial-attention shifts on time and space processing, produced through PA, extend to stimuli presented beyond the immediate near space. Results indicated that PA affected both temporal and spatial representations not only in the near space (i.e., the region within which the adaptation occurred), but also in the far space. In addition, both rightward and leftward PA directions caused opposite and symmetrical modulations on time processing, whereas only leftward PA biased space processing rightward. We discuss these findings within the ATOM framework and models that account for PA effects on space and time processing. We propose that the differential and asymmetrical effects following PA may suggest that temporal and spatial representations are not perfectly aligned.

From molecular noise to behavioural variability in a single bacterium

NASA Astrophysics Data System (ADS)

Korobkova, Ekaterina; Emonet, Thierry; Vilar, Jose M. G.; Shimizu, Thomas S.; Cluzel, Philippe

2004-04-01

The chemotaxis network that governs the motion of Escherichia coli has long been studied to gain a general understanding of signal transduction. Although this pathway is composed of just a few components, it exhibits some essential characteristics of biological complexity, such as adaptation and response to environmental signals. In studying intracellular networks, most experiments and mathematical models have assumed that network properties can be inferred from population measurements. However, this approach masks underlying temporal fluctuations of intracellular signalling events. We have inferred fundamental properties of the chemotaxis network from a noise analysis of behavioural variations in individual bacteria. Here we show that certain properties established by population measurements, such as adapted states, are not conserved at the single-cell level: for timescales ranging from seconds to several minutes, the behaviour of non-stimulated cells exhibit temporal variations much larger than the expected statistical fluctuations. We find that the signalling network itself causes this noise and identify the molecular events that produce it. Small changes in the concentration of one key network component suppress temporal behavioural variability, suggesting that such variability is a selected property of this adaptive system.

A high speed model-based approach for wavefront sensorless adaptive optics systems

NASA Astrophysics Data System (ADS)

Lianghua, Wen; Yang, Ping; Shuai, Wang; Wenjing, Liu; Shanqiu, Chen; Xu, Bing

2018-02-01

To improve temporal-frequency property of wavefront sensorless adaptive optics (AO) systems, a fast general model-based aberration correction algorithm is presented. The fast general model-based approach is based on the approximately linear relation between the mean square of the aberration gradients and the second moment of far-field intensity distribution. The presented model-based method is capable of completing a mode aberration effective correction just applying one disturbing onto the deformable mirror(one correction by one disturbing), which is reconstructed by the singular value decomposing the correlation matrix of the Zernike functions' gradients. Numerical simulations of AO corrections under the various random and dynamic aberrations are implemented. The simulation results indicate that the equivalent control bandwidth is 2-3 times than that of the previous method with one aberration correction after applying N times disturbing onto the deformable mirror (one correction by N disturbing).

Fitting perception in and to cognition.

PubMed

Goldstone, Robert L; de Leeuw, Joshua R; Landy, David H

2015-02-01

Perceptual modules adapt at evolutionary, lifelong, and moment-to-moment temporal scales to better serve the informational needs of cognizers. Perceptual learning is a powerful way for an individual to become tuned to frequently recurring patterns in its specific local environment that are pertinent to its goals without requiring costly executive control resources to be deployed. Mechanisms like predictive coding, categorical perception, and action-informed vision allow our perceptual systems to interface well with cognition by generating perceptual outputs that are systematically guided by how they will be used. In classic conceptions of perceptual modules, people have access to the modules' outputs but no ability to adjust their internal workings. However, humans routinely and strategically alter their perceptual systems via training regimes that have predictable and specific outcomes. In fact, employing a combination of strategic and automatic devices for adapting perception is one of the most promising approaches to improving cognition. Copyright © 2014 Elsevier B.V. All rights reserved.

Model-based adaptive 3D sonar reconstruction in reverberating environments.

PubMed

Saucan, Augustin-Alexandru; Sintes, Christophe; Chonavel, Thierry; Caillec, Jean-Marc Le

2015-10-01

In this paper, we propose a novel model-based approach for 3D underwater scene reconstruction, i.e., bathymetry, for side scan sonar arrays in complex and highly reverberating environments like shallow water areas. The presence of multipath echoes and volume reverberation generates false depth estimates. To improve the resulting bathymetry, this paper proposes and develops an adaptive filter, based on several original geometrical models. This multimodel approach makes it possible to track and separate the direction of arrival trajectories of multiple echoes impinging the array. Echo tracking is perceived as a model-based processing stage, incorporating prior information on the temporal evolution of echoes in order to reject cluttered observations generated by interfering echoes. The results of the proposed filter on simulated and real sonar data showcase the clutter-free and regularized bathymetric reconstruction. Model validation is carried out with goodness of fit tests, and demonstrates the importance of model-based processing for bathymetry reconstruction.

Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

Efficient computation of the Grünwald-Letnikov fractional diffusion derivative using adaptive time step memory

NASA Astrophysics Data System (ADS)

MacDonald, Christopher L.; Bhattacharya, Nirupama; Sprouse, Brian P.; Silva, Gabriel A.

2015-09-01

Computing numerical solutions to fractional differential equations can be computationally intensive due to the effect of non-local derivatives in which all previous time points contribute to the current iteration. In general, numerical approaches that depend on truncating part of the system history while efficient, can suffer from high degrees of error and inaccuracy. Here we present an adaptive time step memory method for smooth functions applied to the Grünwald-Letnikov fractional diffusion derivative. This method is computationally efficient and results in smaller errors during numerical simulations. Sampled points along the system's history at progressively longer intervals are assumed to reflect the values of neighboring time points. By including progressively fewer points backward in time, a temporally 'weighted' history is computed that includes contributions from the entire past of the system, maintaining accuracy, but with fewer points actually calculated, greatly improving computational efficiency.

The circadian clock controls toll-like receptor 9-mediated innate and adaptive immunity

PubMed Central

Silver, Adam C.; Arjona, Alvaro; Walker, Wendy E.; Fikrig, Erol

2012-01-01

Circadian rhythms refer to biologic processes that oscillate with a period of approximately 24 hours. These rhythms are sustained by a molecular clock and provide a temporal matrix that ensures the coordination of homeostatic processes with the periodicity of environmental challenges. We demonstrate the circadian molecular clock controls the expression and function of toll like receptor 9 (TLR9). In a vaccination model using TLR9 ligand as adjuvant, mice immunized at the time of enhanced TLR9 responsiveness presented weeks later with an improved adaptive immune response. In a TLR9-dependent mouse model of sepsis, we found that disease severity was dependent on the timing of sepsis induction, coinciding with the daily changes in TLR9 expression and function. These findings unveil a direct molecular link between the circadian and innate immune systems with important implications for immunoprophylaxis and immunotherapy. PMID:22342842

Domain Adaptation Methods for Improving Lab-to-field Generalization of Cocaine Detection using Wearable ECG.

PubMed

Natarajan, Annamalai; Angarita, Gustavo; Gaiser, Edward; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin M

2016-09-01

Mobile health research on illicit drug use detection typically involves a two-stage study design where data to learn detectors is first collected in lab-based trials, followed by a deployment to subjects in a free-living environment to assess detector performance. While recent work has demonstrated the feasibility of wearable sensors for illicit drug use detection in the lab setting, several key problems can limit lab-to-field generalization performance. For example, lab-based data collection often has low ecological validity, the ground-truth event labels collected in the lab may not be available at the same level of temporal granularity in the field, and there can be significant variability between subjects. In this paper, we present domain adaptation methods for assessing and mitigating potential sources of performance loss in lab-to-field generalization and apply them to the problem of cocaine use detection from wearable electrocardiogram sensor data.

Temporal correlation coefficient for directed networks.

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

Previous studies dealing with network theory focused mainly on the static aggregation of edges over specific time window lengths. Thus, most of the dynamic information gets lost. To assess the quality of such a static aggregation the temporal correlation coefficient can be calculated. It measures the overall possibility for an edge to persist between two consecutive snapshots. Up to now, this measure is only defined for undirected networks. Therefore, we introduce the adaption of the temporal correlation coefficient to directed networks. This new methodology enables the distinction between ingoing and outgoing edges. Besides a small example network presenting the single calculation steps, we also calculated the proposed measurements for a real pig trade network to emphasize the importance of considering the edge direction. The farm types at the beginning of the pork supply chain showed clearly higher values for the outgoing temporal correlation coefficient compared to the farm types at the end of the pork supply chain. These farm types showed higher values for the ingoing temporal correlation coefficient. The temporal correlation coefficient is a valuable tool to understand the structural dynamics of these systems, as it assesses the consistency of the edge configuration. The adaption of this measure for directed networks may help to preserve meaningful additional information about the investigated network that might get lost if the edge directions are ignored.

Analyzing extreme sea levels for broad-scale impact and adaptation studies

NASA Astrophysics Data System (ADS)

Wahl, T.; Haigh, I. D.; Nicholls, R. J.; Arns, A.; Dangendorf, S.; Hinkel, J.; Slangen, A.

2017-12-01

Coastal impact and adaptation assessments require detailed knowledge on extreme sea levels (ESL), because increasing damage due to extreme events is one of the major consequences of sea-level rise (SLR) and climate change. Over the last few decades, substantial research efforts have been directed towards improved understanding of past and future SLR; different scenarios were developed with process-based or semi-empirical models and used for coastal impact studies at various temporal and spatial scales to guide coastal management and adaptation efforts. Uncertainties in future SLR are typically accounted for by analyzing the impacts associated with a range of scenarios and model ensembles. ESL distributions are then displaced vertically according to the SLR scenarios under the inherent assumption that we have perfect knowledge on the statistics of extremes. However, there is still a limited understanding of present-day ESL which is largely ignored in most impact and adaptation analyses. The two key uncertainties stem from: (1) numerical models that are used to generate long time series of storm surge water levels, and (2) statistical models used for determining present-day ESL exceedance probabilities. There is no universally accepted approach to obtain such values for broad-scale flood risk assessments and while substantial research has explored SLR uncertainties, we quantify, for the first time globally, key uncertainties in ESL estimates. We find that contemporary ESL uncertainties exceed those from SLR projections and, assuming that we meet the Paris agreement, the projected SLR itself by the end of the century. Our results highlight the necessity to further improve our understanding of uncertainties in ESL estimates through (1) continued improvement of numerical and statistical models to simulate and analyze coastal water levels and (2) exploit the rich observational database and continue data archeology to obtain longer time series and remove model bias. Finally, ESL uncertainties need to be integrated with SLR uncertainties. Otherwise, important improvements in providing more robust SLR projections are of less benefit for broad-scale impact and adaptation studies and decision processes.

Advanced Wavefront Control Techniques

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

Olivier, S S; Brase, J M; Avicola, K

2001-02-21

Programs at LLNL that involve large laser systems--ranging from the National Ignition Facility to new tactical laser weapons--depend on the maintenance of laser beam quality through precise control of the optical wavefront. This can be accomplished using adaptive optics, which compensate for time-varying aberrations that are often caused by heating in a high-power laser system. Over the past two decades, LLNL has developed a broad capability in adaptive optics technology for both laser beam control and high-resolution imaging. This adaptive optics capability has been based on thin deformable glass mirrors with individual ceramic actuators bonded to the back. In themore » case of high-power lasers, these adaptive optics systems have successfully improved beam quality. However, as we continue to extend our applications requirements, the existing technology base for wavefront control cannot satisfy them. To address this issue, this project studied improved modeling tools to increase our detailed understanding of the performance of these systems, and evaluated novel approaches to low-order wavefront control that offer the possibility of reduced cost and complexity. We also investigated improved beam control technology for high-resolution wavefront control. Many high-power laser systems suffer from high-spatial-frequency aberrations that require control of hundreds or thousands of phase points to provide adequate correction. However, the cost and size of current deformable mirrors can become prohibitive for applications requiring more than a few tens of phase control points. New phase control technologies are becoming available which offer control of many phase points with small low-cost devices. The goal of this project was to expand our wavefront control capabilities with improved modeling tools, new devices that reduce system cost and complexity, and extensions to high spatial and temporal frequencies using new adaptive optics technologies. In FY 99, the second year of this project, work was performed in four areas (1) advanced modeling tools for deformable mirrors (2) low-order wavefront correctors with Alvarez lenses, (3) a direct phase measuring heterdyne wavefront sensor, and (4) high-spatial-frequency wavefront control using spatial light modulators.« less

Secondary adaptation of memory-guided saccades

PubMed Central

Srimal, Riju; Curtis, Clayton E.

2011-01-01

Adaptation of saccade gains in response to errors keeps vision and action co-registered in the absence of awareness or effort. Timing is key, as the visual error must be available shortly after the saccade is generated or adaptation does not occur. Here, we tested the hypothesis that when feedback is delayed, learning still occurs, but does so through small secondary corrective saccades. Using a memory-guided saccade task, we gave feedback about the accuracy of saccades that was falsely displaced by a consistent amount, but only after long delays. Despite the delayed feedback, over time subjects improved in accuracy toward the false feedback. They did so not by adjusting their primary saccades, but via directed corrective saccades made before feedback was given. We propose that saccade learning may be driven by different types of feedback teaching signals. One teaching signal relies upon a tight temporal relation with the saccade and contributes to obligatory learning independent of awareness. When this signal is ineffective due to delayed error feedback, a second compensatory teaching signal enables flexible adjustments to the spatial goal of saccades and helps maintain sensorimotor accuracy. PMID:20803135

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles.

PubMed

Horne, Avril C; Szemis, Joanna M; Webb, J Angus; Kaur, Simranjit; Stewardson, Michael J; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles

NASA Astrophysics Data System (ADS)

Horne, Avril C.; Szemis, Joanna M.; Webb, J. Angus; Kaur, Simranjit; Stewardson, Michael J.; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

Performance assessment of MEMS adaptive optics in tactical airborne systems

NASA Astrophysics Data System (ADS)

Tyson, Robert K.

1999-09-01

Tactical airborne electro-optical systems are severely constrained by weight, volume, power, and cost. Micro- electrical-mechanical adaptive optics provide a solution that addresses the engineering realities without compromising spatial and temporal compensation requirements. Through modeling and analysis, we determined that substantial benefits could be gained for laser designators, ladar, countermeasures, and missile seekers. The developments potential exists for improving seeker imagery resolution 20 percent, extending countermeasures keep-out range by a factor of 5, doubling the range for ladar detection and identification, and compensating for supersonic and hypersonic aircraft boundary layers. Innovative concepts are required for atmospheric pat hand boundary layer compensation. We have developed design that perform these tasks using high speed scene-based wavefront sensing, IR aerosol laser guide stars, and extended-object wavefront beacons. We have developed a number of adaptive optics system configurations that met the spatial resolution requirements and we have determined that sensing and signal processing requirements can be met. With the help of micromachined deformable mirrors and sensor, we will be able to integrate the systems into existing airborne pods and missiles as well as next generation electro-optical systems.

Auditory temporal perceptual learning and transfer in Chinese-speaking children with developmental dyslexia.

PubMed

Zhang, Manli; Xie, Weiyi; Xu, Yanzhi; Meng, Xiangzhi

2018-03-01

Perceptual learning refers to the improvement of perceptual performance as a function of training. Recent studies found that auditory perceptual learning may improve phonological skills in individuals with developmental dyslexia in alphabetic writing system. However, whether auditory perceptual learning could also benefit the reading skills of those learning the Chinese logographic writing system is, as yet, unknown. The current study aimed to investigate the remediation effect of auditory temporal perceptual learning on Mandarin-speaking school children with developmental dyslexia. Thirty children with dyslexia were screened from a large pool of students in 3th-5th grades. They completed a series of pretests and then were assigned to either a non-training control group or a training group. The training group worked on a pure tone duration discrimination task for 7 sessions over 2 weeks with thirty minutes per session. Post-tests immediately after training and a follow-up test 2 months later were conducted. Analyses revealed a significant training effect in the training group relative to non-training group, as well as near transfer to the temporal interval discrimination task and far transfer to phonological awareness, character recognition and reading fluency. Importantly, the training effect and all the transfer effects were stable at the 2-month follow-up session. Further analyses found that a significant correlation between character recognition performance and learning rate mainly existed in the slow learning phase, the consolidation stage of perceptual learning, and this effect was modulated by an individuals' executive function. These findings indicate that adaptive auditory temporal perceptual learning can lead to learning and transfer effects on reading performance, and shed further light on the potential role of basic perceptual learning in the remediation and prevention of developmental dyslexia. Copyright © 2018 Elsevier Ltd. All rights reserved.

Climate-Smart Design for Ecosystem Management: A Test Application for Coral Reefs.

PubMed

West, Jordan M; Courtney, Catherine A; Hamilton, Anna T; Parker, Britt A; Julius, Susan H; Hoffman, Jennie; Koltes, Karen H; MacGowan, Petra

2017-01-01

The interactive and cumulative impacts of climate change on natural resources such as coral reefs present numerous challenges for conservation planning and management. Climate change adaptation is complex due to climate-stressor interactions across multiple spatial and temporal scales. This leaves decision makers worldwide faced with local, regional, and global-scale threats to ecosystem processes and services, occurring over time frames that require both near-term and long-term planning. Thus there is a need for structured approaches to adaptation planning that integrate existing methods for vulnerability assessment with design and evaluation of effective adaptation responses. The Corals and Climate Adaptation Planning project of the U.S. Coral Reef Task Force seeks to develop guidance for improving coral reef management through tailored application of a climate-smart approach. This approach is based on principles from a recently-published guide which provides a framework for adopting forward-looking goals, based on assessing vulnerabilities to climate change and applying a structured process to design effective adaptation strategies. Work presented in this paper includes: (1) examination of the climate-smart management cycle as it relates to coral reefs; (2) a compilation of adaptation strategies for coral reefs drawn from a comprehensive review of the literature; (3) in-depth demonstration of climate-smart design for place-based crafting of robust adaptation actions; and (4) feedback from stakeholders on the perceived usefulness of the approach. We conclude with a discussion of lessons-learned on integrating climate-smart design into real-world management planning processes and a call from stakeholders for an "adaptation design tool" that is now under development.

Reduced functional loads alter the physical characteristics of the bone-PDL-cementum complex

PubMed Central

Niver, Eric L.; Leong, Narita; Greene, Janelle; Curtis, Donald; Ryder, Mark I.; Ho, Sunita P.

2011-01-01

Background Adaptive properties of the bone-PDL-tooth complex have been identified by changing the magnitude of functional loads using small-scale animal models such as rodents. Reported adaptive responses as a result of lower loads due to softer diet include decreased muscle development, change in structure-function relationship of the cranium, narrowed PDL-space, changes in mineral level of the cortical bone and alveolar jaw bone, and glycosaminoglycans of the alveolar bone. However, the adaptive role of the dynamic bone-PDL-cementum complex due to prolonged reduced loads has not been fully explained to date, especially with regards to concurrent adaptations of bone, PDL and cementum. Hence, the temporal effect of reduced functional loads on physical characteristics such as morphology and mechanical properties, and mineral profiles of the bone-periodontal ligament (PDL)-cementum complex using a rat model was investigated. Materials and Methods Two groups of six-week-old male Sprague-Dawley rats were fed nutritionally identical food with a stiffness range of 127–158N/mm for hard pellet or 0.32–0.47N/mm for soft powder forms. Spatio-temporal adaptation of the bone-PDL-cementum complex was identified by mapping changes in: 1) PDL-collagen orientation and birefringence using polarized light microscopy, bone and cementum adaptation using histochemistry, and bone and cementum morphology using micro X-ray computed tomography, 2) mineral profiles of the PDL-cementum and PDL-bone interfaces by X-ray attenuation, and 3) microhardness of bone and cementum by microindentation of specimens at ages six, eight, twelve, and fifteen weeks. Results Reduced functional loads over prolonged time resulted in 1) altered PDL orientation and decreased PDL collagen birefringence indicating decreased PDL turnover rate and decreased apical cementum resorption; 2) a gradual increase in X-ray attenuation, owing to mineral differences, at the PDL-bone and PDL-cementum interfaces without significant differences in the gradients for either group; 3) significantly (p<0.05) lower microhardness of alveolar bone (0.93±0.16 GPa) and secondary cementum (0.803±0.13 GPa) compared to the higher load group (1.10±0.17 GPa and 0.940±0.15 GPa respectively) at fifteen weeks indicating a temporal effect of loads on local mineralization of bone and cementum. Conclusions Based on the results from this study, the effect of reduced functional loads for a prolonged time could differentially affect morphology and mechanical properties, and mineral variations and of the local load-bearing sites in a bone-PDL-cementum complex. These observed local changes in turn could help explain the overall biomechanical function and adaptations of the tooth-bone joint. From a clinical translation perspective, our study provides an insight into modulation of load on the complex for improved tooth function during periodontal disease, and/or orthodontic and prosthodontic treatments. PMID:21848615

Wave Mode Discrimination of Coded Ultrasonic Guided Waves Using Two-Dimensional Compressed Pulse Analysis.

PubMed

Malo, Sergio; Fateri, Sina; Livadas, Makis; Mares, Cristinel; Gan, Tat-Hean

2017-07-01

Ultrasonic guided waves testing is a technique successfully used in many industrial scenarios worldwide. For many complex applications, the dispersive nature and multimode behavior of the technique still poses a challenge for correct defect detection capabilities. In order to improve the performance of the guided waves, a 2-D compressed pulse analysis is presented in this paper. This novel technique combines the use of pulse compression and dispersion compensation in order to improve the signal-to-noise ratio (SNR) and temporal-spatial resolution of the signals. The ability of the technique to discriminate different wave modes is also highlighted. In addition, an iterative algorithm is developed to identify the wave modes of interest using adaptive peak detection to enable automatic wave mode discrimination. The employed algorithm is developed in order to pave the way for further in situ applications. The performance of Barker-coded and chirp waveforms is studied in a multimodal scenario where longitudinal and flexural wave packets are superposed. The technique is tested in both synthetic and experimental conditions. The enhancements in SNR and temporal resolution are quantified as well as their ability to accurately calculate the propagation distance for different wave modes.

A time series based sequence prediction algorithm to detect activities of daily living in smart home.

PubMed

Marufuzzaman, M; Reaz, M B I; Ali, M A M; Rahman, L F

2015-01-01

The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included. The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge. The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED. Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Characterization of the Mineral Trioxide Aggregate–Resin Modified Glass Ionomer Cement Interface in Different Setting Conditions

PubMed Central

Eid, Ashraf A.; Komabayashi, Takashi; Watanabe, Etsuko; Shiraishi, Takanobu; Watanabe, Ikuya

2012-01-01

Introduction Mineral trioxide aggregate (MTA) has been used successfully for perforation repair, vital pulpotomies, and direct pulp capping. However, little is known about the interactions between MTA and glass ionomer cement (GIC) in final restorations. In this study, 2 null hypotheses were tested: (1) GIC placement time does not affect the MTA-GIC structural interface and hardness and (2) moisture does not affect the MTA-GIC structural interface and hardness. Methods Fifty cylinders were half filled with MTA and divided into 5 groups. The other half was filled with resin-modified GIC either immediately after MTA placement or after 1 or 7 days of temporization in the presence or absence of a wet cotton pellet. The specimens were then sectioned, carbon coated, and examined using a scanning electron microscope and an electron probe micro-analyzer (SEM-EPMA) for interfacial adaptation, gap formation, and elemental analysis. The Vickers hardness numbers of the interfacial MTA were recorded 24 hours after GIC placement and 8 days after MTA placement and analyzed using the analysis of variance test. Results Hardness testing 24 hours after GIC placement revealed a significant increase in hardness with an increase of temporization time but not with a change of moisture conditions (P < .05). Hardness testing 8 days after MTA placement indicated no significant differences among groups. SEM-EPMA showed interfacial adaptation to improve with temporization time and moisture. Observed changes were limited to the outermost layer of MTA. The 2 null hypotheses were not rejected. Conclusions GIC can be applied over freshly mixed MTA with minimal effects on the MTA, which seemed to decrease with time. PMID:22794220

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

A pipeline of spatio-temporal filtering for predicting the laterality of self-initiated fine movements from single trial readiness potentials.

PubMed

Zeid, Elias Abou; Sereshkeh, Alborz Rezazadeh; Chau, Tom

2016-12-01

In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have attempted single trial classification of RP via spatial and temporal filtering methods, or by combining the RP with event-related desynchronization. However, RP feature extraction remains challenging due to the slow non-oscillatory nature of the potential, its variability among participants and the inherent noise in EEG signals. Here, we propose a participant-specific, individually optimized pipeline of spatio-temporal filtering (PSTF) to improve RP feature extraction for laterality prediction. PSTF applies band-pass filtering on RP signals, followed by Fisher criterion spatial filtering to maximize class separation, and finally temporal window averaging for feature dimension reduction. Optimal parameters are simultaneously found by cross-validation for each participant. Using EEG data from 14 participants performing self-initiated left or right key presses as well as two benchmark BCI datasets, we compared the performance of PSTF to two popular methods: common spatial subspace decomposition, and adaptive spatio-temporal filtering. On the BCI benchmark data sets, PSTF performed comparably to both existing methods. With the key press EEG data, PSTF extracted more discriminative features, thereby leading to more accurate (74.99% average accuracy) predictions of RP laterality than that achievable with existing methods. Naturalistic and volitional interaction with the world is an important capacity that is lost with traditional system-paced BCIs. We demonstrated a significant improvement in fine movement laterality prediction from RP features alone. Our work supports further study of RP-based BCI for intuitive asynchronous control of the environment, such as augmentative communication or wheelchair navigation.

A pipeline of spatio-temporal filtering for predicting the laterality of self-initiated fine movements from single trial readiness potentials

NASA Astrophysics Data System (ADS)

Abou Zeid, Elias; Rezazadeh Sereshkeh, Alborz; Chau, Tom

2016-12-01

Objective. In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have attempted single trial classification of RP via spatial and temporal filtering methods, or by combining the RP with event-related desynchronization. However, RP feature extraction remains challenging due to the slow non-oscillatory nature of the potential, its variability among participants and the inherent noise in EEG signals. Here, we propose a participant-specific, individually optimized pipeline of spatio-temporal filtering (PSTF) to improve RP feature extraction for laterality prediction. Approach. PSTF applies band-pass filtering on RP signals, followed by Fisher criterion spatial filtering to maximize class separation, and finally temporal window averaging for feature dimension reduction. Optimal parameters are simultaneously found by cross-validation for each participant. Using EEG data from 14 participants performing self-initiated left or right key presses as well as two benchmark BCI datasets, we compared the performance of PSTF to two popular methods: common spatial subspace decomposition, and adaptive spatio-temporal filtering. Main results. On the BCI benchmark data sets, PSTF performed comparably to both existing methods. With the key press EEG data, PSTF extracted more discriminative features, thereby leading to more accurate (74.99% average accuracy) predictions of RP laterality than that achievable with existing methods. Significance. Naturalistic and volitional interaction with the world is an important capacity that is lost with traditional system-paced BCIs. We demonstrated a significant improvement in fine movement laterality prediction from RP features alone. Our work supports further study of RP-based BCI for intuitive asynchronous control of the environment, such as augmentative communication or wheelchair navigation.

Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring.

PubMed

Wu, Mingquan; Li, Hua; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-01

There is a shortage of daily high spatial land surface temperature (LST) data for use in high spatial and temporal resolution environmental process monitoring. To address this shortage, this work used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and the Spatial and Temporal Data Fusion Approach (STDFA) to estimate high spatial and temporal resolution LST by combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST and Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The actual ASTER LST products were used to evaluate the precision of the combined LST images using the correlation analysis method. This method was tested and validated in study areas located in Gansu Province, China. The results show that all the models can generate daily synthetic LST image with a high correlation coefficient (r) of 0.92 between the synthetic image and the actual ASTER LST observations. The ESTARFM has the best performance, followed by the STDFA and the STARFM. Those models had better performance in desert areas than in cropland. The STDFA had better noise immunity than the other two models.

Optimizing the general linear model for functional near-infrared spectroscopy: an adaptive hemodynamic response function approach

PubMed Central

Uga, Minako; Dan, Ippeita; Sano, Toshifumi; Dan, Haruka; Watanabe, Eiju

2014-01-01

Abstract. An increasing number of functional near-infrared spectroscopy (fNIRS) studies utilize a general linear model (GLM) approach, which serves as a standard statistical method for functional magnetic resonance imaging (fMRI) data analysis. While fMRI solely measures the blood oxygen level dependent (BOLD) signal, fNIRS measures the changes of oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb) signals at a temporal resolution severalfold higher. This suggests the necessity of adjusting the temporal parameters of a GLM for fNIRS signals. Thus, we devised a GLM-based method utilizing an adaptive hemodynamic response function (HRF). We sought the optimum temporal parameters to best explain the observed time series data during verbal fluency and naming tasks. The peak delay of the HRF was systematically changed to achieve the best-fit model for the observed oxy- and deoxy-Hb time series data. The optimized peak delay showed different values for each Hb signal and task. When the optimized peak delays were adopted, the deoxy-Hb data yielded comparable activations with similar statistical power and spatial patterns to oxy-Hb data. The adaptive HRF method could suitably explain the behaviors of both Hb parameters during tasks with the different cognitive loads during a time course, and thus would serve as an objective method to fully utilize the temporal structures of all fNIRS data. PMID:26157973

A novel visual saliency detection method for infrared video sequences

NASA Astrophysics Data System (ADS)

Wang, Xin; Zhang, Yuzhen; Ning, Chen

2017-12-01

Infrared video applications such as target detection and recognition, moving target tracking, and so forth can benefit a lot from visual saliency detection, which is essentially a method to automatically localize the ;important; content in videos. In this paper, a novel visual saliency detection method for infrared video sequences is proposed. Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered. For spatial saliency, we adopt a mutual consistency-guided spatial cues combination-based method to capture the regions with obvious luminance contrast and contour features. For temporal saliency, a multi-frame symmetric difference approach is proposed to discriminate salient moving regions of interest from background motions. Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy. Besides, to highlight the spatiotemporal salient regions uniformly, a multi-scale fusion approach is embedded into the spatiotemporal saliency model. Finally, a Gestalt theory-inspired optimization algorithm is designed to further improve the reliability of the final saliency map. Experimental results demonstrate that our method outperforms many state-of-the-art saliency detection approaches for infrared videos under various backgrounds.

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

NASA Technical Reports Server (NTRS)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Observations to support adaptation: Principles, scales and decision-making

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2012-12-01

As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks including overcoming unrealistically precise information demands. While monitoring systems design and operation should be guided by the standards and requirements of management, those who provide information to the system (e.g. hydromet services) should also derive benefits. Drawing on identified information needs to support climate risk management (in drought, water resources and other areas) we outline principles of effective monitoring and develop preliminary strategic guidance for information systems being developed through the GEO, GCOS and Global and national frameworks for climate services. The efficacy of such services are improved by a problem-solving orientation, participatory planning, extension management and improvements in the use and value of existing data to legitimize new investments.

Value of Information for Optimal Adaptive Routing in Stochastic Time-Dependent Traffic Networks: Algorithms and Computational Tools

DOT National Transportation Integrated Search

2010-10-25

Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...

Spatial and Temporal Visual Masking and Visibility.

DTIC Science & Technology

1982-10-01

but is generally enhanced by nonzero adaptation ,7elocities. The enchancement occurs irrespective of direction of motion of the adapt and test...with monochrome images, which are then presented in full czlor. It cannot be used with natural color images, ncr with monochrome images presented in

Reduced functional loads alter the physical characteristics of the bone-periodontal ligament-cementum complex.

PubMed

Niver, E L; Leong, N; Greene, J; Curtis, D; Ryder, M I; Ho, S P

2011-12-01

Adaptive properties of the bone-periodontal ligament-tooth complex have been identified by changing the magnitude of functional loads using small-scale animal models, such as rodents. Reported adaptive responses as a result of lower loads due to softer diet include decreased muscle development, change in structure-function relationship of the cranium, narrowed periodontal ligament space, and changes in the mineral level of the cortical bone and alveolar jaw bone and in the glycosaminoglycans of the alveolar bone. However, the adaptive role of the dynamic bone-periodontal ligament-cementum complex to prolonged reduced loads has not been fully explained to date, especially with regard to concurrent adaptations of bone, periodontal ligament and cementum. Therefore, in the present study, using a rat model, the temporal effect of reduced functional loads on physical characteristics, such as morphology and mechanical properties and the mineral profiles of the bone-periodontal ligament-cementum complex was investigated. Two groups of 6-wk-old male Sprague-Dawley rats were fed nutritionally identical food with a stiffness range of 127-158 N/mm for hard pellet or 0.3-0.5 N/mm for soft powder forms. Spatio-temporal adaptation of the bone-periodontal ligament-cementum complex was identified by mapping changes in the following: (i) periodontal ligament collagen orientation and birefringence using polarized light microscopy, bone and cementum adaptation using histochemistry, and bone and cementum morphology using micro-X-ray computed tomography; (ii) mineral profiles of the periodontal ligament-cementum and periodontal ligament-bone interfaces by X-ray attenuation; and (iii) microhardness of bone and cementum by microindentation of specimens at ages 6, 8, 12 and 15 wk. Reduced functional loads over prolonged time resulted in the following adaptations: (i) altered periodontal ligament orientation and decreased periodontal ligament collagen birefringence, indicating decreased periodontal ligament turnover rate and decreased apical cementum resorption; (ii) a gradual increase in X-ray attenuation, owing to mineral differences, at the periodontal ligament-bone and periodontal ligament-cementum interfaces, without significant differences in the gradients for either group; (iii) significantly (p < 0.05) lower microhardness of alveolar bone (0.93 ± 0.16 GPa) and secondary cementum (0.803 ± 0.13 GPa) compared with the higher load group insert bone = (1.10 ± 0.17 and cementum = 0.940 ± 0.15 GPa, respectively) at 15 wk, indicating a temporal effect of loads on the local mineralization of bone and cementum. Based on the results from this study, the effect of reduced functional loads for a prolonged time could differentially affect morphology, mechanical properties and mineral variations of the local load-bearing sites in the bone-periodontal ligament-cementum complex. These observed local changes in turn could help to explain the overall biomechanical function and adaptations of the tooth-bone joint. From a clinical translation perspective, our study provides an insight into modulation of load on the complex for improved tooth function during periodontal disease and/or orthodontic and prosthodontic treatments. © 2011 John Wiley & Sons A/S.

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...

