Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume; Koster, Randal D. (Editor)

2014-01-01

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality

PubMed Central

Hondula, David M.; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-01-01

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634 PMID:28885979

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele; Kovach, Robin M.; Vernieres, Guillaume

2014-01-01

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Adapting Evidence-Based Mental Health Treatments in Community Settings: Preliminary Results from a Partnership Approach

ERIC Educational Resources Information Center

Southam-Gerow, Michael A.; Hourigan, Shannon E.; Allin, Robert B., Jr.

2009-01-01

This article describes the application of a university-community partnership model to the problem of adapting evidence-based treatment approaches in a community mental health setting. Background on partnership research is presented, with consideration of methodological and practical issues related to this kind of research. Then, a rationale for…

Mutational Effects and Population Dynamics During Viral Adaptation Challenge Current Models

PubMed Central

Miller, Craig R.; Joyce, Paul; Wichman, Holly A.

2011-01-01

Adaptation in haploid organisms has been extensively modeled but little tested. Using a microvirid bacteriophage (ID11), we conducted serial passage adaptations at two bottleneck sizes (104 and 106), followed by fitness assays and whole-genome sequencing of 631 individual isolates. Extensive genetic variation was observed including 22 beneficial, several nearly neutral, and several deleterious mutations. In the three large bottleneck lines, up to eight different haplotypes were observed in samples of 23 genomes from the final time point. The small bottleneck lines were less diverse. The small bottleneck lines appeared to operate near the transition between isolated selective sweeps and conditions of complex dynamics (e.g., clonal interference). The large bottleneck lines exhibited extensive interference and less stochasticity, with multiple beneficial mutations establishing on a variety of backgrounds. Several leapfrog events occurred. The distribution of first-step adaptive mutations differed significantly from the distribution of second-steps, and a surprisingly large number of second-step beneficial mutations were observed on a highly fit first-step background. Furthermore, few first-step mutations appeared as second-steps and second-steps had substantially smaller selection coefficients. Collectively, the results indicate that the fitness landscape falls between the extremes of smooth and fully uncorrelated, violating the assumptions of many current mutational landscape models. PMID:21041559

Adaptation and visual salience

PubMed Central

McDermott, Kyle C.; Malkoc, Gokhan; Mulligan, Jeffrey B.; Webster, Michael A.

2011-01-01

We examined how the salience of color is affected by adaptation to different color distributions. Observers searched for a color target on a dense background of distractors varying along different directions in color space. Prior adaptation to the backgrounds enhanced search on the same background while adaptation to orthogonal background directions slowed detection. Advantages of adaptation were seen for both contrast adaptation (to different color axes) and chromatic adaptation (to different mean chromaticities). Control experiments, including analyses of eye movements during the search, suggest that these aftereffects are unlikely to reflect simple learning or changes in search strategies on familiar backgrounds, and instead result from how adaptation alters the relative salience of the target and background colors. Comparable effects were observed along different axes in the chromatic plane or for axes defined by different combinations of luminance and chromatic contrast, consistent with visual search and adaptation mediated by multiple color mechanisms. Similar effects also occurred for color distributions characteristic of natural environments with strongly selective color gamuts. Our results are consistent with the hypothesis that adaptation may play an important functional role in highlighting the salience of novel stimuli by discounting ambient properties of the visual environment. PMID:21106682

Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations

PubMed Central

Good, Benjamin H.; Rouzine, Igor M.; Balick, Daniel J.; Hallatschek, Oskar; Desai, Michael M.

2012-01-01

When large asexual populations adapt, competition between simultaneously segregating mutations slows the rate of adaptation and restricts the set of mutations that eventually fix. This phenomenon of interference arises from competition between mutations of different strengths as well as competition between mutations that arise on different fitness backgrounds. Previous work has explored each of these effects in isolation, but the way they combine to influence the dynamics of adaptation remains largely unknown. Here, we describe a theoretical model to treat both aspects of interference in large populations. We calculate the rate of adaptation and the distribution of fixed mutational effects accumulated by the population. We focus particular attention on the case when the effects of beneficial mutations are exponentially distributed, as well as on a more general class of exponential-like distributions. In both cases, we show that the rate of adaptation and the influence of genetic background on the fixation of new mutants is equivalent to an effective model with a single selection coefficient and rescaled mutation rate, and we explicitly calculate these effective parameters. We find that the effective selection coefficient exactly coincides with the most common fixed mutational effect. This equivalence leads to an intuitive picture of the relative importance of different types of interference effects, which can shift dramatically as a function of the population size, mutation rate, and the underlying distribution of fitness effects. PMID:22371564

Teaching Service Modelling to a Mixed Class: An Integrated Approach

ERIC Educational Resources Information Center

Deng, Jeremiah D.; Purvis, Martin K.

2015-01-01

Service modelling has become an increasingly important area in today's telecommunications and information systems practice. We have adapted a Network Design course in order to teach service modelling to a mixed class of both the telecommunication engineering and information systems backgrounds. An integrated approach engaging mathematics teaching…

Optimal Appearance Model for Visual Tracking

PubMed Central

Wang, Yuru; Jiang, Longkui; Liu, Qiaoyuan; Yin, Minghao

2016-01-01

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models. PMID:26789639

Human Lung Cancer Risks from Radon – Part II – Influence from Combined Adaptive Response and Bystander Effects – A Microdose Analysis

PubMed Central

Leonard, Bobby E.; Thompson, Richard E.; Beecher, Georgia C.

2010-01-01

In the prior Part I, the potential influence of the low level alpha radiation induced bystander effect (BE) on human lung cancer risks was examined. Recent analysis of adaptive response (AR) research results with a Microdose Model has shown that single low LET radiation induced charged particles traversals through the cell nucleus activates AR. We have here conducted an analysis based on what is presently known about adaptive response and the bystander effect (BE) and what new research is needed that can assist in the further evaluation human cancer risks from radon. We find that, at the UNSCEAR (2000) worldwide average human exposures from natural background and man-made radiations, the human lung receives about a 25% adaptive response protection against the radon alpha bystander damage. At the UNSCEAR (2000) minimum range of background exposure levels, the lung receives minimal AR protection but at higher background levels, in the high UNSCEAR (2000) range, the lung receives essentially 100% protection from both the radon alpha damage and also the endogenic, spontaneously occurring, potentially carcinogenic, lung cellular damage. PMID:22461760

Ground-states for the liquid drop and TFDW models with long-range attraction

NASA Astrophysics Data System (ADS)

Alama, Stan; Bronsard, Lia; Choksi, Rustum; Topaloglu, Ihsan

2017-10-01

We prove that both the liquid drop model in R 3 with an attractive background nucleus and the Thomas-Fermi-Dirac-von Weizsäcker (TFDW) model attain their ground-states for all masses as long as the external potential V(x) in these models is of long range, that is, it decays slower than Newtonian (e.g., V ( x ) ≫ | x | - 1 for large |x|.) For the TFDW model, we adapt classical concentration-compactness arguments by Lions, whereas for the liquid drop model with background attraction, we utilize a recent compactness result for sets of finite perimeter by Frank and Lieb.

Human dimension in scientific models in high-mountain climate change and risk projects: Peruvian-Swiss experiences

NASA Astrophysics Data System (ADS)

Vicuña, Luis; Jurt, Christine; Minan, Fiorella; Huggel, Christian

2014-05-01

Models in a range of scientific disciplines are increasingly seen as indispensable for successful adaptation. Governments as well as international organizations and cooperations put their efforts in basing their adaptation projects on scientific results. Thereby, it is critical that scientific models are first put into the particular context in which they will be applied. This paper addresses the experience of the project 'Glaciers 513- Climate change adaptation and disaster risk management for glacier retreat in the Andes' conducted in the districts of Carhuaz (Ancash region) and Santa Teresa (Cusco region) in Peru. The Peruvian and the Swiss governments put their joint efforts in an adaptation project in the context of climate change and the retreat of the glaciers. The project is led by a consortium of Care Peru and the University of Zurich with additional Swiss partners and its principal aim is to improve the capacity for integral adaptation and reduce the risk of disasters from glaciers and high-mountain areas, and effects of climate change, particularly in the regions of Cusco and Ancash. The paper shows how the so called "human dimension" on the one hand, and models from a range of disciplines, including climatology, glaciology, and hydrology on the other hand, were conceptualized and perceived by the different actors involved in the project. Important aspects have been, among others, the role of local knowledge including ancestral knowledge, demographic information, socio-economic indicators as well as the social, political and cultural framework and the historical background. Here we analyze the role and context of local knowledge and the historical background. The analysis of the implications of the differences and similarities of the perceptions of a range of actors contributes to the discussion about how, and to what extent scientific models can be contextualized, what kind of information can be helpful for the contextualization and how it can be obtained. The results, thus, should contribute to more concerted, locally based and accepted risk and adaptation measures.

Equivalent background speed in recovery from motion adaptation.

PubMed

Simpson, W A; Newman, A; Aasland, W

1997-01-01

We measured, in the same observers, (1) the detectability, d, of a small rotational jump following adaptation to rotational motion and (2) the detectability of the same jump when superimposed on one of several background rotation speeds. Following 90 s of motion adaptation the detectability of the jump was impaired, and sensitivity slowly recovered over the course of 60 s. The detectability of the jump was also impaired by the background speed in a way consistent with a quadratic form of Weber's law. We propose that motion adaptation impairs the detectability of the small jump because it is as if an equivalent background speed has been superimposed on the display. We measured the equivalent background by finding the real background speed that produced the same d' at each instant in the recovery from motion adaptation. The equivalent background started at approximately one to two thirds the speed of the adapting motion, declined rapidly, rose to a small peak at 30 s, then disappeared by 60 s. Since the equivalent background speed corresponds to the speed of the motion aftereffect, we have measured the time course of the motion aftereffect with objective psychophysics.

Using an Adaptive Expertise Lens to Understand the Quality of Teachers' Classroom Implementation of Computer-Supported Complex Systems Curricula in High School Science

ERIC Educational Resources Information Center

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-01-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to…

Reconfigurable Control Design with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

The viewgraphs present background information about reconfiguration control design, design methods used for paper, control failure survivability results, and results and time histories of tests. Topics examined include control reconfiguration, general information about adaptive controllers, model reference adaptive control (MRAC), the utility of neural networks, radial basis functions (RBF) neural network outputs, neurons, and results of investigations of failures.

Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model

PubMed Central

Joh, Ju Youn; Kim, Sun; Park, Jun Li

2013-01-01

Background The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. Methods We used the data from 398 adolescent participants who were in middle school. A self-reported questionnaire was used to evaluate the FACES III and Youth Self Report. Results According to the level of family adaptability, significant differences were evident in internalizing problems (P = 0.014). But, in externalizing problems, the results were not significant (P = 0.305). Also, according to the level of family cohesion, significant differences were in internalizing problems (P = 0.002) and externalizing problems (P = 0.004). Conclusion The relationship between the dimensions of adaptability, cohesion and adolescent problem behaviors was not curvilinear. In other words, adolescents with high adaptability and high cohesion showed low problem behaviors. PMID:23730484

Influence of background size, luminance and eccentricity on different adaptation mechanisms

PubMed Central

Gloriani, Alejandro H.; Matesanz, Beatriz M.; Barrionuevo, Pablo A.; Arranz, Isabel; Issolio, Luis; Mar, Santiago; Aparicio, Juan A.

2016-01-01

Mechanisms of light adaptation have been traditionally explained with reference to psychophysical experimentation. However, the neural substrata involved in those mechanisms remain to be elucidated. Our study analyzed links between psychophysical measurements and retinal physiological evidence with consideration for the phenomena of rod-cone interactions, photon noise, and spatial summation. Threshold test luminances were obtained with steady background fields at mesopic and photopic light levels (i.e., 0.06–110 cd/m2) for retinal eccentricities from 0° to 15° using three combinations of background/test field sizes (i.e., 10°/2°, 10°/0.45°, and 1°/0.45°). A two-channel Maxwellian view optical system was employed to eliminate pupil effects on the measured thresholds. A model based on visual mechanisms that were described in the literature was optimized to fit the measured luminance thresholds in all experimental conditions. Our results can be described by a combination of visual mechanisms. We determined how spatial summation changed with eccentricity and how subtractive adaptation changed with eccentricity and background field size. According to our model, photon noise plays a significant role to explain contrast detection thresholds measured with the 1/0.45° background/test size combination at mesopic luminances and at off-axis eccentricities. In these conditions, our data reflect the presence of rod-cone interaction for eccentricities between 6° and 9° and luminances between 0.6 and 5 cd/m2. In spite of the increasing noise effects with eccentricity, results also show that the visual system tends to maintain a constant signal-to-noise ratio in the off-axis detection task over the whole mesopic range. PMID:27210038

Influence of background size, luminance and eccentricity on different adaptation mechanisms.

PubMed

Gloriani, Alejandro H; Matesanz, Beatriz M; Barrionuevo, Pablo A; Arranz, Isabel; Issolio, Luis; Mar, Santiago; Aparicio, Juan A

2016-08-01

Mechanisms of light adaptation have been traditionally explained with reference to psychophysical experimentation. However, the neural substrata involved in those mechanisms remain to be elucidated. Our study analyzed links between psychophysical measurements and retinal physiological evidence with consideration for the phenomena of rod-cone interactions, photon noise, and spatial summation. Threshold test luminances were obtained with steady background fields at mesopic and photopic light levels (i.e., 0.06-110cd/m(2)) for retinal eccentricities from 0° to 15° using three combinations of background/test field sizes (i.e., 10°/2°, 10°/0.45°, and 1°/0.45°). A two-channel Maxwellian view optical system was employed to eliminate pupil effects on the measured thresholds. A model based on visual mechanisms that were described in the literature was optimized to fit the measured luminance thresholds in all experimental conditions. Our results can be described by a combination of visual mechanisms. We determined how spatial summation changed with eccentricity and how subtractive adaptation changed with eccentricity and background field size. According to our model, photon noise plays a significant role to explain contrast detection thresholds measured with the 1/0.45° background/test size combination at mesopic luminances and at off-axis eccentricities. In these conditions, our data reflect the presence of rod-cone interaction for eccentricities between 6° and 9° and luminances between 0.6 and 5cd/m(2). In spite of the increasing noise effects with eccentricity, results also show that the visual system tends to maintain a constant signal-to-noise ratio in the off-axis detection task over the whole mesopic range. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adapting the Individual Placement and Support Model with Homeless Young Adults

ERIC Educational Resources Information Center

Ferguson, Kristin M.; Xie, Bin; Glynn, Shirley

2012-01-01

Background: Prior research reveals high unemployment rates among homeless young adults. The literature offers many examples of using evidence-based supported employment models with vulnerable populations to assist them in obtaining and maintaining competitive employment; yet few examples exist to date with homeless young adults with mental…

3-C Models Teaching Tools to Promote Social Justice

ERIC Educational Resources Information Center

Marbley, Aretha Faye; Rouson, Leon; Burley, Hansel; Ross, Wendy; Bonner, Fred A., II; Lértora, Ian; Huang, Shih-Han

2017-01-01

Equipping future professionals and educators with critical global multicultural competences and skills to work with people from diverse backgrounds is a challenge for both predominantly White institutions (PWIs) and Historically Black Colleges and Universities (HBCUs). The major objective of this article is to introduce an adaptable model with an…

Problem-Based Learning: Modifying the Medical School Model for Teaching High School Economics.

ERIC Educational Resources Information Center

Maxwell, Nan L.; Bellisimo, Yolanda; Mergendoller, John

2001-01-01

Provides background information on the problem-based learning (PBL) model used in medical education that was adapted for high school economics. Describes the high school economics curriculum and outline the stages of the PBL model using examples from a unit called "The High School Food Court." Discusses the design considerations. (CMK)

Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery

PubMed Central

Taravat, Alireza; Oppelt, Natascha

2014-01-01

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376

Dissipation function and adaptive gradient reconstruction based smoke detection in video

NASA Astrophysics Data System (ADS)

Li, Bin; Zhang, Qiang; Shi, Chunlei

2017-11-01

A method for smoke detection in video is proposed. The camera monitoring the scene is assumed to be stationary. With the atmospheric scattering model, dissipation function is reflected transmissivity between the background objects in the scene and the camera. Dark channel prior and fast bilateral filter are used for estimating dissipation function which is only the function of the depth of field. Based on dissipation function, visual background extractor (ViBe) can be used for detecting smoke as a result of smoke's motion characteristics as well as detecting other moving targets. Since smoke has semi-transparent parts, the things which are covered by these parts can be recovered by poisson equation adaptively. The similarity between the recovered parts and the original background parts in the same position is calculated by Normalized Cross Correlation (NCC) and the original background's value is selected from the frame which is nearest to the current frame. The parts with high similarity are considered as smoke parts.

Stroke-model-based character extraction from gray-level document images.

PubMed

Ye, X; Cheriet, M; Suen, C Y

2001-01-01

Global gray-level thresholding techniques such as Otsu's method, and local gray-level thresholding techniques such as edge-based segmentation or the adaptive thresholding method are powerful in extracting character objects from simple or slowly varying backgrounds. However, they are found to be insufficient when the backgrounds include sharply varying contours or fonts in different sizes. A stroke-model is proposed to depict the local features of character objects as double-edges in a predefined size. This model enables us to detect thin connected components selectively, while ignoring relatively large backgrounds that appear complex. Meanwhile, since the stroke width restriction is fully factored in, the proposed technique can be used to extract characters in predefined font sizes. To process large volumes of documents efficiently, a hybrid method is proposed for character extraction from various backgrounds. Using the measurement of class separability to differentiate images with simple backgrounds from those with complex backgrounds, the hybrid method can process documents with different backgrounds by applying the appropriate methods. Experiments on extracting handwriting from a check image, as well as machine-printed characters from scene images demonstrate the effectiveness of the proposed model.

Saccade adaptation goes for the goal

PubMed Central

Madelain, Laurent; Herman, James P.; Harwood, Mark R.

2013-01-01

The oculomotor system maintains saccade accuracy by adjusting saccades that are consistently inaccurate. Four experiments were performed to determine the relative contribution of background and target postsaccadic displacement. Unlike typical saccade adaptation experiments, we used natural image scenes and masked target and background displacements during the saccade to exclude motion signals from allowing detection of the displacements. We found that the background had no effect on saccade gain while the target drove gain changes. Only when the target was blanked after the saccade did we observe some adaptation in the direction of the background displacement. We conclude that target selection is critical to saccade adaptation, and operates effectively against natural image backgrounds. PMID:23492925

Infrared dim small target segmentation method based on ALI-PCNN model

NASA Astrophysics Data System (ADS)

Zhao, Shangnan; Song, Yong; Zhao, Yufei; Li, Yun; Li, Xu; Jiang, Yurong; Li, Lin

2017-10-01

Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.

Man-Machine Communication in Remote Manipulation: Task-Oriented Supervisory Command Language (TOSC).

DTIC Science & Technology

1980-03-01

ORIENTED SUPERVISORY CONTROL SYSTEM METHODOLOGY 3-1 3.1 Overview 3-1 3.2 Background 3-3 3.2.1 General 3-3 3.2.2 Preliminary Principles of Command Language...Design 3-4 3.2.3 Preliminary Principles of Feedback Display Design 3-9 3.3 Man-Machine Communication Models 3-12 3.3.1 Background 3-12 3.3.2 Adapted...and feedback mode. The work ends with the presentation of a performance prediction model and a set of principles and guidelines, applicable to the

Alertness function of thalamus in conflict adaptation.

PubMed

Wang, Xiangpeng; Zhao, Xiaoyue; Xue, Gui; Chen, Antao

2016-05-15

Conflict adaptation reflects the ability to improve current conflict resolution based on previously experienced conflict, which is crucial for our goal-directed behaviors. In recent years, the roles of alertness are attracting increasing attention when discussing the generation of conflict adaptation. However, due to the difficulty of manipulating alertness, very limited progress has been made in this line. Inspired by that color may affect alertness, we manipulated background color of experimental task and found that conflict adaptation significantly presented in gray and red backgrounds but did not in blue background. Furthermore, behavioral and functional magnetic resonance imaging results revealed that the modulation of color on conflict adaptation was implemented through changing alertness level. In particular, blue background eliminated conflict adaptation by damping the alertness regulating function of thalamus and the functional connectivity between thalamus and inferior frontal gyrus (IFG). In contrast, in gray and red backgrounds where alertness levels are typically high, the thalamus and the right IFG functioned normally and conflict adaptations were significant. Therefore, the alertness function of thalamus is determinant to conflict adaptation, and thalamus and right IFG are crucial nodes of the neural circuit subserving this ability. Present findings provide new insights into the neural mechanisms of conflict adaptation. Copyright © 2016 Elsevier Inc. All rights reserved.

The company they keep: Background similarity influences transfer of aftereffects from second- to first-order stimuli

PubMed Central

Qian, Ning; Dayan, Peter

2013-01-01

A wealth of studies has found that adapting to second-order visual stimuli has little effect on the perception of first-order stimuli. This is physiologically and psychologically troubling, since many cells show similar tuning to both classes of stimuli, and since adapting to first-order stimuli leads to aftereffects that do generalize to second-order stimuli. Focusing on high-level visual stimuli, we recently proposed the novel explanation that the lack of transfer arises partially from the characteristically different backgrounds of the two stimulus classes. Here, we consider the effect of stimulus backgrounds in the far more prevalent, lower-level, case of the orientation tilt aftereffect. Using a variety of first- and second-order oriented stimuli, we show that we could increase or decrease both within- and cross-class adaptation aftereffects by increasing or decreasing the similarity of the otherwise apparently uninteresting or irrelevant backgrounds of adapting and test patterns. Our results suggest that similarity between background statistics of the adapting and test stimuli contributes to low-level visual adaptation, and that these backgrounds are thus not discarded by visual processing but provide contextual modulation of adaptation. Null cross-adaptation aftereffects must also be interpreted cautiously. These findings reduce the apparent inconsistency between psychophysical and neurophysiological data about first- and second-order stimuli. PMID:23732217

A hand tracking algorithm with particle filter and improved GVF snake model

NASA Astrophysics Data System (ADS)

Sun, Yi-qi; Wu, Ai-guo; Dong, Na; Shao, Yi-zhe

2017-07-01

To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion.

Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection

USGS Publications Warehouse

Jarnevich, Catherine S.; Talbert, Marian; Morisette, Jeffrey T.; Aldridge, Cameron L.; Brown, Cynthia; Kumar, Sunil; Manier, Daniel; Talbert, Colin; Holcombe, Tracy R.

2017-01-01

Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pseudo-absence locations, and method choice affects model outcomes. We evaluated combinations of both model algorithms (simple and complex generalized linear models, multivariate adaptive regression splines, Maxent, boosted regression trees, and random forest) and background methods (random, minimum convex polygon, and continuous and binary kernel density estimator (KDE)) to assess the sensitivity of model outcomes to choices made. We evaluated six questions related to model results, including five beyond the common comparison of model accuracy assessment metrics (biological interpretability of response curves, cross-validation robustness, independent data accuracy and robustness, and prediction consistency). For our case study with cheatgrass in the western US, random forest was least sensitive to background choice and the binary KDE method was least sensitive to model algorithm choice. While this outcome may not hold for other locations or species, the methods we used can be implemented to help determine appropriate methodologies for particular research questions.

Detecting consistent patterns of directional adaptation using differential selection codon models.