Global References, Local Translation: Adaptation of the Bologna Process Degree Structure and Credit System at Universities in Cameroon

ERIC Educational Resources Information Center

Eta, Elizabeth Agbor; Vubo, Emmanuel Yenshu

2016-01-01

This article uses temporal comparison and thematic analytical approaches to analyse text documents and interviews, examining the adaptation of the Bologna Process degree structure and credit system in two sub-systems of education in Cameroon: the Anglo-Saxon and the French systems. The central aim is to verify whether such adaptation has replaced,…

Using the Cn2 and wind profiler method with wide-field laser-guide-stars adaptive optics to quantify the frozen-flow decay

NASA Astrophysics Data System (ADS)

Guesalaga, Andrés; Neichel, Benoit; Cortés, Angela; Béchet, Clémentine; Guzmán, Dani

2014-05-01

We use the spatio-temporal cross-correlations of slopes from five Shack-Hartmann wavefront sensors to analyse the temporal evolution of the atmospheric turbulence layers at different altitudes. The focus is on the verification of the frozen-flow assumption. The data come from the Gemini South Multiconjugate Adaptive Optics System (GeMS). First, we present the Cn2 and wind profiling technique. This method provides useful information for the operation of the adaptive optics system, such as the number of existing turbulence layers, their associated velocities, altitudes and strengths, and also a mechanism to estimate the dome-seeing contribution to the total turbulence. Next, by identifying the turbulence layers, we show that it is possible to estimate the rate of decay in time of the correlation among turbulence measurements. We reduce on-sky data obtained during the 2011, 2012 and 2013 campaigns. The first results suggest that the rate of temporal decorrelation can be expressed in terms of a single parameter that is independent of the layer altitude and turbulence strength. Finally, we show that the decay rate of the frozen-flow contribution increases linearly with the layer speed. The observed evolution of the decay rate confirms the potential interest of the predictive control for wide-field adaptive optics systems.

On the sub-model errors of a generalized one-way coupling scheme for linking models at different scales

NASA Astrophysics Data System (ADS)

Zeng, Jicai; Zha, Yuanyuan; Zhang, Yonggen; Shi, Liangsheng; Zhu, Yan; Yang, Jinzhong

2017-11-01

Multi-scale modeling of the localized groundwater flow problems in a large-scale aquifer has been extensively investigated under the context of cost-benefit controversy. An alternative is to couple the parent and child models with different spatial and temporal scales, which may result in non-trivial sub-model errors in the local areas of interest. Basically, such errors in the child models originate from the deficiency in the coupling methods, as well as from the inadequacy in the spatial and temporal discretizations of the parent and child models. In this study, we investigate the sub-model errors within a generalized one-way coupling scheme given its numerical stability and efficiency, which enables more flexibility in choosing sub-models. To couple the models at different scales, the head solution at parent scale is delivered downward onto the child boundary nodes by means of the spatial and temporal head interpolation approaches. The efficiency of the coupling model is improved either by refining the grid or time step size in the parent and child models, or by carefully locating the sub-model boundary nodes. The temporal truncation errors in the sub-models can be significantly reduced by the adaptive local time-stepping scheme. The generalized one-way coupling scheme is promising to handle the multi-scale groundwater flow problems with complex stresses and heterogeneity.

Differential face-network adaptation in children, adolescents and adults.

PubMed

Cohen Kadosh, Kathrin; Johnson, Mark H; Henson, Richard N A; Dick, Frederic; Blakemore, Sarah-Jayne

2013-04-01

Faces are complex social stimuli, which can be processed both at the categorical and the individual level. Behavioral studies have shown that children take more than a decade of exposure and training to become proficient at processing faces at the individual level. The neurodevelopmental trajectories for different aspects of face-processing are still poorly understood. In this study, we used an fMR-adaptation design to investigate differential processing of three face aspects (identity, expression and gaze) in children, adolescents and adults. We found that, while all three tasks showed some overlap in activation patterns, there was a significant age effect in the occipital and temporal lobes and the inferior frontal gyrus. More importantly, the degree of adaptation differed across the three age groups in the inferior occipital gyrus, a core face processing area that has been shown in previous studies to be both integral and necessary for individual-level face processing. In the younger children, adaptation in this region seemed to suggest the use of a predominantly featural processing strategy, whereas adaptation effects in the adults exhibited a more strategic pattern that depended on the task. Interestingly, our sample of adolescents did not exhibit any differential adaptation effects; possibly reflecting increased heterogeneity in processing strategies in this age group. Our results support the notion that, in line with improving behavioral face-processing abilities, core face-responsive regions develop throughout the first two decades of life. Copyright © 2012 Elsevier Inc. All rights reserved.

Computational memory architectures for autobiographic agents interacting in a complex virtual environment: a working model

NASA Astrophysics Data System (ADS)

Ho, Wan Ching; Dautenhahn, Kerstin; Nehaniv, Chrystopher

2008-03-01

In this paper, we discuss the concept of autobiographic agent and how memory may extend an agent's temporal horizon and increase its adaptability. These concepts are applied to an implementation of a scenario where agents are interacting in a complex virtual artificial life environment. We present computational memory architectures for autobiographic virtual agents that enable agents to retrieve meaningful information from their dynamic memories which increases their adaptation and survival in the environment. The design of the memory architectures, the agents, and the virtual environment are described in detail. Next, a series of experimental studies and their results are presented which show the adaptive advantage of autobiographic memory, i.e. from remembering significant experiences. Also, in a multi-agent scenario where agents can communicate via stories based on their autobiographic memory, it is found that new adaptive behaviours can emerge from an individual's reinterpretation of experiences received from other agents whereby higher communication frequency yields better group performance. An interface is described that visualises the memory contents of an agent. From an observer perspective, the agents' behaviours can be understood as individually structured, and temporally grounded, and, with the communication of experience, can be seen to rely on emergent mixed narrative reconstructions combining the experiences of several agents. This research leads to insights into how bottom-up story-telling and autobiographic reconstruction in autonomous, adaptive agents allow temporally grounded behaviour to emerge. The article concludes with a discussion of possible implications of this research direction for future autobiographic, narrative agents.

HyCAW: Hydrological Climate change Adaptation Wizard

NASA Astrophysics Data System (ADS)

Bagli, Stefano; Mazzoli, Paolo; Broccoli, Davide; Luzzi, Valerio

2016-04-01

Changes in temporal and total water availability due to hydrologic and climate change requires an efficient use of resources through the selection of the best adaptation options. HyCAW provides a novel service to users willing or needing to adapt to hydrological change, by turning available scientific information into a user friendly online wizard that lets to: • Evaluate the monthly reduction of water availability induced by climate change; • Select the best adaptation options and visualize the benefits in terms of water balance and cost reduction; • Quantify potential of water saving by improving of water use efficiency. The tool entails knowledge of the intra-annual distribution of available surface and groundwater flows at a site under present and future (climate change) scenarios. This information is extracted from long term scenario simulation by E-HYPE (European hydrological predictions for the environment) model from Swedish Meteorological and Hydrological Institute, to quantify the expected evolution in water availability (e.g. percent reduction of soil infiltration and aquifer recharge; relative seasonal shift of runoff from summer to winter in mountain areas; etc.). Users are requested to provide in input their actual water supply on a monthly basis, both from surface and groundwater sources. Appropriate decision trees and an embedded precompiled database of Water saving technology for different sectors (household, agriculture, industrial, tourisms) lead them to interactively identify good practices for water saving/recycling/harvesting that they may implement in their specific context. Thanks to this service, users are not required to have a detailed understanding neither of data nor of hydrological processes, but may benefit of scientific analysis directly for practical adaptation in a simple and user friendly way, effectively improving their adaptation capacity. The tool is being developed under a collaborative FP7 funded project called SWITCH-ON (EU FP7 project No 603587) coordinated by SMHI (http://water-switch-on.eu/) and online demo is available at www.gecosistema.com/switchon

Learning of spatio-temporal codes in a coupled oscillator system.

PubMed

Orosz, Gábor; Ashwin, Peter; Townley, Stuart

2009-07-01

In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

Local adaptation in transgenerational responses to predators

PubMed Central

Walsh, Matthew R.; Castoe, Todd; Holmes, Julian; Packer, Michelle; Biles, Kelsey; Walsh, Melissa; Munch, Stephan B.; Post, David M.

2016-01-01

Environmental signals can induce phenotypic changes that span multiple generations. Along with phenotypic responses that occur during development (i.e. ‘within-generation’ plasticity), such ‘transgenerational plasticity’ (TGP) has been documented in a diverse array of taxa spanning many environmental perturbations. New theory predicts that temporal stability is a key driver of the evolution of TGP. We tested this prediction using natural populations of zooplankton from lakes in Connecticut that span a large gradient in the temporal dynamics of predator-induced mortality. We reared more than 120 clones of Daphnia ambigua from nine lakes for multiple generations in the presence/absence of predator cues. We found that temporal variation in mortality selects for within-generation plasticity while consistently strong (or weak) mortality selects for increased TGP. Such results provide us the first evidence for local adaptation in TGP and argue that divergent ecological conditions select for phenotypic responses within and across generations. PMID:26817775

Eye movements show similar adaptations in temporal coordination to movement planning conditions in both people with and without cerebral palsy.

PubMed

Payne, Alexander R; Plimmer, Beryl; McDaid, Andrew; Davies, T Claire

2017-05-01

The effects of cerebral palsy on movement planning for simple reaching tasks are not well understood. Movement planning is complex and entails many processes which could be affected. This study specifically sought to evaluate integrating task information, decoupling movements, and adjusting to altered mapping. For a reaching task, the asynchrony between the eye onset and the hand onset was measured across different movement planning conditions for participants with and without cerebral palsy. Previous research shows people without cerebral palsy vary this temporal coordination for different planning conditions. Our measurements show similar adaptations in temporal coordination for groups with and without cerebral palsy, to three of the four variations in planning condition tested. However, movement durations were still longer for the participants with cerebral palsy. Hence for simple goal-directed reaching, movement execution problems appear to limit activity more than movement planning deficits.

Rapid temporal recalibration is unique to audiovisual stimuli.

PubMed

Van der Burg, Erik; Orchard-Mills, Emily; Alais, David

2015-01-01

Following prolonged exposure to asynchronous multisensory signals, the brain adapts to reduce the perceived asynchrony. Here, in three separate experiments, participants performed a synchrony judgment task on audiovisual, audiotactile or visuotactile stimuli and we used inter-trial analyses to examine whether temporal recalibration occurs rapidly on the basis of a single asynchronous trial. Even though all combinations used the same subjects, task and design, temporal recalibration occurred for audiovisual stimuli (i.e., the point of subjective simultaneity depended on the preceding trial's modality order), but none occurred when the same auditory or visual event was combined with a tactile event. Contrary to findings from prolonged adaptation studies showing recalibration for all three combinations, we show that rapid, inter-trial recalibration is unique to audiovisual stimuli. We conclude that recalibration occurs at two different timescales for audiovisual stimuli (fast and slow), but only on a slow timescale for audiotactile and visuotactile stimuli.

Building entity models through observation and learning

NASA Astrophysics Data System (ADS)

Garcia, Richard; Kania, Robert; Fields, MaryAnne; Barnes, Laura

2011-05-01

To support the missions and tasks of mixed robotic/human teams, future robotic systems will need to adapt to the dynamic behavior of both teammates and opponents. One of the basic elements of this adaptation is the ability to exploit both long and short-term temporal data. This adaptation allows robotic systems to predict/anticipate, as well as influence, future behavior for both opponents and teammates and will afford the system the ability to adjust its own behavior in order to optimize its ability to achieve the mission goals. This work is a preliminary step in the effort to develop online entity behavior models through a combination of learning techniques and observations. As knowledge is extracted from the system through sensor and temporal feedback, agents within the multi-agent system attempt to develop and exploit a basic movement model of an opponent. For the purpose of this work, extraction and exploitation is performed through the use of a discretized two-dimensional game. The game consists of a predetermined number of sentries attempting to keep an unknown intruder agent from penetrating their territory. The sentries utilize temporal data coupled with past opponent observations to hypothesize the probable locations of the opponent and thus optimize their guarding locations.

Temporal resolution in children.

PubMed

Wightman, F; Allen, P; Dolan, T; Kistler, D; Jamieson, D

1989-06-01

The auditory temporal resolving power of young children was measured using an adaptive forced-choice psychophysical paradigm that was disguised as a video game. 20 children between 3 and 7 years of age and 5 adults were asked to detect the presence of a temporal gap in a burst of half-octave-band noise at band center frequencies of 400 and 2,000 Hz. The minimum detectable gap (gap threshold) was estimated adaptively in 20-trial runs. The mean gap thresholds in the 400-Hz condition were higher for the younger children than for the adults, with the 3-year-old children producing the highest thresholds. Gap thresholds in the 2,000-Hz condition were generally lower than in the 400-Hz condition and showed a similar age effect. All the individual adaptive runs were "adult-like," suggesting that the children were generally attentive to the task during each run. However, the variability of threshold estimates from run to run was substantial, especially in the 3-5-year-old children. Computer simulations suggested that this large within-subjects variability could have resulted from frequent, momentary lapses of attention, which would lead to "guessing" on a substantial portion of the trials.

Adaptation to Cognitive Context and Item Information in the Medial Temporal Lobes

ERIC Educational Resources Information Center

Diana, Rachel A.; Yonelinas, Andrew P.; Ranganath, Charan

2012-01-01

The medial temporal lobes (MTL) play an essential role in episodic memory, and accumulating evidence indicates that two MTL subregions--the perirhinal (PRc) and parahippocampal (PHc) cortices--might have different functions. According to the binding of item and context theory ( [16] and [21]), PRc is involved in processing item information, the…

A hyper-temporal remote sensing protocol for detecting ecosystem disturbance, classifying ecological state, and assessing soil resilience

USDA-ARS?s Scientific Manuscript database

Hyper-temporal remote sensing is capable of detecting detailed information on vegetation dynamics relating to plant functional types (PFT), a useful proxy for estimating soil physical and chemical properties. A central concept of PFT is that plant morphological and physiological adaptations are link...

Facilitating insights with a user adaptable dashboard, illustrated by airport connectivity data

NASA Astrophysics Data System (ADS)

Dobraja, Ieva; Kraak, Menno-Jan; Engelhardt, Yuri

2018-05-01

Since the movement data exist, there have been approaches to collect and analyze them to get insights. This kind of data is often heterogeneous, multiscale and multi-temporal. Those interested in spatio-temporal patterns of movement data do not gain insights from textual descriptions. Therefore, visualization is required. As spatio-temporal movement data can be complex because size and characteristics, it is even challenging to create an overview of it. Plotting all the data on the screen will not be the solution as it likely will result into cluttered images where no data exploration is possible. To ensure that users will receive the information they are interested in, it is important to provide a graphical data representation environment where exploration to gain insights are possible not only in the overall level but at sub-levels as well. A dashboard would be a solution the representation of heterogeneous spatio- temporal data. It provides an overview and helps to unravel the complexity of data by splitting data in multiple data representation views. The adaptability of dashboard will help to reveal the information which cannot be seen in the overview.

Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows

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

Bent, Russell W

This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositionsmore » which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions.« less

Neural network for processing both spatial and temporal data with time based back-propagation

NASA Technical Reports Server (NTRS)

Villarreal, James A. (Inventor); Shelton, Robert O. (Inventor)

1993-01-01

Neural networks are computing systems modeled after the paradigm of the biological brain. For years, researchers using various forms of neural networks have attempted to model the brain's information processing and decision-making capabilities. Neural network algorithms have impressively demonstrated the capability of modeling spatial information. On the other hand, the application of parallel distributed models to the processing of temporal data has been severely restricted. The invention introduces a novel technique which adds the dimension of time to the well known back-propagation neural network algorithm. In the space-time neural network disclosed herein, the synaptic weights between two artificial neurons (processing elements) are replaced with an adaptable-adjustable filter. Instead of a single synaptic weight, the invention provides a plurality of weights representing not only association, but also temporal dependencies. In this case, the synaptic weights are the coefficients to the adaptable digital filters. Novelty is believed to lie in the disclosure of a processing element and a network of the processing elements which are capable of processing temporal as well as spacial data.

Biomonitoring of metals under the water framework directive: detecting temporal trends and abrupt changes, in relation to the removal of pollution sources.

PubMed

Solaun, O; Rodríguez, J G; Borja, A; González, M; Saiz-Salinas, J I

2013-02-15

Temporal trends in metal concentrations, i.e. Ag, Cd, Cu, Cr, Hg, Ni, Pb and Zn, measured in soft tissues of Mytilus galloprovincialis mussels and Crassostrea gigas oysters collected from estuarine waters within the Basque Country (Bay of Biscay), have been investigated to determine if actions undertaken have improved the environmental quality of rivers and estuaries. Data compiled between 1990 and 2010 have been analysed statistically, applying the Mann-Kendall and the Mann-Whitney-Wilcoxon tests. Moreover, in those cases with significant trends, the Kolmogorov-Zurbenko Adaptive (KZA) filter was applied to detect abrupt changes. Results showed significant decreasing trends for some metals, i.e. Ni, Cu, Pb and Zn, and differences between medians. Trend lines showed abrupt changes occurring between 1998 and 2002. Therefore, observed downward trends were related to increased wastewater treatment and diversions of discharges to ocean, implemented mainly during 2000-2002. Copyright © 2012 Elsevier Ltd. All rights reserved.

Adapting geostatistics to analyze spatial and temporal trends in weed populations

USDA-ARS?s Scientific Manuscript database

Geostatistics were originally developed in mining to estimate the location, abundance and quality of ore over large areas from soil samples to optimize future mining efforts. Here, some of these methods were adapted to weeds to account for a limited distribution area (i.e., inside a field), variatio...

Evaluation of intensified image enhancement through conspicuity and triangle orientation discrimination measures

NASA Astrophysics Data System (ADS)

Dijk, Judith; van Eekeren, Adam W. M.; Toet, Alexander; den Hollander, Richard J. M.; Schutte, Klamer; van Heijningen, Ad W. P.; Bijl, Piet

2013-04-01

For many military operations, situational awareness is of great importance. During night conditions, this situational awareness can be improved using both analog and digital image-intensified cameras. The quality of image intensifiers is a topic of interest. One of the differences between a digital and analog system is noise behavior. For digital image intensifiers, the noise behavior is not as good as for analog image intensifiers, but it can be improved using noise-reduction techniques. In this paper, the improvement using temporal noise reduction and local adaptive contrast enhancement is shown and quantitatively evaluated by subjective measurement of the conspicuity and triangle orientation discrimination (TOD). The results of the conspicuity and TOD experiments are consistent with each other. The highest improvement is found for a low-clutter environment; for medium- and high-clutter environments, the improvement is less. This can be explained by the fact that image enhancement increases contrast of all image details, irrespective of whether they are targets or clutter. For low-clutter image enhancement, target conspicuity and target detection improvement will be largest, since there are not many distracting elements.

Modeling the 2012-2013 lava flows of Tolbachik, Russia using thermal infrared satellite data and PyFLOWGO

NASA Astrophysics Data System (ADS)

Ramsey, M. S.; Chevrel, O.; Harris, A. J. L.

2017-12-01

Satellite-based thermal infrared (TIR) observations of new volcanic activity and ongoing lava flow emplacement become increasingly more detailed with improved spatial, spectral and/or temporal resolution data. The cooling of the glassy surface is directly imaged by TIR instruments in order to determine temperature, which is then used to initiate thermo-rheological-based models. Higher temporal resolution data (i.e., minutes to hours), are used to detect new eruptions and determine the time-averaged discharge rate (TADR). Calculation of the TADR along with new observations later in time and accurate digital elevation models (DEMs) enable modeling of the advancing flow's down-slope inundation area. Better spectral and spatial resolution data, on the other hand, allow the flow's composition, small-scale morphological changes and real-time DEMs to be determined, in addition to confirming prior model predictions. Combined, these data help improve the accuracy of models such as FLOWGO. A new adaptation of this model in python (PyFLOWGO) has been used to produce the best fit eruptive conditions to the final flow morphology for the 2012-2013 eruption of Tolbachik volcano, Russia. This was the largest and most thermally-intense flow-forming eruption in the past 50 years, producing longer lava flows than that of typical Kilauea or Etna eruptions. The progress of these flows were imaged by a multiple TIR sensors at various spatial, spectral and temporal scales throughout the flow field emplacement. We have refined the model based on the high resolution data to determine the TADR and make improved estimates of cooling, viscosity, velocity and crystallinity with distance. Understanding the cooling and dynamics of basaltic surfaces ultimately produces an improved hazard forecast capability. In addition, the direct connection of the final flow morphology to the specific eruption conditions that produced it allows the eruptive conditions of older flows to be estimated.

Adaptability of expert visual anticipation in baseball batting.

PubMed

Müller, Sean; Fadde, Peter J; Harbaugh, Allen G

2017-09-01

By manipulating stimulus variation in terms of opponent pitcher actions, this study investigated the capability of expert (n = 30) and near-expert (n = 95) professional baseball batters to adapt anticipation skill when using the video simulation temporal occlusion paradigm. Participants watched in-game footage of two pitchers, one after the other, that was temporally occluded at ball release and various points during ball flight. They were required to make a written prediction of pitch types and locations. Per cent accuracy was calculated for pitch type, for pitch location, and for type and location combined. Results indicated that experts and near-experts could adapt their anticipation to predict above guessing level across both pitchers, but adaptation to the left-handed pitcher was poorer than the right-handed pitcher. Small-to-moderate effect sizes were found in terms of superior adaptation by experts over near-experts at the ball release and early ball flight occlusion conditions. The findings of this study extend theoretical and applied knowledge of expertise in striking sports. Practical application of the instruments and findings are discussed in terms of applied researchers, practitioners and high-performance staff in professional sporting organisations.

Use of Co-occurrences for Temporal Expressions Annotation

NASA Astrophysics Data System (ADS)

Craveiro, Olga; Macedo, Joaquim; Madeira, Henrique

The annotation or extraction of temporal information from text documents is becoming increasingly important in many natural language processing applications such as text summarization, information retrieval, question answering, etc.. This paper presents an original method for easy recognition of temporal expressions in text documents. The method creates semantically classified temporal patterns, using word co-occurrences obtained from training corpora and a pre-defined seed keywords set, derived from the used language temporal references. A participation on a Portuguese named entity evaluation contest showed promising effectiveness and efficiency results. This approach can be adapted to recognize other type of expressions or languages, within other contexts, by defining the suitable word sets and training corpora.

Adaptive 4d Psi-Based Change Detection

NASA Astrophysics Data System (ADS)

Yang, Chia-Hsiang; Soergel, Uwe

2018-04-01

In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.

Identification of a motor to auditory pathway important for vocal learning

PubMed Central

Roberts, Todd F.; Hisey, Erin; Tanaka, Masashi; Kearney, Matthew; Chattree, Gaurav; Yang, Cindy F.; Shah, Nirao M.; Mooney, Richard

2017-01-01

Summary Learning to vocalize depends on the ability to adaptively modify the temporal and spectral features of vocal elements. Neurons that convey motor-related signals to the auditory system are theorized to facilitate vocal learning, but the identity and function of such neurons remain unknown. Here we identify a previously unknown neuron type in the songbird brain that transmits vocal motor signals to the auditory cortex. Genetically ablating these neurons in juveniles disrupted their ability to imitate features of an adult tutor’s song. Ablating these neurons in adults had little effect on previously learned songs, but interfered with their ability to adaptively modify the duration of vocal elements and largely prevented the degradation of song’s temporal features normally caused by deafening. These findings identify a motor to auditory circuit essential to vocal imitation and to the adaptive modification of vocal timing. PMID:28504672

The Role of Brain Inflammation in Epileptogenesis in TSC

DTIC Science & Technology

2013-07-01

and adaptive immunity during epileptogenesis and spontaneous seizures: evidence from experimental models and human temporal lobe epilepsy . Neurobiol...tissue obtained from epilepsy patients, such as with mesial temporal sclerosis. Different types of inflammatory mediators and pathways have been...13. SUPPLEMENTARY NOTES 14. ABSTRACT Epilepsy is a common, disabling problem in patients with tuberous sclerosis complex (TSC) and

The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States

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

Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.

Abstract: Urban heat island (UHI), a major concern worldwide, affects human health and energy use. With current and anticipated rapid urbanization, improved understanding of the response of UHI to urbanization is important for impact analysis and developing effective adaptation measures and mitigation strategies. Current studies mainly focus on a single or a few big cities and knowledge on the response of UHI to urbanization for large areas is very limited. Modelling UHI caused by urbanization for large areas that encompass multiple metropolitans remains a major scientific challenge/opportunity. As a major indicator of urbanization, urban area size lends itself well formore » representation in prognostic models to investigate the impacts of urbanization on UHI and the related socioeconomic and environmental effects. However, we have little knowledge on how UHI responds to the increase of urban area size, namely urban expansion, and its spatial and temporal variation over large areas. In this study, we investigated the relationship between surface UHI (SUHI) and urban area size in the climate and ecological context, and its spatial and temporal variations, based on a panel analysis of about 5000 urban areas of 10 km2 or larger, in the conterminous U.S. We found statistically significant positive relationship between SUHI and urban area size, and doubling the urban area size led to a SUHI increase of higher than 0.7 °C. The response of SUHI to the increase of urban area size shows spatial and temporal variations, with stronger SUHI increase in the Northern region of U.S., and during daytime and summer. Urban area size alone can explain as much as 87% of the variance of SUHI among cities studied, but with large spatial and temporal variations. Urban area size shows higher association with SUHI in regions where the thermal characteristics of land cover surrounding the urban are more homogeneous, such as in Eastern U.S., and in the summer months. This study provides a practical approach for large-scale assessment and modeling of the impact of urbanization on SUHI, both spatially and temporally, for developing mitigation/adaptation measures, especially in anticipated warmer climate conditions for the rest of this century.« less

Working memory training using mental calculation impacts regional gray matter of the frontal and parietal regions.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Sassa, Yuko; Hashizume, Hiroshi; Sekiguchi, Atsushi; Fukushima, Ai; Kawashima, Ryuta

2011-01-01

Training working memory (WM) improves performance on untrained cognitive tasks and alters functional activity. However, WM training's effects on gray matter morphology and a wide range of cognitive tasks are still unknown. We investigated this issue using voxel-based morphometry (VBM), various psychological measures, such as non-trained WM tasks and a creativity task, and intensive adaptive training of WM using mental calculations (IATWMMC), all of which are typical WM tasks. IATWMMC was associated with reduced regional gray matter volume in the bilateral fronto-parietal regions and the left superior temporal gyrus. It improved verbal letter span and complex arithmetic ability, but deteriorated creativity. These results confirm the training-induced plasticity in psychological mechanisms and the plasticity of gray matter structures in regions that have been assumed to be under strong genetic control.

Performance improvement of optical wireless communication through fog with a decision feedback equalizer.

PubMed

Aharonovich, Marius; Arnon, Shlomi

2005-08-01

Optical wireless communication (OWC) systems use the atmosphere as a propagation medium. However, a common problem is that from time to time moderate cloud and fog emerge between the receiver and the transmitter. These adverse weather conditions impose temporal broadening and power loss on the optical signal, which reduces the digital signal-to-noise ratio (DSNR), produces significant intersymbol interference (ISI), and degrades the communication system's bit error rate (BER) and throughput. We propose and investigate the use of a combined adaptive bandwidth mechanism and decision feedback equalizer (DFE) to mitigate these atmospheric multipath effects. Based on theoretical analysis and simulations of DSNR penalties, BER, and optimum system bandwidths, we show that a DFE improves the outdoor OWC system immunity to ISI in foggy weather while maintaining high throughput and desired low BER.

Visuomotor adaptation to a visual rotation is gravity dependent.

PubMed

Toma, Simone; Sciutti, Alessandra; Papaxanthis, Charalambos; Pozzo, Thierry

2015-03-15

Humans perform vertical and horizontal arm motions with different temporal patterns. The specific velocity profiles are chosen by the central nervous system by integrating the gravitational force field to minimize energy expenditure. However, what happens when a visuomotor rotation is applied, so that a motion performed in the horizontal plane is perceived as vertical? We investigated the dynamic of the adaptation of the spatial and temporal properties of a pointing motion during prolonged exposure to a 90° visuomotor rotation, where a horizontal movement was associated with a vertical visual feedback. We found that participants immediately adapted the spatial parameters of motion to the conflicting visual scene in order to keep their arm trajectory straight. In contrast, the initial symmetric velocity profiles specific for a horizontal motion were progressively modified during the conflict exposure, becoming more asymmetric and similar to those appropriate for a vertical motion. Importantly, this visual effect that increased with repetitions was not followed by a consistent aftereffect when the conflicting visual feedback was absent (catch and washout trials). In a control experiment we demonstrated that an intrinsic representation of the temporal structure of perceived vertical motions could provide the error signal allowing for this progressive adaptation of motion timing. These findings suggest that gravity strongly constrains motor learning and the reweighting process between visual and proprioceptive sensory inputs, leading to the selection of a motor plan that is suboptimal in terms of energy expenditure. Copyright © 2015 the American Physiological Society.

Abstracts of Papers Submitted in 1975 for Publication,

DTIC Science & Technology

1975-01-01

Supported by NSF Grant GA-35393) Temporal Adaptations in Sibling Species of Capitetla . .B-20 J. Frederick Grassle, Judith P. Grassle, Rudolph S. Sheltema...Charlene D. Van Raalte and Edward J. Carpenter (Supported by NSF Grant GA-43008) Physiological Adaptations of Marsh Animals to a Hydrocarbon-Polluted Envi...therapy prior to hospitalization did not vitiate the validity of the test. A bedside adaptation of the limulus test, performed by house officers and

Processing of spectral and amplitude envelope of animal vocalizations in the human auditory cortex.

PubMed

Altmann, Christian F; Gomes de Oliveira Júnior, Cícero; Heinemann, Linda; Kaiser, Jochen

2010-08-01

In daily life, we usually identify sounds effortlessly and efficiently. Two properties are particularly salient and of importance for sound identification: the sound's overall spectral envelope and its temporal amplitude envelope. In this study, we aimed at investigating the representation of these two features in the human auditory cortex by using a functional magnetic resonance imaging adaptation paradigm. We presented pairs of sound stimuli derived from animal vocalizations that preserved the time-averaged frequency spectrum of the animal vocalizations and the amplitude envelope. We presented the pairs in four different conditions: (a) pairs with the same amplitude envelope and mean spectral envelope, (b) same amplitude envelope, but different mean spectral envelope, (c) different amplitude envelope, but same mean spectral envelope and (d) both different amplitude envelope and mean spectral envelope. We found fMRI adaptation effects for both the mean spectral envelope and the amplitude envelope of animal vocalizations in overlapping cortical areas in the bilateral superior temporal gyrus posterior to Heschl's gyrus. Areas sensitive to the amplitude envelope extended further anteriorly along the lateral superior temporal gyrus in the left hemisphere, while areas sensitive to the spectral envelope extended further anteriorly along the right lateral superior temporal gyrus. Posterior tonotopic areas within the left superior temporal lobe displayed sensitivity for the mean spectrum. Our findings suggest involvement of primary auditory areas in the representation of spectral cues and encoding of general spectro-temporal features of natural sounds in non-primary posterior and lateral superior temporal cortex. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Making Sense by Building Sense: Kindergarten Children's Construction and Understanding of Adaptive Robot Behaviors

ERIC Educational Resources Information Center

Mioduser, David; Levy, Sharona T.

2010-01-01

This study explores young children's ability to construct and explain adaptive behaviors of a behaving artifact, an autonomous mobile robot with sensors. A central component of the behavior construction environment is the RoboGan software that supports children's construction of spatiotemporal events with an a-temporal rule structure. Six…

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

NASA Technical Reports Server (NTRS)

Lai, Jonathan Y.

1994-01-01

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Exploiting spatio-temporal characteristics of human vision for mobile video applications

NASA Astrophysics Data System (ADS)

Jillani, Rashad; Kalva, Hari

2008-08-01

Video applications on handheld devices such as smart phones pose a significant challenge to achieve high quality user experience. Recent advances in processor and wireless networking technology are producing a new class of multimedia applications (e.g. video streaming) for mobile handheld devices. These devices are light weight and have modest sizes, and therefore very limited resources - lower processing power, smaller display resolution, lesser memory, and limited battery life as compared to desktop and laptop systems. Multimedia applications on the other hand have extensive processing requirements which make the mobile devices extremely resource hungry. In addition, the device specific properties (e.g. display screen) significantly influence the human perception of multimedia quality. In this paper we propose a saliency based framework that exploits the structure in content creation as well as the human vision system to find the salient points in the incoming bitstream and adapt it according to the target device, thus improving the quality of new adapted area around salient points. Our experimental results indicate that the adaptation process that is cognizant of video content and user preferences can produce better perceptual quality video for mobile devices. Furthermore, we demonstrated how such a framework can affect user experience on a handheld device.

Motion adaptive Kalman filter for super-resolution

NASA Astrophysics Data System (ADS)

Richter, Martin; Nasse, Fabian; Schröder, Hartmut

2011-01-01

Superresolution is a sophisticated strategy to enhance image quality of both low and high resolution video, performing tasks like artifact reduction, scaling and sharpness enhancement in one algorithm, all of them reconstructing high frequency components (above Nyquist frequency) in some way. Especially recursive superresolution algorithms can fulfill high quality aspects because they control the video output using a feed-back loop and adapt the result in the next iteration. In addition to excellent output quality, temporal recursive methods are very hardware efficient and therefore even attractive for real-time video processing. A very promising approach is the utilization of Kalman filters as proposed by Farsiu et al. Reliable motion estimation is crucial for the performance of superresolution. Therefore, robust global motion models are mainly used, but this also limits the application of superresolution algorithm. Thus, handling sequences with complex object motion is essential for a wider field of application. Hence, this paper proposes improvements by extending the Kalman filter approach using motion adaptive variance estimation and segmentation techniques. Experiments confirm the potential of our proposal for ideal and real video sequences with complex motion and further compare its performance to state-of-the-art methods like trainable filters.

Can We Improve Structured Sequence Processing? Exploring the Direct and Indirect Effects of Computerized Training Using a Mediational Model

PubMed Central

Smith, Gretchen N. L.; Conway, Christopher M.; Bauernschmidt, Althea; Pisoni, David B.

2015-01-01

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest. PMID:25946222

Can we improve structured sequence processing? Exploring the direct and indirect effects of computerized training using a mediational model.

PubMed

Smith, Gretchen N L; Conway, Christopher M; Bauernschmidt, Althea; Pisoni, David B

2015-01-01

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest.

Transcranial Alternating Current Stimulation Attenuates Neuronal Adaptation.

PubMed

Kar, Kohitij; Duijnhouwer, Jacob; Krekelberg, Bart

2017-03-01

We previously showed that brief application of 2 mA (peak-to-peak) transcranial currents alternating at 10 Hz significantly reduces motion adaptation in humans. This is but one of many behavioral studies showing that weak currents applied to the scalp modulate neural processing. Transcranial stimulation has been shown to improve perception, learning, and a range of clinical symptoms. Few studies, however, have measured the neural consequences of transcranial current stimulation. We capitalized on the strong link between motion perception and neural activity in the middle temporal (MT) area of the macaque monkey to study the neural mechanisms that underlie the behavioral consequences of transcranial alternating current stimulation. First, we observed that 2 mA currents generated substantial intracranial fields, which were much stronger in the stimulated hemisphere (0.12 V/m) than on the opposite side of the brain (0.03 V/m). Second, we found that brief application of transcranial alternating current stimulation at 10 Hz reduced spike-frequency adaptation of MT neurons and led to a broadband increase in the power spectrum of local field potentials. Together, these findings provide a direct demonstration that weak electric fields applied to the scalp significantly affect neural processing in the primate brain and that this includes a hitherto unknown mechanism that attenuates sensory adaptation. SIGNIFICANCE STATEMENT Transcranial stimulation has been claimed to improve perception, learning, and a range of clinical symptoms. Little is known, however, how transcranial current stimulation generates such effects, and the search for better stimulation protocols proceeds largely by trial and error. We investigated, for the first time, the neural consequences of stimulation in the monkey brain. We found that even brief application of alternating current stimulation reduced the effects of adaptation on single-neuron firing rates and local field potentials; this mechanistic insight explains previous behavioral findings and suggests a novel way to modulate neural information processing using transcranial currents. In addition, by developing an animal model to help understand transcranial stimulation, this study will aid the rational design of stimulation protocols for the treatment of mental illnesses, and the improvement of perception and learning. Copyright © 2017 the authors 0270-6474/17/372325-11$15.00/0.

Watching the brain recalibrate: Neural correlates of renormalization during face adaptation.

PubMed

Kloth, Nadine; Rhodes, Gillian; Schweinberger, Stefan R

2017-07-15

The face perception system flexibly adjusts its neural responses to current face exposure, inducing aftereffects in the perception of subsequent faces. For instance, adaptation to expanded faces makes undistorted faces appear compressed, and adaptation to compressed faces makes undistorted faces appear expanded. Such distortion aftereffects have been proposed to result from renormalization, in which the visual system constantly updates a prototype according to the adaptors' characteristics and evaluates subsequent faces relative to that. However, although consequences of adaptation are easily observed in behavioral aftereffects, it has proven difficult to observe renormalization during adaptation itself. Here we directly measured brain responses during adaptation to establish a neural correlate of renormalization. Given that the face-evoked occipito-temporal P2 event-related brain potential has been found to increase with face prototypicality, we reasoned that the adaptor-elicited P2 could serve as an electrophysiological indicator for renormalization. Participants adapted to sequences of four distorted (compressed or expanded) or undistorted faces, followed by a slightly distorted test face, which they had to classify as undistorted or distorted. We analysed ERPs evoked by each of the adaptors and found that P2 (but not N170) amplitudes evoked by consecutive adaptor faces exhibited an electrophysiological pattern of renormalization during adaptation to distorted faces: P2 amplitudes evoked by both compressed and expanded adaptors significantly increased towards asymptotic levels as adaptation proceeded. P2 amplitudes were smallest for the first adaptor, significantly larger for the second, and yet larger for the third adaptor. We conclude that the sensitivity of the occipito-temporal P2 to the perceived deviation of a face from the norm makes this component an excellent tool to study adaptation-induced renormalization. Copyright © 2017 Elsevier Inc. All rights reserved.

On-sky validation of an optimal LQG control with vibration mitigation: from the CANARY Multi-Object Adaptive Optics demonstrator to the Gemini Multi-Conjugated Adaptive Optics facility.

NASA Astrophysics Data System (ADS)

Sivo, Gaetano; Kulcsár, Caroline; Conan, Jean-Marc; Raynaud, Henri-François; Gendron, Éric; Basden, Alastair; Gratadour, Damien; Morris, Tim; Petit, Cyril; Meimon, Serge; Rousset, Gérard; Garrel, Vincent; Neichel, Benoit; van Dam, Marcos; Marin, Eduardo; Carrasco, Rodrigo; Schirmer, Mischa; Rambold, William; Moreno, Cristian; Montes, Vanessa; Hardie, Kayla; Trujillo, Chad

2015-01-01

Adaptive optics provides real time correction of wavefront perturbations on ground-based telescopes and allow to reach the diffraction limit performances. Optimizing control and performance is a key issue for ever more demanding instruments on ever larger telescopes affected not only by atmospheric turbulence, but also by vibrations, windshake and tracking errors. Linear Quadratic Gaussian control achieves optimal correction when provided with a temporal model of the disturbance. We present in this paper the first on-sky results of a Kalman filter based LQG control with vibration mitigation on the CANARY instrument at the Nasmyth platform of the 4.2-m William Herschel Telescope (La Palma, Spain). The results demonstrate a clear improvement of performance for full LQG compared with standard integrator control, and assess the additional improvement brought by vibration filtering with a tip-tilt model identified from on-sky data (by 10 points of Strehl ratio), thus validating the strategy retained on the instrument SPHERE (eXtreme-AO system for extra-solar planets detection and characterization) at the VLT. The MOAO on-sky pathfinder CANARY features two AO configurations that have both been tested: single- conjugated AO and multi-object AO with NGS and NGS+ Rayleigh LGS, together with vibration mitigation on tip and tilt modes. We finally present the ongoing development done to commission such a control law on a regular Sodium laser Multi-Conjuagated Adaptive Optics (MCAO) system GeMS at the 8-m Gemini South Telescope. This implementation does not require new hardware and is already available in the real-time computer.

Dynamic Model Improves Agronomic and Environmental Outcomes for Maize Nitrogen Management over Static Approach.

PubMed

Sela, Shai; van Es, Harold M; Moebius-Clune, Bianca N; Marjerison, Rebecca; Moebius-Clune, Daniel; Schindelbeck, Robert; Severson, Keith; Young, Eric

2017-03-01

Large temporal and spatial variability in soil nitrogen (N) availability leads many farmers across the United States to over-apply N fertilizers in maize ( L.) production environments, often resulting in large environmental N losses. Static Stanford-type N recommendation tools are typically promoted in the United States, but new dynamic model-based decision tools allow for highly adaptive N recommendations that account for specific production environments and conditions. This study compares the Corn N Calculator (CNC), a static N recommendation tool for New York, to Adapt-N, a dynamic simulation tool that combines soil, crop, and management information with real-time weather data to estimate optimum N application rates for maize. The efficiency of the two tools in predicting the Economically Optimum N Rate (EONR) is compared using field data from 14 multiple N-rate trials conducted in New York during the years 2011 through 2015. The CNC tool was used with both realistic grower-estimated potential yields and those extracted from the CNC default database, which were found to be unrealistically low when compared with field data. By accounting for weather and site-specific conditions, the Adapt-N tool was found to increase the farmer profits and significantly improve the prediction of the EONR (RMSE = 34 kg ha). Furthermore, using a dynamic instead of a static approach led to reduced N application rates, which in turn resulted in substantially lower simulated environmental N losses. This study shows that better N management through a dynamic decision tool such as Adapt-N can help reduce environmental impacts while sustaining farm economic viability. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Identification of Hot Moments and Hot Spots for Real-Time Adaptive Control of Multi-scale Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Wietsma, T.; Minsker, B. S.

2012-12-01

Increased sensor throughput combined with decreasing hardware costs has led to a disruptive growth in data volume. This disruption, popularly termed "the data deluge," has placed new demands for cyberinfrastructure and information technology skills among researchers in many academic fields, including the environmental sciences. Adaptive sampling has been well established as an effective means of improving network resource efficiency (energy, bandwidth) without sacrificing sample set quality relative to traditional uniform sampling. However, using adaptive sampling for the explicit purpose of improving resolution over events -- situations displaying intermittent dynamics and unique hydrogeological signatures -- is relatively new. In this paper, we define hot spots and hot moments in terms of sensor signal activity as measured through discrete Fourier analysis. Following this frequency-based approach, we apply the Nyquist-Shannon sampling theorem, a fundamental contribution from signal processing that led to the field of information theory, for analysis of uni- and multivariate environmental signal data. In the scope of multi-scale environmental sensor networks, we present several sampling control algorithms, derived from the Nyquist-Shannon theorem, that operate at local (field sensor), regional (base station for aggregation of field sensor data), and global (Cloud-based, computationally intensive models) scales. Evaluated over soil moisture data, results indicate significantly greater sample density during precipitation events while reducing overall sample volume. Using these algorithms as indicators rather than control mechanisms, we also discuss opportunities for spatio-temporal modeling as a tool for planning/modifying sensor network deployments. Locally adaptive model based on Nyquist-Shannon sampling theorem Pareto frontiers for local, regional, and global models relative to uniform sampling. Objectives are (1) overall sampling efficiency and (2) sampling efficiency during hot moments as identified using heuristic approach.

Mobile membrane introduction tandem mass spectrometry for on-the-fly measurements and adaptive sampling of VOCs around oil and gas projects in Alberta, Canada

NASA Astrophysics Data System (ADS)

Krogh, E.; Gill, C.; Bell, R.; Davey, N.; Martinsen, M.; Thompson, A.; Simpson, I. J.; Blake, D. R.

2012-12-01

The release of hydrocarbons into the environment can have significant environmental and economic consequences. The evolution of smaller, more portable mass spectrometers to the field can provide spatially and temporally resolved information for rapid detection, adaptive sampling and decision support. We have deployed a mobile platform membrane introduction mass spectrometer (MIMS) for the in-field simultaneous measurement of volatile and semi-volatile organic compounds. In this work, we report instrument and data handling advances that produce geographically referenced data in real-time and preliminary data where these improvements have been combined with high precision ultra-trace VOCs analysis to adaptively sample air plumes near oil and gas operations in Alberta, Canada. We have modified a commercially available ion-trap mass spectrometer (Griffin ICX 400) with an in-house temperature controlled capillary hollow fibre polydimethylsiloxane (PDMS) polymer membrane interface and in-line permeation tube flow cell for a continuously infused internal standard. The system is powered by 24 VDC for remote operations in a moving vehicle. Software modifications include the ability to run continuous, interlaced tandem mass spectrometry (MS/MS) experiments for multiple contaminants/internal standards. All data are time and location stamped with on-board GPS and meteorological data to facilitate spatial and temporal data mapping. Tandem MS/MS scans were employed to simultaneously monitor ten volatile and semi-volatile analytes, including benzene, toluene, ethylbenzene and xylene (BTEX), reduced sulfur compounds, halogenated organics and naphthalene. Quantification was achieved by calibrating against a continuously infused deuterated internal standard (toluene-d8). Time referenced MS/MS data were correlated with positional data and processed using Labview and Matlab to produce calibrated, geographical Google Earth data-visualizations that enable adaptive sampling protocols. This real-time approach has been employed in a moving vehicle to identify and track downwind plumes of fugitive VOC emissions near hydrocarbon upgrading and chemical processing facilities in Fort Saskatchewan, Alberta. This information was relayed to a trailing vehicle, which collected stationary grab samples in evacuated canisters for ultra trace analysis of over seventy VOC analytes. In addition, stationary time series data were collected and compared with grab samples co-located with our sampling line. Spatially and temporally resolved, time referenced MS/MS data for several air contaminants associated with oil and gas processing were processed in real time to produce geospatial data for visualization in Google Earth. This information was used to strategically locate grab samples for high precision, ultra trace analysis.

Spatio-Temporal Process Simulation of Dam-Break Flood Based on SPH

NASA Astrophysics Data System (ADS)

Wang, H.; Ye, F.; Ouyang, S.; Li, Z.

2018-04-01

On the basis of introducing the SPH (Smooth Particle Hydrodynamics) simulation method, the key research problems were given solutions in this paper, which ere the spatial scale and temporal scale adapting to the GIS(Geographical Information System) application, the boundary condition equations combined with the underlying surface, and the kernel function and parameters applicable to dam-break flood simulation. In this regards, a calculation method of spatio-temporal process emulation with elaborate particles for dam-break flood was proposed. Moreover the spatio-temporal process was dynamic simulated by using GIS modelling and visualization. The results show that the method gets more information, objectiveness and real situations.

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

PubMed

Yang, Yehui; Hu, Wenrui; Xie, Yuan; Zhang, Wensheng; Zhang, Tianzhu

2017-02-01

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l 1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

NASA Astrophysics Data System (ADS)

Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

2013-10-01

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties

NASA Astrophysics Data System (ADS)

Ralli, George P.; Chappell, Michael A.; McGowan, Daniel R.; Sharma, Ricky A.; Higgins, Geoff S.; Fenwick, John D.

2018-05-01

4D reconstruction of dynamic positron emission tomography (dPET) data can improve the signal-to-noise ratio in reconstructed image sequences by fitting smooth temporal functions to the voxel time-activity-curves (TACs) during the reconstruction, though the optimal choice of function remains an open question. We propose a spline-residue model, which describes TACs as weighted sums of convolutions of the arterial input function with cubic B-spline basis functions. Convolution with the input function constrains the spline-residue model at early time-points, potentially enhancing noise suppression in early time-frames, while still allowing a wide range of TAC descriptions over the entire imaged time-course, thus limiting bias. Spline-residue based 4D-reconstruction is compared to that of a conventional (non-4D) maximum a posteriori (MAP) algorithm, and to 4D-reconstructions based on adaptive-knot cubic B-splines, the spectral model and an irreversible two-tissue compartment (‘2C3K’) model. 4D reconstructions were carried out using a nested-MAP algorithm including spatial and temporal roughness penalties. The algorithms were tested using Monte-Carlo simulated scanner data, generated for a digital thoracic phantom with uptake kinetics based on a dynamic [18F]-Fluromisonidazole scan of a non-small cell lung cancer patient. For every algorithm, parametric maps were calculated by fitting each voxel TAC within a sub-region of the reconstructed images with the 2C3K model. Compared to conventional MAP reconstruction, spline-residue-based 4D reconstruction achieved  >50% improvements for five of the eight combinations of the four kinetics parameters for which parametric maps were created with the bias and noise measures used to analyse them, and produced better results for 5/8 combinations than any of the other reconstruction algorithms studied, while spectral model-based 4D reconstruction produced the best results for 2/8. 2C3K model-based 4D reconstruction generated the most biased parametric maps. Inclusion of a temporal roughness penalty function improved the performance of 4D reconstruction based on the cubic B-spline, spectral and spline-residue models.

Neural processing of emotions in traumatized children treated with Eye Movement Desensitization and Reprocessing therapy: a hdEEG study

PubMed Central

Trentini, Cristina; Pagani, Marco; Fania, Piercarlo; Speranza, Anna Maria; Nicolais, Giampaolo; Sibilia, Alessandra; Inguscio, Lucio; Verardo, Anna Rita; Fernandez, Isabel; Ammaniti, Massimo

2015-01-01

Eye Movement Desensitization and Reprocessing (EMDR) therapy has been proven efficacious in restoring affective regulation in post-traumatic stress disorder (PTSD) patients. However, its effectiveness on emotion processing in children with complex trauma has yet to be explored. High density electroencephalography (hdEEG) was used to investigate the effects of EMDR on brain responses to adults’ emotions on children with histories of early maltreatment. Ten school-aged children were examined before (T0) and within one month after the conclusion of EMDR (T1). hdEEGs were recorded while children passively viewed angry, afraid, happy, and neutral faces. Clinical scales were administered at the same time. Correlation analyses were performed to detect brain regions whose activity was linked to children’s traumatic symptom-related and emotional-adaptive problem scores. In all four conditions, hdEEG showed similar significantly higher activity on the right medial prefrontal and fronto-temporal limbic regions at T0, shifting toward the left medial and superior temporal regions at T1. Moreover, significant correlations were found between clinical scales and the same regions whose activity significantly differed between pre- and post-treatment. These preliminary results demonstrate that, after EMDR, children suffering from complex trauma show increased activity in areas implicated in high-order cognitive processing when passively viewing pictures of emotional expressions. These changes are associated with the decrease of depressive and traumatic symptoms, and with the improvement of emotional-adaptive functioning over time. PMID:26594183

Adaptive significance of right hemisphere activation in aphasic language comprehension

PubMed Central

Meltzer, Jed A.; Wagage, Suraji; Ryder, Jennifer; Solomon, Beth; Braun, Allen R.

2013-01-01

Aphasic patients often exhibit increased right hemisphere activity during language tasks. This may represent takeover of function by regions homologous to the left-hemisphere language networks, maladaptive interference, or adaptation of alternate compensatory strategies. To distinguish between these accounts, we tested language comprehension in 25 aphasic patients using an online sentence-picture matching paradigm while measuring brain activation with MEG. Linguistic conditions included semantically irreversible (“The boy is eating the apple”) and reversible (“The boy is pushing the girl”) sentences at three levels of syntactic complexity. As expected, patients performed well above chance on irreversible sentences, and at chance on reversible sentences of high complexity. Comprehension of reversible non-complex sentences ranged from nearly perfect to chance, and was highly correlated with offline measures of language comprehension. Lesion analysis revealed that comprehension deficits for reversible sentences were predicted by damage to the left temporal lobe. Although aphasic patients activated homologous areas in the right temporal lobe, such activation was not correlated with comprehension performance. Rather, patients with better comprehension exhibited increased activity in dorsal fronto-parietal regions. Correlations between performance and dorsal network activity occurred bilaterally during perception of sentences, and in the right hemisphere during a post-sentence memory delay. These results suggest that effortful reprocessing of perceived sentences in short-term memory can support improved comprehension in aphasia, and that strategic recruitment of alternative networks, rather than homologous takeover, may account for some findings of right hemisphere language activation in aphasia. PMID:23566891

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations

PubMed Central

Swings, Toon; Weytjens, Bram; Schalck, Thomas; Bonte, Camille; Verstraeten, Natalie; Michiels, Jan

2017-01-01

Abstract Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well. PMID:28961727

Objective assessment of chromatic and achromatic pattern adaptation reveals the temporal response properties of different visual pathways.

PubMed

Robson, Anthony G; Kulikowski, Janus J

2012-11-01

The aim was to investigate the temporal response properties of magnocellular, parvocellular, and koniocellular visual pathways using increment/decrement changes in contrast to elicit visual evoked potentials (VEPs). Static achromatic and isoluminant chromatic gratings were generated on a monitor. Chromatic gratings were modulated along red/green (R/G) or subject-specific tritanopic confusion axes, established using a minimum distinct border criterion. Isoluminance was determined using minimum flicker photometry. Achromatic and chromatic VEPs were recorded to contrast increments and decrements of 0.1 or 0.2 superimposed on the static gratings (masking contrast 0-0.6). Achromatic increment/decrement changes in contrast evoked a percept of apparent motion when the spatial frequency was low; VEPs to such stimuli were positive in polarity and largely unaffected by high levels of static contrast, consistent with transient response mechanisms. VEPs to finer achromatic gratings showed marked attenuation as static contrast was increased. Chromatic VEPs to R/G or tritan chromatic contrast increments were of negative polarity and showed progressive attenuation as static contrast was increased, in keeping with increasing desensitization of the sustained responses of the color-opponent visual pathways. Chromatic contrast decrement VEPs were of positive polarity and less sensitive to pattern adaptation. The relative contribution of sustained/transient mechanisms to achromatic processing is spatial frequency dependent. Chromatic contrast increment VEPs reflect the sustained temporal response properties of parvocellular and koniocellular pathways. Cortical VEPs can provide an objective measure of pattern adaptation and can be used to probe the temporal response characteristics of different visual pathways.

Climate change in the oceans: evolutionary versus phenotypically plastic responses of marine animals and plants

PubMed Central

Reusch, Thorsten B H

2014-01-01

I summarize marine studies on plastic versus adaptive responses to global change. Due to the lack of time series, this review focuses largely on the potential for adaptive evolution in marine animals and plants. The approaches were mainly synchronic comparisons of phenotypically divergent populations, substituting spatial contrasts in temperature or CO2 environments for temporal changes, or in assessments of adaptive genetic diversity within populations for traits important under global change. The available literature is biased towards gastropods, crustaceans, cnidarians and macroalgae. Focal traits were mostly environmental tolerances, which correspond to phenotypic buffering, a plasticity type that maintains a functional phenotype despite external disturbance. Almost all studies address coastal species that are already today exposed to fluctuations in temperature, pH and oxygen levels. Recommendations for future research include (i) initiation and analyses of observational and experimental temporal studies encompassing diverse phenotypic traits (including diapausing cues, dispersal traits, reproductive timing, morphology) (ii) quantification of nongenetic trans-generational effects along with components of additive genetic variance (iii) adaptive changes in microbe–host associations under the holobiont model in response to global change (iv) evolution of plasticity patterns under increasingly fluctuating environments and extreme conditions and (v) joint consideration of demography and evolutionary adaptation in evolutionary rescue approaches. PMID:24454551

Data-adaptive harmonic analysis and prediction of sea level change in North Atlantic region

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2017-12-01

This study aims to characterize North Atlantic sea level variability across the temporal and spatial scales. We apply recently developed data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) stochastic modeling techniques [Chekroun and Kondrashov, 2017] to monthly 1993-2017 dataset of Combined TOPEX/Poseidon, Jason-1 and Jason-2/OSTM altimetry fields over North Atlantic region. The key numerical feature of the DAH relies on the eigendecomposition of a matrix constructed from time-lagged spatial cross-correlations. In particular, eigenmodes form an orthogonal set of oscillating data-adaptive harmonic modes (DAHMs) that come in pairs and in exact phase quadrature for a given temporal frequency. Furthermore, the pairs of data-adaptive harmonic coefficients (DAHCs), obtained by projecting the dataset onto associated DAHMs, can be very efficiently modeled by a universal parametric family of simple nonlinear stochastic models - coupled Stuart-Landau oscillators stacked per frequency, and synchronized across different frequencies by the stochastic forcing. Despite the short record of altimetry dataset, developed DAH-MSLM model provides for skillful prediction of key dynamical and statistical features of sea level variability. References M. D. Chekroun and D. Kondrashov, Data-adaptive harmonic spectra and multilayer Stuart-Landau models. HAL preprint, 2017, https://hal.archives-ouvertes.fr/hal-01537797

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.

Structured illumination 3D microscopy using adaptive lenses and multimode fibers

NASA Astrophysics Data System (ADS)

Czarske, Jürgen; Philipp, Katrin; Koukourakis, Nektarios

2017-06-01

Microscopic techniques with high spatial and temporal resolution are required for in vivo studying biological cells and tissues. Adaptive lenses exhibit strong potential for fast motion-free axial scanning. However, they also lead to a degradation of the achievable resolution because of aberrations. This hurdle can be overcome by digital optical technologies. We present a novel High-and-Low-frequency (HiLo) 3D-microscope using structured illumination and an adaptive lens. Uniform illumination is used to obtain optical sectioning for the high-frequency (Hi) components of the image, and nonuniform illumination is needed to obtain optical sectioning for the low-frequency (Lo) components of the image. Nonuniform illumination is provided by a multimode fiber. It ensures robustness against optical aberrations of the adaptive lens. The depth-of-field of our microscope can be adjusted a-posteriori by computational optics. It enables to create flexible scans, which compensate for irregular axial measurement positions. The adaptive HiLo 3D-microscope provides an axial scanning range of 1 mm with an axial resolution of about 4 microns and sub-micron lateral resolution over the full scanning range. In result, volumetric measurements with high temporal and spatial resolution are provided. Demonstration measurements of zebrafish embryos with reporter gene-driven fluorescence in the thyroid gland are presented.

Improved motion compensation in 3D-CT using respiratory-correlated segment reconstruction: diagnostic and radiotherapy applications.

PubMed

Mori, S; Endo, M; Kohno, R; Minohara, S

2006-09-01

Conventional respiratory-gated CT and four-dimensional CT (4DCT) are disadvantaged by their low temporal resolution, which results in the inclusion of anatomic motion-induced artefacts. These represent a significant source of error both in radiotherapy treatment planning for the thorax and upper abdomen and in diagnostic procedures. In particular, temporal resolution and image quality are vitally important to accurate diagnosis and the minimization of planning target volume margin due to respiratory motion. To improve both temporal resolution and signal-to-noise ratio (SNR), we developed a respiratory-correlated segment reconstruction method (RS) and adapted it to the Feldkamp-Davis-Kress algorithm (FDK) with a 256 multidetector row CT (256MDCT). The 256MDCT scans approximately 100 mm in the craniocaudal direction with a 0.5 mm slice thickness in one rotation. Data acquisition for the RS-FDK relies on the assistance of a respiratory sensing system operating in cine scan mode (continuous axial scan with the table stationary). We evaluated the RS-FDK for volume accuracy and image noise in a phantom study with the 256MDCT and compared results with those for a full scan (FS-FDK), which is usually employed in conventional 4DCT and in half scan (HS-FDK). Results showed that the RS-FDK gave a more accurate volume than the others and had the same SNR as the FS-FDK. In a subsequent animal study, we demonstrated a practical sorting process for projection data which was unaffected by variations in respiratory period, and found that the RS-FDK gave the clearest visualization among the three algorithms of the margins of the liver and pulmonary vessels. In summary, the RS-FDK algorithm provides multi-phase images with higher temporal resolution and better SNR. This method should prove useful when combined with new radiotherapeutic and diagnostic techniques.

Biodiversity can support a greener revolution in Africa

PubMed Central

Snapp, Sieglinde S.; Blackie, Malcolm J.; Gilbert, Robert A.; Bezner-Kerr, Rachel; Kanyama-Phiri, George Y.

2010-01-01

The Asian green revolution trebled grain yields through agrochemical intensification of monocultures. Associated environmental costs have subsequently emerged. A rapidly changing world necessitates sustainability principles be developed to reinvent these technologies and test them at scale. The need is particularly urgent in Africa, where ecosystems are degrading and crop yields have stagnated. An unprecedented opportunity to reverse this trend is unfolding in Malawi, where a 90% subsidy has ensured access to fertilization and improved maize seed, with substantive gains in productivity for millions of farmers. To test if economic and ecological sustainability could be improved, we preformed manipulative experimentation with crop diversity in a countrywide trial (n = 991) and at adaptive, local scales through a decade of participatory research (n = 146). Spatial and temporal treatments compared monoculture maize with legume-diversified maize that included annual and semiperennial (SP) growth habits in temporal and spatial combinations, including rotation, SP rotation, intercrop, and SP intercrop systems. Modest fertilizer intensification doubled grain yield compared with monoculture maize. Biodiversity improved ecosystem function further: SP rotation systems at half-fertilizer rates produced equivalent quantities of grain, on a more stable basis (yield variability reduced from 22% to 13%) compared with monoculture. Across sites, profitability and farmer preference matched: SP rotations provided twofold superior returns, whereas diversification of maize with annual legumes provided more modest returns. In this study, we provide evidence that in Africa, crop diversification can be effective at a countrywide scale, and that shrubby, grain legumes can enhance environmental and food security. PMID:21098285

Measuring temporal summation in visual detection with a single-photon source.

PubMed

Holmes, Rebecca; Victora, Michelle; Wang, Ranxiao Frances; Kwiat, Paul G

2017-11-01

Temporal summation is an important feature of the visual system which combines visual signals that arrive at different times. Previous research estimated complete summation to last for 100ms for stimuli judged "just detectable." We measured the full range of temporal summation for much weaker stimuli using a new paradigm and a novel light source, developed in the field of quantum optics for generating small numbers of photons with precise timing characteristics and reduced variance in photon number. Dark-adapted participants judged whether a light was presented to the left or right of their fixation in each trial. In Experiment 1, stimuli contained a stream of photons delivered at a constant rate while the duration was systematically varied. Accuracy should increase with duration as long as the later photons can be integrated with the proceeding ones into a single signal. The temporal integration window was estimated as the point that performance no longer improved, and was found to be 650ms on average. In Experiment 2, the duration of the visual stimuli was kept short (100ms or <30ms) while the number of photons was varied to explore the efficiency of summation over the integration window compared to Experiment 1. There was some indication that temporal summation remains efficient over the integration window, although there is variation between individuals. The relatively long integration window measured in this study may be relevant to studies of the absolute visual threshold, i.e., tests of single-photon vision, where "single" photons should be separated by greater than the integration window to avoid summation. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Phosphorylation State of the Drosophila TRP Channel Modulates the Frequency Response to Oscillating Light In Vivo

PubMed Central

Rhodes-Mordov, Elisheva; Katz, Ben; Oberegelsbacher, Claudia; Yasin, Bushra; Tzadok, Hanan; Huber, Armin

2017-01-01

Drosophila photoreceptors respond to oscillating light of high frequency (∼100 Hz), while the detected maximal frequency is modulated by the light rearing conditions, thus enabling high sensitivity to light and high temporal resolution. However, the molecular basis for this adaptive process is unclear. Here, we report that dephosphorylation of the light-activated transient receptor potential (TRP) ion channel at S936 is a fast, graded, light-dependent, and Ca2+-dependent process that is partially modulated by the rhodopsin phosphatase retinal degeneration C (RDGC). Electroretinogram measurements of the frequency response to oscillating lights in vivo revealed that dark-reared flies expressing wild-type TRP exhibited a detection limit of oscillating light at relatively low frequencies, which was shifted to higher frequencies upon light adaptation. Strikingly, preventing phosphorylation of the S936-TRP site by alanine substitution in transgenic Drosophila (trpS936A) abolished the difference in frequency response between dark-adapted and light-adapted flies, resulting in high-frequency response also in dark-adapted flies. In contrast, inserting a phosphomimetic mutation by substituting the S936-TRP site to aspartic acid (trpS936D) set the frequency response of light-adapted flies to low frequencies typical of dark-adapted flies. Light-adapted rdgC mutant flies showed relatively high S936-TRP phosphorylation levels and light–dark phosphorylation dynamics. These findings suggest that RDGC is one but not the only phosphatase involved in pS936-TRP dephosphorylation. Together, this study indicates that TRP channel dephosphorylation is a regulatory process that affects the detection limit of oscillating light according to the light rearing condition, thus adjusting dynamic processing of visual information under varying light conditions. SIGNIFICANCE STATEMENT Drosophila photoreceptors exhibit high temporal resolution as manifested in frequency response to oscillating light of high frequency (≤∼100 Hz). Light rearing conditions modulate the maximal frequency detected by photoreceptors, thus enabling them to maintain high sensitivity to light and high temporal resolution. However, the precise mechanisms for this process are not fully understood. Here, we show by combination of biochemistry and in vivo electrophysiology that transient receptor potential (TRP) channel dephosphorylation at a specific site is a fast, light-activated and Ca2+-dependent regulatory process. TRP dephosphorylation affects the detection limit of oscillating light according to the adaptation state of the photoreceptor cells by shifting the detection limit to higher frequencies upon light adaptation. This novel mechanism thus adjusts dynamic processing of visual information under varying light conditions. PMID:28314815

Cross-cultural Adaptation of the Self-care of Hypertension Inventory Into Brazilian Portuguese.

PubMed

Silveira, Luana Claudia Jacoby; Rabelo-Silva, Eneida Rejane; Ávila, Christiane Whast; Beltrami Moreira, Leila; Dickson, Victoria Vaughan; Riegel, Barbara

Lifestyle changes and treatment adherence still constitute a challenge to healthcare providers involved in the care of persons with hypertension. The lack of validated instruments measuring the ability of hypertensive patients to manage their disease has slowed research progress in this area. The Self-care of Hypertension Inventory, originally developed in the United States, consists of 23 items divided across 3 scales: Self-care Maintenance, Self-care Management, and Self-care Confidence. These scales measure how well patients with hypertension adhere to treatment and manage elevated blood pressure, as well as their confidence in their ability to perform self-care. A rigorous cross-cultural adaptation and validation process is required before this instrument can be used in other countries. The aims of this study were to translate the Self-care of Hypertension Inventory into Brazilian Portuguese with cross-cultural adaptation and to evaluate interobserver reliability and temporal stability. This methodological study involved forward translation, synthesis of forward translations, back-translation, synthesis of back-translations, expert committee review, and pretesting. Interobserver agreement and the temporal stability of the scales were assessed. The expert committee proposed semantic and cultural modifications to some items and the addition of guidance statements to facilitate administration of the scale. Interobserver analysis demonstrated substantial agreement. Analysis of temporal stability showed near-perfect agreement. Cross-cultural adaptation of the Self-care of Hypertension Inventory successfully produced a Portuguese-language version of the instrument for further evaluation of psychometric properties. Once that step is completed, the scale can be used in Brazil.

ARCH: Adaptive recurrent-convolutional hybrid networks for long-term action recognition

PubMed Central

Xin, Miao; Zhang, Hong; Wang, Helong; Sun, Mingui; Yuan, Ding

2017-01-01

Recognition of human actions from digital video is a challenging task due to complex interfering factors in uncontrolled realistic environments. In this paper, we propose a learning framework using static, dynamic and sequential mixed features to solve three fundamental problems: spatial domain variation, temporal domain polytrope, and intra- and inter-class diversities. Utilizing a cognitive-based data reduction method and a hybrid “network upon networks” architecture, we extract human action representations which are robust against spatial and temporal interferences and adaptive to variations in both action speed and duration. We evaluated our method on the UCF101 and other three challenging datasets. Our results demonstrated a superior performance of the proposed algorithm in human action recognition. PMID:29290647

Blind deconvolution post-processing of images corrected by adaptive optics

NASA Astrophysics Data System (ADS)

Christou, Julian C.

1995-08-01

Experience with the adaptive optics system at the Starfire Optical Range has shown that the point spread function is non-uniform and varies both spatially and temporally as well as being object dependent. Because of this, the application of a standard linear and non-linear deconvolution algorithms make it difficult to deconvolve out the point spread function. In this paper we demonstrate the application of a blind deconvolution algorithm to adaptive optics compensated data where a separate point spread function is not needed.

Eulerian Lagrangian Adaptive Fup Collocation Method for solving the conservative solute transport in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Gotovac, Hrvoje; Srzic, Veljko

2014-05-01

Contaminant transport in natural aquifers is a complex, multiscale process that is frequently studied using different Eulerian, Lagrangian and hybrid numerical methods. Conservative solute transport is typically modeled using the advection-dispersion equation (ADE). Despite the large number of available numerical methods that have been developed to solve it, the accurate numerical solution of the ADE still presents formidable challenges. In particular, current numerical solutions of multidimensional advection-dominated transport in non-uniform velocity fields are affected by one or all of the following problems: numerical dispersion that introduces artificial mixing and dilution, grid orientation effects, unresolved spatial and temporal scales and unphysical numerical oscillations (e.g., Herrera et al, 2009; Bosso et al., 2012). In this work we will present Eulerian Lagrangian Adaptive Fup Collocation Method (ELAFCM) based on Fup basis functions and collocation approach for spatial approximation and explicit stabilized Runge-Kutta-Chebyshev temporal integration (public domain routine SERK2) which is especially well suited for stiff parabolic problems. Spatial adaptive strategy is based on Fup basis functions which are closely related to the wavelets and splines so that they are also compactly supported basis functions; they exactly describe algebraic polynomials and enable a multiresolution adaptive analysis (MRA). MRA is here performed via Fup Collocation Transform (FCT) so that at each time step concentration solution is decomposed using only a few significant Fup basis functions on adaptive collocation grid with appropriate scales (frequencies) and locations, a desired level of accuracy and a near minimum computational cost. FCT adds more collocations points and higher resolution levels only in sensitive zones with sharp concentration gradients, fronts and/or narrow transition zones. According to the our recent achievements there is no need for solving the large linear system on adaptive grid because each Fup coefficient is obtained by predefined formulas equalizing Fup expansion around corresponding collocation point and particular collocation operator based on few surrounding solution values. Furthermore, each Fup coefficient can be obtained independently which is perfectly suited for parallel processing. Adaptive grid in each time step is obtained from solution of the last time step or initial conditions and advective Lagrangian step in the current time step according to the velocity field and continuous streamlines. On the other side, we implement explicit stabilized routine SERK2 for dispersive Eulerian part of solution in the current time step on obtained spatial adaptive grid. Overall adaptive concept does not require the solving of large linear systems for the spatial and temporal approximation of conservative transport. Also, this new Eulerian-Lagrangian-Collocation scheme resolves all mentioned numerical problems due to its adaptive nature and ability to control numerical errors in space and time. Proposed method solves advection in Lagrangian way eliminating problems in Eulerian methods, while optimal collocation grid efficiently describes solution and boundary conditions eliminating usage of large number of particles and other problems in Lagrangian methods. Finally, numerical tests show that this approach enables not only accurate velocity field, but also conservative transport even in highly heterogeneous porous media resolving all spatial and temporal scales of concentration field.

Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter

USGS Publications Warehouse

Kim, Jin-Woo; Lu, Zhong; Jones, John W.; Shum, C.K.; Lee, Hyongki; Jia, Yuanyuan

2014-01-01

The Florida Everglades plays a significant role in controlling floods, improving water quality, supporting ecosystems, and maintaining biodiversity in south Florida. Adaptive restoration and management of the Everglades requires the best information possible regarding wetland hydrology. We developed a new and innovative approach to quantify spatial and temporal variations in wetland water levels within the Everglades, Florida. We observed high correlations between water level measured at in situ gages and L-band SAR backscatter coefficients in the freshwater marsh, though C-band SAR backscatter has no close relationship with water level. Here we illustrate the complementarity of SAR backscatter coefficient differencing and interferometry (InSAR) for improved estimation of high spatial resolution water level variations in the Everglades. This technique has a certain limitation in applying to swamp forests with dense vegetation cover, but we conclude that this new method is promising in future applications to wetland hydrology research.

Stilt walking: how do we learn those first steps?

PubMed

Akram, Sakineh B; Frank, James S

2009-09-01

This study examined how young healthy adults learn stilt walking. Ten healthy male university students attended two sessions of testing held on two consecutive days. In each session participants performed three blocks of 10 stilt-walking trials. Angular movements of head and trunk and the spatial and temporal gait parameters were recorded. When walking on stilts young adults improved their gait velocity through modifications of step parameters while maintaining trunk movements close to that observed during normal over-ground walking. Participants improved their performance by increasing their step frequency and step length and reducing the double support percentage of the gait cycle. Stilts are often used for drywall installation, painting over-the-head areas and raising workers above the ground without the burden of erecting scaffolding. This research examines the locomotor adaptation as young healthy adults learn the complex motor task of stilt walking; a task that is frequently used in the construction industry.

Excitation and Adaptation in Bacteria–a Model Signal Transduction System that Controls Taxis and Spatial Pattern Formation

PubMed Central

Othmer, Hans G.; Xin, Xiangrong; Xue, Chuan

2013-01-01

The machinery for transduction of chemotactic stimuli in the bacterium E. coli is one of the most completely characterized signal transduction systems, and because of its relative simplicity, quantitative analysis of this system is possible. Here we discuss models which reproduce many of the important behaviors of the system. The important characteristics of the signal transduction system are excitation and adaptation, and the latter implies that the transduction system can function as a “derivative sensor” with respect to the ligand concentration in that the DC component of a signal is ultimately ignored if it is not too large. This temporal sensing mechanism provides the bacterium with a memory of its passage through spatially- or temporally-varying signal fields, and adaptation is essential for successful chemotaxis. We also discuss some of the spatial patterns observed in populations and indicate how cell-level behavior can be embedded in population-level descriptions. PMID:23624608

MULTISCALE ADAPTIVE SMOOTHING MODELS FOR THE HEMODYNAMIC RESPONSE FUNCTION IN FMRI*

PubMed Central

Wang, Jiaping; Zhu, Hongtu; Fan, Jianqing; Giovanello, Kelly; Lin, Weili

2012-01-01

In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response function (HRF) and its associated statistics (e.g., the magnitude and duration of the activation). Most methods to date are developed in the time domain and they have utilized almost exclusively the temporal information of fMRI data without accounting for the spatial information. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) in the frequency domain by integrating the spatial and temporal information to adaptively and accurately estimate HRFs pertaining to each stimulus sequence across all voxels in a three-dimensional (3D) volume. We use two sets of simulation studies and a real data set to examine the finite sample performance of MASM in estimating HRFs. Our real and simulated data analyses confirm that MASM outperforms several other state-of-art methods, such as the smooth finite impulse response (sFIR) model. PMID:24533041

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

PubMed Central

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-01

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management. PMID:29342852

Speaker Invariance for Phonetic Information: an fMRI Investigation

PubMed Central

Salvata, Caden; Blumstein, Sheila E.; Myers, Emily B.

2012-01-01

The current study explored how listeners map the variable acoustic input onto a common sound structure representation while being able to retain phonetic detail to distinguish among the identity of talkers. An adaptation paradigm was utilized to examine areas which showed an equal neural response (equal release from adaptation) to phonetic change when spoken by the same speaker and when spoken by two different speakers, and insensitivity (failure to show release from adaptation) when the same phonetic input was spoken by a different speaker. Neural areas which showed speaker invariance were located in the anterior portion of the middle superior temporal gyrus bilaterally. These findings provide support for the view that speaker normalization processes allow for the translation of a variable speech input to a common abstract sound structure. That this process appears to occur early in the processing stream, recruiting temporal structures, suggests that this mapping takes place prelexically, before sound structure input is mapped on to lexical representations. PMID:23264714

Step Detection Robust against the Dynamics of Smartphones

PubMed Central

Lee, Hwan-hee; Choi, Suji; Lee, Myeong-jin

2015-01-01

A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms. PMID:26516857

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region.

PubMed

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-13

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management.

Causal Entropies – a measure for determining changes in the temporal organization of neural systems

PubMed Central

Waddell, Jack; Dzakpasu, Rhonda; Booth, Victoria; Riley, Brett; Reasor, Jonathan; Poe, Gina; Zochowski, Michal

2009-01-01

We propose a novel measure to detect temporal ordering in the activity of individual neurons in a local network, which is thought to be a hallmark of activity-dependent synaptic modifications during learning. The measure, called Causal Entropy, is based on the time-adaptive detection of asymmetries in the relative temporal patterning between neuronal pairs. We characterize properties of the measure on both simulated data and experimental multiunit recordings of hippocampal neurons from the awake, behaving rat, and show that the metric can more readily detect those asymmetries than standard cross correlation-based techniques, especially since the temporal sensitivity of causal entropy can detect such changes rapidly and dynamically. PMID:17275095

Temporal BYY encoding, Markovian state spaces, and space dimension determination.

PubMed

Xu, Lei

2004-09-01

As a complementary to those temporal coding approaches of the current major stream, this paper aims at the Markovian state space temporal models from the perspective of the temporal Bayesian Ying-Yang (BYY) learning with both new insights and new results on not only the discrete state featured Hidden Markov model and extensions but also the continuous state featured linear state spaces and extensions, especially with a new learning mechanism that makes selection of the state number or the dimension of state space either automatically during adaptive learning or subsequently after learning via model selection criteria obtained from this mechanism. Experiments are demonstrated to show how the proposed approach works.

Brain structural changes following adaptive cognitive training assessed by Tensor-Based Morphometry (TBM)

PubMed Central

Colom, Roberto; Hua, Xue; Martínez, Kenia; Burgaleta, Miguel; Román, Francisco J.; Gunter, Jeffrey L.; Carmona, Susanna; Jaeggi, Susanne M.; Thompson, Paul M.

2016-01-01

Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. PMID:27477628

Sentence Syntax and Content in the Human Temporal Lobe: An fMRI Adaptation Study in Auditory and Visual Modalities

ERIC Educational Resources Information Center

Devauchelle, Anne-Dominique; Oppenheim, Catherine; Rizzi, Luigi; Dehaene, Stanislas; Pallier, Christophe

2009-01-01

Priming effects have been well documented in behavioral psycholinguistics experiments: The processing of a word or a sentence is typically facilitated when it shares lexico-semantic or syntactic features with a previously encountered stimulus. Here, we used fMRI priming to investigate which brain areas show adaptation to the repetition of a…

Does adaptation to vertebrate codon usage relate to flavivirus emergence potential?

PubMed Central

Freire, Caio César de Melo

2018-01-01

Codon adaptation index (CAI) is a measure of synonymous codon usage biases given a usage reference. Through mutation, selection, and drift, viruses can optimize their replication efficiency and produce more offspring, which could increase the chance of secondary transmission. To evaluate how higher CAI towards the host has been associated with higher viral titers, we explored temporal trends of several historic and extensively sequenced zoonotic flaviviruses and relationships within the genus itself. To showcase evolutionary and epidemiological relationships associated with silent, adaptive synonymous changes of viruses, we used codon usage tables from human housekeeping and antiviral immune genes, as well as tables from arthropod vectors and vertebrate species involved in the flavivirus maintenance cycle. We argue that temporal trends of CAI changes could lead to a better understanding of zoonotic emergences, evolutionary dynamics, and host adaptation. CAI appears to help illustrate historically relevant trends of well-characterized viruses, in different viral species and genetic diversity within a single species. CAI can be a useful tool together with in vivo and in vitro kinetics, phylodynamics, and additional functional genomics studies to better understand species trafficking and viral emergence in a new host. PMID:29385205

A typology of household-level adaptation to coastal flooding and its spatio-temporal patterns.

PubMed

Koerth, Jana; Vafeidis, Athanasios T; Carretero, Silvina; Sterr, Horst; Hinkel, Jochen

2014-01-01

The predicted sea-level rise and changes in storm surge regimes are expected to lead to an increasing risk of flooding in coastal regions. Accommodation can be an alternative to protection in many areas, with household-level adaptation potentially constituting an important element of such a strategy, as it can significantly reduce costs. To date, a systematic typology of household-level adaptation to coastal flooding does not exist. In order to bridge this gap, we conducted a series of quantitative surveys in different coastal areas in Denmark, Germany and Argentina. We applied a cluster analysis in order to categorise the adaptive behaviour of coastal households. Coastal households were found to cluster in four groups that we term: the comprehensives, the theoreticians, the minimalists and the structurals. With the exception of households focusing on the implementation of high-effort structural measures, our results show the affiliation to these groups to follow a specific temporal sequence. At the same time, large differences in category affiliation exist between the study areas. Risk communication tools can utilise our typology to selectively target specific types of households or to ensure that the information needs of all groups are addressed.

The brain dynamics of rapid perceptual adaptation to adverse listening conditions.

PubMed

Erb, Julia; Henry, Molly J; Eisner, Frank; Obleser, Jonas

2013-06-26

Listeners show a remarkable ability to quickly adjust to degraded speech input. Here, we aimed to identify the neural mechanisms of such short-term perceptual adaptation. In a sparse-sampling, cardiac-gated functional magnetic resonance imaging (fMRI) acquisition, human listeners heard and repeated back 4-band-vocoded sentences (in which the temporal envelope of the acoustic signal is preserved, while spectral information is highly degraded). Clear-speech trials were included as baseline. An additional fMRI experiment on amplitude modulation rate discrimination quantified the convergence of neural mechanisms that subserve coping with challenging listening conditions for speech and non-speech. First, the degraded speech task revealed an "executive" network (comprising the anterior insula and anterior cingulate cortex), parts of which were also activated in the non-speech discrimination task. Second, trial-by-trial fluctuations in successful comprehension of degraded speech drove hemodynamic signal change in classic "language" areas (bilateral temporal cortices). Third, as listeners perceptually adapted to degraded speech, downregulation in a cortico-striato-thalamo-cortical circuit was observable. The present data highlight differential upregulation and downregulation in auditory-language and executive networks, respectively, with important subcortical contributions when successfully adapting to a challenging listening situation.

An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances.

PubMed

Melcher, Anthony A; Horsburgh, Jeffery S

2017-06-01

Water quality in urban streams and stormwater systems is highly dynamic, both spatially and temporally, and can change drastically during storm events. Infrequent grab samples commonly collected for estimating pollutant loadings are insufficient to characterize water quality in many urban water systems. In situ water quality measurements are being used as surrogates for continuous pollutant load estimates; however, relatively few studies have tested the validity of surrogate indicators in urban stormwater conveyances. In this paper, we describe an observatory aimed at demonstrating the infrastructure required for surrogate monitoring in urban water systems and for capturing the dynamic behavior of stormwater-driven pollutant loads. We describe the instrumentation of multiple, autonomous water quality and quantity monitoring sites within an urban observatory. We also describe smart and adaptive sampling procedures implemented to improve data collection for developing surrogate relationships and for capturing the temporal and spatial variability of pollutant loading events in urban watersheds. Results show that the observatory is able to capture short-duration storm events within multiple catchments and, through inter-site communication, sampling efforts can be synchronized across multiple monitoring sites.

Prediction of human gait parameters from temporal measures of foot-ground contact

NASA Technical Reports Server (NTRS)

Breit, G. A.; Whalen, R. T.

1997-01-01

Investigation of the influence of human physical activity on bone functional adaptation requires long-term histories of gait-related ground reaction force (GRF). Towards a simpler portable GRF measurement, we hypothesized that: 1) the reciprocal of foot-ground contact time (1/tc); or 2) the reciprocal of stride-period-normalized contact time (T/tc) predict peak vertical and horizontal GRF, loading rates, and horizontal speed during gait. GRF data were collected from 24 subjects while they walked and ran at a variety of speeds. Linear regression and ANCOVA determined the dependence of gait parameters on 1/tc and T/tc, and prediction SE. All parameters were significantly correlated to 1/tc and T/tc. The closest pooled relationship existed between peak running vertical GRF and T/tc (r2 = 0.896; SE = 3.6%) and improved with subject-specific regression (r2 = 0.970; SE = 2.2%). We conclude that temporal measures can predict force parameters of gait and may represent an alternative to direct GRF measurements for determining daily histories of habitual lower limb loading quantities necessary to quantify a bone remodeling stimulus.

A highly sensitive and temporal visualization system for gaseous ethanol with chemiluminescence enhancer.

PubMed

Arakawa, Takahiro; Ando, Eri; Wang, Xin; Kumiko, Miyajima; Kudo, Hiroyuki; Saito, Hirokazu; Mitani, Tomoyo; Takahashi, Mitsuo; Mitsubayashi, Kohji

2012-01-01

A two-dimensional gaseous ethanol visualization system has been developed and demonstrated using a horseradish peroxidase-luminol-hydrogen peroxide system with high-purity luminol solution and a chemiluminescence (CL) enhancer. This system measures ethanol concentrations as intensities of CL via the luminol reaction. CL was emitted when the gaseous ethanol was injected onto an enzyme-immobilized membrane, which was employed as a screen for two-dimensional gas visualization. The average intensity of CL on the substrate was linearly related to the concentration of standard ethanol gas. These results were compared with the CL intensity of the CCD camera recording image in the visualization system. This system is available for gas components not only for spatial but also for temporal analysis in real time. A high-purity sodium salt HG solution (L-HG) instead of standard luminol solution and an enhancer, eosin Y (EY) solution, were adapted for improvement of CL intensity of the system. The visualization of gaseous ethanol was achieved at a detection limit of 3 ppm at optimized concentrations of L-HG solution and EY. Copyright © 2011 John Wiley & Sons, Ltd.

Combining PALM and SOFI for quantitative imaging of focal adhesions in living cells

NASA Astrophysics Data System (ADS)

Deschout, Hendrik; Lukes, Tomas; Sharipov, Azat; Feletti, Lely; Lasser, Theo; Radenovic, Aleksandra

2017-02-01

Focal adhesions are complicated assemblies of hundreds of proteins that allow cells to sense their extracellular matrix and adhere to it. Although most focal adhesion proteins have been identified, their spatial organization in living cells remains challenging to observe. Photo-activated localization microscopy (PALM) is an interesting technique for this purpose, especially since it allows estimation of molecular parameters such as the number of fluorophores. However, focal adhesions are dynamic entities, requiring a temporal resolution below one minute, which is difficult to achieve with PALM. In order to address this problem, we merged PALM with super-resolution optical fluctuation imaging (SOFI) by applying both techniques to the same data. Since SOFI tolerates an overlap of single molecule images, it can improve the temporal resolution compared to PALM. Moreover, an adaptation called balanced SOFI (bSOFI) allows estimation of molecular parameters, such as the fluorophore density. We therefore performed simulations in order to assess PALM and SOFI for quantitative imaging of dynamic structures. We demonstrated the potential of our PALM-SOFI concept as a quantitative imaging framework by investigating moving focal adhesions in living cells.

Adaptation to Temporally Fluctuating Environments by the Evolution of Maternal Effects.

PubMed

Dey, Snigdhadip; Proulx, Stephen R; Teotónio, Henrique

2016-02-01

All organisms live in temporally fluctuating environments. Theory predicts that the evolution of deterministic maternal effects (i.e., anticipatory maternal effects or transgenerational phenotypic plasticity) underlies adaptation to environments that fluctuate in a predictably alternating fashion over maternal-offspring generations. In contrast, randomizing maternal effects (i.e., diversifying and conservative bet-hedging), are expected to evolve in response to unpredictably fluctuating environments. Although maternal effects are common, evidence for their adaptive significance is equivocal since they can easily evolve as a correlated response to maternal selection and may or may not increase the future fitness of offspring. Using the hermaphroditic nematode Caenorhabditis elegans, we here show that the experimental evolution of maternal glycogen provisioning underlies adaptation to a fluctuating normoxia-anoxia hatching environment by increasing embryo survival under anoxia. In strictly alternating environments, we found that hermaphrodites evolved the ability to increase embryo glycogen provisioning when they experienced normoxia and to decrease embryo glycogen provisioning when they experienced anoxia. At odds with existing theory, however, populations facing irregularly fluctuating normoxia-anoxia hatching environments failed to evolve randomizing maternal effects. Instead, adaptation in these populations may have occurred through the evolution of fitness effects that percolate over multiple generations, as they maintained considerably high expected growth rates during experimental evolution despite evolving reduced fecundity and reduced embryo survival under one or two generations of anoxia. We develop theoretical models that explain why adaptation to a wide range of patterns of environmental fluctuations hinges on the existence of deterministic maternal effects, and that such deterministic maternal effects are more likely to contribute to adaptation than randomizing maternal effects.

Adaptation to Temporally Fluctuating Environments by the Evolution of Maternal Effects

PubMed Central

Dey, Snigdhadip; Proulx, Stephen R.; Teotónio, Henrique

2016-01-01

All organisms live in temporally fluctuating environments. Theory predicts that the evolution of deterministic maternal effects (i.e., anticipatory maternal effects or transgenerational phenotypic plasticity) underlies adaptation to environments that fluctuate in a predictably alternating fashion over maternal-offspring generations. In contrast, randomizing maternal effects (i.e., diversifying and conservative bet-hedging), are expected to evolve in response to unpredictably fluctuating environments. Although maternal effects are common, evidence for their adaptive significance is equivocal since they can easily evolve as a correlated response to maternal selection and may or may not increase the future fitness of offspring. Using the hermaphroditic nematode Caenorhabditis elegans, we here show that the experimental evolution of maternal glycogen provisioning underlies adaptation to a fluctuating normoxia–anoxia hatching environment by increasing embryo survival under anoxia. In strictly alternating environments, we found that hermaphrodites evolved the ability to increase embryo glycogen provisioning when they experienced normoxia and to decrease embryo glycogen provisioning when they experienced anoxia. At odds with existing theory, however, populations facing irregularly fluctuating normoxia–anoxia hatching environments failed to evolve randomizing maternal effects. Instead, adaptation in these populations may have occurred through the evolution of fitness effects that percolate over multiple generations, as they maintained considerably high expected growth rates during experimental evolution despite evolving reduced fecundity and reduced embryo survival under one or two generations of anoxia. We develop theoretical models that explain why adaptation to a wide range of patterns of environmental fluctuations hinges on the existence of deterministic maternal effects, and that such deterministic maternal effects are more likely to contribute to adaptation than randomizing maternal effects. PMID:26910440

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations.

PubMed

Swings, Toon; Weytjens, Bram; Schalck, Thomas; Bonte, Camille; Verstraeten, Natalie; Michiels, Jan; Marchal, Kathleen

2017-11-01

Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Adaptive and non-adaptive models of depression: A comparison using register data on antidepressant medication during divorce

PubMed Central

Fawcett, Tim W.; Higginson, Andrew D.; Metsä-Simola, Niina; Hagen, Edward H.; Houston, Alasdair I.; Martikainen, Pekka

2017-01-01

Divorce is associated with an increased probability of a depressive episode, but the causation of events remains unclear. Adaptive models of depression propose that depression is a social strategy in part, whereas non-adaptive models tend to propose a diathesis-stress mechanism. We compare an adaptive evolutionary model of depression to three alternative non-adaptive models with respect to their ability to explain the temporal pattern of depression around the time of divorce. Register-based data (304,112 individuals drawn from a random sample of 11% of Finnish people) on antidepressant purchases is used as a proxy for depression. This proxy affords an unprecedented temporal resolution (a 3-monthly prevalence estimates over 10 years) without any bias from non-compliance, and it can be linked with underlying episodes via a statistical model. The evolutionary-adaptation model (all time periods with risk of divorce are depressogenic) was the best quantitative description of the data. The non-adaptive stress-relief model (period before divorce is depressogenic and period afterwards is not) provided the second best quantitative description of the data. The peak-stress model (periods before and after divorce can be depressogenic) fit the data less well, and the stress-induction model (period following divorce is depressogenic and the preceding period is not) did not fit the data at all. The evolutionary model was the most detailed mechanistic description of the divorce-depression link among the models, and the best fit in terms of predicted curvature; thus, it offers most rigorous hypotheses for further study. The stress-relief model also fit very well and was the best model in a sensitivity analysis, encouraging development of more mechanistic models for that hypothesis. PMID:28614385

Adaptive and non-adaptive models of depression: A comparison using register data on antidepressant medication during divorce.

PubMed

Rosenström, Tom; Fawcett, Tim W; Higginson, Andrew D; Metsä-Simola, Niina; Hagen, Edward H; Houston, Alasdair I; Martikainen, Pekka

2017-01-01

Divorce is associated with an increased probability of a depressive episode, but the causation of events remains unclear. Adaptive models of depression propose that depression is a social strategy in part, whereas non-adaptive models tend to propose a diathesis-stress mechanism. We compare an adaptive evolutionary model of depression to three alternative non-adaptive models with respect to their ability to explain the temporal pattern of depression around the time of divorce. Register-based data (304,112 individuals drawn from a random sample of 11% of Finnish people) on antidepressant purchases is used as a proxy for depression. This proxy affords an unprecedented temporal resolution (a 3-monthly prevalence estimates over 10 years) without any bias from non-compliance, and it can be linked with underlying episodes via a statistical model. The evolutionary-adaptation model (all time periods with risk of divorce are depressogenic) was the best quantitative description of the data. The non-adaptive stress-relief model (period before divorce is depressogenic and period afterwards is not) provided the second best quantitative description of the data. The peak-stress model (periods before and after divorce can be depressogenic) fit the data less well, and the stress-induction model (period following divorce is depressogenic and the preceding period is not) did not fit the data at all. The evolutionary model was the most detailed mechanistic description of the divorce-depression link among the models, and the best fit in terms of predicted curvature; thus, it offers most rigorous hypotheses for further study. The stress-relief model also fit very well and was the best model in a sensitivity analysis, encouraging development of more mechanistic models for that hypothesis.

Effects of heat acclimation on time perception.

PubMed

Tamm, Maria; Jakobson, Ainika; Havik, Merle; Timpmann, Saima; Burk, Andres; Ööpik, Vahur; Allik, Jüri; Kreegipuu, Kairi

2015-03-01

Cognitive performance is impaired during prolonged exercise in hot environment compared to temperate conditions. These effects are related to both peripheral markers of heats stress and alterations in CNS functioning. Repeated-exposure to heat stress results in physiological adaptations, and therefore improvement in exercise capacity and cognitive functioning are observed. The objective of the current study was to clarify the factors contributing to time perception under heat stress and examine the effect of heat acclimation. 20 young healthy male subjects completed three exercise tests on a treadmill: H1 (at 60% VO(2)peak until exhaustion at 42°C), N (at 22°C; duration equal to H1) and H2 (walk until exhaustion at 42°C) following a 10-day heat acclimation program. Core temperature (T(C)) and heart rate (HR), ratings of perceived fatigue and exertion were obtained continuously during the exercise, and blood samples of hormones were taken before, during and after the exercise test for estimating the prolactin, growth hormone and cortisol response to acute exercise-heat stress. Interval production task was performed before, during and after the exercise test. Lower rate of rise in core temperature, heart rate, hormone response and subjective ratings indicated that the subjects had successfully acclimated. Before heat acclimation, significant distortions in produced intervals occurred after 60 minutes of exercise relative to pre-trial coefficients, indicating speeded temporal processing. However, this effect was absent after in acclimated subjects. Blood prolactin concentration predicted temporal performance in both conditions. Heat acclimation slows down the increase in physiological measures, and improvement in temporal processing is also evident. The results are explained within the internal clock model in terms of the pacemaker-accumulator functioning. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Temporal processing of speech in a time-feature space

NASA Astrophysics Data System (ADS)

Avendano, Carlos

1997-09-01

The performance of speech communication systems often degrades under realistic environmental conditions. Adverse environmental factors include additive noise sources, room reverberation, and transmission channel distortions. This work studies the processing of speech in the temporal-feature or modulation spectrum domain, aiming for alleviation of the effects of such disturbances. Speech reflects the geometry of the vocal organs, and the linguistically dominant component is in the shape of the vocal tract. At any given point in time, the shape of the vocal tract is reflected in the short-time spectral envelope of the speech signal. The rate of change of the vocal tract shape appears to be important for the identification of linguistic components. This rate of change, or the rate of change of the short-time spectral envelope can be described by the modulation spectrum, i.e. the spectrum of the time trajectories described by the short-time spectral envelope. For a wide range of frequency bands, the modulation spectrum of speech exhibits a maximum at about 4 Hz, the average syllabic rate. Disturbances often have modulation frequency components outside the speech range, and could in principle be attenuated without significantly affecting the range with relevant linguistic information. Early efforts for exploiting the modulation spectrum domain (temporal processing), such as the dynamic cepstrum or the RASTA processing, used ad hoc designed processing and appear to be suboptimal. As a major contribution, in this dissertation we aim for a systematic data-driven design of temporal processing. First we analytically derive and discuss some properties and merits of temporal processing for speech signals. We attempt to formalize the concept and provide a theoretical background which has been lacking in the field. In the experimental part we apply temporal processing to a number of problems including adaptive noise reduction in cellular telephone environments, reduction of reverberation for speech enhancement, and improvements on automatic recognition of speech degraded by linear distortions and reverberation.

Unique characteristics of motor adaptation during walking in young children.

PubMed

Musselman, Kristin E; Patrick, Susan K; Vasudevan, Erin V L; Bastian, Amy J; Yang, Jaynie F

2011-05-01

Children show precocious ability in the learning of languages; is this the case with motor learning? We used split-belt walking to probe motor adaptation (a form of motor learning) in children. Data from 27 children (ages 8-36 mo) were compared with those from 10 adults. Children walked with the treadmill belts at the same speed (tied belt), followed by walking with the belts moving at different speeds (split belt) for 8-10 min, followed again by tied-belt walking (postsplit). Initial asymmetries in temporal coordination (i.e., double support time) induced by split-belt walking were slowly reduced, with most children showing an aftereffect (i.e., asymmetry in the opposite direction to the initial) in the early postsplit period, indicative of learning. In contrast, asymmetries in spatial coordination (i.e., center of oscillation) persisted during split-belt walking and no aftereffect was seen. Step length, a measure of both spatial and temporal coordination, showed intermediate effects. The time course of learning in double support and step length was slower in children than in adults. Moreover, there was a significant negative correlation between the size of the initial asymmetry during early split-belt walking (called error) and the aftereffect for step length. Hence, children may have more difficulty learning when the errors are large. The findings further suggest that the mechanisms controlling temporal and spatial adaptation are different and mature at different times.

Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network).

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods depend on the number of nodes in the network or on the maximal number of connected nodes in the consecutive time steps. In the first case, this methodology breaks down if there are nodes with no edges. In the second case, it fails if the maximal number of active nodes is larger than the maximal number of connected nodes. In the following, an adaption of the calculation of the temporal correlation coefficient and of the topological overlap of the graph between two consecutive time steps is presented, which shows the expected behaviour mentioned above. The newly proposed adaption uses the maximal number of active nodes, i.e. the number of nodes with at least one edge, for the calculation of the topological overlap. The three methods were compared with the help of vivid example networks to reveal the differences between the proposed notations. Furthermore, these three calculation methods were applied to a real-world network of animal movements in order to detect influences of the network structure on the outcome of the different methods.

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

PubMed Central

Potjans, Wiebke; Diesmann, Markus; Morrison, Abigail

2011-01-01

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards. PMID:21589888

Dynamic monitoring of the Poyang Lake wetland by integrating Landsat and MODIS observations

NASA Astrophysics Data System (ADS)

Chen, Bin; Chen, Lifan; Huang, Bo; Michishita, Ryo; Xu, Bing

2018-05-01

The spatial and temporal adaptive reflectance fusion models (STARFM) have limited practical applications, because they often enforce the invalid assumption that land cover change does not occur between prior/posterior and target dates. To deal with this challenge, we proposed a spatiotemporal adaptive fusion model for NDVI products (STAFFN), to better blend highly resolved spatial and temporal information from multiple sensors. Compared with existing spatiotemporal fusion models, the proposed model integrates an initial prediction into a hierarchical selection strategy of similar pixels, and can capture landscape changes very well. Experiments using spatial details and temporal abundance comparison among MODIS, Landsat, and fusion results show that the predicted data can accurately capture temporal changes while preserving fine-spatial-resolution details. Model comparison also shows that STAFFNs produce consistently lower biases than STARFMs and the flexible spatiotemporal data fusion models (FSDAFs). A synthetic NDVI product (342 scenes in total) was produced with STAFFNs having a 16-day revisit frequency at 30-m spatial resolution from 2000 to 2014. With this product, we further provided a 15-year spatiotemporal change monitoring map of the Poyang Lake wetland. Results show that the water area in the dry season tended to lose 38.3 km2 yr-1 in coverage over the past 15 years, decreasing by 18.24% of the lake area between 2001 and 2014. The wetland vegetation group tended to increase in coverage, increasing by 10.08% of the lake area in the past 15 years. Our study indicates the STAFFN model can be reasonably applied in monitoring wetland dynamics, and can be easily adapted for the use with other ecosystems.

Adaptive social learning strategies in temporally and spatially varying environments : how temporal vs. spatial variation, number of cultural traits, and costs of learning influence the evolution of conformist-biased transmission, payoff-biased transmission, and individual learning.

PubMed

Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph

2012-12-01

Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data.

PubMed

Kotasidis, F A; Mehranian, A; Zaidi, H

2016-05-07

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

NASA Astrophysics Data System (ADS)

Kotasidis, F. A.; Mehranian, A.; Zaidi, H.

2016-05-01

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.

Global Population Structure and Evolution of Bordetella pertussis and Their Relationship with Vaccination

PubMed Central

Bart, Marieke J.; Harris, Simon R.; Advani, Abdolreza; Arakawa, Yoshichika; Bottero, Daniela; Bouchez, Valérie; Cassiday, Pamela K.; Chiang, Chuen-Sheue; Dalby, Tine; Fry, Norman K.; Gaillard, María Emilia; van Gent, Marjolein; Guiso, Nicole; Hallander, Hans O.; Harvill, Eric T.; He, Qiushui; van der Heide, Han G. J.; Heuvelman, Kees; Hozbor, Daniela F.; Kamachi, Kazunari; Karataev, Gennady I.; Lan, Ruiting; Lutyńska, Anna; Maharjan, Ram P.; Mertsola, Jussi; Miyamura, Tatsuo; Octavia, Sophie; Preston, Andrew; Quail, Michael A.; Sintchenko, Vitali; Stefanelli, Paola; Tondella, M. Lucia; Tsang, Raymond S. W.; Xu, Yinghua; Yao, Shu-Man; Zhang, Shumin; Mooi, Frits R.

2014-01-01

ABSTRACT Bordetella pertussis causes pertussis, a respiratory disease that is most severe for infants. Vaccination was introduced in the 1950s, and in recent years, a resurgence of disease was observed worldwide, with significant mortality in infants. Possible causes for this include the switch from whole-cell vaccines (WCVs) to less effective acellular vaccines (ACVs), waning immunity, and pathogen adaptation. Pathogen adaptation is suggested by antigenic divergence between vaccine strains and circulating strains and by the emergence of strains with increased pertussis toxin production. We applied comparative genomics to a worldwide collection of 343 B. pertussis strains isolated between 1920 and 2010. The global phylogeny showed two deep branches; the largest of these contained 98% of all strains, and its expansion correlated temporally with the first descriptions of pertussis outbreaks in Europe in the 16th century. We found little evidence of recent geographical clustering of the strains within this lineage, suggesting rapid strain flow between countries. We observed that changes in genes encoding proteins implicated in protective immunity that are included in ACVs occurred after the introduction of WCVs but before the switch to ACVs. Furthermore, our analyses consistently suggested that virulence-associated genes and genes coding for surface-exposed proteins were involved in adaptation. However, many of the putative adaptive loci identified have a physiological role, and further studies of these loci may reveal less obvious ways in which B. pertussis and the host interact. This work provides insight into ways in which pathogens may adapt to vaccination and suggests ways to improve pertussis vaccines. PMID:24757216

Brugga basin's TACD Model Adaptation to current GIS PCRaster 4.1

NASA Astrophysics Data System (ADS)

Lopez Rozo, Nicolas Antonio; Corzo Perez, Gerald Augusto; Santos Granados, Germán Ricardo

2017-04-01

The process-oriented catchment model TACD (Tracer-Aided Catchment model - Distributed) was developed in the Brugga Basin (Dark Forest, Germany) with a modular structure in the Geographic Information System PCRaster Version 2, in order to dynamically model the natural processes of a complex Basin, such as rainfall, air temperature, solar radiation, evapotranspiration and flow routing among others. Further research and application on this model has been done, such as adapting other meso-scaled basins and adding erosion processes in the hydrological model. However, TACD model is computationally intensive. This has made it not efficient on large and well discretized river basins. Aswell, the current version is not compatible with latest PCRaster Version 4.1, which offers new capabilities on 64-bit hardware architecture, hydraulic calculation improvements, in maps creation, some error and bug fixes. The current work studied and adapted TACD model into the latest GIS PCRaster Version 4.1. This was done by editing the original scripts, replacing deprecated functionalities without losing correctness of the TACD model. The correctness of the adapted TACD model was verified by using the original study case of the Brugga Basin and comparing the adapted model results with the original model results by Stefan Roser in 2001. Small differences were found due to the fact that some hydraulic and hydrological routines were optimized since version 2 of GIS PCRaster. Therefore, the hydraulic and hydrological processes are well represented. With this new working model, further research and development on current topics like uncertainty analysis, GCM downscaling techniques and spatio-temporal modelling are encouraged.

Just-in-time adaptive classifiers-part II: designing the classifier.

PubMed

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

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.

Linking multi-temporal satellite imagery to coastal wetland dynamics and bird distribution

USGS Publications Warehouse

Pickens, Bradley A.; King, Sammy L.