PubMed

Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

Asynchronous adaptive time step in quantitative cellular automata modeling

PubMed Central

Zhu, Hao; Pang, Peter YH; Sun, Yan; Dhar, Pawan

2004-01-01

Background The behaviors of cells in metazoans are context dependent, thus large-scale multi-cellular modeling is often necessary, for which cellular automata are natural candidates. Two related issues are involved in cellular automata based multi-cellular modeling: how to introduce differential equation based quantitative computing to precisely describe cellular activity, and upon it, how to solve the heavy time consumption issue in simulation. Results Based on a modified, language based cellular automata system we extended that allows ordinary differential equations in models, we introduce a method implementing asynchronous adaptive time step in simulation that can considerably improve efficiency yet without a significant sacrifice of accuracy. An average speedup rate of 4–5 is achieved in the given example. Conclusions Strategies for reducing time consumption in simulation are indispensable for large-scale, quantitative multi-cellular models, because even a small 100 × 100 × 100 tissue slab contains one million cells. Distributed and adaptive time step is a practical solution in cellular automata environment. PMID:15222901

Studying Implementation within a Continuous Continuous-Improvement Process: What Happens When We Design with Adaptations in Mind?

ERIC Educational Resources Information Center

Tichnor-Wagner, Ariel; Allen, Danielle; Socol, Allison Rose; Cohen-Vogel, Lora; Rutledge, Stacey A.; Xing, Qi W.

2018-01-01

Background/Context: This study examines the implementation of an academic and social-emotional learning innovation called Personalization for Academic and Social-Emotional Learning, or PASL. The innovation was designed, tested, and implemented using a continuous continuous-improvement model. The model emphasized a top-and-bottom process in which…

BgCut: automatic ship detection from UAV images.

PubMed

Xu, Chao; Zhang, Dongping; Zhang, Zhengning; Feng, Zhiyong

2014-01-01

Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches.

Catheter tracking via online learning for dynamic motion compensation in transcatheter aortic valve implantation.

PubMed

Wang, Peng; Zheng, Yefeng; John, Matthias; Comaniciu, Dorin

2012-01-01

Dynamic overlay of 3D models onto 2D X-ray images has important applications in image guided interventions. In this paper, we present a novel catheter tracking for motion compensation in the Transcatheter Aortic Valve Implantation (TAVI). To address such challenges as catheter shape and appearance changes, occlusions, and distractions from cluttered backgrounds, we present an adaptive linear discriminant learning method to build a measurement model online to distinguish catheters from background. An analytic solution is developed to effectively and efficiently update the discriminant model and to minimize the classification errors between the tracking object and backgrounds. The online learned discriminant model is further combined with an offline learned detector and robust template matching in a Bayesian tracking framework. Quantitative evaluations demonstrate the advantages of this method over current state-of-the-art tracking methods in tracking catheters for clinical applications.

BgCut: Automatic Ship Detection from UAV Images

PubMed Central

Zhang, Zhengning; Feng, Zhiyong

2014-01-01

Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches. PMID:24977182

TIMSS 2011 User Guide for the International Database. Supplement 2: National Adaptations of International Background Questionnaires

ERIC Educational Resources Information Center

Foy, Pierre, Ed.; Arora, Alka, Ed.; Stanco, Gabrielle M., Ed.

2013-01-01

This supplement describes national adaptations made to the international version of the TIMSS 2011 background questionnaires. This information provides users with a guide to evaluate the availability of internationally comparable data for use in secondary analyses involving the TIMSS 2011 background variables. Background questionnaire adaptations…

Lessons learned: Optimization of a murine small bowel resection model

PubMed Central

Taylor, Janice A.; Martin, Colin A.; Nair, Rajalakshmi; Guo, Jun; Erwin, Christopher R.; Warner, Brad W.

2008-01-01

Background/Purpose Central to the use of murine models of disease is the ability to derive reproducible data. The purpose of this study was to determine factors contributing to variability in our murine model of small bowel resection (SBR). Methods Male C57Bl/6 mice were randomized to sham or 50% SBR. The effect of housing type (pathogen-free versus standard housing), nutrition (reconstituted powder versus tube feeding formulation), and correlates of intestinal morphology with gene expression changes were investigated Multiple linear regression modeling or one-way ANOVA was used for data analysis. Results Pathogen-free mice had significantly shorter ileal villi at baseline and demonstrated greater villus growth after SBR compared to mice housed in standard rooms. Food type did not affect adaptation. Gene expression changes were more consistent and significant in isolated crypt cells that demonstrated adaptive growth when compared with crypts that did not deepen after SBR. Conclusion Maintenance of mice in pathogen-free conditions and restricting gene expression analysis to individual animals exhibiting morphologic adaptation enhances sensitivity and specificity of data derived from this model. These refinements will minimize experimental variability and lead to improved understanding of the complex process of intestinal adaptation. PMID:18558176

Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

2012-01-01

Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

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.

ViBe: a universal background subtraction algorithm for video sequences.

PubMed

Barnich, Olivier; Van Droogenbroeck, Marc

2011-06-01

This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. Finally, when the pixel is found to be part of the background, its value is propagated into the background model of a neighboring pixel. We describe our method in full details (including pseudo-code and the parameter values used) and compare it to other background subtraction techniques. Efficiency figures show that our method outperforms recent and proven state-of-the-art methods in terms of both computation speed and detection rate. We also analyze the performance of a downscaled version of our algorithm to the absolute minimum of one comparison and one byte of memory per pixel. It appears that even such a simplified version of our algorithm performs better than mainstream techniques.

Childhood Personality Types: Vulnerability and Adaptation over Time

ERIC Educational Resources Information Center

De Clercq, Barbara; Rettew, David; Althoff, Robert R.; De Bolle, Marleen

2012-01-01

Background: Substantial evidence suggests that a Five-Factor Model personality assessment generates a valid description of childhood individual differences and relates to a range of psychological outcomes. Less is known, however, about naturally occurring profiles of personality and their links to psychopathology. The current study explores…

Patterns of coral bleaching: Modeling the adaptive bleaching hypothesis

USGS Publications Warehouse

Ware, J.R.; Fautin, D.G.; Buddemeier, R.W.

1996-01-01

Bleaching - the loss of symbiotic dinoflagellates (zooxanthellae) from animals normally possessing them - can be induced by a variety of stresses, of which temperature has received the most attention. Bleaching is generally considered detrimental, but Buddemeier and Fautin have proposed that bleaching is also adaptive, providing an opportunity for recombining hosts with alternative algal types to form symbioses that might be better adapted to altered circumstances. Our mathematical model of this "adaptive bleaching hypothesis" provides insight into how animal-algae symbioses might react under various circumstances. It emulates many aspects of the coral bleaching phenomenon including: corals bleaching in response to a temperature only slightly greater than their average local maximum temperature; background bleaching; bleaching events being followed by bleaching of lesser magnitude in the subsequent one to several years; higher thermal tolerance of corals subject to environmental variability compared with those living under more constant conditions; patchiness in bleaching; and bleaching at temperatures that had not previously resulted in bleaching. ?? 1996 Elsevier Science B.V. All rights reserved.

Revealing the selection history of adaptive loci using genome-wide scans for selection: an example from domestic sheep.

PubMed

Rochus, Christina Marie; Tortereau, Flavie; Plisson-Petit, Florence; Restoux, Gwendal; Moreno-Romieux, Carole; Tosser-Klopp, Gwenola; Servin, Bertrand

2018-01-23

One of the approaches to detect genetics variants affecting fitness traits is to identify their surrounding genomic signatures of past selection. With established methods for detecting selection signatures and the current and future availability of large datasets, such studies should have the power to not only detect these signatures but also to infer their selective histories. Domesticated animals offer a powerful model for these approaches as they adapted rapidly to environmental and human-mediated constraints in a relatively short time. We investigated this question by studying a large dataset of 542 individuals from 27 domestic sheep populations raised in France, genotyped for more than 500,000 SNPs. Population structure analysis revealed that this set of populations harbour a large part of European sheep diversity in a small geographical area, offering a powerful model for the study of adaptation. Identification of extreme SNP and haplotype frequency differences between populations listed 126 genomic regions likely affected by selection. These signatures revealed selection at loci commonly identified as selection targets in many species ("selection hotspots") including ABCG2, LCORL/NCAPG, MSTN, and coat colour genes such as ASIP, MC1R, MITF, and TYRP1. For one of these regions (ABCG2, LCORL/NCAPG), we could propose a historical scenario leading to the introgression of an adaptive allele into a new genetic background. Among selection signatures, we found clear evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. We confirmed this allelic heterogeneity in one case by resequencing the MC1R gene in three black-faced breeds. Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations.

One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

PubMed

Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

2016-05-10

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

Nyx: Adaptive mesh, massively-parallel, cosmological simulation code

NASA Astrophysics Data System (ADS)

Almgren, Ann; Beckner, Vince; Friesen, Brian; Lukic, Zarija; Zhang, Weiqun

2017-12-01

Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx use a finite volume methodology on an adaptive set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics for accurately modeling the intergalactic medium; in optically thin limits and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field.

Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load.

PubMed

Holper, L; Van Brussel, L D; Schmidt, L; Schulthess, S; Burke, C J; Louie, K; Seifritz, E; Tobler, P N

2017-01-01

Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values. Adaptive value coding typically relies on contextual information either obtained from the environment or retrieved from and maintained in memory. However, it is unknown whether having to retrieve and maintain context information modulates the brain's capacity for value adaptation. To address this issue, we measured hemodynamic responses of the prefrontal cortex (PFC) in two studies on risky decision-making. In each trial, healthy human subjects chose between a risky and a safe alternative; half of the participants had to remember the risky alternatives, whereas for the other half they were presented visually. The value of safe alternatives varied across trials. PFC responses adapted to contextual risk information, with steeper coding of safe alternative value in lower-risk contexts. Importantly, this adaptation depended on working memory load, such that response functions relating PFC activity to safe values were steeper with presented versus remembered risk. An independent second study replicated the findings of the first study and showed that similar slope reductions also arose when memory maintenance demands were increased with a secondary working memory task. Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and revealed that reduced suppression of background activity was the critical parameter impairing normalization with increased memory maintenance demand. Our findings suggest that mnemonic processes can constrain normalization of neural value representations.

Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

PubMed

Gao, Jingli; Wen, Chenglin; Liu, Meiqin

2017-09-29

In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

Development of adaptive observation strategy using retrospective optimal interpolation

NASA Astrophysics Data System (ADS)

Noh, N.; Kim, S.; Song, H.; Lim, G.

2011-12-01

Retrospective optimal interpolation (ROI) is a method that is used to minimize cost functions with multiple minima without using adjoint models. Song and Lim (2011) perform the experiments to reduce the computational costs for implementing ROI by transforming the control variables into eigenvectors of background error covariance. We adapt the ROI algorithm to compute sensitivity estimates of severe weather events over the Korean peninsula. The eigenvectors of the ROI algorithm is modified every time the observations are assimilated. This implies that the modified eigenvectors shows the error distribution of control variables which are updated by assimilating observations. So, We can estimate the effects of the specific observations. In order to verify the adaptive observation strategy, High-impact weather over the Korean peninsula is simulated and interpreted using WRF modeling system and sensitive regions for each high-impact weather is calculated. The effects of assimilation for each observation type is discussed.

Use of the EFPA Test Review Model by the UK and Issues Relating to the Internationalization of Test Standards

ERIC Educational Resources Information Center

Lindley, Patricia A.; Bartram, Dave

2012-01-01

In this article, we present the background to the development of test reviewing by the British Psychological Society (BPS) in the United Kingdom. We also describe the role played by the BPS in the development of the EFPA test review model and its adaptation for use in test reviewing in the United Kingdom. We conclude with a discussion of lessons…

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation.

PubMed

Lande, Russell

2009-07-01

Adaptation to a sudden extreme change in environment, beyond the usual range of background environmental fluctuations, is analysed using a quantitative genetic model of phenotypic plasticity. Generations are discrete, with time lag tau between a critical period for environmental influence on individual development and natural selection on adult phenotypes. The optimum phenotype, and genotypic norms of reaction, are linear functions of the environment. Reaction norm elevation and slope (plasticity) vary among genotypes. Initially, in the average background environment, the character is canalized with minimum genetic and phenotypic variance, and no correlation between reaction norm elevation and slope. The optimal plasticity is proportional to the predictability of environmental fluctuations over time lag tau. During the first generation in the new environment the mean fitness suddenly drops and the mean phenotype jumps towards the new optimum phenotype by plasticity. Subsequent adaptation occurs in two phases. Rapid evolution of increased plasticity allows the mean phenotype to closely approach the new optimum. The new phenotype then undergoes slow genetic assimilation, with reduction in plasticity compensated by genetic evolution of reaction norm elevation in the original environment.

Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model

PubMed Central

Neidhart, Johannes; Szendro, Ivan G.; Krug, Joachim

2014-01-01

Much of the current theory of adaptation is based on Gillespie’s mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage. PMID:25123507

Adaptive finite element modelling of three-dimensional magnetotelluric fields in general anisotropic media

NASA Astrophysics Data System (ADS)

Liu, Ying; Xu, Zhenhuan; Li, Yuguo

2018-04-01

We present a goal-oriented adaptive finite element (FE) modelling algorithm for 3-D magnetotelluric fields in generally anisotropic conductivity media. The model consists of a background layered structure, containing anisotropic blocks. Each block and layer might be anisotropic by assigning to them 3 × 3 conductivity tensors. The second-order partial differential equations are solved using the adaptive finite element method (FEM). The computational domain is subdivided into unstructured tetrahedral elements, which allow for complex geometries including bathymetry and dipping interfaces. The grid refinement process is guided by a global posteriori error estimator and is performed iteratively. The system of linear FE equations for electric field E is solved with a direct solver MUMPS. Then the magnetic field H can be found, in which the required derivatives are computed numerically using cubic spline interpolation. The 3-D FE algorithm has been validated by comparisons with both the 3-D finite-difference solution and 2-D FE results. Two model types are used to demonstrate the effects of anisotropy upon 3-D magnetotelluric responses: horizontal and dipping anisotropy. Finally, a 3D sea hill model is modelled to study the effect of oblique interfaces and the dipping anisotropy.

A Nonlinear Model for Transient Responses from Light-Adapted Wolf Spider Eyes

PubMed Central

DeVoe, Robert D.

1967-01-01

A quantitative model is proposed to test the hypothesis that the dynamics of nonlinearities in retinal action potentials from light-adapted wolf spider eyes may be due to delayed asymmetries in responses of the visual cells. For purposes of calculation, these delayed asymmetries are generated in an analogue by a time-variant resistance. It is first shown that for small incremental stimuli, the linear behavior of such a resistance describes peaking and low frequency phase lead in frequency responses of the eye to sinusoidal modulations of background illumination. It also describes the overshoots in linear step responses. It is next shown that the analogue accounts for nonlinear transient and short term DC responses to large positive and negative step stimuli and for the variations in these responses with changes in degree of light adaptation. Finally, a physiological model is proposed in which the delayed asymmetries in response are attributed to delayed rectification by the visual cell membrane. In this model, cascaded chemical reactions may serve to transduce visual stimuli into membrane resistance changes. PMID:6056011

Constructing Noise-Invariant Representations of Sound in the Auditory Pathway

PubMed Central

Rabinowitz, Neil C.; Willmore, Ben D. B.; King, Andrew J.; Schnupp, Jan W. H.

2013-01-01

Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics. Here we investigated the extent of neuronal adaptation to the mean and contrast of auditory stimulation as one ascends the auditory pathway. We measured these forms of adaptation by presenting complex synthetic and natural sounds, recording neuronal responses in the inferior colliculus and primary fields of the auditory cortex of anaesthetized ferrets, and comparing these responses with a sophisticated model of the auditory nerve. We find that the strength of both forms of adaptation increases as one ascends the auditory pathway. To investigate whether this adaptation to stimulus statistics contributes to the construction of noise-invariant sound representations, we also presented complex, natural sounds embedded in stationary noise, and used a decoding approach to assess the noise tolerance of the neuronal population code. We find that the code for complex sounds in the periphery is affected more by the addition of noise than the cortical code. We also find that noise tolerance is correlated with adaptation to stimulus statistics, so that populations that show the strongest adaptation to stimulus statistics are also the most noise-tolerant. This suggests that the increase in adaptation to sound statistics from auditory nerve to midbrain to cortex is an important stage in the construction of noise-invariant sound representations in the higher auditory brain. PMID:24265596

Multi-disciplinary scientists as global change adaptation anchors: Filling the gaps in the Boundary Organization paradigm

NASA Astrophysics Data System (ADS)

Terando, A. J.; Collazo, J.

2017-12-01

Boundary organizations, entities that facilitate the co-production and translation of scientific research in decision making processes, have been promoted as a means to assist global change adaptation, particularly in the areas of landscape conservation and natural resource management. However, scientists can and often still must perform a similar role and act as anchoring agents within wicked adaptation problems that involve a myriad of actors, values, scientific uncertainties, governance structures, and multidisciplinary research needs. We illustrate one such case study in Puerto Rico's Bosque Modelo (Model Forest) where we discuss an ongoing scientific effort to undertake a multi-objective landscape conservation design project that intersects with the Bosque Modelo geography and goals. Perspectives are provided from two research ecologists, one with a background in terrestrial ecology who has worked at the intersection of science, conservation, and government for over 30 years, and the other with a multi-disciplinary background in earth sciences, climatology, and terrestrial ecology. We frame our discussion around the learning process that accompanies the development of global change scenarios that are both useful and useable for a wide spectrum of scientists, and the likelihood that scientifically informed adaptive management actions will ultimately be implemented in this complex and changing landscape.

Performance evaluation and modeling of a conformal filter (CF) based real-time standoff hazardous material detection sensor

NASA Astrophysics Data System (ADS)

Nelson, Matthew P.; Tazik, Shawna K.; Bangalore, Arjun S.; Treado, Patrick J.; Klem, Ethan; Temple, Dorota

2017-05-01

Hyperspectral imaging (HSI) systems can provide detection and identification of a variety of targets in the presence of complex backgrounds. However, current generation sensors are typically large, costly to field, do not usually operate in real time and have limited sensitivity and specificity. Despite these shortcomings, HSI-based intelligence has proven to be a valuable tool, thus resulting in increased demand for this type of technology. By moving the next generation of HSI technology into a more adaptive configuration, and a smaller and more cost effective form factor, HSI technologies can help maintain a competitive advantage for the U.S. armed forces as well as local, state and federal law enforcement agencies. Operating near the physical limits of HSI system capability is often necessary and very challenging, but is often enabled by rigorous modeling of detection performance. Specific performance envelopes we consistently strive to improve include: operating under low signal to background conditions; at higher and higher frame rates; and under less than ideal motion control scenarios. An adaptable, low cost, low footprint, standoff sensor architecture we have been maturing includes the use of conformal liquid crystal tunable filters (LCTFs). These Conformal Filters (CFs) are electro-optically tunable, multivariate HSI spectrometers that, when combined with Dual Polarization (DP) optics, produce optimized spectral passbands on demand, which can readily be reconfigured, to discriminate targets from complex backgrounds in real-time. With DARPA support, ChemImage Sensor Systems (CISS™) in collaboration with Research Triangle Institute (RTI) International are developing a novel, real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS) based on DP-CF technology. RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses recent test and performance modeling results of a RCIS breadboard apparatus.

Adaptive typography for dynamic mapping environments

NASA Astrophysics Data System (ADS)

Bardon, Didier

1991-08-01

When typography moves across a map, it passes over areas of different colors, densities, and textures. In such a dynamic environment, the aspect of typography must be constantly adapted to provide disernibility for every new background. Adaptive typography undergoes two adaptive operations: background control and contrast control. The background control prevents the features of the map (edges, lines, abrupt changes of densities) from destroying the integrity of the letterform. This is achieved by smoothing the features of the map in the area where a text label is displayed. The modified area is limited to the space covered by the characters of the label. Dispositions are taken to insure that the smoothing operation does not introduce any new visual noise. The contrast control assures that there are sufficient lightness differences between the typography and its ever-changing background. For every new situation, background color and foreground color are compared and the foreground color lightness is adjusted according to a chosen contrast value. Criteria and methods of choosing the appropriate contrast value are presented as well as the experiments that led to them.

How hard they hit? Perception, adaptation and public health implications of heat waves in urban and peri-urban Pakistan.

PubMed

Rauf, Sara; Bakhsh, Khuda; Abbas, Azhar; Hassan, Sarfraz; Ali, Asghar; Kächele, Harald

2017-04-01

Heat waves threaten human health given the fast changing climatic scenarios in the recent past. Adaptation to heat waves would take place when people perceive their impacts based on their knowledge. The present study examines perception level and its determinants resulting in adaptation to heat waves in Pakistan. The study used cross-sectional data from urban and peri-urban respondents of Faisalabad District. The study employs a health belief model to assess risk perception among the respondents. Logistic model is used to determine factors affecting level of knowledge, perception and adaptation to heat waves. Around 30% of peri-urban respondents have a low level of knowledge about the fatal impacts of heat waves. Risk perception of heat waves is very low among urban (57%) and peri-urban (66%) respondents. Households' knowledge on heat waves is significantly related to age, gender, education, wealth and access to health services. Determinants of perception include knowledge of heat waves, age and joint effect of marital status and knowledge while income level, family size, urban/peri-urban background, perceived barriers, perceived benefits and cues to action significantly affect adaptation to heat waves. To reduce deadly health impacts, mass awareness campaigns are needed to build perception and improve adaptation to heat waves.

Discoveries far from the lamppost with matrix elements and ranking

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

Debnath, Dipsikha; Gainer, James S.; Matchev, Konstantin T.

2015-04-01

The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inversemore » of the background distribution.« less

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume

2013-01-01

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load

PubMed Central

Burke, C. J.; Seifritz, E.; Tobler, P. N.

2017-01-01

Abstract Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values. Adaptive value coding typically relies on contextual information either obtained from the environment or retrieved from and maintained in memory. However, it is unknown whether having to retrieve and maintain context information modulates the brain’s capacity for value adaptation. To address this issue, we measured hemodynamic responses of the prefrontal cortex (PFC) in two studies on risky decision-making. In each trial, healthy human subjects chose between a risky and a safe alternative; half of the participants had to remember the risky alternatives, whereas for the other half they were presented visually. The value of safe alternatives varied across trials. PFC responses adapted to contextual risk information, with steeper coding of safe alternative value in lower-risk contexts. Importantly, this adaptation depended on working memory load, such that response functions relating PFC activity to safe values were steeper with presented versus remembered risk. An independent second study replicated the findings of the first study and showed that similar slope reductions also arose when memory maintenance demands were increased with a secondary working memory task. Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and revealed that reduced suppression of background activity was the critical parameter impairing normalization with increased memory maintenance demand. Our findings suggest that mnemonic processes can constrain normalization of neural value representations. PMID:28462394

Adaptive Learning in Smart Cities--The Cases of Catania and Helsinki

ERIC Educational Resources Information Center

Laitinen, Ilpo; Piazza, Roberta; Stenvall, Jari

2017-01-01

Our research is a comparative qualitative study. The material has been gathered from the cities of Helsinki and Catania. The target cities showcase varied successes and models of smart cities. In the cities, key people involved in the smart city concept--with different kinds of professional backgrounds--were interviewed, both individually and in…

Swedish PE Teachers' Understandings of Legitimate Movement in a Criterion-Referenced Grading System

ERIC Educational Resources Information Center

Svennberg, Lena

2017-01-01

Background: Physical Education (PE) has been associated with a multi-activity model in which movement is related to sport discourses and sport techniques. However, as in many international contexts, the Swedish national PE syllabus calls for a wider and more inclusive concept of movement. Complex movement adapted to different settings is valued,…

Multiview road sign detection via self-adaptive color model and shape context matching

NASA Astrophysics Data System (ADS)

Liu, Chunsheng; Chang, Faliang; Liu, Chengyun

2016-09-01

The multiview appearance of road signs in uncontrolled environments has made the detection of road signs a challenging problem in computer vision. We propose a road sign detection method to detect multiview road signs. This method is based on several algorithms, including the classical cascaded detector, the self-adaptive weighted Gaussian color model (SW-Gaussian model), and a shape context matching method. The classical cascaded detector is used to detect the frontal road signs in video sequences and obtain the parameters for the SW-Gaussian model. The proposed SW-Gaussian model combines the two-dimensional Gaussian model and the normalized red channel together, which can largely enhance the contrast between the red signs and background. The proposed shape context matching method can match shapes with big noise, which is utilized to detect road signs in different directions. The experimental results show that compared with previous detection methods, the proposed multiview detection method can reach higher detection rate in detecting signs with different directions.