2014-01-01

Ecosystems are characterized by dynamic ecological processes, such as flooding and fires, but spatial models are often limited to a single measurement in time. The characterization of direct, fine-scale processes affecting animals is potentially valuable for management applications, but these are difficult to quantify over broad extents. Direct predictors are also expected to improve transferability of models beyond the area of study. Here, we investigated the ability of non-static and multi-temporal habitat characteristics to predict marsh bird distributions, while testing model generality and transferability between two coastal habitats. Distribution models were developed for king rail (Rallus elegans), common gallinule (Gallinula galeata), least bittern (Ixobrychus exilis), and purple gallinule (Porphyrio martinica) in fresh and intermediate marsh types in the northern Gulf Coast of Louisiana and Texas, USA. For model development, repeated point count surveys of marsh birds were conducted from 2009 to 2011. Landsat satellite imagery was used to quantify both annual conditions and cumulative, multi-temporal habitat characteristics. We used multivariate adaptive regression splines to quantify bird-habitat relationships for fresh, intermediate, and combined marsh habitats. Multi-temporal habitat characteristics ranked as more important than single-date characteristics, as temporary water was most influential in six of eight models. Predictive power was greater for marsh type-specific models compared to general models and model transferability was poor. Birds in fresh marsh selected for annual habitat characterizations, while birds in intermediate marsh selected for cumulative wetness and heterogeneity. Our findings emphasize that dynamic ecological processes can affect species distribution and species-habitat relationships may differ with dominant landscape characteristics.

Low-rank matrix decomposition and spatio-temporal sparse recovery for STAP radar

DOE PAGES

Sen, Satyabrata

2015-08-04

We develop space-time adaptive processing (STAP) methods by leveraging the advantages of sparse signal processing techniques in order to detect a slowly-moving target. We observe that the inherent sparse characteristics of a STAP problem can be formulated as the low-rankness of clutter covariance matrix when compared to the total adaptive degrees-of-freedom, and also as the sparse interference spectrum on the spatio-temporal domain. By exploiting these sparse properties, we propose two approaches for estimating the interference covariance matrix. In the first approach, we consider a constrained matrix rank minimization problem (RMP) to decompose the sample covariance matrix into a low-rank positivemore » semidefinite and a diagonal matrix. The solution of RMP is obtained by applying the trace minimization technique and the singular value decomposition with matrix shrinkage operator. Our second approach deals with the atomic norm minimization problem to recover the clutter response-vector that has a sparse support on the spatio-temporal plane. We use convex relaxation based standard sparse-recovery techniques to find the solutions. With extensive numerical examples, we demonstrate the performances of proposed STAP approaches with respect to both the ideal and practical scenarios, involving Doppler-ambiguous clutter ridges, spatial and temporal decorrelation effects. As a result, the low-rank matrix decomposition based solution requires secondary measurements as many as twice the clutter rank to attain a near-ideal STAP performance; whereas the spatio-temporal sparsity based approach needs a considerably small number of secondary data.« less

A multi-object statistical atlas adaptive for deformable registration errors in anomalous medical image segmentation

NASA Astrophysics Data System (ADS)

Botter Martins, Samuel; Vallin Spina, Thiago; Yasuda, Clarissa; Falcão, Alexandre X.

2017-02-01

Statistical Atlases have played an important role towards automated medical image segmentation. However, a challenge has been to make the atlas more adaptable to possible errors in deformable registration of anomalous images, given that the body structures of interest for segmentation might present significant differences in shape and texture. Recently, deformable registration errors have been accounted by a method that locally translates the statistical atlas over the test image, after registration, and evaluates candidate objects from a delineation algorithm in order to choose the best one as final segmentation. In this paper, we improve its delineation algorithm and extend the model to be a multi-object statistical atlas, built from control images and adaptable to anomalous images, by incorporating a texture classifier. In order to provide a first proof of concept, we instantiate the new method for segmenting, object-by-object and all objects simultaneously, the left and right brain hemispheres, and the cerebellum, without the brainstem, and evaluate it on MRT1-images of epilepsy patients before and after brain surgery, which removed portions of the temporal lobe. The results show efficiency gain with statistically significant higher accuracy, using the mean Average Symmetric Surface Distance, with respect to the original approach.

An adaptive Bayesian inference algorithm to estimate the parameters of a hazardous atmospheric release

NASA Astrophysics Data System (ADS)

Rajaona, Harizo; Septier, François; Armand, Patrick; Delignon, Yves; Olry, Christophe; Albergel, Armand; Moussafir, Jacques

2015-12-01

In the eventuality of an accidental or intentional atmospheric release, the reconstruction of the source term using measurements from a set of sensors is an important and challenging inverse problem. A rapid and accurate estimation of the source allows faster and more efficient action for first-response teams, in addition to providing better damage assessment. This paper presents a Bayesian probabilistic approach to estimate the location and the temporal emission profile of a pointwise source. The release rate is evaluated analytically by using a Gaussian assumption on its prior distribution, and is enhanced with a positivity constraint to improve the estimation. The source location is obtained by the means of an advanced iterative Monte-Carlo technique called Adaptive Multiple Importance Sampling (AMIS), which uses a recycling process at each iteration to accelerate its convergence. The proposed methodology is tested using synthetic and real concentration data in the framework of the Fusion Field Trials 2007 (FFT-07) experiment. The quality of the obtained results is comparable to those coming from the Markov Chain Monte Carlo (MCMC) algorithm, a popular Bayesian method used for source estimation. Moreover, the adaptive processing of the AMIS provides a better sampling efficiency by reusing all the generated samples.

Horizontal Line-of-Sight Turbulence Over Near-Ground Paths and Implications for Adaptive Optics Corrections in Laser Communications.

PubMed

Levine, B M; Martinsen, E A; Wirth, A; Jankevics, A; Toledo-Quinones, M; Landers, F; Bruno, T L

1998-07-20

Atmospheric turbulence over long horizontal paths perturbs phase and can also cause severe intensity scintillation in the pupil of an optical communications receiver, which limits the data rate over which intensity-based modulation schemes can operate. The feasibility of using low-order adaptive optics by applying phase-only corrections over horizontal propagation paths is investigated. A Shack-Hartmann wave-front sensor was built and data were gathered on paths 1 m above ground and between a 1- and 2.5-km range. Both intensity fluctuations and optical path fluctuation statistics were gathered within a single frame, and the wave-front reconstructor was modified to allow for scintillated data. The temporal power spectral density for various Zernike polynomial modes was used to determine the effects of the expected corrections by adaptive optics. The slopes of the inertial subrange of turbulence were found to be less than predicted by Kolmogorov theory with an infinite outer scale, and the distribution of variance explained by increasing order was also found to be different. Statistical analysis of these data in the 1-km range indicates that at communications wavelengths of 1.3 mum, a significant improvement in transmitted beam quality could be expected most of the time, to a performance of 10% Strehl ratio or better.

Influence of adaptive statistical iterative reconstruction algorithm on image quality in coronary computed tomography angiography.

PubMed

Precht, Helle; Thygesen, Jesper; Gerke, Oke; Egstrup, Kenneth; Waaler, Dag; Lambrechtsen, Jess

2016-12-01

Coronary computed tomography angiography (CCTA) requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR) techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. To evaluate whether adaptive statistical iterative reconstruction (ASIR) enhances perceived image quality in CCTA compared to filtered back projection (FBP). Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA) and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR]) was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR ( P  = 0.004). The objective measures showed significant differences between FBP and 60% ASIR ( P  < 0.0001) for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR.

Adapting improvements to context: when, why and how?

PubMed Central

Ovretveit, John; Dolan-Branton, Lisa; Marx, Michael; Reid, Amy; Reed, Julie; Agins, Bruce

2018-01-01

Abstract There is evidence that practitioners applying quality improvements often adapt the improvement method or the change they are implementing, either unknowingly, or intentionally to fit their service or situation. This has been observed especially in programs seeking to spread or ‘scale up’ an improvement change to other services. Sometimes their adaptations result in improved outcomes, sometimes they do not, and sometimes they do not have data make this assessment or to describe the adaptation. The purpose of this paper is to summarize key points about adaptation and context discussed at the Salzburg Global Seminar in order to help improvers judge when and how to adapt an improvement change. It aims also to encourage more research into such adaptations to develop our understanding of the when, why and how of effective adaptation and to provide more research informed guidance to improvers. The paper gives examples to illustrate key issues in adaptation and to consider more systematic and purposeful adaptation of improvements so as to increase the chances of achieving improvements in different settings for different participants. We describe methods for assessing whether adaptation is necessary or likely to reduce the effectiveness of an improvement intervention, which adaptations might be required, and methods for collecting data to assess whether the adaptations are successful. We also note areas where research is most needed in order to enable more effective scale up of quality improvements changes and wider take up and use of the methods.

Automated extraction of temporal motor activity signals from video recordings of neonatal seizures based on adaptive block matching.

PubMed

Karayiannis, Nicolaos B; Sami, Abdul; Frost, James D; Wise, Merrill S; Mizrahi, Eli M

2005-04-01

This paper presents an automated procedure developed to extract quantitative information from video recordings of neonatal seizures in the form of motor activity signals. This procedure relies on optical flow computation to select anatomical sites located on the infants' body parts. Motor activity signals are extracted by tracking selected anatomical sites during the seizure using adaptive block matching. A block of pixels is tracked throughout a sequence of frames by searching for the most similar block of pixels in subsequent frames; this search is facilitated by employing various update strategies to account for the changing appearance of the block. The proposed procedure is used to extract temporal motor activity signals from video recordings of neonatal seizures and other events not associated with seizures.

Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

2015-12-01

A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each individual product and demonstrate the precipitation data fusion performance, both individual and fused QPE products are evaluated using rainfall measurements from a disdrometer and gauge network.

Understanding, management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

NASA Astrophysics Data System (ADS)

Fletcher, T. D.; Andrieu, H.; Hamel, P.

2013-01-01

Urban hydrology has evolved to improve the way urban runoff is managed for flood protection, public health and environmental protection. There have been significant recent advances in the measurement and prediction of urban rainfall, with technologies such as radar and microwave networks showing promise. The ability to predict urban hydrology has also evolved, to deliver models suited to the small temporal and spatial scales typical of urban and peri-urban applications. Urban stormwater management increasingly consider the needs of receiving environments as well as those of humans. There is a clear trend towards approaches that attempt to restore pre-development flow-regimes and water quality, with an increasing recognition that restoring a more natural water balance benefits not only the environment, but enhances the liveability of the urban landscape. Once regarded only as a nuisance, stormwater is now increasingly regarded as a resource. Despite the advances, many important challenges in urban hydrology remain. Further research into the spatio-temporal dynamics of urban rainfall is required to improve short-term rainfall prediction. The performance of stormwater technologies in restoring the water balance and in removing emerging priority pollutants remain poorly quantified. All of these challenges are overlaid by the uncertainty of climate change, which imposes a requirement to ensure that stormwater management systems are adaptable and resilient to changes. Urban hydrology will play a critical role in addressing these challenges.

The fundamentals of adaptive grid movement

NASA Technical Reports Server (NTRS)

Eiseman, Peter R.

1990-01-01

Basic grid point movement schemes are studied. The schemes are referred to as adaptive grids. Weight functions and equidistribution in one dimension are treated. The specification of coefficients in the linear weight, attraction to a given grid or a curve, and evolutionary forces are considered. Curve by curve and finite volume methods are described. The temporal coupling of partial differential equations solvers and grid generators was discussed.

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Treesearch

Michael S. Balshi; A. David McGuire; Paul Duffy; Mike Flannigan; John Walsh; Jerry Melillo

2009-01-01

We developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5o (latitude x longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was...

Adaptive Numerical Algorithms in Space Weather Modeling

NASA Technical Reports Server (NTRS)

Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.;

Quantifying interictal metabolic activity in human temporal lobe epilepsy

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

Henry, T.R.; Mazziotta, J.C.; Engel, J. Jr.

1990-09-01

The majority of patients with complex partial seizures of unilateral temporal lobe origin have interictal temporal hypometabolism on (18F)fluorodeoxyglucose positron emission tomography (FDG PET) studies. Often, this hypometabolism extends to ipsilateral extratemporal sites. The use of accurately quantified metabolic data has been limited by the absence of an equally reliable method of anatomical analysis of PET images. We developed a standardized method for visual placement of anatomically configured regions of interest on FDG PET studies, which is particularly adapted to the widespread, asymmetric, and often severe interictal metabolic alterations of temporal lobe epilepsy. This method was applied by a singlemore » investigator, who was blind to the identity of subjects, to 10 normal control and 25 interictal temporal lobe epilepsy studies. All subjects had normal brain anatomical volumes on structural neuroimaging studies. The results demonstrate ipsilateral thalamic and temporal lobe involvement in the interictal hypometabolism of unilateral temporal lobe epilepsy. Ipsilateral frontal, parietal, and basal ganglial metabolism is also reduced, although not as markedly as is temporal and thalamic metabolism.« less

Application of Recent Advances in Forward Modeling of Emissions from Boreal and Temperate Wildfires to Real-time Forecasting of Aerosol and Trace Gas Concentrations

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Kasischke, E. S.; Allen, D. J.

2005-12-01

The magnitude of trace gas and aerosol emissions from wildfires is a scientific problem with important implications for atmospheric composition, and is also integral to understanding carbon cycling in terrestrial ecosystems. Recent ecological research on modeling wildfire emissions has integrated theoretical advances derived from ecological fieldwork with improved spatial and temporal databases to produce "post facto" estimates of emissions with high spatial and temporal resolution. These advances have been shown to improve agreement with atmospheric observations at coarse scales, but can in principle be applied to applications, such as forecasting, at finer scales. However, several of the approaches employed in these forward models are incompatible with the requirements of real-time forecasting, requiring modification of data inputs and calculation methods. Because of the differences in data inputs used for real-time and "post-facto" emissions modeling, the key uncertainties in the forward problem are not necessarily the same for these two applications. However, adaptation of these advances in forward modeling to forecasting applications has the potential to improve air quality forecasts, and also to provide a large body of experimental data which can be used to constrain crucial uncertainties in current conceptual models of wildfire emissions. This talk describes a forward modeling method developed at the University of Maryland and its application to the Fire Locating and Modeling of Burning Emissions (FLAMBE) system at the Naval Research Laboratory. Methods for applying the outputs of the NRL aerosol forecasting system to the inverse problem of constraining emissions will also be discussed. The system described can use the feedback supplied by atmospheric observations to improve the emissions source description in the forecasting model, and can also be used for hypothesis testing regarding fire behavior and data inputs.

Improving the community-temperature index as a climate change indicator.

PubMed

Bowler, Diana; Böhning-Gaese, Katrin

2017-01-01

Climate change indicators are tools to assess, visualize and communicate the impacts of climate change on species and communities. Indicators that can be applied to different taxa are particularly useful because they allow comparative analysis to identify which kinds of species are being more affected. A general prediction, supported by empirical data, is that the abundance of warm-adapted species should increase over time, relative to the cool-adapted ones within communities, under increasing ambient temperatures. The community temperature index (CTI) is a community weighted mean of species' temperature preferences and has been used as an indicator to summarize this temporal shift. The CTI has the advantages of being a simple and generalizable indicator; however, a core problem is that temporal trends in the CTI may not only reflect changes in temperature. This is because species' temperature preferences often covary with other species attributes, and these other attributes may affect species response to other environmental drivers. Here, we propose a novel model-based approach that separates the effects of temperature preference from the effects of other species attributes on species' abundances and subsequently on the CTI. Using long-term population data of breeding birds in Denmark and demersal marine fish in the southeastern North Sea, we find differences in CTI trends with the original approach and our model-based approach, which may affect interpretation of climate change impacts. We suggest that our method can be used to test the robustness of CTI trends to the possible effects of other drivers of change, apart from climate change.

TH-E-17A-09: High Quality and Artifact-Free 4D Cone Beam CT and Its Application in Adaptive Treatment Planning

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

Niu, K; Li, K; Smilowitz, J

2014-06-15

Purpose: To develop a high quality 4D cone beam CT (4DCBCT) method that is immune to patient/couch truncations and to investigate its application in adaptive replanning of lung XRT. Methods: In this study, IRB-approved human subject CBCT data was acquired using a Varian on-board imager with 1 minute rotation time. The acquired projection data was retrospectively sorted into 20 respiratory phase bins, from which 4DCBCT images with high SNR and high temporal resolution were generated using Prior Image Constrained Compressed Sensing (PICCS). Couch and patient truncations generate strong data inconsistency in the projection data and artifacts in the 4DCBCT image.more » They were addressed using an adaptive PICCS method. The artifact-free PICCS-4DCBCT images were used to generate adaptive treatment plans for the same patient at the 10th (day 21) and 30th (day 47) fractions. Dosimetric impacts with and without PICCS- 4DCBCT were evaluated by isodose distributions, DVHs, and other dosimetric factors. Results: The adaptive PICCS-4DCBCT method improves image quality by removing residue truncation artifacts; measured universal image quality increased 37%. The isodose lines and DVHs with PICCS-4DCBCT-based adaptive replanning were significantly more conformal to PTV than without replanning due to changes in patient anatomy caused by progress of the treatment. The mean dose to PTV at the 10th fraction was 63.1Gy with replanning and 64.2Gy without replanning, where the prescribed dose was 60Gy, in 2Gy × 30 fractions. The mean dose to PTV at the 30th fraction was 61.6Gy with replanning and 64.9Gy without replanning. Lung V20 was 37.1%, 41.9% and 43.3% for original plan, 10th fraction plan and 30th fraction plan; with re-planning, Lung V20 was 37.1%, 32%, 27.8%. Conclusion: 4DCBCT imaging using adaptive PICCS is able to generate high quality, artifact-free images that potentially can be used to create replanning for improving radiotherapy of the lung. K Niu, K Li, J Smilowitz: Nothing to Disclose. G Chen: General Electric Company Research funded, Siemens AG Research funded, Varian Medical Systems Research funded, Hologic Research funded.« less

An improved rotated staggered-grid finite-difference method with fourth-order temporal accuracy for elastic-wave modeling in anisotropic media

DOE PAGES

Gao, Kai; Huang, Lianjie

2017-08-31

The rotated staggered-grid (RSG) finite-difference method is a powerful tool for elastic-wave modeling in 2D anisotropic media where the symmetry axes of anisotropy are not aligned with the coordinate axes. We develop an improved RSG scheme with fourth-order temporal accuracy to reduce the numerical dispersion associated with prolonged wave propagation or a large temporal step size. The high-order temporal accuracy is achieved by including high-order temporal derivatives, which can be converted to high-order spatial derivatives to reduce computational cost. Dispersion analysis and numerical tests show that our method exhibits very low temporal dispersion even with a large temporal step sizemore » for elastic-wave modeling in complex anisotropic media. Using the same temporal step size, our method is more accurate than the conventional RSG scheme. In conclusion, our improved RSG scheme is therefore suitable for prolonged modeling of elastic-wave propagation in 2D anisotropic media.« less

An improved rotated staggered-grid finite-difference method with fourth-order temporal accuracy for elastic-wave modeling in anisotropic media

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

Gao, Kai; Huang, Lianjie

The rotated staggered-grid (RSG) finite-difference method is a powerful tool for elastic-wave modeling in 2D anisotropic media where the symmetry axes of anisotropy are not aligned with the coordinate axes. We develop an improved RSG scheme with fourth-order temporal accuracy to reduce the numerical dispersion associated with prolonged wave propagation or a large temporal step size. The high-order temporal accuracy is achieved by including high-order temporal derivatives, which can be converted to high-order spatial derivatives to reduce computational cost. Dispersion analysis and numerical tests show that our method exhibits very low temporal dispersion even with a large temporal step sizemore » for elastic-wave modeling in complex anisotropic media. Using the same temporal step size, our method is more accurate than the conventional RSG scheme. In conclusion, our improved RSG scheme is therefore suitable for prolonged modeling of elastic-wave propagation in 2D anisotropic media.« less

DEVELOPMENT AND IMPROVEMENT OF TEMPORAL ALLOCATION FACTOR FILES

EPA Science Inventory

The report gives results of a project to: (1) evaluate the quality and completeness of data and methods being used for temporal allocation of emissions data, (2) identify and prioritize needed improvements to current methods for developing temporal allocation factors (TAFs), and ...

Rod phototransduction determines the trade-off of temporal integration and speed of vision in dark-adapted toads.

PubMed

Haldin, Charlotte; Nymark, Soile; Aho, Ann-Christine; Koskelainen, Ari; Donner, Kristian

2009-05-06

Human vision is approximately 10 times less sensitive than toad vision on a cool night. Here, we investigate (1) how far differences in the capacity for temporal integration underlie such differences in sensitivity and (2) whether the response kinetics of the rod photoreceptors can explain temporal integration at the behavioral level. The toad was studied as a model that allows experimentation at different body temperatures. Sensitivity, integration time, and temporal accuracy of vision were measured psychophysically by recording snapping at worm dummies moving at different velocities. Rod photoresponses were studied by ERG recording across the isolated retina. In both types of experiments, the general timescale of vision was varied by using two temperatures, 15 and 25 degrees C. Behavioral integration times were 4.3 s at 15 degrees C and 0.9 s at 25 degrees C, and rod integration times were 4.2-4.3 s at 15 degrees C and 1.0-1.3 s at 25 degrees C. Maximal behavioral sensitivity was fivefold lower at 25 degrees C than at 15 degrees C, which can be accounted for by inability of the "warm" toads to integrate light over longer times than the rods. However, the long integration time at 15 degrees C, allowing high sensitivity, degraded the accuracy of snapping toward quickly moving worms. We conclude that temporal integration explains a considerable part of all variation in absolute visual sensitivity. The strong correlation between rods and behavior suggests that the integration time of dark-adapted vision is set by rod phototransduction at the input to the visual system. This implies that there is an inexorable trade-off between temporal integration and resolution.

Engineering healthcare as a service system.

PubMed

Tien, James M; Goldschmidt-Clermont, Pascal J

2010-01-01

Engineering has and will continue to have a critical impact on healthcare; the application of technology-based techniques to biological problems can be defined to be technobiology applications. This paper is primarily focused on applying the technobiology approach of systems engineering to the development of a healthcare service system that is both integrated and adaptive. In general, healthcare services are carried out with knowledge-intensive agents or components which work together as providers and consumers to create or co-produce value. Indeed, the engineering design of a healthcare system must recognize the fact that it is actually a complex integration of human-centered activities that is increasingly dependent on information technology and knowledge. Like any service system, healthcare can be considered to be a combination or recombination of three essential components - people (characterized by behaviors, values, knowledge, etc.), processes (characterized by collaboration, customization, etc.) and products (characterized by software, hardware, infrastructures, etc.). Thus, a healthcare system is an integrated and adaptive set of people, processes and products. It is, in essence, a system of systems which objectives are to enhance its efficiency (leading to greater interdependency) and effectiveness (leading to improved health). Integration occurs over the physical, temporal, organizational and functional dimensions, while adaptation occurs over the monitoring, feedback, cybernetic and learning dimensions. In sum, such service systems as healthcare are indeed complex, especially due to the uncertainties associated with the human-centered aspects of these systems. Moreover, the system complexities can only be dealt with methods that enhance system integration and adaptation.

Can you sequence ecology? Metagenomics of adaptive diversification.

PubMed

Marx, Christopher J

2013-01-01

Few areas of science have benefited more from the expansion in sequencing capability than the study of microbial communities. Can sequence data, besides providing hypotheses of the functions the members possess, detect the evolutionary and ecological processes that are occurring? For example, can we determine if a species is adapting to one niche, or if it is diversifying into multiple specialists that inhabit distinct niches? Fortunately, adaptation of populations in the laboratory can serve as a model to test our ability to make such inferences about evolution and ecology from sequencing. Even adaptation to a single niche can give rise to complex temporal dynamics due to the transient presence of multiple competing lineages. If there are multiple niches, this complexity is augmented by segmentation of the population into multiple specialists that can each continue to evolve within their own niche. For a known example of parallel diversification that occurred in the laboratory, sequencing data gave surprisingly few obvious, unambiguous signs of the ecological complexity present. Whereas experimental systems are open to direct experimentation to test hypotheses of selection or ecological interaction, the difficulty in "seeing ecology" from sequencing for even such a simple system suggests translation to communities like the human microbiome will be quite challenging. This will require both improved empirical methods to enhance the depth and time resolution for the relevant polymorphisms and novel statistical approaches to rigorously examine time-series data for signs of various evolutionary and ecological phenomena within and between species.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-05-01

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

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.

Ensemble framework based real-time respiratory motion prediction for adaptive radiotherapy applications.

PubMed

Tatinati, Sivanagaraja; Nazarpour, Kianoush; Tech Ang, Wei; Veluvolu, Kalyana C

2016-08-01

Successful treatment of tumors with motion-adaptive radiotherapy requires accurate prediction of respiratory motion, ideally with a prediction horizon larger than the latency in radiotherapy system. Accurate prediction of respiratory motion is however a non-trivial task due to the presence of irregularities and intra-trace variabilities, such as baseline drift and temporal changes in fundamental frequency pattern. In this paper, to enhance the accuracy of the respiratory motion prediction, we propose a stacked regression ensemble framework that integrates heterogeneous respiratory motion prediction algorithms. We further address two crucial issues for developing a successful ensemble framework: (1) selection of appropriate prediction methods to ensemble (level-0 methods) among the best existing prediction methods; and (2) finding a suitable generalization approach that can successfully exploit the relative advantages of the chosen level-0 methods. The efficacy of the developed ensemble framework is assessed with real respiratory motion traces acquired from 31 patients undergoing treatment. Results show that the developed ensemble framework improves the prediction performance significantly compared to the best existing methods. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Flood risk analysis and adaptive strategy in context of uncertainties: a case study of Nhieu Loc Thi Nghe Basin, Ho Chi Minh City

NASA Astrophysics Data System (ADS)

Ho, Long-Phi; Chau, Nguyen-Xuan-Quang; Nguyen, Hong-Quan

2013-04-01

The Nhieu Loc - Thi Nghe basin is the most important administrative and business area of Ho Chi Minh City. Due to system complexity of the basin such as the increasing trend of rainfall intensity, (tidal) water level and land subsidence, the simulation of hydrological, hydraulic variables for flooding prediction seems rather not adequate in practical projects. The basin is still highly vulnerable despite of multi-million USD investment for urban drainage improvement projects since the last decade. In this paper, an integrated system analysis in both spatial and temporal aspects based on statistical, GIS and modelling approaches has been conducted in order to: (1) Analyse risks before and after projects, (2) Foresee water-related risk under uncertainties of unfavourable driving factors and (3) Develop a sustainable flood risk management strategy for the basin. The results show that given the framework of risk analysis and adaptive strategy, certain urban developing plans in the basin must be carefully revised and/or checked in order to reduce the highly unexpected loss in the future

Gray matter responsiveness to adaptive working memory training: a surface-based morphometry study

PubMed Central

Román, Francisco J.; Lewis, Lindsay B.; Chen, Chi-Hua; Karama, Sherif; Burgaleta, Miguel; Martínez, Kenia; Lepage, Claude; Jaeggi, Susanne M.; Evans, Alan C.; Kremen, William S.

2016-01-01

Here we analyze gray matter indices before and after completing a challenging adaptive cognitive training program based on the n-back task. The considered gray matter indices were cortical thickness (CT) and cortical surface area (CSA). Twenty-eight young women (age range 17–22 years) completed 24 training sessions over the course of 3 months (12 weeks, 24 sessions), showing expected performance improvements. CT and CSA values for the training group were compared with those of a matched control group. Statistical analyses were computed using a ROI framework defined by brain areas distinguished by their genetic underpinning. The interaction between group and time was analyzed. Middle temporal, ventral frontal, inferior parietal cortices, and pars opercularis were the regions where the training group showed conservation of gray matter with respect to the control group. These regions support working memory, resistance to interference, and inhibition. Furthermore, an interaction with baseline intelligence differences showed that the expected decreasing trend at the biological level for individuals showing relatively low intelligence levels at baseline was attenuated by the completed training. PMID:26701168

Nonlinearly preconditioned semismooth Newton methods for variational inequality solution of two-phase flow in porous media

NASA Astrophysics Data System (ADS)

Yang, Haijian; Sun, Shuyu; Yang, Chao

2017-03-01

Most existing methods for solving two-phase flow problems in porous media do not take the physically feasible saturation fractions between 0 and 1 into account, which often destroys the numerical accuracy and physical interpretability of the simulation. To calculate the solution without the loss of this basic requirement, we introduce a variational inequality formulation of the saturation equilibrium with a box inequality constraint, and use a conservative finite element method for the spatial discretization and a backward differentiation formula with adaptive time stepping for the temporal integration. The resulting variational inequality system at each time step is solved by using a semismooth Newton algorithm. To accelerate the Newton convergence and improve the robustness, we employ a family of adaptive nonlinear elimination methods as a nonlinear preconditioner. Some numerical results are presented to demonstrate the robustness and efficiency of the proposed algorithm. A comparison is also included to show the superiority of the proposed fully implicit approach over the classical IMplicit Pressure-Explicit Saturation (IMPES) method in terms of the time step size and the total execution time measured on a parallel computer.

Adaptive control with self-tuning for non-invasive beat-by-beat blood pressure measurement.

PubMed

Nogawa, Masamichi; Ogawa, Mitsuhiro; Yamakoshi, Takehiro; Tanaka, Shinobu; Yamakoshi, Ken-ichi

2011-01-01

Up to now, we have successfully carried out the non-invasive beat-by-beat measurement of blood pressure (BP) in the root of finger, superficial temporal and radial artery based on the volume-compensation technique with reasonable accuracy. The present study concerns with improvement of control method for this beat-by-beat BP measurement. The measurement system mainly consists of a partial pressurization cuff with a pair of LED and photo-diode for the detection of arterial blood volume, and a digital self-tuning control method. Using healthy subjects, the performance and accuracy of this system were evaluated through comparison experiments with the system using a conventional empirically tuned PID controller. The significant differences of BP measured in finger artery were not showed in systolic (SBP), p=0.52, and diastolic BP (DBP), p=0.35. With the advantage of the adaptive control with self-tuning method, which can tune the control parameters without disturbing the control system, the application area of the non-invasive beat-by-beat measurement method will be broadened.

Clipping in neurocontrol by adaptive dynamic programming.

PubMed

Fairbank, Michael; Prokhorov, Danil; Alonso, Eduardo

2014-10-01

In adaptive dynamic programming, neurocontrol, and reinforcement learning, the objective is for an agent to learn to choose actions so as to minimize a total cost function. In this paper, we show that when discretized time is used to model the motion of the agent, it can be very important to do clipping on the motion of the agent in the final time step of the trajectory. By clipping, we mean that the final time step of the trajectory is to be truncated such that the agent stops exactly at the first terminal state reached, and no distance further. We demonstrate that when clipping is omitted, learning performance can fail to reach the optimum, and when clipping is done properly, learning performance can improve significantly. The clipping problem we describe affects algorithms that use explicit derivatives of the model functions of the environment to calculate a learning gradient. These include backpropagation through time for control and methods based on dual heuristic programming. However, the clipping problem does not significantly affect methods based on heuristic dynamic programming, temporal differences learning, or policy-gradient learning algorithms.

Temporal Doppler Effect and Future Orientation: Adaptive Function and Moderating Conditions.

PubMed

Gan, Yiqun; Miao, Miao; Zheng, Lei; Liu, Haihua

2017-06-01

The objectives of this study were to examine whether the temporal Doppler effect exists in different time intervals and whether certain individual and environmental factors act as moderators of the effect. Using hierarchical linear modeling, we examined the existence of the temporal Doppler effect and the moderating effect of future orientation among 139 university students (Study 1), and then the moderating conditions of the temporal Doppler effect using two independent samples of 143 and 147 university students (Studies 2 and 3). Results indicated that the temporal Doppler effect existed in all of our studies, and that future orientation moderated the temporal Doppler effect. Further, time interval perception mediated the relationship between future orientation and the motivation to cope at long time intervals. Finally, positive affect was found to enhance the temporal Doppler effect, whereas control deprivation did not influence the effect. The temporal Doppler effect is moderated by the personality trait of future orientation and by the situational variable of experimentally manipulated positive affect. We have identified personality and environmental processes that could enhance the temporal Doppler effect, which could be valuable in cases where attention to a future task is necessary. © 2016 Wiley Periodicals, Inc.

Temporal compression in episodic memory for real-life events.

PubMed

Jeunehomme, Olivier; Folville, Adrien; Stawarczyk, David; Van der Linden, Martial; D'Argembeau, Arnaud

2018-07-01

Remembering an event typically takes less time than experiencing it, suggesting that episodic memory represents past experience in a temporally compressed way. Little is known, however, about how the continuous flow of real-life events is summarised in memory. Here we investigated the nature and determinants of temporal compression by directly comparing memory contents with the objective timing of events as measured by a wearable camera. We found that episodic memories consist of a succession of moments of prior experience that represent events with varying compression rates, such that the density of retrieved information is modulated by goal processing and perceptual changes. Furthermore, the results showed that temporal compression rates remain relatively stable over one week and increase after a one-month delay, particularly for goal-related events. These data shed new light on temporal compression in episodic memory and suggest that compression rates are adaptively modulated to maintain current goal-relevant information.

Modelling the effect of religion on human empathy based on an adaptive temporal-causal network model.

PubMed

van Ments, Laila; Roelofsma, Peter; Treur, Jan

2018-01-01

Religion is a central aspect of many individuals' lives around the world, and its influence on human behaviour has been extensively studied from many different perspectives. The current study integrates a number of these perspectives into one adaptive temporal-causal network model describing the mental states involved, their mutual relations, and the adaptation of some of these relations over time due to learning. By first developing a conceptual representation of a network model based on the literature, and then formalizing this model into a numerical representation, simulations can be done for almost any kind of religion and person, showing different behaviours for persons with different religious backgrounds and characters. The focus was mainly on the influence of religion on human empathy and dis-empathy, a topic very relevant today. The developed model could be valuable for many uses, involving support for a better understanding, and even prediction, of the behaviour of religious individuals. It is illustrated for a number of different scenarios based on different characteristics of the persons and of the religion.

Temporal recalibration of motor and visual potentials in lag adaptation in voluntary movement.

PubMed

Cai, Chang; Ogawa, Kenji; Kochiyama, Takanori; Tanaka, Hirokazu; Imamizu, Hiroshi

2018-05-15

Adaptively recalibrating motor-sensory asynchrony is critical for animals to perceive self-produced action consequences. It is controversial whether motor- or sensory-related neural circuits recalibrate this asynchrony. By combining magnetoencephalography (MEG) and functional MRI (fMRI), we investigate the temporal changes in brain activities caused by repeated exposure to a 150-ms delay inserted between a button-press action and a subsequent flash. We found that readiness potentials significantly shift later in the motor system, especially in parietal regions (average: 219.9 ms), while visually evoked potentials significantly shift earlier in occipital regions (average: 49.7 ms) in the delay condition compared to the no-delay condition. Moreover, the shift in readiness potentials, but not in visually evoked potentials, was significantly correlated with the psychophysical measure of motor-sensory adaptation. These results suggest that although both motor and sensory processes contribute to the recalibration, the motor process plays the major role, given the magnitudes of shift and the correlation with the psychophysical measure. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Spatial and temporal task characteristics as stress: a test of the dynamic adaptability theory of stress, workload, and performance.