Effect of the Temperature-Emissivity Contrast on the Chemical Signal for Gas Plume Detection Using Thermal Image Data

PubMed Central

Walsh, Stephen; Chilton, Larry; Tardiff, Mark; Metoyer, Candace

2008-01-01

Detecting and identifying weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based radiance model, which describes at-sensor observed radiance. The background emissivity and plume/ground temperatures are isolated, and their effects on chemical signal are described. This analysis shows that the plume's physical state, emission or absorption, is directly dependent on the background emissivity and plume/ground temperatures. It then describes what conditions on the background emissivity and plume/ground temperatures have inhibiting or amplifying effects on the chemical signal. These claims are illustrated by analyzing synthetic hyperspectral imaging data with the adaptive matched filter using two chemicals and three distinct background emissivities. PMID:27873881

Effect of wine-based marinades on the behavior of Salmonella Typhimurium and background flora in beef fillets.

PubMed

Nisiotou, A; Chorianopoulos, N G; Gounadaki, A; Panagou, E Z; Nychas, G-J E

2013-06-17

The aim of this study was to evaluate the wine-based marinades to control the survival of acid-adapted and non-adapted Salmonella Typhimurium and background flora of fresh beef stored aerobically or under modified atmosphere. Beef slices were inoculated with a 3-strain cocktail of acid-adapted or non-adapted Salmonella Typhimurium strains DT 193, 4/74 and DSM 554 and marinated by immersion in wine (W) or wine supplemented with 0.3% thyme essential oil (WEO), for 12h at 4°C. Marinated slices were then stored under air or modified atmosphere conditions at 5°C. S. Typhimurium and background flora were followed for a 19-day period of storage. S. Typhimurium individual strains were monitored by pulsed field gel electrophoresis. Marination with wine significantly (P<0.05) reduced the background flora compared to the control (non-marinated). Furthermore, immersion of fillets in W or WEO marinades for 12h significantly (P<0.05) reduced the levels of S. Typhimurium compared to the non-marinated (control) samples by 1.1 and 1.4logCFU/g or 2.0 and 1.9logCFU/g for acid-adapted and non-adapted cells, respectively. Acid-adapted cells were more susceptible (P<0.05) to the addition of thyme essential oil in the wine marinade. The epidemic multi-drug resistant DT 193, the 4/74 and DSM 554 strains survived marination (for both W and WEO) and were detected at about similar proportions as revealed by PFGE results. Present results indicate that wine-based marinades are efficient, from a safety and shelf life stand point, in reducing pathogen's levels as well as the background beef flora. Copyright © 2013 Elsevier B.V. All rights reserved.

Adaptive removal of background and white space from document images using seam categorization

NASA Astrophysics Data System (ADS)

Fillion, Claude; Fan, Zhigang; Monga, Vishal

2011-03-01

Document images are obtained regularly by rasterization of document content and as scans of printed documents. Resizing via background and white space removal is often desired for better consumption of these images, whether on displays or in print. While white space and background are easy to identify in images, existing methods such as naïve removal and content aware resizing (seam carving) each have limitations that can lead to undesirable artifacts, such as uneven spacing between lines of text or poor arrangement of content. An adaptive method based on image content is hence needed. In this paper we propose an adaptive method to intelligently remove white space and background content from document images. Document images are different from pictorial images in structure. They typically contain objects (text letters, pictures and graphics) separated by uniform background, which include both white paper space and other uniform color background. Pixels in uniform background regions are excellent candidates for deletion if resizing is required, as they introduce less change in document content and style, compared with deletion of object pixels. We propose a background deletion method that exploits both local and global context. The method aims to retain the document structural information and image quality.

Rinsing paired-agent model (RPAM) to quantify cell-surface receptor concentrations in topical staining applications of thick tissues

NASA Astrophysics Data System (ADS)

Xu, Xiaochun; Wang, Yu; Xiang, Jialing; Liu, Jonathan T. C.; Tichauer, Kenneth M.

2017-06-01

Conventional molecular assessment of tissue through histology, if adapted to fresh thicker samples, has the potential to enhance cancer detection in surgical margins and monitoring of 3D cell culture molecular environments. However, in thicker samples, substantial background staining is common despite repeated rinsing, which can significantly reduce image contrast. Recently, ‘paired-agent’ methods—which employ co-administration of a control (untargeted) imaging agent—have been applied to thick-sample staining applications to account for background staining. To date, these methods have included (1) a simple ratiometric method that is relatively insensitive to noise in the data but has accuracy that is dependent on the staining protocol and the characteristics of the sample; and (2) a complex paired-agent kinetic modeling method that is more accurate but is more noise-sensitive and requires a precise serial rinsing protocol. Here, a new simplified mathematical model—the rinsing paired-agent model (RPAM)—is derived and tested that offers a good balance between the previous models, is adaptable to arbitrary rinsing-imaging protocols, and does not require calibration of the imaging system. RPAM is evaluated against previous models and is validated by comparison to estimated concentrations of targeted biomarkers on the surface of 3D cell culture and tumor xenograft models. This work supports the use of RPAM as a preferable model to quantitatively analyze targeted biomarker concentrations in topically stained thick tissues, as it was found to match the accuracy of the complex paired-agent kinetic model while retaining the low noise-sensitivity characteristics of the ratiometric method.

Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python.

PubMed

Irvine, Michael A; Hollingsworth, T Déirdre

2018-05-26

Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

State Norms for IQ, Adaptive Behavior, and Sociocultural Status: Implications for Nonbiased Assessment.

ERIC Educational Resources Information Center

Reschly, Daniel J.; And Others

Findings from the Iowa Assessment Project are examined regarding the assessment and use of information on adaptive behavior and sociocultural background in decisions about students with mild mental retardation. Background aspects reviewed include terminology regarding mild retardation; research, litigation, and legislation on the topic during the…

Imi Ho'ola: an educational model for disadvantaged students at the University of Hawai''i School of Medicine.

PubMed

Judd, Nanette L K; Sakamoto, Karen K; Hishinuma, Earl S; DeCambra, Chessa; Malate, Agnes R

2007-03-01

This paper describes an educational model that provides opportunities in medicine to students from disadvantaged backgrounds that have a commitment to serve in areas of need, and it presents guidelines on how this model could be adapted to various settings. From 1973 to 2002, the Imi Ho'ola Program (Hawaiian for "Those Who Seek to Heal") of the University of Hawai'i John A. Burns School of Medicine (JABSOM) has provided opportunities in medicine to 379 students from disadvantaged backgrounds. In 1995-1996, Imi Ho'ola underwent a transformation from a pre-medical enrichment program to a post-baccalaureate program that included provisional acceptance and financial support into JABSOM for students who successfully completed the program. As a result, the acceptance rate increased from 47.6% to 98.0%. In addition to provisional acceptance to JABSOM and financial support, the program's educational model incorporates five components, the key factors of the program's success: 1) JABSOM commitment and the institutionalization of the program; 2) emphasis placed on a comprehensive approach and the implementation of a curriculum and learning process that are aligned with JABSOM curricula; 3) faculty and staff who support the instructional methodology and work as a team to address students' needs; 4) assessment of students and systematic feedback regarding individualized education plans and academic and non-academic progress; and 5) a positive learning environment for students. Guidelines are provided in this article for consideration in adapting this educational model to other academic settings.

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster

PubMed Central

Jha, Aashish R.; Miles, Cecelia M.; Lippert, Nodia R.; Brown, Christopher D.; White, Kevin P.; Kreitman, Martin

2015-01-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. PMID:26044351

Course Selection Theory and College Transition Seminars: An Adaptation of College Choice Models to Explain First-Year Students' Course Enrollment Behavior

ERIC Educational Resources Information Center

Graff, Curt Gerard

2011-01-01

This dissertation examines the course-enrollment behavior of first-year students at a public Midwestern university. Using the student choice construct, modern college choice theory, and the constructs of habitus, human capital, financial capital, social capital, cultural capital, along with background variables such as gender and locus of control,…

The "CHARM" Policy Analysis Framework: Evaluation of Policies to Promote Immigrant Students' Resilience. OECD Education Working Papers, No. 158

ERIC Educational Resources Information Center

Bilgili, Özge

2017-01-01

This paper focuses on children with a migration background and conceptualises their migration experience as adversity. The paper adapts the resilience framework to understand how immigrant children can overcome adversity. The paper discusses policy models that can be derived from adopting a resilience approach to the measurement of immigrant…

Assisting a College's Service Area in the Transition to the New Technology Society through Strategic Planning and Management.

ERIC Educational Resources Information Center

Groff, Warren H.

North Central Technical College's (NCTC's) strategic planning and human resource development model is described in this paper in terms of its role in assisting the college's service area in adapting to new technologies. First, background information is presented on NCTC's planning process with respect to the strategic goal areas of: (1)…

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach

PubMed Central

2016-01-01

Background Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach. PMID:26812235

A two-way street: bridging implementation science and cultural adaptations of mental health treatments

PubMed Central

2013-01-01

Background Racial and ethnic disparities in the United States exist along the entire continuum of mental health care, from access and use of services to the quality and outcomes of care. Efforts to address these inequities in mental health care have focused on adapting evidence-based treatments to clients’ diverse cultural backgrounds. Yet, like many evidence-based treatments, culturally adapted interventions remain largely unused in usual care settings. We propose that a viable avenue to address this critical question is to create a dialogue between the fields of implementation science and cultural adaptation. In this paper, we discuss how integrating these two fields can make significant contributions to reducing racial and ethnic disparities in mental health care. Discussion The use of cultural adaptation models in implementation science can deepen the explicit attention to culture, particularly at the client and provider levels, in implementation studies making evidence-based treatments more responsive to the needs and preferences of diverse populations. The integration of both fields can help clarify and specify what to adapt in order to achieve optimal balance between adaptation and fidelity, and address important implementation outcomes (e.g., acceptability, appropriateness). A dialogue between both fields can help clarify the knowledge, skills and roles of who should facilitate the process of implementation, particularly when cultural adaptations are needed. The ecological perspective of implementation science provides an expanded lens to examine how contextual factors impact how treatments (adapted or not) are ultimately used and sustained in usual care settings. Integrating both fields can also help specify when in the implementation process adaptations may be considered in order to enhance the adoption and sustainability of evidence-based treatments. Summary Implementation science and cultural adaptation bring valuable insights and methods to how and to what extent treatments and/or context should be customized to enhance the implementation of evidence-based treatments across settings and populations. Developing a two-way street between these two fields can provide a better avenue for moving the best available treatments into practice and for helping to reduce racial and ethnic disparities in mental health care. PMID:23958445

Adaptive microfluidic gradient generator for quantitative chemotaxis experiments.

PubMed

Anielski, Alexander; Pfannes, Eva K B; Beta, Carsten

2017-03-01

Chemotactic motion in a chemical gradient is an essential cellular function that controls many processes in the living world. For a better understanding and more detailed modelling of the underlying mechanisms of chemotaxis, quantitative investigations in controlled environments are needed. We developed a setup that allows us to separately address the dependencies of the chemotactic motion on the average background concentration and on the gradient steepness of the chemoattractant. In particular, both the background concentration and the gradient steepness can be kept constant at the position of the cell while it moves along in the gradient direction. This is achieved by generating a well-defined chemoattractant gradient using flow photolysis. In this approach, the chemoattractant is released by a light-induced reaction from a caged precursor in a microfluidic flow chamber upstream of the cell. The flow photolysis approach is combined with an automated real-time cell tracker that determines changes in the cell position and triggers movement of the microscope stage such that the cell motion is compensated and the cell remains at the same position in the gradient profile. The gradient profile can be either determined experimentally using a caged fluorescent dye or may be alternatively determined by numerical solutions of the corresponding physical model. To demonstrate the function of this adaptive microfluidic gradient generator, we compare the chemotactic motion of Dictyostelium discoideum cells in a static gradient and in a gradient that adapts to the position of the moving cell.

A 3D image sensor with adaptable charge subtraction scheme for background light suppression

NASA Astrophysics Data System (ADS)

Shin, Jungsoon; Kang, Byongmin; Lee, Keechang; Kim, James D. K.

2013-02-01

We present a 3D ToF (Time-of-Flight) image sensor with adaptive charge subtraction scheme for background light suppression. The proposed sensor can alternately capture high resolution color image and high quality depth map in each frame. In depth-mode, the sensor requires enough integration time for accurate depth acquisition, but saturation will occur in high background light illumination. We propose to divide the integration time into N sub-integration times adaptively. In each sub-integration time, our sensor captures an image without saturation and subtracts the charge to prevent the pixel from the saturation. In addition, the subtraction results are cumulated N times obtaining a final result image without background illumination at full integration time. Experimental results with our own ToF sensor show high background suppression performance. We also propose in-pixel storage and column-level subtraction circuit for chiplevel implementation of the proposed method. We believe the proposed scheme will enable 3D sensors to be used in out-door environment.

AMModels: An R package for storing models, data, and metadata to facilitate adaptive management

PubMed Central

Katz, Jonathan E.

2018-01-01

Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future. AMModels facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process, AMModels allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While AMModels was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge, AMModels is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date. PMID:29489825

AMModels: An R package for storing models, data, and metadata to facilitate adaptive management.

PubMed

Donovan, Therese M; Katz, Jonathan E

2018-01-01

Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future. AMModels facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process, AMModels allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While AMModels was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge, AMModels is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date.

An Adapted Dialogic Reading Program for Turkish Kindergarteners from Low Socio-Economic Backgrounds

ERIC Educational Resources Information Center

Ergül, Cevriye; Akoglu, Gözde; Sarica, Ayse D.; Karaman, Gökçe; Tufan, Mümin; Bahap-Kudret, Zeynep; Zülfikar, Deniz

2016-01-01

The study aimed to examine the effectiveness of the Adapted Dialogic Reading Program (ADR) on the language and early literacy skills of Turkish kindergarteners from low socio-economic (SES) backgrounds. The effectiveness of ADR was investigated across six different treatment conditions including classroom and home based implementations in various…

Limitations to Thermoregulation and Acclimatization Challenge Human Adaptation to Global Warming.

PubMed

Hanna, Elizabeth G; Tait, Peter W

2015-07-15

Human thermoregulation and acclimatization are core components of the human coping mechanism for withstanding variations in environmental heat exposure. Amidst growing recognition that curtailing global warming to less than two degrees is becoming increasing improbable, human survival will require increasing reliance on these mechanisms. The projected several fold increase in extreme heat events suggests we need to recalibrate health protection policies and ratchet up adaptation efforts. Climate researchers, epidemiologists, and policy makers engaged in climate change adaptation and health protection are not commonly drawn from heat physiology backgrounds. Injecting a scholarly consideration of physiological limitations to human heat tolerance into the adaptation and policy literature allows for a broader understanding of heat health risks to support effective human adaptation and adaptation planning. This paper details the physiological and external environmental factors that determine human thermoregulation and acclimatization. We present a model to illustrate the interrelationship between elements that modulate the physiological process of thermoregulation. Limitations inherent in these processes, and the constraints imposed by differing exposure levels, and thermal comfort seeking on achieving acclimatization, are then described. Combined, these limitations will restrict the likely contribution that acclimatization can play in future human adaptation to global warming. We postulate that behavioral and technological adaptations will need to become the dominant means for human individual and societal adaptations as global warming progresses.

Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

PubMed Central

Brown, Patrick O.

2013-01-01

Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766

Web-based computer adaptive assessment of individual perceptions of job satisfaction for hospital workplace employees

PubMed Central

2011-01-01

Background To develop a web-based computer adaptive testing (CAT) application for efficiently collecting data regarding workers' perceptions of job satisfaction, we examined whether a 37-item Job Content Questionnaire (JCQ-37) could evaluate the job satisfaction of individual employees as a single construct. Methods The JCQ-37 makes data collection via CAT on the internet easy, viable and fast. A Rasch rating scale model was applied to analyze data from 300 randomly selected hospital employees who participated in job-satisfaction surveys in 2008 and 2009 via non-adaptive and computer-adaptive testing, respectively. Results Of the 37 items on the questionnaire, 24 items fit the model fairly well. Person-separation reliability for the 2008 surveys was 0.88. Measures from both years and item-8 job satisfaction for groups were successfully evaluated through item-by-item analyses by using t-test. Workers aged 26 - 35 felt that job satisfaction was significantly worse in 2009 than in 2008. Conclusions A Web-CAT developed in the present paper was shown to be more efficient than traditional computer-based or pen-and-paper assessments at collecting data regarding workers' perceptions of job content. PMID:21496311

Adaptive Detector Arrays for Optical Communications Receivers

NASA Technical Reports Server (NTRS)

Vilnrotter, V.; Srinivasan, M.

2000-01-01

The structure of an optimal adaptive array receiver for ground-based optical communications is described and its performance investigated. Kolmogorov phase screen simulations are used to model the sample functions of the focal-plane signal distribution due to turbulence and to generate realistic spatial distributions of the received optical field. This novel array detector concept reduces interference from background radiation by effectively assigning higher confidence levels at each instant of time to those detector elements that contain significant signal energy and suppressing those that do not. A simpler suboptimum structure that replaces the continuous weighting function of the optimal receiver by a hard decision on the selection of the signal detector elements also is described and evaluated. Approximations and bounds to the error probability are derived and compared with the exact calculations and receiver simulation results. It is shown that, for photon-counting receivers observing Poisson-distributed signals, performance improvements of approximately 5 dB can be obtained over conventional single-detector photon-counting receivers, when operating in high background environments.

Adaptive Core Simulation Employing Discrete Inverse Theory - Part II: Numerical Experiments

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

Abdel-Khalik, Hany S.; Turinsky, Paul J.

2005-07-15

Use of adaptive simulation is intended to improve the fidelity and robustness of important core attribute predictions such as core power distribution, thermal margins, and core reactivity. Adaptive simulation utilizes a selected set of past and current reactor measurements of reactor observables, i.e., in-core instrumentation readings, to adapt the simulation in a meaningful way. The companion paper, ''Adaptive Core Simulation Employing Discrete Inverse Theory - Part I: Theory,'' describes in detail the theoretical background of the proposed adaptive techniques. This paper, Part II, demonstrates several computational experiments conducted to assess the fidelity and robustness of the proposed techniques. The intentmore » is to check the ability of the adapted core simulator model to predict future core observables that are not included in the adaption or core observables that are recorded at core conditions that differ from those at which adaption is completed. Also, this paper demonstrates successful utilization of an efficient sensitivity analysis approach to calculate the sensitivity information required to perform the adaption for millions of input core parameters. Finally, this paper illustrates a useful application for adaptive simulation - reducing the inconsistencies between two different core simulator code systems, where the multitudes of input data to one code are adjusted to enhance the agreement between both codes for important core attributes, i.e., core reactivity and power distribution. Also demonstrated is the robustness of such an application.« less

Stochastic dark energy from inflationary quantum fluctuations

NASA Astrophysics Data System (ADS)

Glavan, Dražen; Prokopec, Tomislav; Starobinsky, Alexei A.

2018-05-01

We study the quantum backreaction from inflationary fluctuations of a very light, non-minimally coupled spectator scalar and show that it is a viable candidate for dark energy. The problem is solved by suitably adapting the formalism of stochastic inflation. This allows us to self-consistently account for the backreaction on the background expansion rate of the Universe where its effects are large. This framework is equivalent to that of semiclassical gravity in which matter vacuum fluctuations are included at the one loop level, but purely quantum gravitational fluctuations are neglected. Our results show that dark energy in our model can be characterized by a distinct effective equation of state parameter (as a function of redshift) which allows for testing of the model at the level of the background.

Whole-genome resequencing of Escherichia coli K-12 MG1655 undergoing short-term laboratory evolution in lactate minimal media reveals flexible selection of adaptive mutations

PubMed Central

2009-01-01

Background Short-term laboratory evolution of bacteria followed by genomic sequencing provides insight into the mechanism of adaptive evolution, such as the number of mutations needed for adaptation, genotype-phenotype relationships, and the reproducibility of adaptive outcomes. Results In the present study, we describe the genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in 7 of the 11 adapted strains. This mutation conferred an approximately 15% increase to the growth rate when experimentally introduced to the wild-type background and resulted in an approximately 30% increase to growth rate when introduced to a background already harboring two adaptive mutations. Additionally, most endpoints had a mutation in a regulatory gene (crp or relA, for example) or the RNA polymerase. Conclusions The 82 base-pair deletion found in the rph-pyrE operon of many endpoints may function to relieve a pyrimidine biosynthesis defect present in MG1655. In contrast, a variety of regulators acquire mutations in the different endpoints, suggesting flexibility in overcoming regulatory challenges in the adaptation. PMID:19849850

Enhanced identification and biological validation of differential gene expression via Illumina whole-genome expression arrays through the use of the model-based background correction methodology

PubMed Central

Ding, Liang-Hao; Xie, Yang; Park, Seongmi; Xiao, Guanghua; Story, Michael D.

2008-01-01

Despite the tremendous growth of microarray usage in scientific studies, there is a lack of standards for background correction methodologies, especially in single-color microarray platforms. Traditional background subtraction methods often generate negative signals and thus cause large amounts of data loss. Hence, some researchers prefer to avoid background corrections, which typically result in the underestimation of differential expression. Here, by utilizing nonspecific negative control features integrated into Illumina whole genome expression arrays, we have developed a method of model-based background correction for BeadArrays (MBCB). We compared the MBCB with a method adapted from the Affymetrix robust multi-array analysis algorithm and with no background subtraction, using a mouse acute myeloid leukemia (AML) dataset. We demonstrated that differential expression ratios obtained by using the MBCB had the best correlation with quantitative RT–PCR. MBCB also achieved better sensitivity in detecting differentially expressed genes with biological significance. For example, we demonstrated that the differential regulation of Tnfr2, Ikk and NF-kappaB, the death receptor pathway, in the AML samples, could only be detected by using data after MBCB implementation. We conclude that MBCB is a robust background correction method that will lead to more precise determination of gene expression and better biological interpretation of Illumina BeadArray data. PMID:18450815

Seismic hazard in the Nation's breadbasket

USGS Publications Warehouse

Boyd, Oliver; Haller, Kathleen; Luco, Nicolas; Moschetti, Morgan P.; Mueller, Charles; Petersen, Mark D.; Rezaeian, Sanaz; Rubinstein, Justin L.

2015-01-01

The USGS National Seismic Hazard Maps were updated in 2014 and included several important changes for the central United States (CUS). Background seismicity sources were improved using a new moment-magnitude-based catalog; a new adaptive, nearest-neighbor smoothing kernel was implemented; and maximum magnitudes for background sources were updated. Areal source zones developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities project were simplified and adopted. The weighting scheme for ground motion models was updated, giving more weight to models with a faster attenuation with distance compared to the previous maps. Overall, hazard changes (2% probability of exceedance in 50 years, across a range of ground-motion frequencies) were smaller than 10% in most of the CUS relative to the 2008 USGS maps despite new ground motion models and their assigned logic tree weights that reduced the probabilistic ground motions by 5–20%.