PubMed

Szalma, James L; Teo, Grace W L

2012-03-01

The goal for this study was to test assertions of the dynamic adaptability theory of stress, which proposes two fundamental task dimensions, information rate (temporal properties of a task) and information structure (spatial properties of a task). The theory predicts adaptive stability across stress magnitudes, with progressive and precipitous changes in adaptive response manifesting first as increases in perceived workload and stress and then as performance failure. Information structure was manipulated by varying the number of displays to be monitored (1, 2, 4 or 8 displays). Information rate was manipulated by varying stimulus presentation rate (8, 12, 16, or 20 events/min). A signal detection task was used in which critical signals were pairs of digits that differed by 0 or 1. Performance accuracy declined and workload and stress increased as a function of increased task demand, with a precipitous decline in accuracy at the highest demand levels. However, the form of performance change as well as the pattern of relationships between speed and accuracy and between performance and workload/stress indicates that some aspects of the theory need revision. Implications of the results for the theory and for future research are discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

Adaptation of brain functional and structural networks in aging.

PubMed

Lee, Annie; Ratnarajah, Nagulan; Tuan, Ta Anh; Chen, Shen-Hsing Annabel; Qiu, Anqi

2015-01-01

The human brain, especially the prefrontal cortex (PFC), is functionally and anatomically reorganized in order to adapt to neuronal challenges in aging. This study employed structural MRI, resting-state fMRI (rs-fMRI), and high angular resolution diffusion imaging (HARDI), and examined the functional and structural reorganization of the PFC in aging using a Chinese sample of 173 subjects aged from 21 years and above. We found age-related increases in the structural connectivity between the PFC and posterior brain regions. Such findings were partially mediated by age-related increases in the structural connectivity of the occipital lobe within the posterior brain. Based on our findings, it is thought that the PFC reorganization in aging could be partly due to the adaptation to age-related changes in the structural reorganization of the posterior brain. This thus supports the idea derived from task-based fMRI that the PFC reorganization in aging may be adapted to the need of compensation for resolving less distinctive stimulus information from the posterior brain regions. In addition, we found that the structural connectivity of the PFC with the temporal lobe was fully mediated by the temporal cortical thickness, suggesting that the brain morphology plays an important role in the functional and structural reorganization with aging.

Light and vision in the deep-sea benthos: II. Vision in deep-sea crustaceans.

PubMed

Frank, Tamara M; Johnsen, Sönke; Cronin, Thomas W

2012-10-01

Using new collecting techniques with the Johnson-Sea-Link submersible, eight species of deep-sea benthic crustaceans were collected with intact visual systems. Their spectral sensitivities and temporal resolutions were determined shipboard using electroretinography. Useable spectral sensitivity data were obtained from seven species, and in the dark-adapted eyes, the spectral sensitivity peaks were in the blue region of the visible spectrum, ranging from 470 to 497 nm. Under blue chromatic adaptation, a secondary sensitivity peak in the UV portion of the spectrum appeared for two species of anomuran crabs: Eumunida picta (λ(max)363 nm) and Gastroptychus spinifer (λ(max)383 nm). Wavelength-specific differences in response waveforms under blue chromatic adaptation in these two species suggest that two populations of photoreceptor cells are present. Temporal resolution was determined in all eight species using the maximum critical flicker frequency (CFF(max)). The CFF(max) for the isopod Booralana tricarinata of 4 Hz proved to be the lowest ever measured using this technique, and suggests that this species is not able to track even slow-moving prey. Both the putative dual visual pigment system in the crabs and the extremely slow eye of the isopod may be adaptations for seeing bioluminescence in the benthic environment.

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

PubMed

Tufto, Jarle

2015-08-01

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Crossmodal adaptation in right posterior superior temporal sulcus during face-voice emotional integration.

PubMed

Watson, Rebecca; Latinus, Marianne; Noguchi, Takao; Garrod, Oliver; Crabbe, Frances; Belin, Pascal

2014-05-14

The integration of emotional information from the face and voice of other persons is known to be mediated by a number of "multisensory" cerebral regions, such as the right posterior superior temporal sulcus (pSTS). However, whether multimodal integration in these regions is attributable to interleaved populations of unisensory neurons responding to face or voice or rather by multimodal neurons receiving input from the two modalities is not fully clear. Here, we examine this question using functional magnetic resonance adaptation and dynamic audiovisual stimuli in which emotional information was manipulated parametrically and independently in the face and voice via morphing between angry and happy expressions. Healthy human adult subjects were scanned while performing a happy/angry emotion categorization task on a series of such stimuli included in a fast event-related, continuous carryover design. Subjects integrated both face and voice information when categorizing emotion-although there was a greater weighting of face information-and showed behavioral adaptation effects both within and across modality. Adaptation also occurred at the neural level: in addition to modality-specific adaptation in visual and auditory cortices, we observed for the first time a crossmodal adaptation effect. Specifically, fMRI signal in the right pSTS was reduced in response to a stimulus in which facial emotion was similar to the vocal emotion of the preceding stimulus. These results suggest that the integration of emotional information from face and voice in the pSTS involves a detectable proportion of bimodal neurons that combine inputs from visual and auditory cortices. Copyright © 2014 the authors 0270-6474/14/346813-09$15.00/0.

Earthquake Rupture Dynamics using Adaptive Mesh Refinement and High-Order Accurate Numerical Methods

NASA Astrophysics Data System (ADS)

Kozdon, J. E.; Wilcox, L.

2013-12-01

Our goal is to develop scalable and adaptive (spatial and temporal) numerical methods for coupled, multiphysics problems using high-order accurate numerical methods. To do so, we are developing an opensource, parallel library known as bfam (available at http://bfam.in). The first application to be developed on top of bfam is an earthquake rupture dynamics solver using high-order discontinuous Galerkin methods and summation-by-parts finite difference methods. In earthquake rupture dynamics, wave propagation in the Earth's crust is coupled to frictional sliding on fault interfaces. This coupling is two-way, required the simultaneous simulation of both processes. The use of laboratory-measured friction parameters requires near-fault resolution that is 4-5 orders of magnitude higher than that needed to resolve the frequencies of interest in the volume. This, along with earlier simulations using a low-order, finite volume based adaptive mesh refinement framework, suggest that adaptive mesh refinement is ideally suited for this problem. The use of high-order methods is motivated by the high level of resolution required off the fault in earlier the low-order finite volume simulations; we believe this need for resolution is a result of the excessive numerical dissipation of low-order methods. In bfam spatial adaptivity is handled using the p4est library and temporal adaptivity will be accomplished through local time stepping. In this presentation we will present the guiding principles behind the library as well as verification of code against the Southern California Earthquake Center dynamic rupture code validation test problems.

Crossmodal Adaptation in Right Posterior Superior Temporal Sulcus during Face–Voice Emotional Integration

PubMed Central

Latinus, Marianne; Noguchi, Takao; Garrod, Oliver; Crabbe, Frances; Belin, Pascal

2014-01-01

The integration of emotional information from the face and voice of other persons is known to be mediated by a number of “multisensory” cerebral regions, such as the right posterior superior temporal sulcus (pSTS). However, whether multimodal integration in these regions is attributable to interleaved populations of unisensory neurons responding to face or voice or rather by multimodal neurons receiving input from the two modalities is not fully clear. Here, we examine this question using functional magnetic resonance adaptation and dynamic audiovisual stimuli in which emotional information was manipulated parametrically and independently in the face and voice via morphing between angry and happy expressions. Healthy human adult subjects were scanned while performing a happy/angry emotion categorization task on a series of such stimuli included in a fast event-related, continuous carryover design. Subjects integrated both face and voice information when categorizing emotion—although there was a greater weighting of face information—and showed behavioral adaptation effects both within and across modality. Adaptation also occurred at the neural level: in addition to modality-specific adaptation in visual and auditory cortices, we observed for the first time a crossmodal adaptation effect. Specifically, fMRI signal in the right pSTS was reduced in response to a stimulus in which facial emotion was similar to the vocal emotion of the preceding stimulus. These results suggest that the integration of emotional information from face and voice in the pSTS involves a detectable proportion of bimodal neurons that combine inputs from visual and auditory cortices. PMID:24828635

The Impact of Participation in Music on Learning Mathematics

ERIC Educational Resources Information Center

Holmes, Sylwia; Hallam, Susan

2017-01-01

Music psychologists have established that some forms of musical activity improve intellectual performance, spatial-temporal reasoning and other skills advantageous for learning. In this research, the potential of active music-making for improving pupils' achievement in spatial- temporal reasoning was investigated. As spatial-temporal skills are…

A Plastic Temporal Brain Code for Conscious State Generation

PubMed Central

Dresp-Langley, Birgitta; Durup, Jean

2009-01-01

Consciousness is known to be limited in processing capacity and often described in terms of a unique processing stream across a single dimension: time. In this paper, we discuss a purely temporal pattern code, functionally decoupled from spatial signals, for conscious state generation in the brain. Arguments in favour of such a code include Dehaene et al.'s long-distance reverberation postulate, Ramachandran's remapping hypothesis, evidence for a temporal coherence index and coincidence detectors, and Grossberg's Adaptive Resonance Theory. A time-bin resonance model is developed, where temporal signatures of conscious states are generated on the basis of signal reverberation across large distances in highly plastic neural circuits. The temporal signatures are delivered by neural activity patterns which, beyond a certain statistical threshold, activate, maintain, and terminate a conscious brain state like a bar code would activate, maintain, or inactivate the electronic locks of a safe. Such temporal resonance would reflect a higher level of neural processing, independent from sensorial or perceptual brain mechanisms. PMID:19644552

Relationship of Temporal Lobe Volumes to Neuropsychological Test Performance in Healthy Children

PubMed Central

Wells, Carolyn T.; Matson, Melissa A.; Kates, Wendy R.; Hay, Trisha; Horska, Alena

2008-01-01

Ecological validity of neuropsychological assessment includes the ability of tests to predict real-world functioning and/or covary with brain structures. Studies have examined the relationship between adaptive skills and test performance, with less focus on the association between regional brain volumes and neurobehavioral function in healthy children. The present study examined the relationship between temporal lobe gray matter volumes and performance on two neuropsychological tests hypothesized to measure temporal lobe functioning (Visual Perception-VP; Peabody Picture Vocabulary Test, Third Edition-PPVT-III) in 48 healthy children ages 5-18 years. After controlling for age and gender, left and right temporal and left occipital volumes were significant predictors of VP. Left and right frontal and temporal volumes were significant predictors of PPVT-III. Temporal volume emerged as the strongest lobar correlate with both tests. These results provide convergent and discriminant validity supporting VP as a measure of the “what” system; but suggest the PPVT-III as a complex measure of receptive vocabulary, potentially involving executive function demands. PMID:18513844

Rapid and tunable method to temporally control gene editing based on conditional Cas9 stabilization. | Office of Cancer Genomics

Cancer.gov

The CRISPR/Cas9 system is a powerful tool for studying gene function. Here, we describe a method that allows temporal control of CRISPR/Cas9 activity based on conditional Cas9 destabilization. We demonstrate that fusing an FKBP12-derived destabilizing domain to Cas9 (DD-Cas9) enables conditional Cas9 expression and temporal control of gene editing in the presence of an FKBP12 synthetic ligand. This system can be easily adapted to co-express, from the same promoter, DD-Cas9 with any other gene of interest without co-modulation of the latter.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

A Novel Framework for Adaptation in Agriculture: Lessons Learned from California's Wine Industry (Invited)

NASA Astrophysics Data System (ADS)

Nicholas, K. A.

2010-12-01

While crop yields are threatened by climate change, the management decisions of growers, including their practices to modify the microclimate experienced by the crop, can partially or even completely offset these damages. However, there have been few evaluations of adaptation on the farm scale, where managers are on the front lines of responding to global change. I will present a framework for classifying potential adaptations based on their temporal and spatial scale, their ease of implementation, and their effectiveness in altering or maintaining crop production. Applying this framework to the winegrowing industry in California, it appears that many strategies suggested in the literature for adaptation will either be of limited effectiveness, likely to be cost-prohibitive, or are not compatible with the current values of growers. However, interviews with and observations of winegrowers reveal that novel adaptations, not widely discussed in the literature, are already being employed, often by individuals in an experimental capacity and without community coordination. For example, in addition to irrigation, water is used to modify the vine microclimate for both heating (frost protection) and evaporative cooling. An analysis of responses to past environmental stresses in the wine industry revealed that growers tended to respond to stresses individually rather than collectively, except for severe, novel pests and diseases. Responses may be reactive or proactive; most proactive strategies have been short-term, in response to imminent stress. Growers tend to rely on their own experience to guide their management decisions, which may offer poor guidance under novel climate regimes. These findings highlight some of the difficulties expected in adapting to global change, as well as areas for strategic investments to enhance agricultural resilience to climate change. In particular, strategies to enhance the potential for effective proactive, collective responses could improve adaptive capacity in the context of climate change.

Advancing the adaptive capacity of social-ecological systems to absorb climate extremes

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; Bahn, Michael; Bardgett, Richard; Bloemen, Jasper; Chabay, Ilan; Erb, Karlheinz; Giamberini, Mariasilvia; Gingrich, Simone; Lavorel, Sandra; Liehr, Stefan; Rammig, Anja

2017-04-01

The recent and projected increases in climate variability and the frequency of climate extremes are posing a profound challenge to society and the biosphere (IPCC 2012, IPCC 2013). Climate extremes can affect natural and managed ecosystems more severely than gradual warming. The ability of ecosystems to resist and recover from climate extremes is therefore of fundamental importance for society, which strongly relies on their ability to supply provisioning, regulating, supporting and cultural services. Society in turn triggers land-use and management decisions that affect ecosystem properties. Thus, ecological and socio-economic conditions are tightly coupled in what has been referred to as the social-ecological system. For ensuring human well-being in the light of climate extremes it is crucial to enhance the resilience of the social-ecological system (SES) across spatial, temporal and institutional scales. Stakeholders, such as resource managers, urban, landscape and conservation planners, decision-makers in agriculture and forestry, as well as natural hazards managers, require an improved knowledge base for better-informed decision making. To date the vulnerability and adaptive capacity of SESs to climate extremes is not well understood and large uncertainties exist as to the legacies of climate extremes on ecosystems and on related societal structures and processes. Moreover, we lack empirical evidence and incorporation of simulated future ecosystem and societal responses to support pro-active management and enhance social-ecological resilience. In our presentation, we outline the major research gaps and challenges to be addressed for understanding and enhancing the adaptive capacity of SES to absorb and adapt to climate extremes, including acquisition and elaboration of long-term monitoring data and improvement of ecological models to better project climate extreme effects and provide model uncertainties. We highlight scientific challenges and discuss conceptual and observational gaps that need to be overcome to advance this inter- and transdisciplinary topic.

Integrated climate and land change research to improve decision-making and resource management in Southern Africa: The SASSCAL approach

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Olwoch, J. M.

2017-12-01

The ability of countries in southern Africa to jointly respond to climate challenges with scientifically informed and evidence-based actions and policy decisions remains low due to limited scientific research capacity and infrastructure. The Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL; www.sasscal.org) addresses this gap by implementing a high-level framework to guide research and innovation investments in climate change and adaptive land management interventions in Southern Africa. With a strong climate service component as cross-cutting topic, SASSCAL's focus is to improve the understanding of climate and land management change impacts on the natural and socio-economic environment in Southern Africa. The paper presents a variety of SASSCAL driven activities which contribute to better understand climate and long-term environmental change dynamics at various temporal and spatial scales in Southern Afrika and how these activities are linked to support research and decision-making to optimize agricultural practices as well as sustainable environmental and water resources management. To provide consistent and reliable climate information for Southern Africa, SASSCAL offers various climate services ranging from real-time climate observation across the region utilizing the SASSCAL WeatherNet to regional climate change analysis and modelling efforts at seasonal-to-decadal timescales using climate data from various sources. SASSCAL also offers the current state of the environment in terms of recent data on changes in the environment that are necessary for setting appropriate adaptation strategies . The paper will further demonstrate how these services are utilized for interdisciplinary research on the impact of climate change on natural resources and socio-economic development in the SASSCAL countries and how this knowledge can be effectively used to mitigate and adapt to climate change by informed decision-making from farm to regional level.

Adaptation to visual or auditory time intervals modulates the perception of visual apparent motion

PubMed Central

Zhang, Huihui; Chen, Lihan; Zhou, Xiaolin

2012-01-01

It is debated whether sub-second timing is subserved by a centralized mechanism or by the intrinsic properties of task-related neural activity in specific modalities (Ivry and Schlerf, 2008). By using a temporal adaptation task, we investigated whether adapting to different time intervals conveyed through stimuli in different modalities (i.e., frames of a visual Ternus display, visual blinking discs, or auditory beeps) would affect the subsequent implicit perception of visual timing, i.e., inter-stimulus interval (ISI) between two frames in a Ternus display. The Ternus display can induce two percepts of apparent motion (AM), depending on the ISI between the two frames: “element motion” for short ISIs, in which the endmost disc is seen as moving back and forth while the middle disc at the overlapping or central position remains stationary; “group motion” for longer ISIs, in which both discs appear to move in a manner of lateral displacement as a whole. In Experiment 1, participants adapted to either the typical “element motion” (ISI = 50 ms) or the typical “group motion” (ISI = 200 ms). In Experiments 2 and 3, participants adapted to a time interval of 50 or 200 ms through observing a series of two paired blinking discs at the center of the screen (Experiment 2) or hearing a sequence of two paired beeps (with pitch 1000 Hz). In Experiment 4, participants adapted to sequences of paired beeps with either low pitches (500 Hz) or high pitches (5000 Hz). After adaptation in each trial, participants were presented with a Ternus probe in which the ISI between the two frames was equal to the transitional threshold of the two types of motions, as determined by a pretest. Results showed that adapting to the short time interval in all the situations led to more reports of “group motion” in the subsequent Ternus probes; adapting to the long time interval, however, caused no aftereffect for visual adaptation but significantly more reports of group motion for auditory adaptation. These findings, suggesting amodal representation for sub-second timing across modalities, are interpreted in the framework of temporal pacemaker model. PMID:23133408

Probing the Spatio-Temporal Characteristics of Temporal Aliasing Errors and their Impact on Satellite Gravity Retrievals

NASA Astrophysics Data System (ADS)

Wiese, D. N.; McCullough, C. M.

2017-12-01

Studies have shown that both single pair low-low satellite-to-satellite tracking (LL-SST) and dual-pair LL-SST hypothetical future satellite gravimetry missions utilizing improved onboard measurement systems relative to the Gravity Recovery and Climate Experiment (GRACE) will be limited by temporal aliasing errors; that is, the error introduced through deficiencies in models of high frequency mass variations required for the data processing. Here, we probe the spatio-temporal characteristics of temporal aliasing errors to understand their impact on satellite gravity retrievals using high fidelity numerical simulations. We find that while aliasing errors are dominant at long wavelengths and multi-day timescales, improving knowledge of high frequency mass variations at these resolutions translates into only modest improvements (i.e. spatial resolution/accuracy) in the ability to measure temporal gravity variations at monthly timescales. This result highlights the reliance on accurate models of high frequency mass variations for gravity processing, and the difficult nature of reducing temporal aliasing errors and their impact on satellite gravity retrievals.

Adaptive optics improves multiphoton super-resolution imaging

NASA Astrophysics Data System (ADS)

Zheng, Wei; Wu, Yicong; Winter, Peter; Shroff, Hari

2018-02-01

Three dimensional (3D) fluorescence microscopy has been essential for biological studies. It allows interrogation of structure and function at spatial scales spanning the macromolecular, cellular, and tissue levels. Critical factors to consider in 3D microscopy include spatial resolution, signal-to-noise (SNR), signal-to-background (SBR), and temporal resolution. Maintaining high quality imaging becomes progressively more difficult at increasing depth (where optical aberrations, induced by inhomogeneities of refractive index in the sample, degrade resolution and SNR), and in thick or densely labeled samples (where out-of-focus background can swamp the valuable, in-focus-signal from each plane). In this report, we introduce our new instrumentation to address these problems. A multiphoton structured illumination microscope was simply modified to integrate an adpative optics system for optical aberrations correction. Firstly, the optical aberrations are determined using direct wavefront sensing with a nonlinear guide star and subsequently corrected using a deformable mirror, restoring super-resolution information. We demonstrate the flexibility of our adaptive optics approach on a variety of semi-transparent samples, including bead phantoms, cultured cells in collagen gels and biological tissues. The performance of our super-resolution microscope is improved in all of these samples, as peak intensity is increased (up to 40-fold) and resolution recovered (up to 176+/-10 nm laterally and 729+/-39 nm axially) at depths up to 250 μm from the coverslip surface.

Brain structural changes following adaptive cognitive training assessed by Tensor-Based Morphometry (TBM).

PubMed

Colom, Roberto; Hua, Xue; Martínez, Kenia; Burgaleta, Miguel; Román, Francisco J; Gunter, Jeffrey L; Carmona, Susanna; Jaeggi, Susanne M; Thompson, Paul M

2016-10-01

Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrating Collaboration, Adaptive Management, and Scenario-Planning to Address Rapid Change: Experiences at Las Cienegas National Conservation Area

NASA Astrophysics Data System (ADS)

Caves, J. K.; Bodner, G.; Simms, K.; Fisher, L.; Robertson, T.

2012-12-01

There is growing recognition that public lands cannot be managed as islands; rather, land management must address the ecological, social, and temporal complexity that often spans jurisdictions and traditional planning horizons. Collaborative decision-making and adaptive management (CAM) have been promoted as methods to reconcile competing societal demands and respond to complex ecosystem dynamics. We present the experiences of land managers and stakeholders in using CAM at Las Cienegas National Conservation Area (LCNCA), a highly valued site under the jurisdiction of the Bureau of Land Management (BLM). The CAM process at Las Cienegas is marked by strong stakeholder engagement, with four core elements: 1) shared watershed goals with measurable resource objectives; 2) mechanisms to incorporate new information into decision-making; 3) efforts to make information increasingly relevant and reliable; and 4) shared learning to improve both the process and management actions. The combination of stakeholder engagement and adaptive management has led to agreement on contentious issues, more innovative solutions, and more effective land management. Yet the region is now experiencing rapid changes outside managers' control—including climate change, human population growth, and reduced federal budgets—with large but unpredictable impacts on natural resources. While CAM experience provides a strong foundation for making the difficult and contentious management decisions that such changes are likely to require, neither collaboration nor adaptive management provides a sufficient structure for addressing uncontrollable and unpredictable change. As a result, LCNCA is exploring two specific modifications to CAM that may better address emerging challenges, including: 1) Creating nested resource objectives to distinguish between those objectives which may be crucial from those which may hinder a flexible response to climate change, and 2) Incorporating scenario planning into CAM to explore how climate change may interact with other drivers and alter options for the future, to identify robust management, and to prioritize ecological monitoring efforts. The experiences at LCNCA demonstrate how collaboration and adaptive management can be used to improve social and environmental outcomes and, with a few modifications, may help address the complexity and change that threatens to overwhelm even the best efforts to sustain public lands.

WE-G-BRD-08: Motion Analysis for Rectal Cancer: Implications for Adaptive Radiotherapy On the MR-Linac

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

Kleijnen, J; Asselen, B van; Burbach, M

2015-06-15

Purpose: Purpose of this study is to find the optimal trade-off between adaptation interval and margin reduction and to define the implications of motion for rectal cancer boost radiotherapy on a MR-linac. Methods: Daily MRI scans were acquired of 16 patients, diagnosed with rectal cancer, prior to each radiotherapy fraction in one week (N=76). Each scan session consisted of T2-weighted and three 2D sagittal cine-MRI, at begin (t=0 min), middle (t=9:30 min) and end (t=18:00 min) of scan session, for 1 minute at 2 Hz temporal resolution. Tumor and clinical target volume (CTV) were delineated on each T2-weighted scan andmore » transferred to each cine-MRI. The start frame of the begin scan was used as reference and registered to frames at time-points 15, 30 and 60 seconds, 9:30 and 18:00 minutes and 1, 2, 3 and 4 days later. Per time-point, motion of delineated voxels was evaluated using the deformation vector fields of the registrations and the 95th percentile distance (dist95%) was calculated as measure of motion. Per time-point, the distance that includes 90% of all cases was taken as estimate of required planning target volume (PTV)-margin. Results: Highest motion reduction is observed going from 9:30 minutes to 60 seconds. We observe a reduction in margin estimates from 10.6 to 2.7 mm and 16.1 to 4.6 mm for tumor and CTV, respectively, when adapting every 60 seconds compared to not adapting treatment. A 75% and 71% reduction, respectively. Further reduction in adaptation time-interval yields only marginal motion reduction. For adaptation intervals longer than 18:00 minutes only small motion reductions are observed. Conclusion: The optimal adaptation interval for adaptive rectal cancer (boost) treatments on a MR-linac is 60 seconds. This results in substantial smaller PTV-margin estimates. Adaptation intervals of 18:00 minutes and higher, show little improvement in motion reduction.« less

apGA: An adaptive parallel genetic algorithm

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

Liepins, G.E.; Baluja, S.

1991-01-01

We develop apGA, a parallel variant of the standard generational GA, that combines aggressive search with perpetual novelty, yet is able to preserve enough genetic structure to optimally solve variably scaled, non-uniform block deceptive and hierarchical deceptive problems. apGA combines elitism, adaptive mutation, adaptive exponential scaling, and temporal memory. We present empirical results for six classes of problems, including the DeJong test suite. Although we have not investigated hybrids, we note that apGA could be incorporated into other recent GA variants such as GENITOR, CHC, and the recombination stage of mGA. 12 refs., 2 figs., 2 tabs.

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

NASA Astrophysics Data System (ADS)

Rußwurm, Marc; Körner, Marco

2018-03-01

Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.

Crop vulnerability: Carya

USDA-ARS?s Scientific Manuscript database

Long established native tree populations reflect local adaptations. Representation of diverse populations in accessible ex situ collections that link information on phenotypic expression to information on spatial and temporal origination is the most efficient means of preserving and exploring genet...

Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization

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

Mory, Cyril, E-mail: cyril.mory@philips.com; Philips Research Medisys, 33 rue de Verdun, 92156 Suresnes; Auvray, Vincent

2014-02-15

Purpose: Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patient's electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition. Methods: The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method,more » which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization. Results: 4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patient's left ventricular ejection fraction. Conclusions: 4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.« less

In situ adaptive response to climate and habitat quality variation: spatial and temporal variation in European badger (Meles meles) body weight.

PubMed

Byrne, Andrew W; Fogarty, Ursula; O'Keeffe, James; Newman, Chris

2015-09-01

Variation in climatic and habitat conditions can affect populations through a variety of mechanisms, and these relationships can act at different temporal and spatial scales. Using post-mortem badger body weight records from 15 878 individuals captured across the Republic of Ireland (7224 setts across ca. 15 000 km(2) ; 2009-2012), we employed a hierarchical multilevel mixed model to evaluate the effects of climate (rainfall and temperature) and habitat quality (landscape suitability), while controlling for local abundance (unique badgers caught/sett/year). Body weight was affected strongly by temperature across a number of temporal scales (preceding month or season), with badgers being heavier if preceding temperatures (particularly during winter/spring) were warmer than the long-term seasonal mean. There was less support for rainfall across different temporal scales, although badgers did exhibit heavier weights when greater rainfall occurred one or 2 months prior to capture. Badgers were also heavier in areas with higher landscape habitat quality, modulated by the number of individuals captured per sett, consistent with density-dependent effects reducing weights. Overall, the mean badger body weight of culled individuals rose during the study period (2009-2012), more so for males than for females. With predicted increases in temperature, and rainfall, augmented by ongoing agricultural land conversion in this region, we project heavier individual badger body weights in the future. Increased body weight has been associated with higher fecundity, recruitment and survival rates in badgers, due to improved food availability and energetic budgets. We thus predict that climate change could increase the badger population across the Republic of Ireland. Nevertheless, we emphasize that, locally, populations could still be vulnerable to extreme weather variability coupled with detrimental agricultural practice, including population management. © 2015 John Wiley & Sons Ltd.

Temporal subtraction of chest radiographs compensating pose differences

NASA Astrophysics Data System (ADS)

von Berg, Jens; Dworzak, Jalda; Klinder, Tobias; Manke, Dirk; Kreth, Adrian; Lamecker, Hans; Zachow, Stefan; Lorenz, Cristian

2011-03-01

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason is the occurrence of strong pose differences between two acquisitions with a time interval of months to years in between. Such strong perspective differences occur in a reasonable number of cases. They cannot be compensated by available image registration methods and thus mask interval changes to be undetectable. In this paper a method is proposed to estimate a 3D pose difference by the adaptation of a 3D rib cage model to both projections. The difference between both is then compensated for, thus producing a subtraction image with virtually no change in pose. The method generally assumes that no 3D image data is available from the patient. The accuracy of pose estimation is validated with chest phantom images acquired under controlled geometric conditions. A subtle interval change simulated by a piece of plastic foam attached to the phantom becomes visible in subtraction images generated with this technique even at strong angular pose differences like an anterior-posterior inclination of 13 degrees.

Shared periodic performer movements coordinate interactions in duo improvisations.

PubMed

Eerola, Tuomas; Jakubowski, Kelly; Moran, Nikki; Keller, Peter E; Clayton, Martin

2018-02-01

Human interaction involves the exchange of temporally coordinated, multimodal cues. Our work focused on interaction in the visual domain, using music performance as a case for analysis due to its temporally diverse and hierarchical structures. We made use of two improvising duo datasets-(i) performances of a jazz standard with a regular pulse and (ii) non-pulsed, free improvizations-to investigate whether human judgements of moments of interaction between co-performers are influenced by body movement coordination at multiple timescales. Bouts of interaction in the performances were manually annotated by experts and the performers' movements were quantified using computer vision techniques. The annotated interaction bouts were then predicted using several quantitative movement and audio features. Over 80% of the interaction bouts were successfully predicted by a broadband measure of the energy of the cross-wavelet transform of the co-performers' movements in non-pulsed duos. A more complex model, with multiple predictors that captured more specific, interacting features of the movements, was needed to explain a significant amount of variance in the pulsed duos. The methods developed here have key implications for future work on measuring visual coordination in musical ensemble performances, and can be easily adapted to other musical contexts, ensemble types and traditions.

[Mental disorders due to brain lesions in the DSM-5 in the light of the previous versions].

PubMed

Derouesné, Christian

2013-12-01

The DSM-5 introduces major modifications in the category of mental disorders due to brain lesions compared to the previous DSM versions, which are reviewed in this paper. The description of the category Major neurocognitive disorder, as a substitute for dementia, seems to fit better for patients and families, and more adapted to many neurodegenerative cognitive disorders for which memory impairment is not predominant. Similarly, the introduction of the category of Mild neurocognitive disorder appears to be an improvement although some difficulty still remains for distinguishing mild cognitive disorder from normal aging. The addition of new etiological categories such as fronto-temporal NCD or NCD with Lewy bodies should also to be considered as a significant improvement. Despite these advances, to circumscribe the mental disorders due to brain lesions to cognitive deficits and biological mechanisms remains highly questionable, and does not provide an adequate care for the patients and families if not complemented by a psychological and environmental approach.

Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing.

PubMed

He, Chengbing; Jing, Lianyou; Xi, Rui; Li, Qinyuan; Zhang, Qunfei

2017-04-24

Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between 1 × 10 - 1 and 2 × 10 - 2 for the conventional TR-DFE, and between 1 × 10 - 2 and 1 × 10 - 3 for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB.

How is a motor skill learned? Change and invariance at the levels of task success and trajectory control

PubMed Central

Krakauer, John W.; Mazzoni, Pietro

2012-01-01

The public pays large sums of money to watch skilled motor performance. Notably, however, in recent decades motor skill learning (performance improvement beyond baseline levels) has received less experimental attention than motor adaptation (return to baseline performance in the setting of an external perturbation). Motor skill can be assessed at the levels of task success and movement quality, but the link between these levels remains poorly understood. We devised a motor skill task that required visually guided curved movements of the wrist without a perturbation, and we defined skill learning at the task level as a change in the speed–accuracy trade-off function (SAF). Practice in restricted speed ranges led to a global shift of the SAF. We asked how the SAF shift maps onto changes in trajectory kinematics, to establish a link between task-level performance and fine motor control. Although there were small changes in mean trajectory, improved performance largely consisted of reduction in trial-to-trial variability and increase in movement smoothness. We found evidence for improved feedback control, which could explain the reduction in variability but does not preclude other explanations such as an increased signal-to-noise ratio in cortical representations. Interestingly, submovement structure remained learning invariant. The global generalization of the SAF across a wide range of difficulty suggests that skill for this task is represented in a temporally scalable network. We propose that motor skill acquisition can be characterized as a slow reduction in movement variability, which is distinct from faster model-based learning that reduces systematic error in adaptation paradigms. PMID:22514286

Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing

PubMed Central

He, Chengbing; Jing, Lianyou; Xi, Rui; Li, Qinyuan; Zhang, Qunfei

2017-01-01

Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between 1×10−1 and 2×10−2 for the conventional TR-DFE, and between 1×10−2 and 1×10−3 for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB. PMID:28441763

Influence of adaptive statistical iterative reconstruction algorithm on image quality in coronary computed tomography angiography

PubMed Central

Thygesen, Jesper; Gerke, Oke; Egstrup, Kenneth; Waaler, Dag; Lambrechtsen, Jess

2016-01-01

Background Coronary computed tomography angiography (CCTA) requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR) techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. Purpose To evaluate whether adaptive statistical iterative reconstruction (ASIR) enhances perceived image quality in CCTA compared to filtered back projection (FBP). Material and Methods Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA) and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR]) was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. Results VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR (P = 0.004). The objective measures showed significant differences between FBP and 60% ASIR (P < 0.0001) for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. Conclusion ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR. PMID:28405477

Belowground adaptation and resilience to drought conditions

NASA Astrophysics Data System (ADS)

Sivandran, G.; Gentine, P.; Bras, R. L.

2012-12-01

The most expansive drought in 50 years stretched across the Midwest in 2012. In light of predicted increases in the variability of climate, this type of event can no longer be considered extreme. Understanding the resilience of both managed and natural vegetation and how these systems may adapt to this new climate reality is critical in predicting changes to the global carbon, energy and water balance. An eco-hydrological model (tRIBS+VEGGIE) was employed to model the sensitivity of vegetation to varying drought intensities. Point scale simulations were carried out using two vertical root distribution schemes: (i) Static - a temporally invariant root distribution; and (ii) Dynamic - a temporally variable root carbon allocation scheme. A stochastic climate generator was used to create a series of synthetic climate realizations varying the drought characteristics - in particular the interstorm period. This change in the seasonal distribution of precipitation impacts the spatial (soil layers) and temporal distribution of soil moisture which directly impacts the water resource niche for vegetation. This change in resource niche is reflected in a shift in the optimal static rooting strategy further highlighting the need for the incorporation of a dynamic scheme that responds to local conditions.