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain

NASA Astrophysics Data System (ADS)

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C. M.; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions are preserved in the brain mask. Shadow artifacts due to strong susceptibility variations in the derived QSM maps could also be largely eliminated using the R-SHARP method, leading to more accurate QSM reconstruction.

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain.

PubMed

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C M; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions are preserved in the brain mask. Shadow artifacts due to strong susceptibility variations in the derived QSM maps could also be largely eliminated using the R-SHARP method, leading to more accurate QSM reconstruction. Copyright © 2017. Published by Elsevier Inc.

Colour and pattern change against visually heterogeneous backgrounds in the tree frog Hyla japonica.

PubMed

Kang, Changku; Kim, Ye Eun; Jang, Yikweon

2016-03-02

Colour change in animals can be adaptive phenotypic plasticity in heterogeneous environments. Camouflage through background colour matching has been considered a primary force that drives the evolution of colour changing ability. However, the mechanism to which animals change their colour and patterns under visually heterogeneous backgrounds (i.e. consisting of more than one colour) has only been identified in limited taxa. Here, we investigated the colour change process of the Japanese tree frog (Hyla japonica) against patterned backgrounds and elucidated how the expression of dorsal patterns changes against various achromatic/chromatic backgrounds with/without patterns. Our main findings are i) frogs primarily responded to the achromatic differences in background, ii) their contrasting dorsal patterns were conditionally expressed dependent on the brightness of backgrounds, iii) against mixed coloured background, frogs adopted intermediate forms between two colours. Using predator (avian and snake) vision models, we determined that colour differences against different backgrounds yielded perceptible changes in dorsal colours. We also found substantial individual variation in colour changing ability and the levels of dorsal pattern expression between individuals. We discuss the possibility of correlational selection on colour changing ability and resting behaviour that maintains the high variation in colour changing ability within population.

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

Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

NASA Astrophysics Data System (ADS)

Kesrarat, Darun; Patanavijit, Vorapoj

2017-02-01

In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

Adaptive skin detection based on online training

NASA Astrophysics Data System (ADS)

Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

2007-11-01

Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

Model-based video segmentation for vision-augmented interactive games

NASA Astrophysics Data System (ADS)

Liu, Lurng-Kuo

2000-04-01

This paper presents an architecture and algorithms for model based video object segmentation and its applications to vision augmented interactive game. We are especially interested in real time low cost vision based applications that can be implemented in software in a PC. We use different models for background and a player object. The object segmentation algorithm is performed in two different levels: pixel level and object level. At pixel level, the segmentation algorithm is formulated as a maximizing a posteriori probability (MAP) problem. The statistical likelihood of each pixel is calculated and used in the MAP problem. Object level segmentation is used to improve segmentation quality by utilizing the information about the spatial and temporal extent of the object. The concept of an active region, which is defined based on motion histogram and trajectory prediction, is introduced to indicate the possibility of a video object region for both background and foreground modeling. It also reduces the overall computation complexity. In contrast with other applications, the proposed video object segmentation system is able to create background and foreground models on the fly even without introductory background frames. Furthermore, we apply different rate of self-tuning on the scene model so that the system can adapt to the environment when there is a scene change. We applied the proposed video object segmentation algorithms to several prototype virtual interactive games. In our prototype vision augmented interactive games, a player can immerse himself/herself inside a game and can virtually interact with other animated characters in a real time manner without being constrained by helmets, gloves, special sensing devices, or background environment. The potential applications of the proposed algorithms including human computer gesture interface and object based video coding such as MPEG-4 video coding.

Kalman Filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry.

PubMed

Zhang, Yuxin; Chen, Shuo; Deng, Kexin; Chen, Bingyao; Wei, Xing; Yang, Jiafei; Wang, Shi; Ying, Kui

2017-01-01

To develop a self-adaptive and fast thermometry method by combining the original hybrid magnetic resonance thermometry method and the bio heat transfer equation (BHTE) model. The proposed Kalman filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry, abbreviated as KalBHT hybrid method, introduced the BHTE model to synthesize a window on the regularization term of the hybrid algorithm, which leads to a self-adaptive regularization both spatially and temporally with change of temperature. Further, to decrease the sensitivity to accuracy of the BHTE model, Kalman filter is utilized to update the window at each iteration time. To investigate the effect of the proposed model, computer heating simulation, phantom microwave heating experiment and dynamic in-vivo model validation of liver and thoracic tumor were conducted in this study. The heating simulation indicates that the KalBHT hybrid algorithm achieves more accurate results without adjusting λ to a proper value in comparison to the hybrid algorithm. The results of the phantom heating experiment illustrate that the proposed model is able to follow temperature changes in the presence of motion and the temperature estimated also shows less noise in the background and surrounding the hot spot. The dynamic in-vivo model validation with heating simulation demonstrates that the proposed model has a higher convergence rate, more robustness to susceptibility problem surrounding the hot spot and more accuracy of temperature estimation. In the healthy liver experiment with heating simulation, the RMSE of the hot spot of the proposed model is reduced to about 50% compared to the RMSE of the original hybrid model and the convergence time becomes only about one fifth of the hybrid model. The proposed model is able to improve the accuracy of the original hybrid algorithm and accelerate the convergence rate of MR temperature estimation.

Cosine problem in EPRL/FK spinfoam model

NASA Astrophysics Data System (ADS)

Vojinović, Marko

2014-01-01

We calculate the classical limit effective action of the EPRL/FK spinfoam model of quantum gravity coupled to matter fields. By employing the standard QFT background field method adapted to the spinfoam setting, we find that the model has many different classical effective actions. Most notably, these include the ordinary Einstein-Hilbert action coupled to matter, but also an action which describes antigravity. All those multiple classical limits appear as a consequence of the fact that the EPRL/FK vertex amplitude has cosine-like large spin asymptotics. We discuss some possible ways to eliminate the unwanted classical limits.

The Differentiation of Adaptive Behaviours: Evidence from High and Low Performers

ERIC Educational Resources Information Center

Kane, Harrison; Oakland, Thomas David

2015-01-01

Background: Professionals who use measures of adaptive behaviour when working with special populations may assume that adaptive behaviour is a consistent and linear construct at various ability levels and thus believe the construct of adaptive behaviour is the same for high and low performers. That is, highly adaptive people simply are assumed to…

Skeletal Geometry and Indices of Bone Strength in Artistic Gymnasts

PubMed Central

Dowthwaite, Jodi N.; Scerpella, Tamara A.

2010-01-01

This review addresses bone geometry and indices of skeletal strength associated with exposure to gymnastic loading during growth. A brief background characterizes artistic gymnastics as a mechanical loading model and outlines densitometric techniques, skeletal outcomes and challenges in assessment of skeletal adaptation. The literature on bone geometric adaptation to gymnastic loading is sparse and consists of results for disparate skeletal sites, maturity phases, gender compositions and assessment methods, complicating synthesis of an overriding view. Furthermore, most studies assess only females, with little information on males and adults. Nonetheless, gymnastic loading during growth appears to yield significant enlargement of total and cortical bone geometry (+10 to 30%) and elevation of trabecular density (+20%) in the forearm, yielding elevated indices of skeletal strength (+20 to +50%). Other sites exhibit more moderate geometric and densitometric adaptations (5 to 15%). Mode of adaptation appears to be site-specific; some sites demonstrate marked periosteal and endosteal expansion, whereas other sites exhibit negligible or moderate periosteal expansion coupled with endocortical contraction. Further research is necessary to address sex-, maturity- and bone tissue-specific adaptation, as well as maintenance of benefits beyond loading cessation. PMID:19949278

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

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

McClanahan, Richard; De Leon, Phillip L.

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

DOE PAGES

McClanahan, Richard; De Leon, Phillip L.

2014-08-20

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster.

PubMed

Jha, Aashish R; Miles, Cecelia M; Lippert, Nodia R; Brown, Christopher D; White, Kevin P; Kreitman, Martin

2015-10-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Light adaptation alters inner retinal inhibition to shape OFF retinal pathway signaling

PubMed Central

Mazade, Reece E.

2016-01-01

The retina adjusts its signaling gain over a wide range of light levels. A functional result of this is increased visual acuity at brighter luminance levels (light adaptation) due to shifts in the excitatory center-inhibitory surround receptive field parameters of ganglion cells that increases their sensitivity to smaller light stimuli. Recent work supports the idea that changes in ganglion cell spatial sensitivity with background luminance are due in part to inner retinal mechanisms, possibly including modulation of inhibition onto bipolar cells. To determine how the receptive fields of OFF cone bipolar cells may contribute to changes in ganglion cell resolution, the spatial extent and magnitude of inhibitory and excitatory inputs were measured from OFF bipolar cells under dark- and light-adapted conditions. There was no change in the OFF bipolar cell excitatory input with light adaptation; however, the spatial distributions of inhibitory inputs, including both glycinergic and GABAergic sources, became significantly narrower, smaller, and more transient. The magnitude and size of the OFF bipolar cell center-surround receptive fields as well as light-adapted changes in resting membrane potential were incorporated into a spatial model of OFF bipolar cell output to the downstream ganglion cells, which predicted an increase in signal output strength with light adaptation. We show a prominent role for inner retinal spatial signals in modulating the modeled strength of bipolar cell output to potentially play a role in ganglion cell visual sensitivity and acuity. PMID:26912599

Validity of an adaptation of the Framingham cardiovascular risk function: the VERIFICA study

PubMed Central

Marrugat, Jaume; Subirana, Isaac; Comín, Eva; Cabezas, Carmen; Vila, Joan; Elosua, Roberto; Nam, Byung‐Ho; Ramos, Rafel; Sala, Joan; Solanas, Pascual; Cordón, Ferran; Gené‐Badia, Joan; D'Agostino, Ralph B

2007-01-01

Background To assess the reliability and accuracy of the Framingham coronary heart disease (CHD) risk function adapted by the Registre Gironí del Cor (REGICOR) investigators in Spain. Methods A 5‐year follow‐up study was completed in 5732 participants aged 35–74 years. The adaptation consisted of using in the function the average population risk factor prevalence and the cumulative incidence observed in Spain instead of those from Framingham in a Cox proportional hazards model. Reliability and accuracy in estimating the observed cumulative incidence were tested with the area under the curve comparison and goodness‐of‐fit test, respectively. Results The Kaplan–Meier CHD cumulative incidence during the follow‐up was 4.0% in men and 1.7% in women. The original Framingham function and the REGICOR adapted estimates were 10.4% and 4.8%, and 3.6% and 2.0%, respectively. The REGICOR‐adapted function's estimate did not differ from the observed cumulated incidence (goodness of fit in men, p = 0.078, in women, p = 0.256), whereas all the original Framingham function estimates differed significantly (p<0.001). Reliabilities of the original Framingham function and of the best Cox model fit with the study data were similar in men (area under the receiver operator characteristic curve 0.68 and 0.69, respectively, p = 0.273), whereas the best Cox model fitted better in women (0.73 and 0.81, respectively, p<0.001). Conclusion The Framingham function adapted to local population characteristics accurately and reliably predicted the 5‐year CHD risk for patients aged 35–74 years, in contrast with the original function, which consistently overestimated the actual risk. PMID:17183014

Factor analysis of auto-associative neural networks with application in speaker verification.

PubMed

Garimella, Sri; Hermansky, Hynek

2013-04-01

Auto-associative neural network (AANN) is a fully connected feed-forward neural network, trained to reconstruct its input at its output through a hidden compression layer, which has fewer numbers of nodes than the dimensionality of input. AANNs are used to model speakers in speaker verification, where a speaker-specific AANN model is obtained by adapting (or retraining) the universal background model (UBM) AANN, an AANN trained on multiple held out speakers, using corresponding speaker data. When the amount of speaker data is limited, this adaptation procedure may lead to overfitting as all the parameters of UBM-AANN are adapted. In this paper, we introduce and develop the factor analysis theory of AANNs to alleviate this problem. We hypothesize that only the weight matrix connecting the last nonlinear hidden layer and the output layer is speaker-specific, and further restrict it to a common low-dimensional subspace during adaptation. The subspace is learned using large amounts of development data, and is held fixed during adaptation. Thus, only the coordinates in a subspace, also known as i-vector, need to be estimated using speaker-specific data. The update equations are derived for learning both the common low-dimensional subspace and the i-vectors corresponding to speakers in the subspace. The resultant i-vector representation is used as a feature for the probabilistic linear discriminant analysis model. The proposed system shows promising results on the NIST-08 speaker recognition evaluation (SRE), and yields a 23% relative improvement in equal error rate over the previously proposed weighted least squares-based subspace AANNs system. The experiments on NIST-10 SRE confirm that these improvements are consistent and generalize across datasets.

Dynamical information encoding in neural adaptation.

PubMed

Luozheng Li; Wenhao Zhang; Yuanyuan Mi; Dahui Wang; Xiaohan Lin; Si Wu

2016-08-01

Adaptation refers to the general phenomenon that a neural system dynamically adjusts its response property according to the statistics of external inputs. In response to a prolonged constant stimulation, neuronal firing rates always first increase dramatically at the onset of the stimulation; and afterwards, they decrease rapidly to a low level close to background activity. This attenuation of neural activity seems to be contradictory to our experience that we can still sense the stimulus after the neural system is adapted. Thus, it prompts a question: where is the stimulus information encoded during the adaptation? Here, we investigate a computational model in which the neural system employs a dynamical encoding strategy during the neural adaptation: at the early stage of the adaptation, the stimulus information is mainly encoded in the strong independent firings; and as time goes on, the information is shifted into the weak but concerted responses of neurons. We find that short-term plasticity, a general feature of synapses, provides a natural mechanism to achieve this goal. Furthermore, we demonstrate that with balanced excitatory and inhibitory inputs, this correlation-based information can be read out efficiently. The implications of this study on our understanding of neural information encoding are discussed.

Local motion adaptation enhances the representation of spatial structure at EMD arrays

PubMed Central

Lindemann, Jens P.; Egelhaaf, Martin

2017-01-01

Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects. PMID:29281631

Limitations to Thermoregulation and Acclimatization Challenge Human Adaptation to Global Warming

PubMed Central

Hanna, Elizabeth G.; Tait, Peter W.

2015-01-01

Human thermoregulation and acclimatization are core components of the human coping mechanism for withstanding variations in environmental heat exposure. Amidst growing recognition that curtailing global warming to less than two degrees is becoming increasing improbable, human survival will require increasing reliance on these mechanisms. The projected several fold increase in extreme heat events suggests we need to recalibrate health protection policies and ratchet up adaptation efforts. Climate researchers, epidemiologists, and policy makers engaged in climate change adaptation and health protection are not commonly drawn from heat physiology backgrounds. Injecting a scholarly consideration of physiological limitations to human heat tolerance into the adaptation and policy literature allows for a broader understanding of heat health risks to support effective human adaptation and adaptation planning. This paper details the physiological and external environmental factors that determine human thermoregulation and acclimatization. We present a model to illustrate the interrelationship between elements that modulate the physiological process of thermoregulation. Limitations inherent in these processes, and the constraints imposed by differing exposure levels, and thermal comfort seeking on achieving acclimatization, are then described. Combined, these limitations will restrict the likely contribution that acclimatization can play in future human adaptation to global warming. We postulate that behavioral and technological adaptations will need to become the dominant means for human individual and societal adaptations as global warming progresses. PMID:26184272

A randomized controlled trial of culturally adapted motivational interviewing for Hispanic heavy drinkers: Theory of Adaptation and Study Protocol

PubMed Central

Lee, Christina S.; Colby, Suzanne M.; Magill, Molly; Almeida, Joanna; Tavares, Tonya; Rohsenow, Damaris J.

2016-01-01

Background The NIH Strategic Plan prioritizes health disparities research for socially disadvantaged Hispanics, to reduce the disproportionate burden of alcohol-related negative consequences compared to other racial/ethnic groups. Cultural adaptation of evidence-based treatments, such as motivational interviewing (MI), can improve access and response to alcohol treatment. However, the lack of rigorous clinical trials designed to test the efficacy and theoretical underpinnings of cultural adaptation has made proof of concept difficult. Objective The CAMI2 (Culturally Adapted Motivational Interviewing) study design and its theoretical model, is described to illustrate how MI adapted to social and cultural factors (CAMI) can be discriminated against non-adapted MI. Methods and Design CAMI2, a large, 12 month randomized prospective trial, examines the efficacy of CAMI and MI among heavy drinking Hispanics recruited from the community (n=257). Outcomes are reductions in heavy drinking days (Time Line Follow-Back) and negative consequences of drinking among Hispanics (Drinkers Inventory of Consequences). A second aim examines perceived acculturation stress as a moderator of treatment outcomes in the CAMI condition. Summary The CAMI2 study design protocol is presented and the theory of adaptation is presented. Findings from the trial described may yield important recommendations on the science of cultural adaptation and improve MI dissemination to Hispanics with alcohol risk. PMID:27565832

Los Angeles County Metropolitan Transportation Authority climate change adaptation pilot project report.

DOT National Transportation Integrated Search

2013-08-01

This Climate Change Adaptation Pilot Project Report details the project background of the recently-completed Los Angeles County : Metropolitan Transportation Authority (Metro) Transit Climate Change Adaptation Pilot Project as well as the various wor...

Adding dynamic rules to self-organizing fuzzy systems

NASA Technical Reports Server (NTRS)

Buhusi, Catalin V.

1992-01-01

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Resilience in Utility Technologies

NASA Astrophysics Data System (ADS)

Seaton, Roger

The following sections are included: * Scope of paper * Preamble * Background to the case-study projects * Source projects * Resilience * Case study 1: Electricity generation * Context * Model * Case study 2: Water recycling * Context * Model * Case study 3: Ecotechnology and water treatment * Context * The problem of classification: Finding a classificatory solution * Application of the new taxonomy to water treatment * Concluding comments and questions * Conclusions * Questions and issues * Purposive or Purposeful? * Resilience: Flexibility and adaptivity? * Resilience: With respect of what? * Risk, uncertainty, surprise, emergence - What sort of shock, and who says so? * Co-evolutionary friction * References

AMModels: An R package for storing models, data, and metadata to facilitate adaptive management

USGS Publications Warehouse

Donovan, Therese M.; Katz, Jonathan

2018-01-01

Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future. AMModels facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process, AMModels allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While AMModels was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge, AMModels is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date.

Improved tomographic reconstructions using adaptive time-dependent intensity normalization.

PubMed

Titarenko, Valeriy; Titarenko, Sofya; Withers, Philip J; De Carlo, Francesco; Xiao, Xianghui

2010-09-01

The first processing step in synchrotron-based micro-tomography is the normalization of the projection images against the background, also referred to as a white field. Owing to time-dependent variations in illumination and defects in detection sensitivity, the white field is different from the projection background. In this case standard normalization methods introduce ring and wave artefacts into the resulting three-dimensional reconstruction. In this paper the authors propose a new adaptive technique accounting for these variations and allowing one to obtain cleaner normalized data and to suppress ring and wave artefacts. The background is modelled by the product of two time-dependent terms representing the illumination and detection stages. These terms are written as unknown functions, one scaled and shifted along a fixed direction (describing the illumination term) and one translated by an unknown two-dimensional vector (describing the detection term). The proposed method is applied to two sets (a stem Salix variegata and a zebrafish Danio rerio) acquired at the parallel beam of the micro-tomography station 2-BM at the Advanced Photon Source showing significant reductions in both ring and wave artefacts. In principle the method could be used to correct for time-dependent phenomena that affect other tomographic imaging geometries such as cone beam laboratory X-ray computed tomography.

Development and evaluation of a data-adaptive alerting algorithm for univariate temporal biosurveillance data.

PubMed

Elbert, Yevgeniy; Burkom, Howard S

2009-11-20

This paper discusses further advances in making robust predictions with the Holt-Winters forecasts for a variety of syndromic time series behaviors and introduces a control-chart detection approach based on these forecasts. Using three collections of time series data, we compare biosurveillance alerting methods with quantified measures of forecast agreement, signal sensitivity, and time-to-detect. The study presents practical rules for initialization and parameterization of biosurveillance time series. Several outbreak scenarios are used for detection comparison. We derive an alerting algorithm from forecasts using Holt-Winters-generalized smoothing for prospective application to daily syndromic time series. The derived algorithm is compared with simple control-chart adaptations and to more computationally intensive regression modeling methods. The comparisons are conducted on background data from both authentic and simulated data streams. Both types of background data include time series that vary widely by both mean value and cyclic or seasonal behavior. Plausible, simulated signals are added to the background data for detection performance testing at signal strengths calculated to be neither too easy nor too hard to separate the compared methods. Results show that both the sensitivity and the timeliness of the Holt-Winters-based algorithm proved to be comparable or superior to that of the more traditional prediction methods used for syndromic surveillance.

A manifold learning approach to target detection in high-resolution hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.

Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into the adaptive LLE transformation; the artificial target manifold helps to guide the separation of the target data from the background data in the new, lower-dimensional manifold coordinates. Then, target detection is performed in the manifold space.

Colour preferences of juvenile turbot (Scophthalmus maximus).

PubMed

Li, Xian; Chi, Liang; Tian, Huiqin; Meng, Lingjie; Zheng, Jimeng; Gao, Xiaolong; Liu, Ying

2016-03-15

The background colour of aquaculture tanks is normally chosen based on practical experience and/or observations of fish behaviour and the growth rates achieved. However, some farmed species, including turbot, are sentient and can show a preference for a particular environment. In the current study, a self-referent colour preference device was developed and the self-referent colour preference of farmed fish investigated. In experiment 1, the background colour preference of juvenile turbot cultured under a grey background for >3months post-incubation was evaluated. Based on these results, in experiment 2, juvenile turbot were adapted to blue, pink, white, or black backgrounds for 50days and their preferences established. Meanwhile, the growth rates, feed intake, and metabolic rates (including oxygen consumption rate, and ammonia excretion rate) of the turbot were evaluated. The results showed that turbot farmed under a grey background, or after long-term white, blue, pink and black colour adaptation, always displayed a preference for a white background and a dislike for black, red, or brown backgrounds, although their body colour was greyish. Long-term adaptation influenced the frequency of juveniles selecting white, black, pink or blue backgrounds. They showed the highest growth rate, feed intake, and metabolic rates under blue and white backgrounds, and the lowest under a black background in accordance with their preferences shown in experiment 1. Although it is unclear how turbot determine their self-referent colour preferences over such a short period of time, these results indicate that dark colours are unsuitable for the aquaculture of turbot culture in terms of the welfare of the fish. Copyright © 2016 Elsevier Inc. All rights reserved.

Crystallized and fluid intelligence of university students with intellectual disability who are fully integrated versus those who studied in adapted enrichment courses

PubMed Central

Verkuilen, Jay; Shnitzer-Meirovich, Shlomit; Altman, Carmit

2018-01-01

Background Inclusion of people with intellectual disability (ID) in higher postsecondary academic education is on the rise. However, there are no scientific criteria for determining the eligibility for full inclusion of students with ID in university courses. This study focuses on two models of academic inclusion for students with ID: (a) separate adapted enrichment model: students with ID study in separate enrichment courses adapted to their level; (b) full inclusion model: students with ID are included in undergraduate courses, receive academic credits and are expected to accumulate the amount of credits for a B.A. Aim (a) To examine whether crystallized and fluid intelligence and cognitive tests can serve as screening tests for determining the appropriate placement of students with ID for the adapted enrichment model versus the full inclusion model. (b) To examine the attitudes towards the program of students with ID in the inclusion model. Method/Procedure The sample included 31 adults with ID: students with ID who were fully included (N = 10) and students with ID who participated in the adapted enrichment model (N = 21). Crystallized and fluid intelligence were examined (WAIS-III, Wechsler, 1997) and Hebrew abstract verbal tests (Glanz, 1989). Semi-structured interviews were conducted in order to examine the attitudes of students in the inclusion model towards the program. Outcomes and results The ANOVAs indicate that the most prominent difference between the groups was in vocabulary, knowledge and working memory. ROC analysis, a fundamental tool for diagnostic test evaluation, was used to determine the students’ eligibility for appropriate placement in the two models. Seven tests distinguished between the groups in terms of sensitivity and specificity. The interviews were analyzed according to three phases. Conclusions/Implications The results indicate that students with ID are able to participate in undergraduate courses and achieve academic goals. The general IQ and idioms test seem to be best determiners for appropriate placement of students with ID to one of the two models. The included students with ID are motivated and self-determined in continuing in the program. PMID:29684024

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.

A video-based real-time adaptive vehicle-counting system for urban roads.

PubMed

Liu, Fei; Zeng, Zhiyuan; Jiang, Rong

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

A video-based real-time adaptive vehicle-counting system for urban roads

PubMed Central

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984

Position and speed control of brushless DC motors using sensorless techniques and application trends.

PubMed

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

Improvement of individual camouflage through background choice in ground-nesting birds.

PubMed

Stevens, Martin; Troscianko, Jolyon; Wilson-Aggarwal, Jared K; Spottiswoode, Claire N

2017-09-01

Animal camouflage is a longstanding example of adaptation. Much research has tested how camouflage prevents detection and recognition, largely focusing on changes to an animal's own appearance over evolution. However, animals could also substantially alter their camouflage by behaviourally choosing appropriate substrates. Recent studies suggest that individuals from several animal taxa could select backgrounds or positions to improve concealment. Here, we test whether individual wild animals choose backgrounds in complex environments, and whether this improves camouflage against predator vision. We studied nest site selection by nine species of ground-nesting birds (nightjars, plovers and coursers) in Zambia, and used image analysis and vision modeling to quantify egg and plumage camouflage to predator vision. Individual birds chose backgrounds that enhanced their camouflage, being better matched to their chosen backgrounds than to other potential backgrounds with respect to multiple aspects of camouflage. This occurred at all three spatial scales tested (a few cm and five meters from the nest, and compared to other sites chosen by conspecifics), and was the case for the eggs of all bird groups studied, and for adult nightjar plumage. Thus, individual wild animals improve their camouflage through active background choice, with choices highly refined across multiple spatial scales.

Improvement of individual camouflage through background choice in ground-nesting birds

PubMed Central

Stevens, Martin; Troscianko, Jolyon; Wilson-Aggarwal, Jared K.; Spottiswoode, Claire N.

2017-01-01

Animal camouflage is a longstanding example of adaptation. Much research has tested how camouflage prevents detection and recognition, largely focusing on changes to an animal's own appearance over evolution. However, animals could also substantially alter their camouflage by behaviourally choosing appropriate substrates. Recent studies suggest that individuals from several animal taxa could select backgrounds or positions to improve concealment. Here, we test whether individual wild animals choose backgrounds in complex environments, and whether this improves camouflage against predator vision. We studied nest site selection by nine species of ground-nesting birds (nightjars, plovers and coursers) in Zambia, and used image analysis and vision modeling to quantify egg and plumage camouflage to predator vision. Individual birds chose backgrounds that enhanced their camouflage, being better matched to their chosen backgrounds than to other potential backgrounds with respect to multiple aspects of camouflage. This occurred at all three spatial scales tested (a few cm and five meters from the nest, and compared to other sites chosen by conspecifics), and was the case for the eggs of all bird groups studied, and for adult nightjar plumage. Thus, individual wild animals improve their camouflage through active background choice, with choices highly refined across multiple spatial scales. PMID:28890937

Colour and pattern change against visually heterogeneous backgrounds in the tree frog Hyla japonica

PubMed Central

Kang, Changku; Kim, Ye Eun; Jang, Yikweon

2016-01-01

Colour change in animals can be adaptive phenotypic plasticity in heterogeneous environments. Camouflage through background colour matching has been considered a primary force that drives the evolution of colour changing ability. However, the mechanism to which animals change their colour and patterns under visually heterogeneous backgrounds (i.e. consisting of more than one colour) has only been identified in limited taxa. Here, we investigated the colour change process of the Japanese tree frog (Hyla japonica) against patterned backgrounds and elucidated how the expression of dorsal patterns changes against various achromatic/chromatic backgrounds with/without patterns. Our main findings are i) frogs primarily responded to the achromatic differences in background, ii) their contrasting dorsal patterns were conditionally expressed dependent on the brightness of backgrounds, iii) against mixed coloured background, frogs adopted intermediate forms between two colours. Using predator (avian and snake) vision models, we determined that colour differences against different backgrounds yielded perceptible changes in dorsal colours. We also found substantial individual variation in colour changing ability and the levels of dorsal pattern expression between individuals. We discuss the possibility of correlational selection on colour changing ability and resting behaviour that maintains the high variation in colour changing ability within population. PMID:26932675

Adaptive approaches to licensing, health technology assessment, and introduction of drugs and devices.

PubMed

Husereau, Don; Henshall, Chris; Jivraj, Jamil

2014-07-01

Adaptive approaches to the introduction of drugs and medical devices involve the use of an evolving evidence base rather than conventional single-point-in-time evaluations as a proposed means to promote patient access to innovation, reduce clinical uncertainty, ensure effectiveness, and improve the health technology development process. This report summarizes a Health Technology Assessment International (HTAi) Policy Forum discussion, drawing on presentations from invited experts, discussions among attendees about real-world case examples, and background paper. For adaptive approaches to be understood, accepted, and implemented, the Forum identified several key issues that must be addressed. These include the need to define the goals of and to set priorities for adaptive approaches; to examine evidence collection approaches; to clarify the roles and responsibilities of stakeholders; to understand the implications of adaptive approaches on current legal and ethical standards; to determine costs of such approaches and how they will be met; and to identify differences in applying adaptive approaches to drugs versus medical devices. The Forum also explored the different implications of adaptive approaches for various stakeholders, including patients, regulators, HTA/coverage bodies, health systems, clinicians, and industry. A key outcome of the meeting was a clearer understanding of the opportunities and challenges adaptive approaches present. Furthermore, the Forum brought to light the critical importance of recognizing and including a full range of stakeholders as contributors to a shared decision-making model implicit in adaptive pathways in future discussions on, and implementation of, adaptive approaches.

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

Evolutionary patterns and processes in the radiation of phyllostomid bats

PubMed Central

2011-01-01

Background The phyllostomid bats present the most extensive ecological and phenotypic radiation known among mammal families. This group is an important model system for studies of cranial ecomorphology and functional optimisation because of the constraints imposed by the requirements of flight. A number of studies supporting phyllostomid adaptation have focused on qualitative descriptions or correlating functional variables and diet, but explicit tests of possible evolutionary mechanisms and scenarios for phenotypic diversification have not been performed. We used a combination of morphometric and comparative methods to test hypotheses regarding the evolutionary processes behind the diversification of phenotype (mandible shape and size) and diet during the phyllostomid radiation. Results The different phyllostomid lineages radiate in mandible shape space, with each feeding specialisation evolving towards different axes. Size and shape evolve quite independently, as the main directions of shape variation are associated with mandible elongation (nectarivores) or the relative size of tooth rows and mandibular processes (sanguivores and frugivores), which are not associated with size changes in the mandible. The early period of phyllostomid diversification is marked by a burst of shape, size, and diet disparity (before 20 Mya), larger than expected by neutral evolution models, settling later to a period of relative phenotypic and ecological stasis. The best fitting evolutionary model for both mandible shape and size divergence was an Ornstein-Uhlenbeck process with five adaptive peaks (insectivory, carnivory, sanguivory, nectarivory and frugivory). Conclusions The radiation of phyllostomid bats presented adaptive and non-adaptive components nested together through the time frame of the family's evolution. The first 10 My of the radiation were marked by strong phenotypic and ecological divergence among ancestors of modern lineages, whereas the remaining 20 My were marked by stasis around a number of probable adaptive peaks. A considerable amount of cladogenesis and speciation in this period is likely to be the result of non-adaptive allopatric divergence or adaptations to peaks within major dietary categories. PMID:21605452

Microhabitat choice in island lizards enhances camouflage against avian predators.

PubMed

Marshall, Kate L A; Philpot, Kate E; Stevens, Martin

2016-01-25

Camouflage can often be enhanced by genetic adaptation to different local environments. However, it is less clear how individual behaviour improves camouflage effectiveness. We investigated whether individual Aegean wall lizards (Podarcis erhardii) inhabiting different islands rest on backgrounds that improve camouflage against avian predators. In free-ranging lizards, we found that dorsal regions were better matched against chosen backgrounds than against other backgrounds on the same island. This suggests that P. erhardii make background choices that heighten individual-specific concealment. In achromatic camouflage, this effect was more evident in females and was less distinct in an island population with lower predation risk. This suggests that behavioural enhancement of camouflage may be more important in females than in sexually competing males and related to predation risk. However, in an arena experiment, lizards did not choose the background that improved camouflage, most likely due to the artificial conditions. Overall, our results provide evidence that behavioural preferences for substrates can enhance individual camouflage of lizards in natural microhabitats, and that such adaptations may be sexually dimorphic and dependent on local environments. This research emphasizes the importance of considering links between ecology, behaviour, and appearance in studies of intraspecific colour variation and local adaptation.

Microhabitat choice in island lizards enhances camouflage against avian predators

PubMed Central

Marshall, Kate L. A.; Philpot, Kate E.; Stevens, Martin

2016-01-01

Camouflage can often be enhanced by genetic adaptation to different local environments. However, it is less clear how individual behaviour improves camouflage effectiveness. We investigated whether individual Aegean wall lizards (Podarcis erhardii) inhabiting different islands rest on backgrounds that improve camouflage against avian predators. In free-ranging lizards, we found that dorsal regions were better matched against chosen backgrounds than against other backgrounds on the same island. This suggests that P. erhardii make background choices that heighten individual-specific concealment. In achromatic camouflage, this effect was more evident in females and was less distinct in an island population with lower predation risk. This suggests that behavioural enhancement of camouflage may be more important in females than in sexually competing males and related to predation risk. However, in an arena experiment, lizards did not choose the background that improved camouflage, most likely due to the artificial conditions. Overall, our results provide evidence that behavioural preferences for substrates can enhance individual camouflage of lizards in natural microhabitats, and that such adaptations may be sexually dimorphic and dependent on local environments. This research emphasizes the importance of considering links between ecology, behaviour, and appearance in studies of intraspecific colour variation and local adaptation. PMID:26804463

Divergent adaptation promotes reproductive isolation among experimental populations of the filamentous fungus Neurospora

PubMed Central

2008-01-01

Background An open, focal issue in evolutionary biology is how reproductive isolation and speciation are initiated; elucidation of mechanisms with empirical evidence has lagged behind theory. Under ecological speciation, reproductive isolation between populations is predicted to evolve incidentally as a by-product of adaptation to divergent environments. The increased genetic diversity associated with interspecific hybridization has also been theorized to promote the development of reproductive isolation among independent populations. Using the fungal model Neurospora, we founded experimental lineages from both intra- and interspecific crosses, and evolved them in one of two sub-optimal, selective environments. We then measured the influence that initial genetic diversity and the direction of selection (parallel versus divergent) had on the evolution of reproductive isolation. Results When assayed in the selective environment in which they were evolved, lineages typically had greater asexual fitness than the progenitors and the lineages that were evolved in the alternate, selective environment. Assays for reproductive isolation showed that matings between lineages that were adapted to the same environment had greater sexual reproductive success than matings between lineages that were adapted to different environments. Evidence of this differential reproductive success was observed at two stages of the sexual cycle. For one of the two observed incompatibility phenotypes, results from genetic analyses were consistent with a two-locus, two-allele model with asymmetric (gender-specific), antagonistic epistasis. The effects of divergent adaptation on reproductive isolation were more pronounced for populations with greater initial genetic variation. Conclusion Divergent selection resulted in divergent adaptation and environmental specialization, consistent with fixation of different alleles in different environments. When brought together by mating, these alleles interacted negatively and had detrimental effects on sexual reproductive success, in agreement with the Dobzhansky-Muller model of genetic incompatibilities. As predicted by ecological speciation, greater reproductive isolation was observed among divergent-adapted lineages than among parallel-adapted lineages. These results support that, given adequate standing genetic variation, divergent adaptation can indirectly cause the evolution of reproductive isolation, and eventually lead to speciation. PMID:18237415

Pharmacological induction of skin pigmentation unveils the neuroendocrine circuit regulated by light.

PubMed

Bertolesi, Gabriel E; Vazhappilly, Sherene T; Hehr, Carrie L; McFarlane, Sarah

2016-03-01

Light-regulated skin colour change is an important physiological process in invertebrates and lower vertebrates, and includes daily circadian variation and camouflage (i.e. background adaptation). The photoactivation of melanopsin-expressing retinal ganglion cells (mRGCs) in the eye initiates an uncharacterized neuroendocrine circuit that regulates melanin dispersion/aggregation through the secretion of alpha-melanocyte-stimulating hormone (α-MSH). We developed experimental models of normal or enucleated Xenopus embryos, as well as in situ cultures of skin of isolated dorsal head and tails, to analyse pharmacological induction of skin pigmentation and α-MSH synthesis. Both processes are triggered by a melanopsin inhibitor, AA92593, as well as chloride channel modulators. The AA9253 effect is eye-dependent, while functional data in vivo point to GABAA receptors expressed on pituitary melanotrope cells as the chloride channel blocker target. Based on the pharmacological data, we suggest a neuroendocrine circuit linking mRGCs with α-MSH secretion, which is used normally during background adaptation. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Wind shear measuring on board an airliner

NASA Technical Reports Server (NTRS)

Krauspe, P.

1984-01-01

A measurement technique which continuously determines the wind vector on board an airliner during takeoff and landing is introduced. Its implementation is intended to deliver sufficient statistical background concerning low frequency wind changes in the atmospheric boundary layer and extended knowledge about deterministic wind shear modeling. The wind measurement scheme is described and the adaptation of apparatus onboard an A300 airbus is shown. Preliminary measurements made during level flight demonstrate the validity of the method.

Adaptive optics in spinning disk microscopy: improved contrast and brightness by a simple and fast method.

PubMed

Fraisier, V; Clouvel, G; Jasaitis, A; Dimitrov, A; Piolot, T; Salamero, J

2015-09-01

Multiconfocal microscopy gives a good compromise between fast imaging and reasonable resolution. However, the low intensity of live fluorescent emitters is a major limitation to this technique. Aberrations induced by the optical setup, especially the mismatch of the refractive index and the biological sample itself, distort the point spread function and further reduce the amount of detected photons. Altogether, this leads to impaired image quality, preventing accurate analysis of molecular processes in biological samples and imaging deep in the sample. The amount of detected fluorescence can be improved with adaptive optics. Here, we used a compact adaptive optics module (adaptive optics box for sectioning optical microscopy), which was specifically designed for spinning disk confocal microscopy. The module overcomes undesired anomalies by correcting for most of the aberrations in confocal imaging. Existing aberration detection methods require prior illumination, which bleaches the sample. To avoid multiple exposures of the sample, we established an experimental model describing the depth dependence of major aberrations. This model allows us to correct for those aberrations when performing a z-stack, gradually increasing the amplitude of the correction with depth. It does not require illumination of the sample for aberration detection, thus minimizing photobleaching and phototoxicity. With this model, we improved both signal-to-background ratio and image contrast. Here, we present comparative studies on a variety of biological samples. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

A Content-Adaptive Analysis and Representation Framework for Audio Event Discovery from "Unscripted" Multimedia

NASA Astrophysics Data System (ADS)

Radhakrishnan, Regunathan; Divakaran, Ajay; Xiong, Ziyou; Otsuka, Isao

2006-12-01

We propose a content-adaptive analysis and representation framework to discover events using audio features from "unscripted" multimedia such as sports and surveillance for summarization. The proposed analysis framework performs an inlier/outlier-based temporal segmentation of the content. It is motivated by the observation that "interesting" events in unscripted multimedia occur sparsely in a background of usual or "uninteresting" events. We treat the sequence of low/mid-level features extracted from the audio as a time series and identify subsequences that are outliers. The outlier detection is based on eigenvector analysis of the affinity matrix constructed from statistical models estimated from the subsequences of the time series. We define the confidence measure on each of the detected outliers as the probability that it is an outlier. Then, we establish a relationship between the parameters of the proposed framework and the confidence measure. Furthermore, we use the confidence measure to rank the detected outliers in terms of their departures from the background process. Our experimental results with sequences of low- and mid-level audio features extracted from sports video show that "highlight" events can be extracted effectively as outliers from a background process using the proposed framework. We proceed to show the effectiveness of the proposed framework in bringing out suspicious events from surveillance videos without any a priori knowledge. We show that such temporal segmentation into background and outliers, along with the ranking based on the departure from the background, can be used to generate content summaries of any desired length. Finally, we also show that the proposed framework can be used to systematically select "key audio classes" that are indicative of events of interest in the chosen domain.

Genetic exchange of fimbrial alleles exemplifies the adaptive virulence strategy of Porphyromonas gingivalis.

PubMed

Kerr, Jennifer E; Abramian, Jared R; Dao, Doan-Hieu V; Rigney, Todd W; Fritz, Jamie; Pham, Tan; Gay, Isabel; Parthasarathy, Kavitha; Wang, Bing-yan; Zhang, Wenjian; Tribble, Gena D

2014-01-01

Porphyromonas gingivalis is a gram-negative anaerobic bacterium, a member of the human oral microbiome, and a proposed "keystone" pathogen in the development of chronic periodontitis, an inflammatory disease of the gingiva. P. gingivalis is a genetically diverse species, and is able to exchange chromosomal DNA between strains by natural competence and conjugation. In this study, we investigate the role of horizontal DNA transfer as an adaptive process to modify behavior, using the major fimbriae as our model system, due to their critical role in mediating interactions with the host environment. We show that P. gingivalis is able to exchange fimbrial allele types I and IV into four distinct strain backgrounds via natural competence. In all recombinants, we detected a complete exchange of the entire fimA allele, and the rate of exchange varies between the different strain backgrounds. In addition, gene exchange within other regions of the fimbrial genetic locus was identified. To measure the biological implications of these allele swaps we compared three genotypes of fimA in an isogenic background, strain ATCC 33277. We demonstrate that exchange of fimbrial allele type results in profound phenotypic changes, including the quantity of fimbriae elaborated, membrane blebbing, auto-aggregation and other virulence-associated phenotypes. Replacement of the type I allele with either the type III or IV allele resulted in increased invasion of gingival fibroblast cells relative to the isogenic parent strain. While genetic variability is known to impact host-microbiome interactions, this is the first study to quantitatively assess the adaptive effect of exchanging genes within the pan genome cloud. This is significant as it presents a potential mechanism by which opportunistic pathogens may acquire the traits necessary to modify host-microbial interactions.

A novel star extraction method based on modified water flow model

NASA Astrophysics Data System (ADS)

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Ouyang, Zibiao; Yang, Yanqiang

2017-11-01

Star extraction is the essential procedure for attitude measurement of star sensor. The great challenge for star extraction is to segment star area exactly from various noise and background. In this paper, a novel star extraction method based on Modified Water Flow Model(MWFM) is proposed. The star image is regarded as a 3D terrain. The morphology is adopted for noise elimination and Tentative Star Area(TSA) selection. Star area can be extracted through adaptive water flowing within TSAs. This method can achieve accurate star extraction with improved efficiency under complex conditions such as loud noise and uneven backgrounds. Several groups of different types of star images are processed using proposed method. Comparisons with existing methods are conducted. Experimental results show that MWFM performs excellently under different imaging conditions. The star extraction rate is better than 95%. The star centroid accuracy is better than 0.075 pixels. The time-consumption is also significantly reduced.

Object detection system based on multimodel saliency maps

NASA Astrophysics Data System (ADS)

Guo, Ya'nan; Luo, Chongfan; Ma, Yide

2017-03-01

Detection of visually salient image regions is extensively applied in computer vision and computer graphics, such as object detection, adaptive compression, and object recognition, but any single model always has its limitations to various images, so in our work, we establish a method based on multimodel saliency maps to detect the object, which intelligently absorbs the merits of various individual saliency detection models to achieve promising results. The method can be roughly divided into three steps: in the first step, we propose a decision-making system to evaluate saliency maps obtained by seven competitive methods and merely select the three most valuable saliency maps; in the second step, we introduce heterogeneous PCNN algorithm to obtain three prime foregrounds; and then a self-designed nonlinear fusion method is proposed to merge these saliency maps; at last, the adaptive improved and simplified PCNN model is used to detect the object. Our proposed method can constitute an object detection system for different occasions, which requires no training, is simple, and highly efficient. The proposed saliency fusion technique shows better performance over a broad range of images and enriches the applicability range by fusing different individual saliency models, this proposed system is worthy enough to be called a strong model. Moreover, the proposed adaptive improved SPCNN model is stemmed from the Eckhorn's neuron model, which is skilled in image segmentation because of its biological background, and in which all the parameters are adaptive to image information. We extensively appraise our algorithm on classical salient object detection database, and the experimental results demonstrate that the aggregation of saliency maps outperforms the best saliency model in all cases, yielding highest precision of 89.90%, better recall rates of 98.20%, greatest F-measure of 91.20%, and lowest mean absolute error value of 0.057, the value of proposed saliency evaluation EHA reaches to 215.287. We deem our method can be wielded to diverse applications in the future.

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

PubMed Central

McDowell, Julia Z.; Luber, George

2011-01-01

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

Why background colour matters to bees and flowers.

PubMed

Bukovac, Zoë; Shrestha, Mani; Garcia, Jair E; Burd, Martin; Dorin, Alan; Dyer, Adrian G

2017-05-01

Flowers are often viewed by bee pollinators against a variety of different backgrounds. On the Australian continent, backgrounds are very diverse and include surface examples of all major geological stages of the Earth's history, which have been present during the entire evolutionary period of Angiosperms. Flower signals in Australia are also representative of typical worldwide evolutionary spectral adaptations that enable successful pollination. We measured the spectral properties of 581 natural surfaces, including rocks, sand, green leaves, and dry plant materials, sampled from tropical Cairns through to the southern tip of mainland Australia. We modelled in a hexagon colour space, how interactions between background spectra and flower-like colour stimuli affect reliable discrimination and detection in bee pollinators. We calculated the extent to which a given locus would be conflated with the loci of a different flower-colour stimulus using empirically determined colour discrimination regions for bee vision. Our results reveal that whilst colour signals are robust in homogeneous background viewing conditions, there could be significant pressure on plant flowers to evolve saliently-different colours to overcome background spectral noise. We thus show that perceptual noise has a large influence on how colour information can be used in natural conditions.

Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells

PubMed Central

2011-01-01

Background Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. Results Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. Conclusions The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics. PMID:21418624

Teaching Students How to Analyze and Adapt to Audiences

ERIC Educational Resources Information Center

Seiter, John S.; Gass, Robert H.

2007-01-01

This article describes an exercise that involves providing students with a basic understanding and demonstration of audience adaptation and then asking them to practice and evaluate the skill. In this exercise the instructor begins by providing students with background on analyzing and adapting to audiences. Then the instructor collects several…

The dynamics of genetic draft in rapidly adapting populations.