Adaptive temporal refinement in injection molding

NASA Astrophysics Data System (ADS)

Karyofylli, Violeta; Schmitz, Mauritius; Hopmann, Christian; Behr, Marek

2018-05-01

Mold filling is an injection molding stage of great significance, because many defects of the plastic components (e.g. weld lines, burrs or insufficient filling) can occur during this process step. Therefore, it plays an important role in determining the quality of the produced parts. Our goal is the temporal refinement in the vicinity of the evolving melt front, in the context of 4D simplex-type space-time grids [1, 2]. This novel discretization method has an inherent flexibility to employ completely unstructured meshes with varying levels of resolution both in spatial dimensions and in the time dimension, thus allowing the use of local time-stepping during the simulations. This can lead to a higher simulation precision, while preserving calculation efficiency. A 3D benchmark case, which concerns the filling of a plate-shaped geometry, is used for verifying our numerical approach [3]. The simulation results obtained with the fully unstructured space-time discretization are compared to those obtained with the standard space-time method and to Moldflow simulation results. This example also serves for providing reliable timing measurements and the efficiency aspects of the filling simulation of complex 3D molds while applying adaptive temporal refinement.

Modulation of isochronous movements in a flexible environment: links between motion and auditory experience.

PubMed

Bravi, Riccardo; Del Tongo, Claudia; Cohen, Erez James; Dalle Mura, Gabriele; Tognetti, Alessandro; Minciacchi, Diego

2014-06-01

The ability to perform isochronous movements while listening to a rhythmic auditory stimulus requires a flexible process that integrates timing information with movement. Here, we explored how non-temporal and temporal characteristics of an auditory stimulus (presence, interval occupancy, and tempo) affect motor performance. These characteristics were chosen on the basis of their ability to modulate the precision and accuracy of synchronized movements. Subjects have participated in sessions in which they performed sets of repeated isochronous wrist's flexion-extensions under various conditions. The conditions were chosen on the basis of the defined characteristics. Kinematic parameters were evaluated during each session, and temporal parameters were analyzed. In order to study the effects of the auditory stimulus, we have minimized all other sensory information that could interfere with its perception or affect the performance of repeated isochronous movements. The present study shows that the distinct characteristics of an auditory stimulus significantly influence isochronous movements by altering their duration. Results provide evidence for an adaptable control of timing in the audio-motor coupling for isochronous movements. This flexibility would make plausible the use of different encoding strategies to adapt audio-motor coupling for specific tasks.

Optic nerve signals in a neuromorphic chip I: Outer and inner retina models.

PubMed

Zaghloul, Kareem A; Boahen, Kwabena

2004-04-01

We present a novel model for the mammalian retina and analyze its behavior. Our outer retina model performs bandpass spatiotemporal filtering. It is comprised of two reciprocally connected resistive grids that model the cone and horizontal cell syncytia. We show analytically that its sensitivity is proportional to the space-constant-ratio of the two grids while its half-max response is set by the local average intensity. Thus, this outer retina model realizes luminance adaptation. Our inner retina model performs high-pass temporal filtering. It features slow negative feedback whose strength is modulated by a locally computed measure of temporal contrast, modeling two kinds of amacrine cells, one narrow-field, the other wide-field. We show analytically that, when the input is spectrally pure, the corner-frequency tracks the input frequency. But when the input is broadband, the corner frequency is proportional to contrast. Thus, this inner retina model realizes temporal frequency adaptation as well as contrast gain control. We present CMOS circuit designs for our retina model in this paper as well. Experimental measurements from the fabricated chip, and validation of our analytical results, are presented in the companion paper [Zaghloul and Boahen (2004)].

LPE grown LSO:Tb scintillator films for high-resolution X-ray imaging applications at synchrotron light sources

NASA Astrophysics Data System (ADS)

Cecilia, A.; Rack, A.; Douissard, P.-A.; Martin, T.; Dos Santos Rolo, T.; Vagovič, P.; Hamann, E.; van de Kamp, T.; Riedel, A.; Fiederle, M.; Baumbach, T.

2011-08-01

Within the project ScinTAX of the 6th framework program (FP6) of the European Commission (SCINTAX—STRP 033 427) we have developed a new thin single crystal scintillator for high-resolution X-ray imaging. The scintillator is based on a Tb-doped Lu2SiO5 (LSO) film epitaxially grown on an adapted substrate. The high density, effective atomic number and light yield of the scintillating LSO significantly improves the efficiency of the X-ray imaging detectors currently used in synchrotron micro-imaging applications. In this work we present the characterization of the scintillating LSO films in terms of their spatial resolution performance and we provide two examples of high spatial and high temporal resolution applications.

Optic flow improves adaptability of spatiotemporal characteristics during split-belt locomotor adaptation with tactile stimulation

PubMed Central

Anthony Eikema, Diderik Jan A.; Chien, Jung Hung; Stergiou, Nicholas; Myers, Sara A.; Scott-Pandorf, Melissa M.; Bloomberg, Jacob J.; Mukherjee, Mukul

2015-01-01

Human locomotor adaptation requires feedback and feed-forward control processes to maintain an appropriate walking pattern. Adaptation may require the use of visual and proprioceptive input to decode altered movement dynamics and generate an appropriate response. After a person transfers from an extreme sensory environment and back, as astronauts do when they return from spaceflight, the prolonged period required for re-adaptation can pose a significant burden. In our previous paper, we showed that plantar tactile vibration during a split-belt adaptation task did not interfere with the treadmill adaptation however, larger overground transfer effects with a slower decay resulted. Such effects, in the absence of visual feedback (of motion) and perturbation of tactile feedback, is believed to be due to a higher proprioceptive gain because, in the absence of relevant external dynamic cues such as optic flow, reliance on body-based cues is enhanced during gait tasks through multisensory integration. In this study we therefore investigated the effect of optic flow on tactile stimulated split-belt adaptation as a paradigm to facilitate the sensorimotor adaptation process. Twenty healthy young adults, separated into two matched groups, participated in the study. All participants performed an overground walking trial followed by a split-belt treadmill adaptation protocol. The tactile group (TC) received vibratory plantar tactile stimulation only, whereas the virtual reality and tactile group (VRT) received an additional concurrent visual stimulation: a moving virtual corridor, inducing perceived self-motion. A post-treadmill overground trial was performed to determine adaptation transfer. Interlimb coordination of spatiotemporal and kinetic variables was quantified using symmetry indices, and analyzed using repeated-measures ANOVA. Marked changes of step length characteristics were observed in both groups during split-belt adaptation. Stance and swing time symmetry were similar in the two groups, suggesting that temporal parameters are not modified by optic flow. However, whereas the TC group displayed significant stance time asymmetries during the post-treadmill session, such aftereffects were absent in the VRT group. The results indicated that the enhanced transfer resulting from exposure to plantar cutaneous vibration during adaptation was alleviated by optic flow information. The presence of visual self-motion information may have reduced proprioceptive gain during learning. Thus, during overground walking, the learned proprioceptive split-belt pattern is more rapidly overridden by visual input due to its increased relative gain. The results suggest that when visual stimulation is provided during adaptive training, the system acquires the novel movement dynamics while maintaining the ability to flexibly adapt to different environments. PMID:26525712

Nrf2 and regulation of the antioxidant system in the Antarctic silverfish, Pleuragramma antarctica: Adaptation to environmental changes of pro-oxidant pressure.

PubMed

Giuliani, Maria Elisa; Benedetti, Maura; Nigro, Marco; Regoli, Francesco

2017-08-01

Despite the key importance of Nrf2-Keap1 in regulating antioxidant system in vertebrates, this system is still poorly investigated in marine species. The present study focused on the Antarctic silverfish Pleuragramma antarctica which, during the final phases of embryo development in platelet ice, is challenged by a sudden enhancement of environmental oxidative conditions associated to ice melting. Partial coding sequences were identified for Nrf2, its repressor Keap1 and for typical Nrf2-target antioxidant genes, like catalase, glutathione peroxidase isoform 1 and Cu/Zn-dependent superoxide dismutase. Compared to temperate homologues, the protein sequences showed an elevated conservation of amino acids essential for catalytic functions, while a few specific substitutions in non-essential regions may represent a molecular adaptation to improve flexibility and accessibility to active site at cold temperatures. The role of the Nrf2-Keap1 pathway in modulating the activation of antioxidant defences was demonstrated at both transcriptional and functional levels with a clear temporal increase of antioxidant protection in embryos before the hatching. Such findings confirm the importance of Nrf2 and highlight regulation of antioxidants as an adaptive strategy in P. antarctica to protect the early life stages toward the environmental changes of pro-oxidant pressure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adapting a scenario tree model for freedom from disease as surveillance progresses: the Canadian notifiable avian influenza model.

PubMed

Christensen, Jette; El Allaki, Farouk; Vallières, André

2014-05-01

Scenario tree models with temporal discounting have been applied in four continents to support claims of freedom from animal disease. Recently, a second (new) model was developed for the same population and disease. This is a natural development because surveillance is a dynamic process that needs to adapt to changing circumstances - the difficulty is the justification for, documentation of, presentation of and the acceptance of the changes. Our objective was to propose a systematic approach to present changes to an existing scenario tree model for freedom from disease. We used the example of how we adapted the deterministic Canadian Notifiable Avian Influenza scenario tree model published in 2011 to a stochastic scenario tree model where the definition of sub-populations and the estimation of probability of introduction of the pathogen were modified. We found that the standardized approach by Vanderstichel et al. (2013) with modifications provided a systematic approach to make and present changes to an existing scenario tree model. We believe that the new 2013 CanNAISS scenario tree model is a better model than the 2011 model because the 2013 model included more surveillance data. In particular, the new data on Notifiable Avian Influenza in Canada from the last 5 years were used to improve input parameters and model structure. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

The Dynamics of Incomplete Lineage Sorting across the Ancient Adaptive Radiation of Neoavian Birds

PubMed Central

Suh, Alexander; Smeds, Linnéa; Ellegren, Hans

2015-01-01

The diversification of neoavian birds is one of the most rapid adaptive radiations of extant organisms. Recent whole-genome sequence analyses have much improved the resolution of the neoavian radiation and suggest concurrence with the Cretaceous-Paleogene (K-Pg) boundary, yet the causes of the remaining genome-level irresolvabilities appear unclear. Here we show that genome-level analyses of 2,118 retrotransposon presence/absence markers converge at a largely consistent Neoaves phylogeny and detect a highly differential temporal prevalence of incomplete lineage sorting (ILS), i.e., the persistence of ancestral genetic variation as polymorphisms during speciation events. We found that ILS-derived incongruences are spread over the genome and involve 35% and 34% of the analyzed loci on the autosomes and the Z chromosome, respectively. Surprisingly, Neoaves diversification comprises three adaptive radiations, an initial near-K-Pg super-radiation with highly discordant phylogenetic signals from near-simultaneous speciation events, followed by two post-K-Pg radiations of core landbirds and core waterbirds with much less pronounced ILS. We provide evidence that, given the extreme level of up to 100% ILS per branch in super-radiations, particularly rapid speciation events may neither resemble a fully bifurcating tree nor are they resolvable as such. As a consequence, their complex demographic history is more accurately represented as local networks within a species tree. PMID:26284513

Ground-based adaptive optics coronagraphic performance under closed-loop predictive control

NASA Astrophysics Data System (ADS)

Males, Jared R.; Guyon, Olivier

2018-01-01

The discovery of the exoplanet Proxima b highlights the potential for the coming generation of giant segmented mirror telescopes (GSMTs) to characterize terrestrial-potentially habitable-planets orbiting nearby stars with direct imaging. This will require continued development and implementation of optimized adaptive optics systems feeding coronagraphs on the GSMTs. Such development should proceed with an understanding of the fundamental limits imposed by atmospheric turbulence. Here, we seek to address this question with a semianalytic framework for calculating the postcoronagraph contrast in a closed-loop adaptive optics system. We do this starting with the temporal power spectra of the Fourier basis calculated assuming frozen flow turbulence, and then apply closed-loop transfer functions. We include the benefits of a simple predictive controller, which we show could provide over a factor of 1400 gain in raw point spread function contrast at 1 λ/D on bright stars, and more than a factor of 30 gain on an I=7.5 mag star such as Proxima. More sophisticated predictive control can be expected to improve this even further. Assuming a photon-noise limited observing technique such as high-dispersion coronagraphy, these gains in raw contrast will decrease integration times by the same large factors. Predictive control of atmospheric turbulence should therefore be seen as one of the key technologies that will enable ground-based telescopes to characterize terrestrial planets.

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Changes in auditory nerve responses across the duration of sinusoidally amplitude-modulated electric pulse-train stimuli.

PubMed

Hu, Ning; Miller, Charles A; Abbas, Paul J; Robinson, Barbara K; Woo, Jihwan

2010-12-01

Response rates of auditory nerve fibers (ANFs) to electric pulse trains change over time, reflecting substantial spike-rate adaptation that depends on stimulus parameters. We hypothesize that adaptation affects the representation of amplitude-modulated pulse trains used by cochlear prostheses to transmit speech information to the auditory system. We recorded cat ANF responses to sinusoidally amplitude-modulated (SAM) trains with 5,000 pulse/s carriers. Stimuli delivered by a monopolar intracochlear electrode had fixed modulation frequency (100 Hz) and depth (10%). ANF responses were assessed by spike-rate measures, while representation of modulation was evaluated by vector strength (VS) and the fundamental component of the fast Fourier transform (F(0) amplitude). These measures were assessed across the 400 ms duration of pulse-train stimuli, a duration relevant to speech stimuli. Different stimulus levels were explored and responses were categorized into four spike-rate groups to assess level effects across ANFs. The temporal pattern of rate adaptation to modulated trains was similar to that of unmodulated trains, but with less rate adaptation. VS to the modulator increased over time and tended to saturate at lower spike rates, while F(0) amplitude typically decreased over time for low driven rates and increased for higher driven rates. VS at moderate and high spike rates and degree of F(0) amplitude temporal changes at low and moderate spike rates were positively correlated with the degree of rate adaptation. Thus, high-rate carriers will modify the ANF representation of the modulator over time. As the VS and F(0) measures were sensitive to adaptation-related changes over different spike-rate ranges, there is value in assessing both measures.

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

Temporal and spatial changes in ion homeostasis, antioxidant defense and accumulation of flavonoids and glycolipid in a halophyte Sesuvium portulacastrum (L.) L.

PubMed Central

Nikalje, Ganesh C.; Variyar, P. S.; Joshi, M. V.; Nikam, T. D.

2018-01-01

Salinity is an important environmental constraint limiting plant productivity. Understanding adaptive responses of halophytes to high saline environments may offer clues to manage and improve salt stress in crop plants. We have studied physiological, biochemical and metabolic changes in a perennial, fast growing halophyte, Sesuvium portulacastrum under 0 mM (control), 150 mM (low salt, LS) and 500 mM (high salt, HS) NaCl treatments. The changes in growth, relative water content, cation, osmolyte accumulation, H2O2 and antioxidant enzyme activity (SOD, CAT and APX) were observed under different treatment conditions. A positive correlation was revealed for sodium ion accumulation with malondialdehyde (r2 = 0.77), proline (r2 = 0.88) and chlorophyll content (r2 = 0.82) under salt treatment while a negative correlation was observed with relative tissue water content (r2 = -0.73). The roots and leaves showed contrasting accumulation of potassium and sodium ions under LS treatment. Temporal and spatial study of sodium and potassium ion content indicated differential accumulation pattern in roots and leaves, and, high potassium levels in root. Higher H2O2 content was recorded in roots than leaves and the antioxidant enzyme activities also showed significant induction under salt treatment conditions. Gene expression profiling of sodium transporters, Sodium proton exchanger (NHX3), Vacuolar ATPase (vATPase) and Salt overly sensitive1 (SOS1) showed up regulation under salt stress after 6–24 hr of NaCl treatment. Metabolite changes in the salt stressed leaves showed increased accumulation of flavonoids (3,5-dihydroxy-6,4’-dimethoxy-flavone-7-O-[α-L-rhamnopyranosyl-(1→6)-β-D-glucopyranoside], and3,5-dihydroxy-6,3’,4’-trimethoxy-flavone-7-O-[α-L-rhamnopyranosyl-(1→6)-β-D-glucopyranoside] in both LS and HS treatments, while a glycolipid, 1-O-linolenyl-2-O-(palmitoyl)-3-O-galactopyranosyl glycerol, accumulated more in LS over HS treatments and control. The results suggest that differential spatial and temporal cation levels in roots and leaves, and accumulation of flavanoid and glycolipid could be responsible for salt adaptation of S. portulacastrum. PMID:29641593

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

USGS Publications Warehouse

Balshi, M. S.; McGuire, A.D.; Duffy, P.; Flannigan, M.; Walsh, J.; Melillo, J.

2009-01-01

Fire is a common disturbance in the North American boreal forest that influences ecosystem structure and function. The temporal and spatial dynamics of fire are likely to be altered as climate continues to change. In this study, we ask the question: how will area burned in boreal North America by wildfire respond to future changes in climate? To evaluate this question, we developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5?? (latitude ?? longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was substantially more predictable in the western portion of boreal North America than in eastern Canada. Burned area was also not very predictable in areas of substantial topographic relief and in areas along the transition between boreal forest and tundra. At the scale of Alaska and western Canada, the empirical fire models explain on the order of 82% of the variation in annual area burned for the period 1960-2002. July temperature was the most frequently occurring predictor across all models, but the fuel moisture codes for the months June through August (as a group) entered the models as the most important predictors of annual area burned. To predict changes in the temporal and spatial dynamics of fire under future climate, the empirical fire models used output from the Canadian Climate Center CGCM2 global climate model to predict annual area burned through the year 2100 across Alaska and western Canada. Relative to 1991-2000, the results suggest that average area burned per decade will double by 2041-2050 and will increase on the order of 3.5-5.5 times by the last decade of the 21st century. To improve the ability to better predict wildfire across Alaska and Canada, future research should focus on incorporating additional effects of long-term and successional vegetation changes on area burned to account more fully for interactions among fire, climate, and vegetation dynamics. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing Ltd.

Environmental systems biology of cold-tolerant phenotype in Saccharomyces species adapted to grow at different temperatures.

PubMed

Paget, Caroline Mary; Schwartz, Jean-Marc; Delneri, Daniela

2014-11-01

Temperature is one of the leading factors that drive adaptation of organisms and ecosystems. Remarkably, many closely related species share the same habitat because of their different temporal or micro-spatial thermal adaptation. In this study, we seek to find the underlying molecular mechanisms of the cold-tolerant phenotype of closely related yeast species adapted to grow at different temperatures, namely S. kudriavzevii CA111 (cryo-tolerant) and S. cerevisiae 96.2 (thermo-tolerant). Using two different systems approaches, i. thermodynamic-based analysis of a genome-scale metabolic model of S. cerevisiae and ii. large-scale competition experiment of the yeast heterozygote mutant collection, genes and pathways important for the growth at low temperature were identified. In particular, defects in lipid metabolism, oxidoreductase and vitamin pathways affected yeast fitness at cold. Combining the data from both studies, a list of candidate genes was generated and mutants for two predicted cold-favouring genes, GUT2 and ADH3, were created in two natural isolates. Compared with the parental strains, these mutants showed lower fitness at cold temperatures, with S. kudriavzevii displaying the strongest defect. Strikingly, in S. kudriavzevii, these mutations also significantly improve the growth at warm temperatures. In addition, overexpression of ADH3 in S. cerevisiae increased its fitness at cold. These results suggest that temperature-induced redox imbalances could be compensated by increased glycerol accumulation or production of cytosolic acetaldehyde through the deletion of GUT2 or ADH3, respectively. © 2014 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Cognition and balance control: does processing of explicit contextual cues of impending perturbations modulate automatic postural responses?

PubMed

Coelho, Daniel Boari; Teixeira, Luis Augusto

2017-08-01

Processing of predictive contextual cues of an impending perturbation is thought to induce adaptive postural responses. Cueing in previous research has been provided through repeated perturbations with a constant foreperiod. This experimental strategy confounds explicit predictive cueing with adaptation and non-specific properties of temporal cueing. Two experiments were performed to assess those factors separately. To perturb upright balance, the base of support was suddenly displaced backwards in three amplitudes: 5, 10 and 15 cm. In Experiment 1, we tested the effect of cueing the amplitude of the impending postural perturbation by means of visual signals, and the effect of adaptation to repeated exposures by comparing block versus random sequences of perturbation. In Experiment 2, we evaluated separately the effects of cueing the characteristics of an impending balance perturbation and cueing the timing of perturbation onset. Results from Experiment 1 showed that the block sequence of perturbations led to increased stability of automatic postural responses, and modulation of magnitude and onset latency of muscular responses. Results from Experiment 2 showed that only the condition cueing timing of platform translation onset led to increased balance stability and modulation of onset latency of muscular responses. Conversely, cueing platform displacement amplitude failed to induce any effects on automatic postural responses in both experiments. Our findings support the interpretation of improved postural responses via optimized sensorimotor processes, at the same time that cast doubt on the notion that cognitive processing of explicit contextual cues advancing the magnitude of an impending perturbation can preset adaptive postural responses.

The impact of climate change on infectious disease transmission: perceptions of CDC health professionals in Shanxi Province, China.

PubMed

Wei, Junni; Hansen, Alana; Zhang, Ying; Li, Hong; Liu, Qiyong; Sun, Yehuan; Xue, Shulian; Zhao, Shufang; Bi, Peng

2014-01-01

There have been increasing concerns about the challenge of emerging and re-emerging infectious diseases due to climate change, especially in developing countries including China. Health professionals play a significant role in the battle to control and prevent infectious diseases. This study therefore aims to investigate the perceptions and attitudes of health professionals at the Centers for Disease Control and Prevention (CDC) in different levels in China, and to consider adaptation measures to deal with the challenge of climate change. In 2013, a cross-sectional questionnaire survey was undertaken among 314 staff in CDCs in Shanxi Province, China, whose routine work involves disease control and prevention. Data were analyzed using descriptive methods and logistic regression. A majority of the CDC staff were aware of the health risks from climate change, especially its impacts on infectious disease transmission in their jurisdictions, and believed climate change might bring about both temporal and spatial change in transmission patterns. It was thought that adaptation measures should be established including: strengthening/improving currently existing disease surveillance systems and vector monitoring; building CDC capacity in terms of infrastructure and in-house health professional training; development and refinement of relevant legislation, policies and guidelines; better coordination among various government departments; the involvement of the community in infectious disease interventions; and collaborative research with other institutions. This study provides a snapshot of the understanding of CDC staff regarding climate change risks relevant to infectious diseases and adaptation in China. Results may help inform future efforts to develop adaptation measures to minimize infectious disease risks due to climate change.

Fitness consequences of northward dispersal as possible adaptation to climate change, using experimental translocation of a migratory passerine.

PubMed

Burger, Claudia; Nord, Andreas; Nilsson, Jan-Åke; Gilot-Fromont, Emmanuelle; Both, Christiaan

2013-01-01

Climate change leads to rapid, differential changes in phenology across trophic levels, often resulting in temporal mismatches between predators and their prey. If a species cannot easily adjust its timing, it can adapt by choosing a new breeding location with a later phenology of its prey. In this study, we experimentally investigated whether long-distance dispersal to northern breeding grounds with a later phenology could be a feasible process to restore the match between timing of breeding and peak food abundance and thus improve reproductive success. Here, we report the successful translocation of pied flycatchers (Ficedula hypoleuca) to natural breeding sites 560 km to the Northeast. We expected translocated birds to have a fitness advantage with respect to environmental phenology, but to potentially pay costs through the lack of other locally adapted traits. Translocated individuals started egg laying 11 days earlier than northern control birds, which were translocated only within the northern site. The number of fledglings produced was somewhat lower in translocated birds, compared to northern controls, and fledglings were in lower body condition. Translocated individuals were performing not significantly different to control birds that remained at the original southern site. The lack of advantage of the translocated individuals most likely resulted from the exceptionally cold spring in which the experiment was carried out. Our results, however, suggest that pied flycatchers can successfully introduce their early breeding phenotype after dispersing to more northern areas, and thus that adaptation through dispersal is a viable option for populations that get locally maladapted through climate change.

Employing temporal self-similarity across the entire time domain in computed tomography reconstruction

PubMed Central

Kazantsev, D.; Van Eyndhoven, G.; Lionheart, W. R. B.; Withers, P. J.; Dobson, K. J.; McDonald, S. A.; Atwood, R.; Lee, P. D.

2015-01-01

There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques. PMID:25939621

Multiscale biomechanical responses of adapted bone-periodontal ligament-tooth fibrous joints

PubMed Central

Jang, Andrew T.; Merkle, Arno; Fahey, Kevin; Gansky, Stuart A.; Ho, Sunita P.

2015-01-01

Reduced functional loads cause adaptations in organs. In this study, temporal adaptations of bone-ligament-tooth fibrous joints to reduced functional loads were mapped using a holistic approach. Systematic studies were performed to evaluate organ-level and tissue-level adaptations in specimens harvested periodically from rats given powder food for 6 months (N = 60 over 8,12,16,20, and 24 weeks). Bone-periodontal ligament (PDL)-tooth fibrous joint adaptation was evaluated by comparing changes in joint stiffness with changes in functional space between the tooth and alveolar bony socket. Adaptations in tissues included mapping changes in the PDL and bone architecture as observed from collagen birefringence, bone hardness and volume fraction in rats fed soft foods (soft diet, SD) compared to those fed hard pellets as a routine diet (hard diet, HD). In situ biomechanical testing on harvested fibrous joints revealed increased stiffness in SD groups (SD:239-605 N/mm) (p<0.05) at 8 and 12 weeks. Increased joint stiffness in early development phase was due to decreased functional space (at 8wks change in functional space was −33 µm, at 12wks change in functional space was −30 µm) and shifts in tissue quality as highlighted by birefringence, architecture and hardness. These physical changes were not observed in joints that were well into function, that is, in rodents older than 12 weeks of age. Significant adaptations in older groups were highlighted by shifts in bone growth (bone volume fraction 24wks: Δ-0.06) and bone hardness (8wks: Δ−0.04 GPa, 16 wks: Δ−0.07 GPa, 24wks: Δ−0.06 GPa). The response rate (N/s) of joints to mechanical loads decreased in SD groups. Results from the study showed that joint adaptation depended on age. The initial form-related adaptation (observed change in functional space) can challenge strain-adaptive nature of tissues to meet functional demands with increasing age into adulthood. The coupled effect between functional space in the bone-PDLtooth complex and strain-adaptive nature of tissues is necessary to accommodate functional demands, and is temporally sensitive despite joint malfunction. From an applied science perspective, we propose that adaptations are registered as functional history in tissues and joints. PMID:26151121

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

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

PubMed

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

2014-01-01

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

Timing matters: sonar call groups facilitate target localization in bats

PubMed Central

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

2014-01-01

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

Effect of eccentricity and light level on the timing of light adaptation mechanisms.

PubMed

Barrionuevo, Pablo A; Matesanz, Beatriz M; Gloriani, Alejandro H; Arranz, Isabel; Issolio, Luis; Mar, Santiago; Aparicio, Juan A

2018-04-01

We explored the complexity of the light adaptation process, assessing adaptation recovery (Ar) at different eccentricities and light levels. Luminance thresholds were obtained with transient background fields at mesopic and photopic light levels for temporal retinal eccentricities (0°-15°) with test/background stimulus size of 0.5°/1° using a staircase procedure in a two-channel Maxwellian view optical system. Ar was obtained in comparison with steady data [Vis. Res.125, 12 (2016)VISRAM0042-698910.1016/j.visres.2016.04.008]. Light level proportionally affects Ar only at fovea. Photopic extrafoveal thresholds were one log unit higher for transient conditions. Adaptation was equally fast at low light levels for different retinal locations with variations mainly affected by noise. These results evidence different timing in the mechanisms of adaptation involved.

Q-BIC3 - A Québec-Bavarian international collaboration for adapting regional watershed management to climate change

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2010-05-01

Adapting to the impacts of climate change is certainly one of the major challenges in water resources management over the next decades. Adaptation to climate change risks is most crucial in this domain, since projected increase in mean air temperature in combination with an expected increase in the temporal variability of precipitation patterns will contribute to pressure on current water availability, allocation and management practices. The latter often involve the utilization of valuable infrastructure, such as dams, reservoirs and water intakes, for which adaptation options must by developed over long-term and often dynamic planning horizons. Research to establish novel methodologies for improved adaptation to climate change is thus very important and only beginning to emerge in regional watershed management. The presented project Q-BIC³, funded by the Bavarian Minstry for the Environment and the Québec Ministère du Développement économique, de l'Innovation et de l'Exportation, aims to develop and apply a newly designed spectrum of tools to support the improved assessment of adaptation options to climate change in regional watershed management. It addresses in particular selected study sites in Québec and Bavaria. The following key issues have been prioritized within Q-BIC³: i) The definition of potential adaptation options in the context of climate change for pre-targeted water management key issues using a subsequent and logical chain of modelling tools (climate, hydrological and water management modeling tools) ii) The definition of an approach that accounts for hydrological projection uncertainties in the search for potential adaptation options in the context of climate change iii) The investigation of the required complexity in hydrological models to estimate climate change impacts and to develop specific adaptation options for Québec and Bavaria watersheds. iv) The development and prototyping of a regionally transferable and modular modelling system for integrated watershed management under climate change conditions. The study sites under investigation, namely the Haut-Saint Francois and Gatineau watersheds in Québec and the Isar and Regnitz catchments in Bavaria, are under heavy anthropogenic use. Intense dam and reservoir operations and even water transfer systems are in place to satisfy multi-purpose demands on available water resources. These are imposing extreme modifications to the natural flow regimes. In the first phase of the project, climatic forcing, stemming from an ensemble of selected GCM and RCM runs, is applied to a variety of hydrological models with different complexity. The derived projections of future hydrological conditions serve to investigate, whether current operation rules and/or existing infrastructure needs to be adapted to a changing environment. First findings demonstrate the large uncertainties associated to the model chain outputs, but also indicate that related adaptation is indispensable to meet the challenges of the rapidly changing man-environment systems.

Multilevel processes and cultural adaptation: Examples from past and present small-scale societies.

PubMed

Reyes-García, V; Balbo, A L; Gomez-Baggethun, E; Gueze, M; Mesoudi, A; Richerson, P; Rubio-Campillo, X; Ruiz-Mallén, I; Shennan, S

2016-12-01

Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviours. After a brief review of the concept of "cultural adaptation" from the perspective of cultural evolutionary theory and resilience theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social and political scales. We do so by examining small-scale societies' case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. We end the paper discussing the potential of modelling and computer simulation for studying multilevel processes in cultural adaptation.

Development of a model forecasting Dermanyssus gallinae's population dynamics for advancing Integrated Pest Management in laying hen facilities.

PubMed

Mul, Monique F; van Riel, Johan W; Roy, Lise; Zoons, Johan; André, Geert; George, David R; Meerburg, Bastiaan G; Dicke, Marcel; van Mourik, Simon; Groot Koerkamp, Peter W G

2017-10-15

The poultry red mite, Dermanyssus gallinae, is the most significant pest of egg laying hens in many parts of the world. Control of D. gallinae could be greatly improved with advanced Integrated Pest Management (IPM) for D. gallinae in laying hen facilities. The development of a model forecasting the pests' population dynamics in laying hen facilities without and post-treatment will contribute to this advanced IPM and could consequently improve implementation of IPM by farmers. The current work describes the development and demonstration of a model which can follow and forecast the population dynamics of D. gallinae in laying hen facilities given the variation of the population growth of D. gallinae within and between flocks. This high variation could partly be explained by house temperature, flock age, treatment, and hen house. The total population growth variation within and between flocks, however, was in part explained by temporal variation. For a substantial part this variation was unexplained. A dynamic adaptive model (DAP) was consequently developed, as models of this type are able to handle such temporal variations. The developed DAP model can forecast the population dynamics of D. gallinae, requiring only current flock population monitoring data, temperature data and information of the dates of any D. gallinae treatment. Importantly, the DAP model forecasted treatment effects, while compensating for location and time specific interactions, handling the variability of these parameters. The characteristics of this DAP model, and its compatibility with different mite monitoring methods, represent progression from existing approaches for forecasting D. gallinae that could contribute to advancing improved Integrated Pest Management (IPM) for D. gallinae in laying hen facilities. Copyright © 2017 Elsevier B.V. All rights reserved.

Emotional Modulation of Interval Timing and Time Perception

PubMed Central

Lake, Jessica I.; LaBar, Kevin S.; Meck, Warren H.

2017-01-01

Like other senses, our perception of time is not veridical, but rather, is modulated by changes in environmental context. Anecdotal experiences suggest that emotions can be powerful modulators of time perception; nevertheless, the functional and neural mechanisms underlying emotion-induced temporal distortions remain unclear. Widely accepted pacemaker-accumulator models of time perception suggest that changes in arousal and attention have unique influences on temporal judgments and contribute to emotional distortions of time perception. However, such models conflict with current views of arousal and attention suggesting that current models of time perception do not adequately explain the variability in emotion-induced temporal distortions. Instead, findings provide support for a new perspective of emotion-induced temporal distortions that emphasizes both the unique and interactive influences of arousal and attention on time perception over time. Using this framework, we discuss plausible functional and neural mechanisms of emotion-induced temporal distortions and how these temporal distortions may have important implications for our understanding of how emotions modulate our perceptual experiences in service of adaptive responding to biologically relevant stimuli. PMID:26972824

ContextD: an algorithm to identify contextual properties of medical terms in a Dutch clinical corpus.

PubMed

Afzal, Zubair; Pons, Ewoud; Kang, Ning; Sturkenboom, Miriam C J M; Schuemie, Martijn J; Kors, Jan A

2014-11-29

In order to extract meaningful information from electronic medical records, such as signs and symptoms, diagnoses, and treatments, it is important to take into account the contextual properties of the identified information: negation, temporality, and experiencer. Most work on automatic identification of these contextual properties has been done on English clinical text. This study presents ContextD, an adaptation of the English ConText algorithm to the Dutch language, and a Dutch clinical corpus. We created a Dutch clinical corpus containing four types of anonymized clinical documents: entries from general practitioners, specialists' letters, radiology reports, and discharge letters. Using a Dutch list of medical terms extracted from the Unified Medical Language System, we identified medical terms in the corpus with exact matching. The identified terms were annotated for negation, temporality, and experiencer properties. To adapt the ConText algorithm, we translated English trigger terms to Dutch and added several general and document specific enhancements, such as negation rules for general practitioners' entries and a regular expression based temporality module. The ContextD algorithm utilized 41 unique triggers to identify the contextual properties in the clinical corpus. For the negation property, the algorithm obtained an F-score from 87% to 93% for the different document types. For the experiencer property, the F-score was 99% to 100%. For the historical and hypothetical values of the temporality property, F-scores ranged from 26% to 54% and from 13% to 44%, respectively. The ContextD showed good performance in identifying negation and experiencer property values across all Dutch clinical document types. Accurate identification of the temporality property proved to be difficult and requires further work. The anonymized and annotated Dutch clinical corpus can serve as a useful resource for further algorithm development.

Selective spatial enhancement: Attentional spotlight size impacts spatial but not temporal perception.