PubMed

Kosheleva, Katya; Desai, Michael M

2013-11-01

The accumulation of beneficial mutations on competing genetic backgrounds in rapidly adapting populations has a striking impact on evolutionary dynamics. This effect, known as clonal interference, causes erratic fluctuations in the frequencies of observed mutations, randomizes the fixation times of successful mutations, and leaves distinct signatures on patterns of genetic variation. Here, we show how this form of "genetic draft" affects the forward-time dynamics of site frequencies in rapidly adapting asexual populations. We calculate the probability that mutations at individual sites shift in frequency over a characteristic timescale, extending Gillespie's original model of draft to the case where many strongly selected beneficial mutations segregate simultaneously. We then derive the sojourn time of mutant alleles, the expected fixation time of successful mutants, and the site frequency spectrum of beneficial and neutral mutations. Finally, we show how this form of draft affects inferences in the McDonald-Kreitman test and how it relates to recent observations that some aspects of genetic diversity are described by the Bolthausen-Sznitman coalescent in the limit of very rapid adaptation.

Depth-color fusion strategy for 3-D scene modeling with Kinect.

PubMed

Camplani, Massimo; Mantecon, Tomas; Salgado, Luis

2013-12-01

Low-cost depth cameras, such as Microsoft Kinect, have completely changed the world of human-computer interaction through controller-free gaming applications. Depth data provided by the Kinect sensor presents several noise-related problems that have to be tackled to improve the accuracy of the depth data, thus obtaining more reliable game control platforms and broadening its applicability. In this paper, we present a depth-color fusion strategy for 3-D modeling of indoor scenes with Kinect. Accurate depth and color models of the background elements are iteratively built, and used to detect moving objects in the scene. Kinect depth data is processed with an innovative adaptive joint-bilateral filter that efficiently combines depth and color by analyzing an edge-uncertainty map and the detected foreground regions. Results show that the proposed approach efficiently tackles main Kinect data problems: distance-dependent depth maps, spatial noise, and temporal random fluctuations are dramatically reduced; objects depth boundaries are refined, and nonmeasured depth pixels are interpolated. Moreover, a robust depth and color background model and accurate moving objects silhouette are generated.

Background odour induces adaptation and sensitization of olfactory receptors in the antennae of houseflies.

PubMed

Kelling, F J; Ialenti, F; Den Otter, C J

2002-06-01

The presence of background odour was found to have a small but significant effect on the sensitivity of the antennal olfactory system of houseflies, Musca domestica Linnaeus (Diptera: Muscidae), to new pulses of odour. We show that cross-adaptation and cross-sensitization between a background odour of (+/-)-1-octen-3-ol and pulses of (+/-)-1-octen-3-ol, 2-pentanone and R-(+)-limonene can occur, confirming that olfactory receptor cells are sensitive to different odours. Background odour can increase the responses to low concentration odour pulses and decrease the responses to higher concentration odour pulses. It is suggested that background odour has a larger effect on olfactory receptor cells that respond with a tonic increase of spike frequency, giving information about the level of odour concentration, i.e. the 'static' environment. Cells that respond in a phasic way only provide information on the dynamics of the olfactory environment.

Real-time people counting system using a single video camera

NASA Astrophysics Data System (ADS)

Lefloch, Damien; Cheikh, Faouzi A.; Hardeberg, Jon Y.; Gouton, Pierre; Picot-Clemente, Romain

2008-02-01

There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter is likely to occur whenever multiple persons move closely, e.g. in shopping centers. Several persons may be considered to be a single person by automatic segmentation algorithms, due to occlusions or shadows, leading to under-counting. Therefore, to account for noises, illumination and static objects changes, a background substraction is performed using an adaptive background model (updated over time based on motion information) and automatic thresholding. Furthermore, post-processing of the segmentation results is performed, in the HSV color space, to remove shadows. Moving objects are tracked using an adaptive Kalman filter, allowing a robust estimation of the objects future positions even under heavy occlusion. The system is implemented in Matlab, and gives encouraging results even at high frame rates. Experimental results obtained based on the PETS2006 datasets are presented at the end of the paper.

Right adrenal vein: comparison between adaptive statistical iterative reconstruction and model-based iterative reconstruction.

PubMed

Noda, Y; Goshima, S; Nagata, S; Miyoshi, T; Kawada, H; Kawai, N; Tanahashi, Y; Matsuo, M

2018-06-01

To compare right adrenal vein (RAV) visualisation and contrast enhancement degree on adrenal venous phase images reconstructed using adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) techniques. This prospective study was approved by the institutional review board, and written informed consent was waived. Fifty-seven consecutive patients who underwent adrenal venous phase imaging were enrolled. The same raw data were reconstructed using ASiR 40% and MBIR. The expert and beginner independently reviewed computed tomography (CT) images. RAV visualisation rates, background noise, and CT attenuation of the RAV, right adrenal gland, inferior vena cava (IVC), hepatic vein, and bilateral renal veins were compared between the two reconstruction techniques. RAV visualisation rates were higher with MBIR than with ASiR (95% versus 88%, p=0.13 in expert and 93% versus 75%, p=0.002 in beginner, respectively). RAV visualisation confidence ratings with MBIR were significantly greater than with ASiR (p<0.0001, both in the beginner and the expert). The mean background noise was significantly lower with MBIR than with ASiR (p<0.0001). Mean CT attenuation values of the RAV, right adrenal gland, IVC, and hepatic vein were comparable between the two techniques (p=0.12-0.91). Mean CT attenuation values of the bilateral renal veins were significantly higher with MBIR than with ASiR (p=0.0013 and 0.02). Reconstruction of adrenal venous phase images using MBIR significantly reduces background noise, leading to an improvement in the RAV visualisation compared with ASiR. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Geographic divergence and colour change in response to visual backgrounds and illumination intensity in bearded dragons.

PubMed

Cadena, Viviana; Smith, Kathleen R; Endler, John A; Stuart-Fox, Devi

2017-03-15

Animals may improve camouflage by both dynamic colour change and local evolutionary adaptation of colour but we have little understanding of their relative importance in colour-changing species. We tested for differences in colour change in response to background colour and light intensity in two populations of central bearded dragon lizards ( Pogona vitticeps ) representing the extremes in body coloration and geographical range. We found that bearded dragons change colour in response to various backgrounds and that colour change is affected by illumination intensity. Within-individual colour change was similar in magnitude in the two populations but varied between backgrounds. However, at the endpoints of colour change, each population showed greater similarity to backgrounds that were representative of the local habitat compared with the other population, indicating local adaptation to visual backgrounds. Our results suggest that even in species that change colour, both phenotypic plasticity and geographic divergence of coloration may contribute to improved camouflage. © 2017. Published by The Company of Biologists Ltd.

A Readout Integrated Circuit (ROIC) employing self-adaptive background current compensation technique for Infrared Focal Plane Array (IRFPA)

NASA Astrophysics Data System (ADS)

Zhou, Tong; Zhao, Jian; He, Yong; Jiang, Bo; Su, Yan

2018-05-01

A novel self-adaptive background current compensation circuit applied to infrared focal plane array is proposed in this paper, which can compensate the background current generated in different conditions. Designed double-threshold detection strategy is to estimate and eliminate the background currents, which could significantly reduce the hardware overhead and improve the uniformity among different pixels. In addition, the circuit is well compatible to various categories of infrared thermo-sensitive materials. The testing results of a 4 × 4 experimental chip showed that the proposed circuit achieves high precision, wide application and high intelligence. Tape-out of the 320 × 240 readout circuit, as well as the bonding, encapsulation and imaging verification of uncooled infrared focal plane array, have also been completed.

Application of RNAMlet to surface defect identification of steels

NASA Astrophysics Data System (ADS)

Xu, Ke; Xu, Yang; Zhou, Peng; Wang, Lei

2018-06-01

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.

High blood pressure and visual sensitivity

NASA Astrophysics Data System (ADS)

Eisner, Alvin; Samples, John R.

2003-09-01

The study had two main purposes: (1) to determine whether the foveal visual sensitivities of people treated for high blood pressure (vascular hypertension) differ from the sensitivities of people who have not been diagnosed with high blood pressure and (2) to understand how visual adaptation is related to standard measures of systemic cardiovascular function. Two groups of middle-aged subjects-hypertensive and normotensive-were examined with a series of test/background stimulus combinations. All subjects met rigorous inclusion criteria for excellent ocular health. Although the visual sensitivities of the two subject groups overlapped extensively, the age-related rate of sensitivity loss was, for some measures, greater for the hypertensive subjects, possibly because of adaptation differences between the two groups. Overall, the degree of steady-state sensitivity loss resulting from an increase of background illuminance (for 580-nm backgrounds) was slightly less for the hypertensive subjects. Among normotensive subjects, the ability of a bright (3.8-log-td), long-wavelength (640-nm) adapting background to selectively suppress the flicker response of long-wavelength-sensitive (LWS) cones was related inversely to the ratio of mean arterial blood pressure to heart rate. The degree of selective suppression was also related to heart rate alone, and there was evidence that short-term changes of cardiovascular response were important. The results suggest that (1) vascular hypertension, or possibly its treatment, subtly affects visual function even in the absence of eye disease and (2) changes in blood flow affect retinal light-adaptation processes involved in the selective suppression of the flicker response from LWS cones caused by bright, long-wavelength backgrounds.

The biology of mass extinction: a palaeontological view

NASA Technical Reports Server (NTRS)

Jablonski, D.; Raup, D. M. (Principal Investigator)

1989-01-01

Extinctions are not biologically random: certain taxa or functional/ecological groups are more extinction-prone than others. Analysis of molluscan survivorship patterns for the end-Cretaceous mass extinctions suggests that some traits that tend to confer extinction resistance during times of normal ('background') levels of extinction are ineffectual during mass extinction. For genera, high species-richness and possession of widespread individual species imparted extinction-resistance during background times but not during the mass extinction, when overall distribution of the genus was an important factor. Reanalysis of Hoffman's (1986) data (Neues Jb. Geol. Palaont. Abh. 172, 219) on European bivalves, and preliminary analysis of a new northern European data set, reveals a similar change in survivorship rules, as do data scattered among other taxa and extinction events. Thus taxa and adaptations can be lost not because they were poorly adapted by the standards of the background processes that constitute the bulk of geological time, but because they lacked--or were not linked to--the organismic, species-level or clade-level traits favoured under mass-extinction conditions. Mass extinctions can break the hegemony of species-rich, well-adapted clades and thereby permit radiation of taxa that had previously been minor faunal elements; no net increase in the adaptation of the biota need ensue. Although some large-scale evolutionary trends transcend mass extinctions, post extinction evolutionary pathways are often channelled in directions not predictable from evolutionary patters during background times.

An efficient background modeling approach based on vehicle detection

NASA Astrophysics Data System (ADS)

Wang, Jia-yan; Song, Li-mei; Xi, Jiang-tao; Guo, Qing-hua

2015-10-01

The existing Gaussian Mixture Model(GMM) which is widely used in vehicle detection suffers inefficiency in detecting foreground image during the model phase, because it needs quite a long time to blend the shadows in the background. In order to overcome this problem, an improved method is proposed in this paper. First of all, each frame is divided into several areas(A, B, C and D), Where area A, B, C and D are decided by the frequency and the scale of the vehicle access. For each area, different new learning rate including weight, mean and variance is applied to accelerate the elimination of shadows. At the same time, the measure of adaptive change for Gaussian distribution is taken to decrease the total number of distributions and save memory space effectively. With this method, different threshold value and different number of Gaussian distribution are adopted for different areas. The results show that the speed of learning and the accuracy of the model using our proposed algorithm surpass the traditional GMM. Probably to the 50th frame, interference with the vehicle has been eliminated basically, and the model number only 35% to 43% of the standard, the processing speed for every frame approximately has a 20% increase than the standard. The proposed algorithm has good performance in terms of elimination of shadow and processing speed for vehicle detection, it can promote the development of intelligent transportation, which is very meaningful to the other Background modeling methods.

Latent variable method for automatic adaptation to background states in motor imagery BCI

NASA Astrophysics Data System (ADS)

Dagaev, Nikolay; Volkova, Ksenia; Ossadtchi, Alexei

2018-02-01

Objective. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. Approach. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model’s parameters, we suggest to use the expectation maximization algorithm. The proposed method is aimed at assessing characteristics of background states without any corresponding data labeling. In the context of asynchronous motor imagery paradigm, we applied this method to the real data from twelve able-bodied subjects with open/closed eyes serving as background states. Main results. We found that the latent variable method improved classification of target states compared to the baseline method (in seven of twelve subjects). In addition, we found that our method was also capable of background states recognition (in six of twelve subjects). Significance. Without any supervised information on background states, the latent variable method provides a way to improve classification in BCI by taking background states into account at the training stage and then by making decisions on target states weighted by posterior probabilities of background states at the prediction stage.

Culture.

PubMed

Smith, Timothy B; Rodríguez, Melanie Domenech; Bernal, Guillermo

2011-02-01

This article summarizes the definitions, means, and research of adapting psychotherapy to clients' cultural backgrounds. We begin by reviewing the prevailing definitions of cultural adaptation and providing a clinical example. We present an original meta-analysis of 65 experimental and quasi-experimental studies involving 8,620 participants. The omnibus effect size of d = .46 indicates that treatments specifically adapted for clients of color were moderately more effective with that clientele than traditional treatments. The most effective treatments tended to be those with greater numbers of cultural adaptations. Mental health services targeted to a specific cultural group were several times more effective than those provided to clients from a variety of cultural backgrounds. We recommend a series of research-supported therapeutic practices that account for clients' culture, with culture-specific treatments being more effective than generally culture-sensitive treatments. © 2010 Wiley Periodicals, Inc.

Fantastic animals as an experimental model to teach animal adaptation

PubMed Central

Guidetti, Roberto; Baraldi, Laura; Calzolai, Caterina; Pini, Lorenza; Veronesi, Paola; Pederzoli, Aurora

2007-01-01

Background Science curricula and teachers should emphasize evolution in a manner commensurate with its importance as a unifying concept in science. The concept of adaptation represents a first step to understand the results of natural selection. We settled an experimental project of alternative didactic to improve knowledge of organism adaptation. Students were involved and stimulated in learning processes by creative activities. To set adaptation in a historic frame, fossil records as evidence of past life and evolution were considered. Results The experimental project is schematized in nine phases: review of previous knowledge; lesson on fossils; lesson on fantastic animals; planning an imaginary world; creation of an imaginary animal; revision of the imaginary animals; adaptations of real animals; adaptations of fossil animals; and public exposition. A rubric to evaluate the student's performances is reported. The project involved professors and students of the University of Modena and Reggio Emilia and of the "G. Marconi" Secondary School of First Degree (Modena, Italy). Conclusion The educational objectives of the project are in line with the National Indications of the Italian Ministry of Public Instruction: knowledge of the characteristics of living beings, the meanings of the term "adaptation", the meaning of fossils, the definition of ecosystem, and the particularity of the different biomes. At the end of the project, students will be able to grasp particular adaptations of real organisms and to deduce information about the environment in which the organism evolved. This project allows students to review previous knowledge and to form their personalities. PMID:17767729

Professional Development in Adapted Physical Education with Graduate Web-Based Professional Learning

ERIC Educational Resources Information Center

Sato, Takahiro; Haegele, Justin A.

2017-01-01

Background: The field of adapted physical education (APE) has long struggled to overcome significant and persistent personnel shortages [Healy, S., M. E. Block, and J. Judge. 2014. "Certified Adapted Physical Educator's Perceptions of Advantages and Disadvantages of Online Teacher Development." "Palaestra" 28 (4): 14-16].…

Impact of Cultural Exposure on Young Chinese Students' Adaptation in a UK Business School

ERIC Educational Resources Information Center

Wang, Yi; Harding, Richard; Mai, Li-Wei

2012-01-01

This study examines young Chinese students' (born post 1985) adaptation to cultural exposure in the UK. Built from data collected from in-depth interviews, the research establishes that, through direct communication with students from various cultural backgrounds during teamwork, the Chinese students adapt to varying degrees in ideology,…

A Comparison between 3D Model Results Using Two Different Collision Schemes: Forward Scattering vs. Hard Sphere Collision

NASA Astrophysics Data System (ADS)

Lee, Y.; Combi, M. R.; Tenishev, V.; Bougher, S. W.; Johnson, R. E.; Tully, C.

2016-12-01

The recent observations of the Martian geomorphology suggest that water has played a critical role in forming the present status of the Martian atmosphere and environment. The inventory of water has been depleted throughout the planet's geologic time via various mechanisms from the surface to the uppermost atmosphere where the Sun-Mars interaction occurs. During the current epoch, dissociative recombination of O2+ is suggested as the main nonthermal mechanism that regulates the escape of atomic O, forming the hot O corona. A nascent hot O atom produced deep in the thermosphere undergoes collisions with the background thermal species, where the particle can lose energy and become thermalized before it reaches the collisionless regime and escape. The major hot O collisions with the background species that contribute to the thermalization of hot O are Ohot-Ocold, Ohot-CO2,cold, Ohot-COcold, and Ohot-N2,cold. In order to describe these collisions, there have been different collisions schemes used by the previous models. One of the most realistic descriptions involves using angular differential cross sections, and the simplest approach is using isotropic collision cross sections. Here, we present a comparison between the 3D model results using two different collision schemes to find equivalent hard sphere collision cross sections that satisfy the effects from using forward scattering cross sections. We adapted the newly calculated angular differential cross sections to the major hot O collisions. The hot O corona is simulated by coupling our Mars application of the 3D Adaptive Mesh Particle Simulator (M-AMPS) [Tenishev et al., 2008, 2013] and the Mars Global Ionosphere-Thermosphere Model (M-GITM) [Bougher et al., 2015].

Adaptive sampling of AEM transients

NASA Astrophysics Data System (ADS)

Di Massa, Domenico; Florio, Giovanni; Viezzoli, Andrea

2016-02-01

This paper focuses on the sampling of the electromagnetic transient as acquired by airborne time-domain electromagnetic (TDEM) systems. Typically, the sampling of the electromagnetic transient is done using a fixed number of gates whose width grows logarithmically (log-gating). The log-gating has two main benefits: improving the signal to noise (S/N) ratio at late times, when the electromagnetic signal has amplitudes equal or lower than the natural background noise, and ensuring a good resolution at the early times. However, as a result of fixed time gates, the conventional log-gating does not consider any geological variations in the surveyed area, nor the possibly varying characteristics of the measured signal. We show, using synthetic models, how a different, flexible sampling scheme can increase the resolution of resistivity models. We propose a new sampling method, which adapts the gating on the base of the slope variations in the electromagnetic (EM) transient. The use of such an alternative sampling scheme aims to get more accurate inverse models by extracting the geoelectrical information from the measured data in an optimal way.

A novel partitioning method for block-structured adaptive meshes

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

Fu, Lin, E-mail: lin.fu@tum.de; Litvinov, Sergej, E-mail: sergej.litvinov@aer.mw.tum.de; Hu, Xiangyu Y., E-mail: xiangyu.hu@tum.de

We propose a novel partitioning method for block-structured adaptive meshes utilizing the meshless Lagrangian particle concept. With the observation that an optimum partitioning has high analogy to the relaxation of a multi-phase fluid to steady state, physically motivated model equations are developed to characterize the background mesh topology and are solved by multi-phase smoothed-particle hydrodynamics. In contrast to well established partitioning approaches, all optimization objectives are implicitly incorporated and achieved during the particle relaxation to stationary state. Distinct partitioning sub-domains are represented by colored particles and separated by a sharp interface with a surface tension model. In order to obtainmore » the particle relaxation, special viscous and skin friction models, coupled with a tailored time integration algorithm are proposed. Numerical experiments show that the present method has several important properties: generation of approximately equal-sized partitions without dependence on the mesh-element type, optimized interface communication between distinct partitioning sub-domains, continuous domain decomposition which is physically localized and implicitly incremental. Therefore it is particularly suitable for load-balancing of high-performance CFD simulations.« less

A novel partitioning method for block-structured adaptive meshes

NASA Astrophysics Data System (ADS)

Fu, Lin; Litvinov, Sergej; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-07-01

We propose a novel partitioning method for block-structured adaptive meshes utilizing the meshless Lagrangian particle concept. With the observation that an optimum partitioning has high analogy to the relaxation of a multi-phase fluid to steady state, physically motivated model equations are developed to characterize the background mesh topology and are solved by multi-phase smoothed-particle hydrodynamics. In contrast to well established partitioning approaches, all optimization objectives are implicitly incorporated and achieved during the particle relaxation to stationary state. Distinct partitioning sub-domains are represented by colored particles and separated by a sharp interface with a surface tension model. In order to obtain the particle relaxation, special viscous and skin friction models, coupled with a tailored time integration algorithm are proposed. Numerical experiments show that the present method has several important properties: generation of approximately equal-sized partitions without dependence on the mesh-element type, optimized interface communication between distinct partitioning sub-domains, continuous domain decomposition which is physically localized and implicitly incremental. Therefore it is particularly suitable for load-balancing of high-performance CFD simulations.

Strategies for Reforestation under Uncertain Future Climates: Guidelines for Alberta, Canada

PubMed Central

Gray, Laura K.; Hamann, Andreas

2011-01-01

Background Commercial forestry programs normally use locally collected seed for reforestation under the assumption that tree populations are optimally adapted to local environments. However, in western Canada this assumption is no longer valid because of climate trends that have occurred over the last several decades. The objective of this study is to show how we can arrive at reforestation recommendations with alternative species and genotypes that are viable under a majority of climate change scenarios. Methodology/Principal Findings In a case study for commercially important tree species of Alberta, we use an ecosystem-based bioclimate envelope modeling approach for western North America to project habitat for locally adapted populations of tree species using multi-model climate projections for the 2020s, 2050s and 2080s. We find that genotypes of species that are adapted to drier climatic conditions will be the preferred planting stock over much of the boreal forest that is commercially managed. Interestingly, no alternative species that are currently not present in Alberta can be recommended with any confidence. Finally, we observe large uncertainties in projections of suitable habitat that make reforestation planning beyond the 2050s difficult for most species. Conclusion/Significance More than 50,000 hectares of forests are commercially planted every year in Alberta. Choosing alternative planting stock, suitable for expected future climates, could therefore offer an effective climate change adaptation strategy at little additional cost. Habitat projections for locally adapted tree populations under observed climate change conform well to projections for the 2020s, which suggests that it is a safe strategy to change current reforestation practices and adapt to new climatic realities through assisted migration prescriptions. PMID:21853061

The scotopic threshold response of the dark-adapted electroretinogram of the mouse.

PubMed

Saszik, Shannon M; Robson, John G; Frishman, Laura J

2002-09-15

The most sensitive response in the dark-adapted electroretinogram (ERG), the scotopic threshold response (STR) which originates from the proximal retina, has been identified in several mammals including humans, but previously not in the mouse. The current study established the presence and assessed the nature of the mouse STR. ERGs were recorded from adult wild-type C57/BL6 mice anaesthetized with ketamine (70 mg kg(-1)) and xylazine (7 mg kg(-1)). Recordings were between DTL fibres placed under contact lenses on the two eyes. Monocular test stimuli were brief flashes (lambda(max) 462 nm; -6.1 to +1.8 log scotopic Troland seconds(sc td s)) under fully dark-adapted conditions and in the presence of steady adapting backgrounds (-3.2 to -1.7 log sc td). For the weakest test stimuli, ERGs consisted of a slow negative potential maximal approximately 200 ms after the flash, with a small positive potential preceding it. The negative wave resembled the STR of other species. As intensity was increased, the negative potential saturated but the positive potential (maximal approximately 110 ms) continued to grow as the b-wave. For stimuli that saturated the b-wave, the a-wave emerged. For stimulus strengths up to those at which the a-wave emerged, ERG amplitudes measured at fixed times after the flash (110 and 200 ms) were fitted with a model assuming an initially linear rise of response amplitude with intensity, followed by saturation of five components of declining sensitivity: a negative STR (nSTR), a positive STR (pSTR), a positive scotopic response (pSR), PII (the bipolar cell component) and PIII (the photoreceptor component). The nSTR and pSTR were approximately 3 times more sensitive than the pSR, which was approximately 7 times more sensitive than PII. The sensitive positive components dominated the b-wave up to > 5 % of its saturated amplitude. Pharmacological agents that suppress proximal retinal activity (e.g. GABA) minimized the pSTR, nSTR and pSR, essentially isolating PII which rose linearly with intensity before showing hyperbolic saturation. The nSTR, pSTR and pSR were desensitized by weaker backgrounds than those desensitizing PII. In conclusion, ERG components of proximal retinal origin that are more sensitive to test flashes and adapting backgrounds than PII provide the 'threshold' negative and positive (b-wave) responses of the mouse dark-adapted ERG. These results support the use of the mouse ERG in studies of proximal retinal function.