PubMed

Goodhew, Stephanie C; Shen, Elizabeth; Edwards, Mark

2016-08-01

An important but often neglected aspect of attention is how changes in the attentional spotlight size impact perception. The zoom-lens model predicts that a small ("focal") attentional spotlight enhances all aspects of perception relative to a larger ("diffuse" spotlight). However, based on the physiological properties of the two major classes of visual cells (magnocellular and parvocellular neurons) we predicted trade-offs in spatial and temporal acuity as a function of spotlight size. Contrary to both of these accounts, however, across two experiments we found that attentional spotlight size affected spatial acuity, such that spatial acuity was enhanced for a focal relative to a diffuse spotlight, whereas the same modulations in spotlight size had no impact on temporal acuity. This likely reflects the function of attention: to induce the high spatial resolution of the fovea in periphery, where spatial resolution is poor but temporal resolution is good. It is adaptive, therefore, for the attentional spotlight to enhance spatial acuity, whereas enhancing temporal acuity does not confer the same benefit.

Discriminability limits in spatio-temporal stereo block matching.

PubMed

Jain, Ankit K; Nguyen, Truong Q

2014-05-01

Disparity estimation is a fundamental task in stereo imaging and is a well-studied problem. Recently, methods have been adapted to the video domain where motion is used as a matching criterion to help disambiguate spatially similar candidates. In this paper, we analyze the validity of the underlying assumptions of spatio-temporal disparity estimation, and determine the extent to which motion aids the matching process. By analyzing the error signal for spatio-temporal block matching under the sum of squared differences criterion and treating motion as a stochastic process, we determine the probability of a false match as a function of image features, motion distribution, image noise, and number of frames in the spatio-temporal patch. This performance quantification provides insight into when spatio-temporal matching is most beneficial in terms of the scene and motion, and can be used as a guide to select parameters for stereo matching algorithms. We validate our results through simulation and experiments on stereo video.

Adaptability of anticipatory postural adjustments associated with voluntary movement

PubMed Central

Yiou, Eric; Caderby, Teddy; Hussein, Tarek

2012-01-01

The control of balance is crucial for efficiently performing most of our daily motor tasks, such as those involving goal-directed arm movements or whole body displacement. The purpose of this article is twofold. Firstly, it is to recall how balance can be maintained despite the different sources of postural perturbation arising during voluntary movement. The importance of the so-called “anticipatory postural adjustments” (APA), taken as a “line of defence” against the destabilizing effect induced by a predicted perturbation, is emphasized. Secondly, it is to report the results of recent studies that questioned the adaptability of APA to various constraints imposed on the postural system. The postural constraints envisaged here are classified into biomechanical (postural stability, superimposition of motor tasks), (neuro) physiological (fatigue), temporal (time pressure) and psychological (fear of falling, emotion). Overall, the results of these studies point out the capacity of the central nervous system (CNS) to adapt the spatio-temporal features of APA to each of these constraints. However, it seems that, depending on the constraint, the “priority” of the CNS was focused on postural stability maintenance, on body protection and/or on maintenance of focal movement performance. PMID:22720267

Socio-hydrological modelling of floods: investigating community resilience, adaptation capacity and risk

NASA Astrophysics Data System (ADS)

Ciullo, Alessio; Viglione, Alberto; Castellarin, Attilio

2016-04-01

Changes in flood risk occur because of changes in climate and hydrology, and in societal exposure and vulnerability. Research on change in flood risk has demonstrated that the mutual interactions and continuous feedbacks between floods and societies has to be taken into account in flood risk management. The present work builds on an existing conceptual model of an hypothetical city located in the proximity of a river, along whose floodplains the community evolves over time. The model reproduces the dynamic co-evolution of four variables: flooding, population density of the flooplain, amount of structural protection measures and memory of floods. These variables are then combined in a way to mimic the temporal change of community resilience, defined as the (inverse of the) amount of time for the community to recover from a shock, and adaptation capacity, defined as ratio between damages due to subsequent events. Also, temporal changing exposure, vulnerability and probability of flooding are also modelled, which results in a dynamically varying flood-risk. Examples are provided that show how factors such as collective memory and risk taking attitude influence the dynamics of community resilience, adaptation capacity and risk.

The acoustic adaptation hypothesis in a widely distributed South American frog: Southernmost signals propagate better.

PubMed

Velásquez, Nelson A; Moreno-Gómez, Felipe N; Brunetti, Enzo; Penna, Mario

2018-05-03

Animal communication occurs in environments that affect the properties of signals as they propagate from senders to receivers. We studied the geographic variation of the advertisement calls of male Pleurodema thaul individuals from eight localities in Chile. Furthermore, by means of signal propagation experiments, we tested the hypothesis that local calls are better transmitted and less degraded than foreign calls (i.e. acoustic adaptation hypothesis). Overall, the advertisement calls varied greatly along the distribution of P. thaul in Chile, and it was possible to discriminate localities grouped into northern, central and southern stocks. Propagation distance affected signal amplitude and spectral degradation in all localities, but temporal degradation was only affected by propagation distance in one out of seven localities. Call origin affected signal amplitude in five out of seven localities and affected spectral and temporal degradation in six out of seven localities. In addition, in northern localities, local calls degraded more than foreign calls, and in southern localities the opposite was observed. The lack of a strict optimal relationship between signal characteristics and environment indicates partial concordance with the acoustic adaptation hypothesis. Inter-population differences in selectivity for call patterns may compensate for such environmental constraints on acoustic communication.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

Adaptation can explain evidence for encoding of probabilistic information in macaque inferior temporal cortex.

PubMed

Vinken, Kasper; Vogels, Rufin

2017-11-20

In predictive coding theory, the brain is conceptualized as a prediction machine that constantly constructs and updates expectations of the sensory environment [1]. In the context of this theory, Bell et al.[2] recently studied the effect of the probability of task-relevant stimuli on the activity of macaque inferior temporal (IT) neurons and observed a reduced population response to expected faces in face-selective neurons. They concluded that "IT neurons encode long-term, latent probabilistic information about stimulus occurrence", supporting predictive coding. They manipulated expectation by the frequency of face versus fruit stimuli in blocks of trials. With such a design, stimulus repetition is confounded with expectation. As previous studies showed that IT neurons decrease their response with repetition [3], such adaptation (or repetition suppression), instead of expectation suppression as assumed by the authors, could explain their effects. The authors attempted to control for this alternative interpretation with a multiple regression approach. Here we show by using simulation that adaptation can still masquerade as expectation effects reported in [2]. Further, the results from the regression model used for most analyses cannot be trusted, because the model is not uniquely defined. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing

PubMed Central

Weber, Kirsten; Lau, Ellen F.; Stillerman, Benjamin; Kuperberg, Gina R.

2016-01-01

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions—a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the statistical structure of the wider environmental context. Together, these findings highlight close links between the networks mediating semantic prediction, executive function and learning, giving new insights into how our brains are able to flexibly adapt to our environment. PMID:27010386

The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

PubMed

Weber, Kirsten; Lau, Ellen F; Stillerman, Benjamin; Kuperberg, Gina R

2016-01-01

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the statistical structure of the wider environmental context. Together, these findings highlight close links between the networks mediating semantic prediction, executive function and learning, giving new insights into how our brains are able to flexibly adapt to our environment.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

PubMed

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

2017-12-01

Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more meaningful information that can be used in decision-making and planning. Future extensions and applications of these tools in a climate context will be considered.

Adaptive regulation of sparseness by feedforward inhibition

PubMed Central

Assisi, Collins; Stopfer, Mark; Laurent, Gilles; Bazhenov, Maxim

2014-01-01

In the mushroom body of insects, odors are represented by very few spikes in a small number of neurons, a highly efficient strategy known as sparse coding. Physiological studies of these neurons have shown that sparseness is maintained across thousand-fold changes in odor concentration. Using a realistic computational model, we propose that sparseness in the olfactory system is regulated by adaptive feedforward inhibition. When odor concentration changes, feedforward inhibition modulates the duration of the temporal window over which the mushroom body neurons may integrate excitatory presynaptic input. This simple adaptive mechanism could maintain the sparseness of sensory representations across wide ranges of stimulus conditions. PMID:17660812

Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.

PubMed

Naud, Richard; Gerstner, Wulfram

2012-01-01

The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for spiking neurons with arbitrary refractoriness and adaptation. As a modeling framework, we use the spike response model, also known as the generalized linear neuron model. Because of refractoriness, the effect of the most recent spike on the spiking probability a few milliseconds later is very strong. The influence of the last spike needs therefore to be described with high precision, while the rest of the neuronal spiking history merely introduces an average self-inhibition or adaptation that depends on the expected number of past spikes but not on the exact spike timings. Based on these insights, we derive a 'quasi-renewal equation' which is shown to yield an excellent description of the firing rate of adapting neurons. We explore the domain of validity of the quasi-renewal equation and compare it with other rate equations for populations of spiking neurons. The problem of decoding the stimulus from the population response (or PSTH) is addressed analogously. We find that for small levels of activity and weak adaptation, a simple accumulator of the past activity is sufficient to decode the original input, but when refractory effects become large decoding becomes a non-linear function of the past activity. The results presented here can be applied to the mean-field analysis of coupled neuron networks, but also to arbitrary point processes with negative self-interaction.

Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus).

PubMed

Marsden, Clare D; Woodroffe, Rosie; Mills, Michael G L; McNutt, J Weldon; Creel, Scott; Groom, Rosemary; Emmanuel, Masenga; Cleaveland, Sarah; Kat, Pieter; Rasmussen, Gregory S A; Ginsberg, Joshua; Lines, Robin; André, Jean-Marc; Begg, Colleen; Wayne, Robert K; Mable, Barbara K

2012-03-01

Deciphering patterns of genetic variation within a species is essential for understanding population structure, local adaptation and differences in diversity between populations. Whilst neutrally evolving genetic markers can be used to elucidate demographic processes and genetic structure, they are not subject to selection and therefore are not informative about patterns of adaptive variation. As such, assessments of pertinent adaptive loci, such as the immunity genes of the major histocompatibility complex (MHC), are increasingly being incorporated into genetic studies. In this study, we combined neutral (microsatellite, mtDNA) and adaptive (MHC class II DLA-DRB1 locus) markers to elucidate the factors influencing patterns of genetic variation in the African wild dog (Lycaon pictus); an endangered canid that has suffered extensive declines in distribution and abundance. Our genetic analyses found all extant wild dog populations to be relatively small (N(e)  < 30). Furthermore, through coalescent modelling, we detected a genetic signature of a recent and substantial demographic decline, which correlates with human expansion, but contrasts with findings in some other African mammals. We found strong structuring of wild dog populations, indicating the negative influence of extensive habitat fragmentation and loss of gene flow between habitat patches. Across populations, we found that the spatial and temporal structure of microsatellite diversity and MHC diversity were correlated and strongly influenced by demographic stability and population size, indicating the effects of genetic drift in these small populations. Despite this correlation, we detected signatures of selection at the MHC, implying that selection has not been completely overwhelmed by genetic drift. © 2012 Blackwell Publishing Ltd.

Signal coding in cockroach photoreceptors is tuned to dim environments.

PubMed

Heimonen, K; Immonen, E-V; Frolov, R V; Salmela, I; Juusola, M; Vähäsöyrinki, M; Weckström, M

2012-11-01

In dim light, scarcity of photons typically leads to poor vision. Nonetheless, many animals show visually guided behavior with dim environments. We investigated the signaling properties of photoreceptors of the dark active cockroach (Periplaneta americana) using intracellular and whole-cell patch-clamp recordings to determine whether they show selective functional adaptations to dark. Expectedly, dark-adapted photoreceptors generated large and slow responses to single photons. However, when light adapted, responses of both phototransduction and the nontransductive membrane to white noise (WN)-modulated stimuli remained slow with corner frequencies ~20 Hz. This promotes temporal integration of light inputs and maintains high sensitivity of vision. Adaptive changes in dynamics were limited to dim conditions. Characteristically, both step and frequency responses stayed effectively unchanged for intensities >1,000 photons/s/photoreceptor. A signal-to-noise ratio (SNR) of the light responses was transiently higher at frequencies <5 Hz for ~5 s after light onset but deteriorated to a lower value upon longer stimulation. Naturalistic light stimuli, as opposed to WN, evoked markedly larger responses with higher SNRs at low frequencies. This allowed realistic estimates of information transfer rates, which saturated at ~100 bits/s at low-light intensities. We found, therefore, selective adaptations beneficial for vision in dim environments in cockroach photoreceptors: large amplitude of single-photon responses, constant high level of temporal integration of light inputs, saturation of response properties at low intensities, and only transiently efficient encoding of light contrasts. The results also suggest that the sources of the large functional variability among different photoreceptors reside mostly in phototransduction processes and not in the properties of the nontransductive membrane.

Working memory network plasticity after anterior temporal lobe resection: a longitudinal functional magnetic resonance imaging study

PubMed Central

Stretton, Jason; Sidhu, Meneka K.; Winston, Gavin P.; Bartlett, Philippa; McEvoy, Andrew W.; Symms, Mark R.; Koepp, Matthias J.; Thompson, Pamela J.

2014-01-01

Working memory is a crucial cognitive function that is disrupted in temporal lobe epilepsy. It is unclear whether this impairment is a consequence of temporal lobe involvement in working memory processes or due to seizure spread to extratemporal eloquent cortex. Anterior temporal lobe resection controls seizures in 50–80% of patients with drug-resistant temporal lobe epilepsy and the effect of surgery on working memory are poorly understood both at a behavioural and neural level. We investigated the impact of temporal lobe resection on the efficiency and functional anatomy of working memory networks. We studied 33 patients with unilateral medial temporal lobe epilepsy (16 left) before, 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were also assessed in parallel. All subjects had neuropsychological testing and performed a visuospatial working memory functional magnetic resonance imaging paradigm on these three separate occasions. Changes in activation and deactivation patterns were modelled individually and compared between groups. Changes in task performance were included as regressors of interest to assess the efficiency of changes in the networks. Left and right temporal lobe epilepsy patients were impaired on preoperative measures of working memory compared to controls. Working memory performance did not decline following left or right temporal lobe resection, but improved at 3 and 12 months following left and, to a lesser extent, following right anterior temporal lobe resection. After left anterior temporal lobe resection, improved performance correlated with greater deactivation of the left hippocampal remnant and the contralateral right hippocampus. There was a failure of increased deactivation of the left hippocampal remnant at 3 months after left temporal lobe resection compared to control subjects, which had normalized 12 months after surgery. Following right anterior temporal lobe resection there was a progressive increase of activation in the right superior parietal lobe at 3 and 12 months after surgery. There was greater deactivation of the right hippocampal remnant compared to controls between 3 and 12 months after right anterior temporal lobe resection that was associated with lesser improvement in task performance. Working memory improved after anterior temporal lobe resection, particularly following left-sided resections. Postoperative working memory was reliant on the functional capacity of the hippocampal remnant and, following left resections, the functional reserve of the right hippocampus. These data suggest that working memory following temporal lobe resection is dependent on the engagement of the posterior medial temporal lobes and eloquent cortex. PMID:24691395

How to choose methods for lake greenhouse gas flux measurements?

NASA Astrophysics Data System (ADS)

Bastviken, David

2017-04-01

Lake greenhouse gas (GHG) fluxes are increasingly recognized as important for lake ecosystems as well as for large scale carbon and GHG budgets. However, many of our flux estimates are uncertain and it can be discussed if the presently available data is representative for the systems studied or not. Data are also very limited for some important flux pathways. Hence, many ongoing efforts try to better constrain fluxes and understand flux regulation. A fundamental challenge towards improved knowledge and when starting new studies is what methods to choose. A variety of approaches to measure aquatic GHG exchange is used and data from different methods and methodological approaches have often been treated as equally valid to create large datasets for extrapolations and syntheses. However, data from different approaches may cover different flux pathways or spatio-temporal domains and are thus not always comparable. Method inter-comparisons and critical method evaluations addressing these issues are rare. Emerging efforts to organize systematic multi-lake monitoring networks for GHG fluxes leads to method choices that may set the foundation for decades of data generation and therefore require fundamental evaluation of different approaches. The method choices do not only regard the equipment but also for example consideration of overall measurement design and field approaches, relevant spatial and temporal resolution for different flux components, and accessory variables to measure. In addition, consideration of how to design monitoring approaches being affordable, suitable for widespread (global) use, and comparable across regions is needed. Inspired by discussions with Prof. Dr. Cristian Blodau during the EGU General Assembly 2016, this presentation aims to (1) illustrate fundamental pros and cons for a number of common methods, (2) show how common methodological approaches originally adapted for other environments can be improved for lake flux measurements, (3) suggest how consideration of spatio-temporal dimensions of flux variability can lead to more optimized approaches, and (4) highlight possibilities of efficient ways forward including low-cost technologies that has potential for world-wide use.

Adaptive spatial combining for passive time-reversed communications.

PubMed

Gomes, João; Silva, António; Jesus, Sérgio

2008-08-01

Passive time reversal has aroused considerable interest in underwater communications as a computationally inexpensive means of mitigating the intersymbol interference introduced by the channel using a receiver array. In this paper the basic technique is extended by adaptively weighting sensor contributions to partially compensate for degraded focusing due to mismatch between the assumed and actual medium impulse responses. Two algorithms are proposed, one of which restores constructive interference between sensors, and the other one minimizes the output residual as in widely used equalization schemes. These are compared with plain time reversal and variants that employ postequalization and channel tracking. They are shown to improve the residual error and temporal stability of basic time reversal with very little added complexity. Results are presented for data collected in a passive time-reversal experiment that was conducted during the MREA'04 sea trial. In that experiment a single acoustic projector generated a 24-PSK (phase-shift keyed) stream at 200400 baud, modulated at 3.6 kHz, and received at a range of about 2 km on a sparse vertical array with eight hydrophones. The data were found to exhibit significant Doppler scaling, and a resampling-based preprocessing method is also proposed here to compensate for that scaling.

Ungulates rely less on visual cues, but more on adapting movement behaviour, when searching for forage.

PubMed

Venter, Jan A; Prins, Herbert H T; Mashanova, Alla; Slotow, Rob

2017-01-01

Finding suitable forage patches in a heterogeneous landscape, where patches change dynamically both spatially and temporally could be challenging to large herbivores, especially if they have no a priori knowledge of the location of the patches. We tested whether three large grazing herbivores with a variety of different traits improve their efficiency when foraging at a heterogeneous habitat patch scale by using visual cues to gain a priori knowledge about potential higher value foraging patches. For each species (zebra ( Equus burchelli ), red hartebeest ( Alcelaphus buselaphus subspecies camaa ) and eland ( Tragelaphus oryx )), we used step lengths and directionality of movement to infer whether they were using visual cues to find suitable forage patches at a habitat patch scale. Step lengths were significantly longer for all species when moving to non-visible patches than to visible patches, but all movements showed little directionality. Of the three species, zebra movements were the most directional. Red hartebeest had the shortest step lengths and zebra the longest. We conclude that these large grazing herbivores may not exclusively use visual cues when foraging at a habitat patch scale, but would rather adapt their movement behaviour, mainly step length, to the heterogeneity of the specific landscape.

Cross-cultural caregiving and the temporal dimension.

PubMed

Escandon, Socorro

2013-11-01

The caregiving research literature has explored and documented findings from psychological, clinical, and policy/program perspectives, but little is known regarding the contextual perspectives of caregiving. Temporal factors influence the structure and functioning of the caregiving family. The proposed paradigm adaptation extends a contextual perspective that addresses the exploration of the caregiving process as a temporal, dynamic, progressive process over time, in which decisions made by caregivers may not always be based on observable tasks but, nevertheless, may have important consequences. When cultures cross, attitudes and behaviors are modified, resulting from contact with a different set of values and beliefs. Cross-cultural research aims to explore these changes that take place over time. Future research should consider the inclusion of measures that assess the temporal aspect of caregiving and the acculturation considerations of family caregivers. These measures are especially needed because of the increased influence of international migration, economic globalization, and political conflicts in today's multicultural societies.

Attentional load and attentional boost: a review of data and theory.

PubMed

Swallow, Khena M; Jiang, Yuhong V

2013-01-01

Both perceptual and cognitive processes are limited in capacity. As a result, attention is selective, prioritizing items and tasks that are important for adaptive behavior. However, a number of recent behavioral and neuroimaging studies suggest that, at least under some circumstances, increasing attention to one task can enhance performance in a second task (e.g., the attentional boost effect). Here we review these findings and suggest a new theoretical framework, the dual-task interaction model, that integrates these findings with current views of attentional selection. To reconcile the attentional boost effect with the effects of attentional load, we suggest that temporal selection results in a temporally specific enhancement across modalities, tasks, and spatial locations. Moreover, the effects of temporal selection may be best observed when the attentional system is optimally tuned to the temporal dynamics of incoming stimuli. Several avenues of research motivated by the dual-task interaction model are then discussed.

Attentional Load and Attentional Boost: A Review of Data and Theory

PubMed Central

Swallow, Khena M.; Jiang, Yuhong V.

2013-01-01

Both perceptual and cognitive processes are limited in capacity. As a result, attention is selective, prioritizing items and tasks that are important for adaptive behavior. However, a number of recent behavioral and neuroimaging studies suggest that, at least under some circumstances, increasing attention to one task can enhance performance in a second task (e.g., the attentional boost effect). Here we review these findings and suggest a new theoretical framework, the dual-task interaction model, that integrates these findings with current views of attentional selection. To reconcile the attentional boost effect with the effects of attentional load, we suggest that temporal selection results in a temporally specific enhancement across modalities, tasks, and spatial locations. Moreover, the effects of temporal selection may be best observed when the attentional system is optimally tuned to the temporal dynamics of incoming stimuli. Several avenues of research motivated by the dual-task interaction model are then discussed. PMID:23730294

Restoration of distorted depth maps calculated from stereo sequences

NASA Technical Reports Server (NTRS)

Damour, Kevin; Kaufman, Howard

1991-01-01

A model-based Kalman estimator is developed for spatial-temporal filtering of noise and other degradations in velocity and depth maps derived from image sequences or cinema. As an illustration of the proposed procedures, edge information from image sequences of rigid objects is used in the processing of the velocity maps by selecting from a series of models for directional adaptive filtering. Adaptive filtering then allows for noise reduction while preserving sharpness in the velocity maps. Results from several synthetic and real image sequences are given.

The Relation Between Intellectual Functioning and Adaptive Behavior in the Diagnosis of Intellectual Disability.

PubMed

Tassé, Marc J; Luckasson, Ruth; Schalock, Robert L

2016-12-01

Intellectual disability originates during the developmental period and is characterized by significant limitations both in intellectual functioning and in adaptive behavior as expressed in conceptual, social, and practical adaptive skills. In this article, we present a brief history of the diagnostic criteria of intellectual disability for both the DSM-5 and AAIDD. The article also (a) provides an update of the understanding of adaptive behavior, (b) dispels two thinking errors regarding mistaken temporal or causal link between intellectual functioning and adaptive behavior, (c) explains that there is a strong correlational, but no causative, relation between intellectual functioning and adaptive behavior, and (d) asserts that once a question of determining intellectual disability is raised, both intellectual functioning and adaptive behavior are assessed and considered jointly and weighed equally in the diagnosis of intellectual disability. We discuss the problems created by an inaccurate statement that appears in the DSM-5 regarding a causal link between deficits in intellectual functioning and adaptive behavior and propose an immediate revision to remove this erroneous and confounding statement.

Multilevel processes and cultural adaptation: Examples from past and present small-scale societies

PubMed Central

Reyes-García, V.; Balbo, A. L.; Gomez-Baggethun, E.; Gueze, M.; Mesoudi, A.; Richerson, P.; Rubio-Campillo, X.; Ruiz-Mallén, I.; Shennan, S.

2016-01-01

Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviours. After a brief review of the concept of “cultural adaptation” from the perspective of cultural evolutionary theory and resilience theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social and political scales. We do so by examining small-scale societies’ case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. We end the paper discussing the potential of modelling and computer simulation for studying multilevel processes in cultural adaptation. PMID:27774109

Detection of new in-path targets by drivers using Stop & Go Adaptive Cruise Control.

PubMed

Stanton, Neville A; Dunoyer, Alain; Leatherland, Adam

2011-05-01

This paper reports on the design and evaluation of in-car displays used to support Stop & Go Adaptive Cruise Control. Stop & Go Adaptive Cruise Control is an extension of Adaptive Cruise Control, as it is able to bring the vehicle to a complete stop. Previous versions of Adaptive Cruise Control have only operated above 26 kph. The greatest concern for these technologies is the appropriateness of the driver's response in any given scenario. Three different driver interfaces were proposed to support the detection of modal, spatial and temporal changes of the system: an iconic display, a flashing iconic display, and a representation of the radar. The results show that drivers correctly identified more changes detected by the system with the radar display than with the other displays, but higher levels of workload accompanied this increased detection. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

An Adaptive Sensor Mining Framework for Pervasive Computing Applications

NASA Astrophysics Data System (ADS)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

PubMed Central

Liu, Aiming; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-01-01

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems. PMID:29117100

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

PubMed

Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-11-08

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

SenThIS - Sentinels of Thuringian information systems

NASA Astrophysics Data System (ADS)

Naue, Sandra; Krause, Peter

2016-04-01

Decision-making for sustainable environmental resource management or risk prevention is facing the problem of constantly changing conditions related to the projected changes of climate, demography and socio-economy. Herefore, adaptable tools and methods which can reflect such changes are needed for an efficient management. The need to improve existing tools is a challenge the departments of German environmental authorities at state and federal level are facing at this time. Additionally the increasing demands for work process optimization due to financial cutbacks are coming into play. Consequently the need for suitable adaptation measurements for short and long term changes of environmental state variables is growing. The importance of spatio-temporal data, providing continuous observation about the state of the environmental system and its changes, is therefore increasing in order to elaborate adaptation strategies. In this case earth observation is a useful source for the required data. With the new Sentinel fleet, ESA's Copernicus Program is providing a possibility to obtain such information free in high temporal and spatial resolution. The BMVI funded project SenThIS, a collaborative project by the Thuringian State Institute for Environment and Geology (TLUG), the Thuringian Forest Department and two SMEs EOS GmbH and Feiffer consult is aiming at utilizing Copernicus data and services for operational tasks on a federal level. It addresses this aforementioned deficit through the development and implementation of a processing chain for synergetic and automated application of remote sensing data and products to accomplish operational state tasks. The product development is characterized by the synergetic application of remote sensing data and suitable models. Design and calibration of the models base on Sentinel 1/2 data and additional information (e.g. meteorological data, in-situ measurements). This results in products of highly temporal and spatial resolution for entire Thuringia. Simultaneously a performance evaluation of the developed products as well as the establishment of those products and other suitable Copernicus services in form of an operational application of public tasks should be reached. Within the project framework prototypical remote sensing products for state authorities will be developed. In particular, a soil moisture product derived by process oriented modelling utilizing remote sensing data that is going to provide updated comprehensive information at a three to six day interval will be developed. The development will be accompanied by detailed evaluation, validation and uncertainty analysis using various information from different sources. The soil moisture product is expected to help in the improvement of the established flood forecast systems, crop yield estimation or forestal state reviews. Additional products like a snow product or the derivation of agricultural stock parameters will be developed or gained from existing Copernicus products. By the resulting data and processing infrastructure SenThIS enables the involved authorities to work faster and more efficient. Thereby a better forecast, detection and reaction to environmental risks and potential catastrophes will become possible. The poster presents the underlying idea and structure of the SenThIS project along with the first results of the first project year.

Using Dynamic Time Warping and Data Forensics to Examine Tradeoffs among Land-Energy-Water Networks Across the Conterminous United States

NASA Astrophysics Data System (ADS)

McManamay, R.; Allen, M. R.; Piburn, J.; Sanyal, J.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Characterizing interdependencies among land-energy-water sectors, their vulnerabilities, and tipping points, is challenging, especially if all sectors are simultaneously considered. Because such holistic system behavior is uncertain, largely unmodeled, and in need of testable hypotheses of system drivers, these dynamics are conducive to exploratory analytics of spatiotemporal patterns, powered by tools, such as Dynamic Time Warping (DTW). Here, we conduct a retrospective analysis (1950 - 2010) of temporal trends in land use, energy use, and water use within US counties to identify commonalities in resource consumption and adaptation strategies to resource limitations. We combine existing and derived data from statistical downscaling to synthesize a temporally comprehensive land-energy-water dataset at the US county level and apply DTW and subsequent hierarchical clustering to examine similar temporal trends in resource typologies for land, energy, and water sectors. As expected, we observed tradeoffs among water uses (e.g., public supply vs irrigation) and land uses (e.g., urban vs ag). Strong associations between clusters amongst sectors reveal tight system interdependencies, whereas weak associations suggest unique behaviors and potential for human adaptations towards disruptive technologies and less resource-dependent population growth. Our framework is useful for exploring complex human-environmental system dynamics and generating hypotheses to guide subsequent energy-water-nexus research.

The successively temporal error concealment algorithm using error-adaptive block matching principle

NASA Astrophysics Data System (ADS)

Lee, Yu-Hsuan; Wu, Tsai-Hsing; Chen, Chao-Chyun

2014-09-01

Generally, the temporal error concealment (TEC) adopts the blocks around the corrupted block (CB) as the search pattern to find the best-match block in previous frame. Once the CB is recovered, it is referred to as the recovered block (RB). Although RB can be the search pattern to find the best-match block of another CB, RB is not the same as its original block (OB). The error between the RB and its OB limits the performance of TEC. The successively temporal error concealment (STEC) algorithm is proposed to alleviate this error. The STEC procedure consists of tier-1 and tier-2. The tier-1 divides a corrupted macroblock into four corrupted 8 × 8 blocks and generates a recovering order for them. The corrupted 8 × 8 block with the first place of recovering order is recovered in tier-1, and remaining 8 × 8 CBs are recovered in tier-2 along the recovering order. In tier-2, the error-adaptive block matching principle (EA-BMP) is proposed for the RB as the search pattern to recover remaining corrupted 8 × 8 blocks. The proposed STEC outperforms sophisticated TEC algorithms on average PSNR by 0.3 dB on the packet error rate of 20% at least.

Flight Test Comparison of Different Adaptive Augmentations for Fault Tolerant Control Laws for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Hanson, Curtis E.; Lee, James A.; Kaneshige, John T.

2009-01-01

This report describes the improvements and enhancements to a neural network based approach for directly adapting to aerodynamic changes resulting from damage or failures. This research is a follow-on effort to flight tests performed on the NASA F-15 aircraft as part of the Intelligent Flight Control System research effort. Previous flight test results demonstrated the potential for performance improvement under destabilizing damage conditions. Little or no improvement was provided under simulated control surface failures, however, and the adaptive system was prone to pilot-induced oscillations. An improved controller was designed to reduce the occurrence of pilot-induced oscillations and increase robustness to failures in general. This report presents an analysis of the neural networks used in the previous flight test, the improved adaptive controller, and the baseline case with no adaptation. Flight test results demonstrate significant improvement in performance by using the new adaptive controller compared with the previous adaptive system and the baseline system for control surface failures.

Precision pharmacology for Alzheimer's disease.

PubMed

Hampel, Harald; Vergallo, Andrea; Aguilar, Lisi Flores; Benda, Norbert; Broich, Karl; Cuello, A Claudio; Cummings, Jeffrey; Dubois, Bruno; Federoff, Howard J; Fiandaca, Massimo; Genthon, Remy; Haberkamp, Marion; Karran, Eric; Mapstone, Mark; Perry, George; Schneider, Lon S; Welikovitch, Lindsay A; Woodcock, Janet; Baldacci, Filippo; Lista, Simone

2018-04-01

The complex multifactorial nature of polygenic Alzheimer's disease (AD) presents significant challenges for drug development. AD pathophysiology is progressing in a non-linear dynamic fashion across multiple systems levels - from molecules to organ systems - and through adaptation, to compensation, and decompensation to systems failure. Adaptation and compensation maintain homeostasis: a dynamic equilibrium resulting from the dynamic non-linear interaction between genome, epigenome, and environment. An individual vulnerability to stressors exists on the basis of individual triggers, drivers, and thresholds accounting for the initiation and failure of adaptive and compensatory responses. Consequently, the distinct pattern of AD pathophysiology in space and time must be investigated on the basis of the individual biological makeup. This requires the implementation of systems biology and neurophysiology to facilitate Precision Medicine (PM) and Precision Pharmacology (PP). The regulation of several processes at multiple levels of complexity from gene expression to cellular cycle to tissue repair and system-wide network activation has different time delays (temporal scale) according to the affected systems (spatial scale). The initial failure might originate and occur at every level potentially affecting the whole dynamic interrelated systems within an organism. Unraveling the spatial and temporal dynamics of non-linear pathophysiological mechanisms across the continuum of hierarchical self-organized systems levels and from systems homeostasis to systems failure is key to understand AD. Measuring and, possibly, controlling space- and time-scaled adaptive and compensatory responses occurring during AD will represent a crucial step to achieve the capacity to substantially modify the disease course and progression at the best suitable timepoints, thus counteracting disrupting critical pathophysiological inputs. This approach will provide the conceptual basis for effective disease-modifying pathway-based targeted therapies. PP is based on an exploratory and integrative strategy to complex diseases such as brain proteinopathies including AD, aimed at identifying simultaneous aberrant molecular pathways and predicting their temporal impact on the systems levels. The depiction of pathway-based molecular signatures of complex diseases contributes to the accurate and mechanistic stratification of distinct subcohorts of individuals at the earliest compensatory stage when treatment intervention may reverse, stop, or delay the disease. In addition, individualized drug selection may optimize treatment safety by decreasing risk and amplitude of side effects and adverse reactions. From a methodological point of view, comprehensive "omics"-based biomarkers will guide the exploration of spatio-temporal systems-wide morpho-functional shifts along the continuum of AD pathophysiology, from adaptation to irreversible failure. The Alzheimer Precision Medicine Initiative (APMI) and the APMI cohort program (APMI-CP) have commenced to facilitate a paradigm shift towards effective drug discovery and development in AD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Children with autism spectrum disorder show reduced adaptation to number

PubMed Central

Turi, Marco; Burr, David C.; Igliozzi, Roberta; Aagten-Murphy, David; Muratori, Filippo; Pellicano, Elizabeth

2015-01-01

Autism is known to be associated with major perceptual atypicalities. We have recently proposed a general model to account for these atypicalities in Bayesian terms, suggesting that autistic individuals underuse predictive information or priors. We tested this idea by measuring adaptation to numerosity stimuli in children diagnosed with autism spectrum disorder (ASD). After exposure to large numbers of items, stimuli with fewer items appear to be less numerous (and vice versa). We found that children with ASD adapted much less to numerosity than typically developing children, although their precision for numerosity discrimination was similar to that of the typical group. This result reinforces recent findings showing reduced adaptation to facial identity in ASD and goes on to show that reduced adaptation is not unique to faces (social stimuli with special significance in autism), but occurs more generally, for both parietal and temporal functions, probably reflecting inefficiencies in the adaptive interpretation of sensory signals. These results provide strong support for the Bayesian theories of autism. PMID:26056294

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Gasser, Gerald

2013-01-01

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.