Annual Research Review: The Neurobiology and Physiology of Resilience and Adaptation across the Life Course

ERIC Educational Resources Information Center

Karatoreos, Ilia N.; McEwen, Bruce S.

2013-01-01

Background: Adaptation is key to survival. An organism must adapt to environmental challenges in order to be able to thrive in the environment in which they find themselves. Resilience can be thought of as a measure of the ability of an organism to adapt, and to withstand challenges to its stability. In higher animals, the brain is a key player in…

[On the problems of the evolutionary optimization of life history. II. To justification of optimization criterion for nonlinear Leslie model].

PubMed

Pasekov, V P

2013-03-01

The paper considers the problems in the adaptive evolution of life-history traits for individuals in the nonlinear Leslie model of age-structured population. The possibility to predict adaptation results as the values of organism's traits (properties) that provide for the maximum of a certain function of traits (optimization criterion) is studied. An ideal criterion of this type is Darwinian fitness as a characteristic of success of an individual's life history. Criticism of the optimization approach is associated with the fact that it does not take into account the changes in the environmental conditions (in a broad sense) caused by evolution, thereby leading to losses in the adequacy of the criterion. In addition, the justification for this criterion under stationary conditions is not usually rigorous. It has been suggested to overcome these objections in terms of the adaptive dynamics theory using the concept of invasive fitness. The reasons are given that favor the application of the average number of offspring for an individual, R(L), as an optimization criterion in the nonlinear Leslie model. According to the theory of quantitative genetics, the selection for fertility (that is, for a set of correlated quantitative traits determined by both multiple loci and the environment) leads to an increase in R(L). In terms of adaptive dynamics, the maximum R(L) corresponds to the evolutionary stability and, in certain cases, convergent stability of the values for traits. The search for evolutionarily stable values on the background of limited resources for reproduction is a problem of linear programming.

On Adaptive Cell-Averaging CFAR (Constant False-Alarm Rate) Radar Signal Detection

DTIC Science & Technology

1987-10-01

SIICILE COPY 4 F FInI Tedwill Rlmrt to October 197 00 C\\JT ON ADAPTIVE CELL-AVERA81NG CFAR I RADAR SIGNAL DETECTION Syracuse University Mourud krket...NY 13441-5700 ELEMENT NO. NO. NO ACCESSION NO. 11. TITLE (Include Security Classification) 61102F 2’ 05 J8 PD - ON ADAPTIVE CELL-AVERAGING CFAR RADAR... CFAR ). One approach to adaptive detection in nonstationary noise and clutter background is to compare the processed target signal to an adaptive

Animal Models of Inflammasomopathies Reveal Roles for Innate but not Adaptive Immunity

PubMed Central

Brydges, Susannah D; Mueller, James L; McGeough, Matthew D; Pena, Carla A; Misaghi, Amirhossein; Gandhi, Chhavi; Putnam, Chris D; Boyle, David L; Firestein, Gary S; Horner, Anthony A; Soroosh, Pejman; Watford, Wendy T; O’Shea, John J; Kastner, Daniel L; Hoffman, Hal M

2009-01-01

SUMMARY Cryopyrin (NALP3) mediates formation of the inflammasome, a protein complex responsible for cleavage of pro-IL-1β to its active form. Mutations in the cryopyrin gene, NLRP3, cause the autoinflammatory disease spectrum: cryopyrin-associated periodic syndromes (CAPS). The central role of IL-1β in CAPS is supported by the remarkable response to IL-1 targeted therapy. We developed two novel Nlrp3 mutant knock-in mouse strains to model CAPS to examine the role of other inflammatory mediators and adaptive immune responses in an innate immune driven disease. These mice had systemic inflammation and poor growth, similar to some human CAPS patients, and demonstrated early mortality, primarily mediated by myeloid cells. Mating these mutant mice to various knock-out backgrounds confirmed the mouse disease phenotype required an intact inflammasome, was only partially dependent on IL-1β, and was independent of T cells. This data suggests CAPS are true inflammasomopathies and provide insight for more common inflammatory disorders. PMID:19501000

Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

PubMed Central

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks. PMID:22163582

Testing model for prediction system of 1-AU arrival times of CME-associated interplanetary shocks

NASA Astrophysics Data System (ADS)

Ogawa, Tomoya; den, Mitsue; Tanaka, Takashi; Sugihara, Kohta; Takei, Toshifumi; Amo, Hiroyoshi; Watari, Shinichi

We test a model to predict arrival times of interplanetary shock waves associated with coronal mass ejections (CMEs) using a three-dimensional adaptive mesh refinement (AMR) code. The model is used for the prediction system we develop, which has a Web-based user interface and aims at people who is not familiar with operation of computers and numerical simulations or is not researcher. We apply the model to interplanetary CME events. We first choose coronal parameters so that property of background solar wind observed by ACE space craft is reproduced. Then we input CME parameters observed by SOHO/LASCO. Finally we compare the predicted arrival times with observed ones. We describe results of the test and discuss tendency of the model.

Intelligent Chatter Bot for Regulation Search

NASA Astrophysics Data System (ADS)

De Luise, María Daniela López; Pascal, Andrés; Saad, Ben; Álvarez, Claudia; Pescio, Pablo; Carrilero, Patricio; Malgor, Rafael; Díaz, Joaquín

2016-01-01

This communication presents a functional prototype, named PTAH, implementing a linguistic model focused on regulations in Spanish. Its global architecture, the reasoning model and short statistics are provided for the prototype. It is mainly a conversational robot linked to an Expert System by a module with many intelligent linguistic filters, implementing the reasoning model of an expert. It is focused on bylaws, regulations, jurisprudence and customized background representing entity mission, vision and profile. This Structure and model are generic enough to self-adapt to any regulatory environment, but as a first step, it was limited to an academic field. This way it is possible to limit the slang and data numbers. The foundations of the linguistic model are also outlined and the way the architecture implements the key features of the behavior.

Use of model calibration to achieve high accuracy in analysis of computer networks

DOEpatents

Frogner, Bjorn; Guarro, Sergio; Scharf, Guy

2004-05-11

A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.

Cultural differences in the lateral occipital complex while viewing incongruent scenes

PubMed Central

Yang, Yung-Jui; Goh, Joshua; Hong, Ying-Yi; Park, Denise C.

2010-01-01

Converging behavioral and neuroimaging evidence indicates that culture influences the processing of complex visual scenes. Whereas Westerners focus on central objects and tend to ignore context, East Asians process scenes more holistically, attending to the context in which objects are embedded. We investigated cultural differences in contextual processing by manipulating the congruence of visual scenes presented in an fMR-adaptation paradigm. We hypothesized that East Asians would show greater adaptation to incongruent scenes, consistent with their tendency to process contextual relationships more extensively than Westerners. Sixteen Americans and 16 native Chinese were scanned while viewing sets of pictures consisting of a focal object superimposed upon a background scene. In half of the pictures objects were paired with congruent backgrounds, and in the other half objects were paired with incongruent backgrounds. We found that within both the right and left lateral occipital complexes, Chinese participants showed significantly greater adaptation to incongruent scenes than to congruent scenes relative to American participants. These results suggest that Chinese were more sensitive to contextual incongruity than were Americans and that they reacted to incongruent object/background pairings by focusing greater attention on the object. PMID:20083532

Design Criteria for Adaptive Roadway Lighting

DOT National Transportation Integrated Search

2014-07-01

This report provides the background and analysis used to develop criteria for the implementation of an adaptive lighting system for roadway lighting. Based on the analysis of crashes and lighting performance, a series of criteria and the associated d...

Adaptive spatial filtering of daytime sky noise in a satellite quantum key distribution downlink receiver

NASA Astrophysics Data System (ADS)

Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.

2016-02-01

Spatial filtering is an important technique for reducing sky background noise in a satellite quantum key distribution downlink receiver. Atmospheric turbulence limits the extent to which spatial filtering can reduce sky noise without introducing signal losses. Using atmospheric propagation and compensation simulations, the potential benefit of adaptive optics (AO) to secure key generation (SKG) is quantified. Simulations are performed assuming optical propagation from a low-Earth-orbit satellite to a terrestrial receiver that includes AO. Higher-order AO correction is modeled assuming a Shack-Hartmann wavefront sensor and a continuous-face-sheet deformable mirror. The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain wave-optics hardware emulator. SKG rates are calculated for a decoy-state protocol as a function of the receiver field of view for various strengths of turbulence, sky radiances, and pointing angles. The results show that at fields of view smaller than those discussed by others, AO technologies can enhance SKG rates in daylight and enable SKG where it would otherwise be prohibited as a consequence of background optical noise and signal loss due to propagation and turbulence effects.

Real-time vehicle noise cancellation techniques for gunshot acoustics

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald

2012-06-01

Acoustical sniper positioning systems rely on the detection and direction-of-arrival (DOA) estimation of the shockwave and the muzzle blast in order to provide an estimate of a potential snipers location. Field tests have shown that detecting and estimating the DOA of the muzzle blast is a rather difficult task in the presence of background noise sources, e.g., vehicle noise, especially in long range detection and absorbing terrains. In our previous work presented in the 2011 edition of this conference we highlight the importance of improving the SNR of the gunshot signals prior to the detection and recognition stages, aiming at lowering the false alarm and miss-detection rates and, thereby, increasing the reliability of the system. This paper reports on real-time noise cancellation techniques, like Spectral Subtraction and Adaptive Filtering, applied to gunshot signals. Our model assumes the background noise as being short-time stationary and uncorrelated to the impulsive gunshot signals. In practice, relatively long periods without signal occur and can be used to estimate the noise spectrum and its first and second order statistics as required in the spectral subtraction and adaptive filtering techniques, respectively. The results presented in this work are supported with extensive simulations based on real data.

Odor-Specific Habituation Arises from Interaction of Afferent Synaptic Adaptation and Intrinsic Synaptic Potentiation in Olfactory Cortex

ERIC Educational Resources Information Center

Linster, Christiane; Menon, Alka V.; Singh, Christopher Y.; Wilson, Donald A.

2009-01-01

Segmentation of target odorants from background odorants is a fundamental computational requirement for the olfactory system and is thought to be behaviorally mediated by olfactory habituation memory. Data from our laboratory have shown that odor-specific adaptation in piriform neurons, mediated at least partially by synaptic adaptation between…

Using Adaptive Learning Technologies to Personalize Instruction to Student Interests: The Impact of Relevant Contexts on Performance and Learning Outcomes

ERIC Educational Resources Information Center

Walkington, Candace A.

2013-01-01

Adaptive learning technologies are emerging in educational settings as a means to customize instruction to learners' background, experiences, and prior knowledge. Here, a technology-based personalization intervention within an intelligent tutoring system (ITS) for secondary mathematics was used to adapt instruction to students' personal interests.…

Hybrid vs Adaptive Ensemble Kalman Filtering for Storm Surge Forecasting

NASA Astrophysics Data System (ADS)

Altaf, M. U.; Raboudi, N.; Gharamti, M. E.; Dawson, C.; McCabe, M. F.; Hoteit, I.

2014-12-01

Recent storm surge events due to Hurricanes in the Gulf of Mexico have motivated the efforts to accurately forecast water levels. Toward this goal, a parallel architecture has been implemented based on a high resolution storm surge model, ADCIRC. However the accuracy of the model notably depends on the quality and the recentness of the input data (mainly winds and bathymetry), model parameters (e.g. wind and bottom drag coefficients), and the resolution of the model grid. Given all these uncertainties in the system, the challenge is to build an efficient prediction system capable of providing accurate forecasts enough ahead of time for the authorities to evacuate the areas at risk. We have developed an ensemble-based data assimilation system to frequently assimilate available data into the ADCIRC model in order to improve the accuracy of the model. In this contribution we study and analyze the performances of different ensemble Kalman filter methodologies for efficient short-range storm surge forecasting, the aim being to produce the most accurate forecasts at the lowest possible computing time. Using Hurricane Ike meteorological data to force the ADCIRC model over a domain including the Gulf of Mexico coastline, we implement and compare the forecasts of the standard EnKF, the hybrid EnKF and an adaptive EnKF. The last two schemes have been introduced as efficient tools for enhancing the behavior of the EnKF when implemented with small ensembles by exploiting information from a static background covariance matrix. Covariance inflation and localization are implemented in all these filters. Our results suggest that both the hybrid and the adaptive approach provide significantly better forecasts than those resulting from the standard EnKF, even when implemented with much smaller ensembles.

Escape Distance in Ground-Nesting Birds Differs with Individual Level of Camouflage.

PubMed

Wilson-Aggarwal, Jared K; Troscianko, Jolyon T; Stevens, Martin; Spottiswoode, Claire N

2016-08-01

Camouflage is one of the most widespread antipredator strategies in the animal kingdom, yet no animal can match its background perfectly in a complex environment. Therefore, selection should favor individuals that use information on how effective their camouflage is in their immediate habitat when responding to an approaching threat. In a field study of African ground-nesting birds (plovers, coursers, and nightjars), we tested the hypothesis that individuals adaptively modulate their escape behavior in relation to their degree of background matching. We used digital imaging and models of predator vision to quantify differences in color, luminance, and pattern between eggs and their background, as well as the plumage of incubating adult nightjars. We found that plovers and coursers showed greater escape distances when their eggs were a poorer pattern match to the background. Nightjars sit on their eggs until a potential threat is nearby, and, correspondingly, they showed greater escape distances when the pattern and color match of the incubating adult's plumage-rather than its eggs-was a poorer match to the background. Finally, escape distances were shorter in the middle of the day, suggesting that escape behavior is mediated by both camouflage and thermoregulation.

Threshold Values for Identification of Contamination Predicted by Reduced-Order Models

DOE PAGES

Last, George V.; Murray, Christopher J.; Bott, Yi-Ju; ...

2014-12-31

The U.S. Department of Energy’s (DOE’s) National Risk Assessment Partnership (NRAP) Project is developing reduced-order models to evaluate potential impacts on underground sources of drinking water (USDWs) if CO2 or brine leaks from deep CO2 storage reservoirs. Threshold values, below which there would be no predicted impacts, were determined for portions of two aquifer systems. These threshold values were calculated using an interwell approach for determining background groundwater concentrations that is an adaptation of methods described in the U.S. Environmental Protection Agency’s Unified Guidance for Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities.

PTBS segmentation scheme for synthetic aperture radar

NASA Astrophysics Data System (ADS)

Friedland, Noah S.; Rothwell, Brian J.

1995-07-01

The Image Understanding Group at Martin Marietta Technologies in Denver, Colorado has developed a model-based synthetic aperture radar (SAR) automatic target recognition (ATR) system using an integrated resource architecture (IRA). IRA, an adaptive Markov random field (MRF) environment, utilizes information from image, model, and neighborhood resources to create a discrete, 2D feature-based world description (FBWD). The IRA FBWD features are peak, target, background and shadow (PTBS). These features have been shown to be very useful for target discrimination. The FBWD is used to accrue evidence over a model hypothesis set. This paper presents the PTBS segmentation process utilizing two IRA resources. The image resource (IR) provides generic (the physics of image formation) and specific (the given image input) information. The neighborhood resource (NR) provides domain knowledge of localized FBWD site behaviors. A simulated annealing optimization algorithm is used to construct a `most likely' PTBS state. Results on simulated imagery illustrate the power of this technique to correctly segment PTBS features, even when vehicle signatures are immersed in heavy background clutter. These segmentations also suppress sidelobe effects and delineate shadows.

A Computational Model of Afterimage Rotation in the Peripheral Drift Illusion Based on Retinal ON/OFF Responses

PubMed Central

Hayashi, Yuichiro; Ishii, Shin; Urakubo, Hidetoshi

2014-01-01

Human observers perceive illusory rotations after the disappearance of circularly repeating patches containing dark-to-light luminance. This afterimage rotation is a very powerful phenomenon, but little is known about the mechanisms underlying it. Here, we use a computational model to show that the afterimage rotation can be explained by a combination of fast light adaptation and the physiological architecture of the early visual system, consisting of ON- and OFF-type visual pathways. In this retinal ON/OFF model, the afterimage rotation appeared as a rotation of focus lines of retinal ON/OFF responses. Focus lines rotated clockwise on a light background, but counterclockwise on a dark background. These findings were consistent with the results of psychophysical experiments, which were also performed by us. Additionally, the velocity of the afterimage rotation was comparable with that observed in our psychophysical experiments. These results suggest that the early visual system (including the retina) is responsible for the generation of the afterimage rotation, and that this illusory rotation may be systematically misinterpreted by our high-level visual system. PMID:25517906

‘Newcomer adaptation’: a lens through which to understand how nursing students fit in with the real world of practice

PubMed Central

Houghton, Catherine E

2014-01-01

Aims and objectives To present a discussion on newcomer adaptation as a lens through which to understand how nursing students adapt to clinical practice and raise awareness of strategies that can be used to enhance their learning experiences. Background Socialisation is an important factor that facilitates students’ learning in the clinical setting. Therefore, it is beneficial to examine organisational socialisation literature, particularly that pertaining to newcomer adaptation. Design This is a critical review of organisational socialisation literature. Methods Seminal literature and more recent research in the field of organisational socialisation and newcomer adaptation were accessed. In addition, nursing and allied health literature examining students’ socialisation and the clinical learning environment was retrieved. Conclusions It is revealed in this article that to create an appropriate clinical learning environment, an understanding of socialisation tactics could be beneficial. Role modelling is deemed crucial to successful newcomer adaptation. Peer support is necessary but must be advocated with caution as it can have a negative impact when students form a ‘parallel community’. Students with some knowledge of the workplace tend to adapt more easily. Likewise, students’ disposition and, in particular, their confidence can also enhance the socialisation process. Relevance to clinical practice Both the organisation and the student can impact on how successfully the nursing student ‘fits in’. Understanding this through the lens of newcomer adaptation means that strategies can be put in place to facilitate this process. PMID:24455974

Influence of temperature fluctuations on infrared limb radiance: a new simulation code

NASA Astrophysics Data System (ADS)

Rialland, Valérie; Chervet, Patrick

2006-08-01

Airborne infrared limb-viewing detectors may be used as surveillance sensors in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. This background clutter, which results from small-scale fluctuations of temperature, density or pressure must therefore be analyzed and modeled. Few existing codes are able to model atmospheric structures and their impact on limb-observed radiance. SAMM-2 (SHARC-4 and MODTRAN4 Merged), the Air Force Research Laboratory (AFRL) background radiance code can be used to in order to predict the radiance fluctuation as a result of a normalized temperature fluctuation, as a function of the line-of-sight. Various realizations of cluttered backgrounds can then be computed, based on these transfer functions and on a stochastic temperature field. The existing SIG (SHARC Image Generator) code was designed to compute the cluttered background which would be observed from a space-based sensor. Unfortunately, this code was not able to compute accurate scenes as seen by an airborne sensor especially for lines-of-sight close to the horizon. Recently, we developed a new code called BRUTE3D and adapted to our configuration. This approach is based on a method originally developed in the SIG model. This BRUTE3D code makes use of a three-dimensional grid of temperature fluctuations and of the SAMM-2 transfer functions to synthesize an image of radiance fluctuations according to sensor characteristics. This paper details the working principles of the code and presents some output results. The effects of the small-scale temperature fluctuations on infrared limb radiance as seen by an airborne sensor are highlighted.

Adaptation of health care for migrants: whose responsibility?

PubMed Central

2014-01-01

Background In a context of increasing ethnic diversity, culturally competent strategies have been recommended to improve care quality and access to health care for ethnic minorities and migrants; their implementation by health professionals, however, has remained patchy. Most programs of cultural competence assume that health professionals accept that they have a responsibility to adapt to migrants, but this assumption has often remained at the level of theory. In this paper, we surveyed health professionals’ views on their responsibility to adapt. Methods Five hundred-and-sixty-nine health professionals from twenty-four inpatient and outpatient health services were selected according to their geographic location. All health care professionals were requested to complete a questionnaire about who should adapt to ethnic diversity: health professionals or patients. After a factorial analysis to identify the underlying responsibility dimensions, we performed a multilevel regression model in order to investigate individual and service covariates of responsibility attribution. Results Three dimensions emerged from the factor analysis: responsibility for the adaptation of communication, responsibility for the adaptation to the negotiation of values, and responsibility for the adaptation to health beliefs. Our results showed that the sense of responsibility for the adaptation of health care depended on the nature of the adaptation required: when the adaptation directly concerned communication with the patient, health professionals declared that they should be the ones to adapt; in relation to cultural preferences, however, the responsibility felt on the patient’s shoulders. Most respondents were unclear in relation to adaptation to health beliefs. Regression indicated that being Belgian, not being a physician, and working in a primary-care service were associated with placing the burden of responsibility on the patient. Conclusions Health care professionals do not consider it to be their responsibility to adapt to ethnic diversity. If health professionals do not feel a responsibility to adapt, they are less likely to be involved in culturally competent health care. PMID:25005021

Metabolic adaptation to a high-fat diet is associated with a change in the gut microbiota.

PubMed

Serino, Matteo; Luche, Elodie; Gres, Sandra; Baylac, Audrey; Bergé, Mathieu; Cenac, Claire; Waget, Aurelie; Klopp, Pascale; Iacovoni, Jason; Klopp, Christophe; Mariette, Jerome; Bouchez, Olivier; Lluch, Jerome; Ouarné, Francoise; Monsan, Pierre; Valet, Philippe; Roques, Christine; Amar, Jacques; Bouloumié, Anne; Théodorou, Vassilia; Burcelin, Remy

2012-04-01

The gut microbiota, which is considered a causal factor in metabolic diseases as shown best in animals, is under the dual influence of the host genome and nutritional environment. This study investigated whether the gut microbiota per se, aside from changes in genetic background and diet, could sign different metabolic phenotypes in mice. The unique animal model of metabolic adaptation was used, whereby C57Bl/6 male mice fed a high-fat carbohydrate-free diet (HFD) became either diabetic (HFD diabetic, HFD-D) or resisted diabetes (HFD diabetes-resistant, HFD-DR). Pyrosequencing of the gut microbiota was carried out to profile the gut microbial community of different metabolic phenotypes. Inflammation, gut permeability, features of white adipose tissue, liver and skeletal muscle were studied. Furthermore, to modify the gut microbiota directly, an additional group of mice was given a gluco-oligosaccharide (GOS)-supplemented HFD (HFD+GOS). Despite the mice having the same genetic background and nutritional status, a gut microbial profile specific to each metabolic phenotype was identified. The HFD-D gut microbial profile was associated with increased gut permeability linked to increased endotoxaemia and to a dramatic increase in cell number in the stroma vascular fraction from visceral white adipose tissue. Most of the physiological characteristics of the HFD-fed mice were modulated when gut microbiota was intentionally modified by GOS dietary fibres. The gut microbiota is a signature of the metabolic phenotypes independent of differences in host genetic background and diet.

Development and validation of a set of six adaptable prognosis prediction (SAP) models based on time-series real-world big data analysis for patients with cancer receiving chemotherapy: A multicenter case crossover study

PubMed Central

Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu

2017-01-01

Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592

Variables affecting the academic and social integration of nursing students.

PubMed

Zeitlin-Ophir, Iris; Melitz, Osnat; Miller, Rina; Podoshin, Pia; Mesh, Gustavo

2004-07-01

This study attempted to analyze the variables that influence the academic integration of nursing students. The theoretical model presented by Leigler was adapted to the existing conditions in a school of nursing in northern Israel. The independent variables included the student's background; amount of support received in the course of studies; extent of outside family and social commitments; satisfaction with the school's facilities and services; and level of social integration. The dependent variable was the student's level of academic integration. The findings substantiated four central hypotheses, with the study model explaining approximately 45% of the variance in the dependent variable. Academic integration is influenced by a number of variables, the most prominent of which is the social integration of the student with colleagues and educational staff. Among the background variables, country of origin was found to be significant to both social and academic integration for two main groups in the sample: Israeli-born students (both Jewish and Arab) and immigrant students.

Adaptive Functioning and Behaviour Problems in Relation to Level of Education in Children and Adolescents with Intellectual Disability

ERIC Educational Resources Information Center

de Bildt, A.; Sytema, S.; Kraijer, D.; Sparrow, S.; Minderaa, R.

2005-01-01

Background: The interrelationship between adaptive functioning, behaviour problems and level of special education was studied in 186 children with IQs ranging from 61 to 70. The objective was to increase the insight into the contribution of adaptive functioning and general and autistic behaviour problems to the level of education in children with…

Altitude, radiation, and mortality from cancer and heart disease

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

Weinberg, C.R.; Brown, K.G.; Hoel, D.G.

The variation in background radiation levels is an important source of information for estimating human risks associated with low-level exposure to ionizing radiation. Several studies conducted in the United States, correlating mortality rates for cancer with estimated background radiation levels, found an unexpected inverse relationship. Such results have been interpreted as suggesting that low levels of ionizing radiation may actually confer some benefit. An environmental factor strongly correlated with background radiation is altitude. Since there are important physiological adaptations associated with breathing thinner air, such changes may themselves influence risk. We therefore fit models that simultaneously incorporated altitude and backgroundmore » radiation as predictors of mortality. The negative correlations with background radiation seen for mortality from arteriosclerotic heart disease and cancers of the lung, the intestine, and the breast disappeared or became positive once altitude was included in the models. By contrast, the significant negative correlations with altitude persisted with adjustment for radiation. Interpretation of these results is problematic, but recent evidence implicating reactive forms of oxygen in carcinogenesis and atherosclerosis may be relevant. We conclude that the cancer correlational studies carried out in the United States using vital statistics data do not in themselves demonstrate a lack of carcinogenic effect of low radiation levels, and that reduced oxygen pressure of inspired air may be protective against certain causes of death.« less

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Adaptive Optics Communications Performance Analysis

NASA Technical Reports Server (NTRS)

Srinivasan, M.; Vilnrotter, V.; Troy, M.; Wilson, K.

2004-01-01

The performance improvement obtained through the use of adaptive optics for deep-space communications in the presence of atmospheric turbulence is analyzed. Using simulated focal-plane signal-intensity distributions, uncoded pulse-position modulation (PPM) bit-error probabilities are calculated assuming the use of an adaptive focal-plane detector array as well as an adaptively sized single detector. It is demonstrated that current practical adaptive optics systems can yield performance gains over an uncompensated system ranging from approximately 1 dB to 6 dB depending upon the PPM order and background radiation level.

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

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.

9: ADAPTATION OF PREGNANCY RISK ASSESSMENT MONITORING SYSTEM (PRAMS) AND PROVIDE A MODEL ON IT

PubMed Central

Kharaghani, Roghieh; Shariati, Mohammad; Keramat, Afsaneh; Yunesian, Masud; Moghisi, Alireza

2017-01-01

Background and aims A surveillance system helps to detect epidemics and the pattern of the problems incidence in the community and it is essential part of evidence based decision making process. This study aimed to adapt of PRAMS and provide a model on it. Methods This study was performed in 7 steps as follows: Surveillance systems in pregnancy were reviewed and appropriate system was selected for Iran by nominal group technique. Two comparative studies were conducted to determine the similarities and differences between Iran and the selected community. PRAMS method and system were adapted based on the results of the comparative studies and experts opinions. The study tool was adapted. A field trial was conducted to assess adapted PRAMS feasibility based on TELOS (technical, economic, legal, operational, and schedule) model in the city of Shahriar, located in the west of Tehran, and to compare data collection methods. Then, based on the results and consultation with related executive managers, the final model of PRAMS was suggested for Iranian health system. Results Review of the surveillance systems in pregnancy, identified six models. The results of the nominal group technique showed that, the appropriate model for Iran is PRAMS. Based on the comparative studies and expert opinions, the appropriate system and method for program was as follows: the sampling frame was composed of data in thyroid screening forms and hospital records, the sampling method was systematic, data collection methods were home and phone based surveys, and participants were women within 2 to 6 months postpartum who had a live or still birth. The study tool was adapted. Thirty-seven health volunteers collected the data in this study (technical feasibility). Any home based completed questionnaire cost 2.45 and a phone cost 1.89 USD. Many indices were achieved from the study, which were worth much more than the expenses (economic feasibility). The project was consistent with legal requirements (legal feasibility). There was no statistically significant differences in mother's participation rate between phone (90.9%) and home visit (92.8%) groups and about 90.8% of different sections of the questionnaire were completed (operational feasibility). All data collection processes took 35 days (schedule feasibility). Based on the study results, the appropriate model of surveillance system was suggested with the goals of reducing infant morbidity and mortality and promoting maternal health by influencing maternal and child health programs, and maternal behaviors during pregnancy and early infancy. Conclusion The adapted PRAMS could be considered feasible in Iran and may offer a potential solution to some data deficits in maternal and child health indicators. Moreover, by monitoring pregnancy risks and outcomes, we can assess, analyses, and modify the current prenatal care program through PRAMS widespread and periodic implementation.

Autosomal and Mitochondrial Adaptation Following Admixture: A Case Study on the Honeybees of Reunion Island

PubMed Central

Wragg, David; Techer, Maéva Angélique; Canale-Tabet, Kamila; Basso, Benjamin; Bidanel, Jean-Pierre; Labarthe, Emmanuelle; Bouchez, Olivier; Le Conte, Yves; Clémencet, Johanna; Delatte, Hélène

2018-01-01

Abstract The honeybee population of the tropical Reunion Island is a genetic admixture of the Apis mellifera unicolor subspecies, originally described in Madagascar, and of European subspecies, mainly A. m. carnica and A. m. ligustica, regularly imported to the island since the late 19th century. We took advantage of this population to study genetic admixing of the tropical-adapted indigenous and temperate-adapted European genetic backgrounds. Whole genome sequencing of 30 workers and 6 males from Reunion, compared with samples from Europe, Madagascar, Mauritius, Rodrigues, and the Seychelles, revealed the Reunion honeybee population to be composed on an average of 53.2 ± 5.9% A. m. unicolor nuclear genomic background, the rest being mainly composed of A. m. carnica and to a lesser extent A. m. ligustica. In striking contrast to this, only 1 out of the 36 honeybees from Reunion had a mitochondrial genome of European origin, suggesting selection has favored the A. m. unicolor mitotype, which is possibly better adapted to the island’s bioclimate. Local ancestry was determined along the chromosomes for all Reunion samples, and a test for preferential selection for the A. m. unicolor or European background revealed 15 regions significantly associated with the A. m. unicolor lineage and 9 regions with the European lineage. Our results provide insights into the long-term consequences of introducing exotic specimen on the nuclear and mitochondrial genomes of locally adapted populations. PMID:29202174

Genome-wide signals of positive selection in human evolution

PubMed Central

Enard, David; Messer, Philipp W.; Petrov, Dmitri A.

2014-01-01

The role of positive selection in human evolution remains controversial. On the one hand, scans for positive selection have identified hundreds of candidate loci, and the genome-wide patterns of polymorphism show signatures consistent with frequent positive selection. On the other hand, recent studies have argued that many of the candidate loci are false positives and that most genome-wide signatures of adaptation are in fact due to reduction of neutral diversity by linked deleterious mutations, known as background selection. Here we analyze human polymorphism data from the 1000 Genomes Project and detect signatures of positive selection once we correct for the effects of background selection. We show that levels of neutral polymorphism are lower near amino acid substitutions, with the strongest reduction observed specifically near functionally consequential amino acid substitutions. Furthermore, amino acid substitutions are associated with signatures of recent adaptation that should not be generated by background selection, such as unusually long and frequent haplotypes and specific distortions in the site frequency spectrum. We use forward simulations to argue that the observed signatures require a high rate of strongly adaptive substitutions near amino acid changes. We further demonstrate that the observed signatures of positive selection correlate better with the presence of regulatory sequences, as predicted by the ENCODE Project Consortium, than with the positions of amino acid substitutions. Our results suggest that adaptation was frequent in human evolution and provide support for the hypothesis of King and Wilson that adaptive divergence is primarily driven by regulatory changes. PMID:24619126

Spectral Tuning of Killer Whale (Orcinus orca) Rhodopsin: Evidence for Positive Selection and Functional Adaptation in a Cetacean Visual Pigment.

PubMed

Dungan, Sarah Z; Kosyakov, Alexander; Chang, Belinda S W

2016-02-01

Cetaceans have undergone a remarkable evolutionary transition that was accompanied by many sensory adaptations, including modification of the visual system for underwater environments. Recent sequencing of cetacean genomes has made it possible to begin exploring the molecular basis of these adaptations. In this study we use in vitro expression methods to experimentally characterize the first step of the visual transduction cascade, the light activation of rhodopsin, for the killer whale. To investigate the spectral effects of amino acid substitutions thought to correspond with absorbance shifts relative to terrestrial mammals, we used the orca gene as a background for the first site-directed mutagenesis experiments in a cetacean rhodopsin. The S292A mutation had the largest effect, and was responsible for the majority of the spectral difference between killer whale and bovine (terrestrial) rhodopsin. Using codon-based likelihood models, we also found significant evidence for positive selection in cetacean rhodopsin sequences, including on spectral tuning sites we experimentally mutated. We then investigated patterns of ecological divergence that may be correlated with rhodopsin functional variation by using a series of clade models that partitioned the data set according to phylogeny, habitat, and foraging depth zone. Only the model partitioning according to depth was significant. This suggests that foraging dives might be a selective regime influencing cetacean rhodopsin divergence, and our experimental results indicate that spectral tuning may be playing an adaptive role in this process. Our study demonstrates that combining computational and experimental methods is crucial for gaining insight into the selection pressures underlying molecular evolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Adaptive Ecosystem Climatology (AEC): Design and Development

NASA Astrophysics Data System (ADS)

deRada, S.; Penta, B.; McCarthy, S.; Gould, R. W., Jr.

2016-02-01

The concept of ecosystem-based management (EBM), recently introduced to rectify the shortcomings of single-species management policies, has been widely accepted as a basis for the conservation and management of natural resources. In line with NOAA's Integrated Ecosystem Assessment (IEA) Program, EBM is an integrated approach that considers the entire ecosystem and the interactions among species rather than focusing on individual components. This integrative approach relies on heterogeneous data, physical as well as biogeochemical data, among many others. Relative to physical data, however, marine biogeochemical records, also critical in IEA and EBM, are still lacking, both in terms of mature models and in terms of observational data availability. TheAdaptive Ecosystem Climatology (AEC) was conceived as a novel approach to address these limitations, mitigating the shortcomings of the individual components and combining their strengths to enhance decision-making activities. AEC is designed on the concept that a high-frequency climatology can be used as a baseline into which available observational data can be ingested to produce a higher accuracy product. In the absence of observations, the climatology acts as a best estimate. AEC was developed using a long-term simulation of a coupled biophysical numerical model configured for the Gulf of Mexico. Using the model results, we constructed a three-dimensional, dynamically balanced, gridded, static climatology for each calendar day. Using this `static' climatology as a background `first guess', observations from a particular date are ingested via optimal interpolation to `nudge' the climatology toward current conditions, thus providing representative fields for that date (adaptive climatology). With this adaptive approach, AEC can support a variety of EBM objectives, from fisheries, to resource management, to coastal resilience.

3-D MHD modeling and stability analysis of jet and spheromak plasmas launched into a magnetized plasma

NASA Astrophysics Data System (ADS)

Fisher, Dustin; Zhang, Yue; Wallace, Ben; Gilmore, Mark; Manchester, Ward; Arge, C. Nick

2016-10-01

The Plasma Bubble Expansion Experiment (PBEX) at the University of New Mexico uses a coaxial plasma gun to launch jet and spheromak magnetic plasma configurations into the Helicon-Cathode (HelCat) plasma device. Plasma structures launched from the gun drag frozen-in magnetic flux into the background magnetic field of the chamber providing a rich set of dynamics to study magnetic turbulence, force-free magnetic spheromaks, and shocks. Preliminary modeling is presented using the highly-developed 3-D, MHD, BATS-R-US code developed at the University of Michigan. BATS-R-US employs an adaptive mesh refinement grid that enables the capture and resolution of shock structures and current sheets, and is particularly suited to model the parameter regime under investigation. CCD images and magnetic field data from the experiment suggest the stabilization of an m =1 kink mode trailing a plasma jet launched into a background magnetic field. Results from a linear stability code investigating the effect of shear-flow as a cause of this stabilization from magnetic tension forces on the jet will be presented. Initial analyses of a possible magnetic Rayleigh Taylor instability seen at the interface between launched spheromaks and their entraining background magnetic field will also be presented. Work supported by the Army Research Office Award No. W911NF1510480.

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

PubMed

Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

2016-11-23

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

Ultraviolet radiation induces dose-dependent pigment dispersion in crustacean chromatophores.

PubMed

Gouveia, Glauce Ribeiro; Lopes, Thaís Martins; Neves, Carla Amorim; Nery, Luiz Eduardo Maia; Trindade, Gilma Santos

2004-10-01

Pigment dispersion in chromatophores as a response to UV radiation was investigated in two species of crustaceans, the crab Chasmagnathus granulata and the shrimp Palaemonetes argentinus. Eyestalkless crabs and shrimps maintained on either a black or a white background were irradiated with different UV bands. In eyestalkless crabs the significant minimal effective dose inducing pigment dispersion was 0.42 J/cm(2) for UVA and 2.15 J/cm(2) for UVB. Maximal response was achieved with 10.0 J/cm(2) UVA and 8.6 J/cm(2) UVB. UVA was more effective than UVB in inducing pigment dispersion. Soon after UV exposure, melanophores once again reached the initial stage of pigment aggregation after 45 min. Aggregated erythrophores of shrimps adapted to a white background showed significant pigment dispersion with 2.5 J/cm(2) UVA and 0.29 J/cm(2) UVC. Dispersed erythrophores of shrimps adapted to a black background did not show any significant response to UVA, UVB or UVC radiation. UVB did not induce any significant pigment dispersion in shrimps adapted to either a white or a black background. As opposed to the tanning response, which only protects against future UV exposure, the pigment dispersion response could be an important agent protecting against the harmful effects of UV radiation exposure.

3D Hall MHD-EPIC Simulations of Ganymede's Magnetosphere

NASA Astrophysics Data System (ADS)

Zhou, H.; Toth, G.; Jia, X.

2017-12-01

Fully kinetic modeling of a complete 3D magnetosphere is still computationally expensive and not feasible on current computers. While magnetohydrodynamic (MHD) models have been successfully applied to a wide range of plasma simulation, they cannot capture some important kinetic effects. We have recently developed a new modeling tool to embed the implicit particle-in-cell (PIC) model iPIC3D into the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme (BATS-R-US) magnetohydrodynamic model. This results in a kinetic model of the regions where kinetic effects are important. In addition to the MHD-EPIC modeling of the magnetosphere, the improved model presented here is now able to represent the moon as a resistive body. We use a stretched spherical grid with adaptive mesh refinement (AMR) to capture the resistive body and its boundary. A semi-implicit scheme is employed for solving the magnetic induction equation to allow time steps that are not limited by the resistivity. We have applied the model to Ganymede, the only moon in the solar system known to possess a strong intrinsic magnetic field, and included finite resistivity beneath the moon`s surface to model the electrical properties of the interior in a self-consistent manner. The kinetic effects of electrons and ions on the dayside magnetopause and tail current sheet are captured with iPIC3D. Magnetic reconnections under different upstream background conditions of several Galileo flybys are simulated to study the global reconnection rate and the magnetospheric dynamics

Hyperspectral data acquisition and analysis in imaging and real-time active MIR backscattering spectroscopy

NASA Astrophysics Data System (ADS)

Jarvis, Jan; Haertelt, Marko; Hugger, Stefan; Butschek, Lorenz; Fuchs, Frank; Ostendorf, Ralf; Wagner, Joachim; Beyerer, Juergen

2017-04-01

In this work we present data analysis algorithms for detection of hazardous substances in hyperspectral observations acquired using active mid-infrared (MIR) backscattering spectroscopy. We present a novel background extraction algorithm based on the adaptive target generation process proposed by Ren and Chang called the adaptive background generation process (ABGP) that generates a robust and physically meaningful set of background spectra for operation of the well-known adaptive matched subspace detection (AMSD) algorithm. It is shown that the resulting AMSD-ABGP detection algorithm competes well with other widely used detection algorithms. The method is demonstrated in measurement data obtained by two fundamentally different active MIR hyperspectral data acquisition devices. A hyperspectral image sensor applicable in static scenes takes a wavelength sequential approach to hyperspectral data acquisition, whereas a rapid wavelength-scanning single-element detector variant of the same principle uses spatial scanning to generate the hyperspectral observation. It is shown that the measurement timescale of the latter is sufficient for the application of the data analysis algorithms even in dynamic scenarios.

[Detection of Weak Speech Signals from Strong Noise Background Based on Adaptive Stochastic Resonance].

PubMed

Lu, Huanhuan; Wang, Fuzhong; Zhang, Huichun

2016-04-01

Traditional speech detection methods regard the noise as a jamming signal to filter,but under the strong noise background,these methods lost part of the original speech signal while eliminating noise.Stochastic resonance can use noise energy to amplify the weak signal and suppress the noise.According to stochastic resonance theory,a new method based on adaptive stochastic resonance to extract weak speech signals is proposed.This method,combined with twice sampling,realizes the detection of weak speech signals from strong noise.The parameters of the systema,b are adjusted adaptively by evaluating the signal-to-noise ratio of the output signal,and then the weak speech signal is optimally detected.Experimental simulation analysis showed that under the background of strong noise,the output signal-to-noise ratio increased from the initial value-7dB to about 0.86 dB,with the gain of signalto-noise ratio is 7.86 dB.This method obviously raises the signal-to-noise ratio of the output speech signals,which gives a new idea to detect the weak speech signals in strong noise environment.

Guidelines for the Practice of Adaptive Diabetes Education for Visually Impaired Persons.

ERIC Educational Resources Information Center

Berkowitz, Kathy

1993-01-01

This article presents guidelines developed by the American Association of Diabetes Educators concerning adaptive diabetes education for visually impaired persons (ADEVIP). The article discusses definitions, values, and assumptions; recommended professional educational background; role delineation; and process and content of ADEVIP. (DB)

Principles and Methods of Adapted Physical Education.

ERIC Educational Resources Information Center

Arnheim, Daniel D.; And Others

Programs in adapted physical education are presented preceded by a background of services for the handicapped, by the psychosocial implications of disability, and by the growth and development of the handicapped. Elements of conducting programs discussed are organization and administration, class organization, facilities, exercise programs…

Cognitive Control and Conflict Adaptation in Youth with High-Functioning Autism

ERIC Educational Resources Information Center

Larson, Michael J.; South, Mikle; Clayson, Peter E.; Clawson, Ann

2012-01-01

Background: Youth diagnosed with autism spectrum disorders (ASD) often show deficits in cognitive control processes, potentially contributing to characteristic difficulties monitoring and regulating behavior. Modification of performance following conflict can be measured by examining conflict adaptation, the adjustment of cognitive resources based…

The molecular biology of inflammatory bowel diseases.

PubMed

Corfield, Anthony P; Wallace, Heather M; Probert, Chris S J

2011-08-01

IBDs (inflammatory bowel diseases) are a group of diseases affecting the gastrointestinal tract. The diseases are multifactorial and cover genetic aspects: susceptibility genes, innate and adaptive responses to inflammation, and structure and efficacy of the mucosal protective barrier. Animal models of IBD have been developed to gain further knowledge of the disease mechanisms. These topics form an overlapping background to enable an improved understanding of the molecular features of these diseases. A series of articles is presented based on the topics covered at the Biochemical Society Focused Meeting The Molecular Biology of Inflammatory Bowel Diseases.

Studies of Tenuous Planetary Atmospheres

NASA Technical Reports Server (NTRS)

Combi, Michael R.

1998-01-01

The final report includes an overall project overview as well as scientific background summaries of dust and sodium in comets, and tenuous atmospheres of Jupiter's natural satellites. Progress and continuing work related to dust coma and tenuous atmospheric studies are presented. Also included are published articles written during the course of the report period. These are entitled: (1) On Europa's Magnetospheric Interaction: An MHD Simulation; (2) Dust-Gas Interrelations in Comets: Observations and Theory; and (3) Io's Plasma Environment During the Galileo Flyby: Global Three Dimensional MHD Modeling with Adaptive Mesh Refinement.

Red lesion detection using background estimation and lesions characteristics in diabetic retinal image

NASA Astrophysics Data System (ADS)

Zhang, Dongbo; Peng, Yinghui; Yi, Yao; Shang, Xingyu

2013-10-01

Detection of red lesions [hemorrhages (HRs) and microaneurysms (MAs)] is crucial for the diagnosis of early diabetic retinopathy. A method based on background estimation and adapted to specific characteristics of HRs and MAs is proposed. Candidate red lesions are located by background estimation and Mahalanobis distance measure and then some adaptive postprocessing techniques, which include vessel detection, nonvessel exclusion based on shape analysis, and noise points exclusion by double-ring filter (only used for MAs detection), are conducted to remove nonlesion pixels. The method is evaluated on our collected image dataset, and experimental results show that it is better than or approximate to other previous approaches. It is effective to reduce the false-positive and false-negative results that arise from incomplete and inaccurate vessel structure.

Beam width and transmitter power adaptive to tracking system performance for free-space optical communication.

PubMed

Arnon, S; Rotman, S; Kopeika, N S

1997-08-20

The basic free-space optical communication system includes at least two satellites. To communicate between them, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is to increase the satellite receiver beacon power. However, this solution requires increased power consumption and weight, both of which are disadvantageous in satellite development. Considering these facts, we derive a mathematical model of a communication system that adapts optimally the transmitter beam width and the transmitted power to the tracking system performance. Based on this model, we investigate the performance of a communication system with discrete element optical phased array transmitter telescope gain. An example for a practical communication system between a Low Earth Orbit Satellite and a Geostationary Earth Orbit Satellite is presented. From the results of this research it can be seen that a four-element adaptive transmitter telescope is sufficient to compensate for vibration amplitude doubling. The benefits of the proposed model are less required transmitter power and improved communication system performance.

Completion of the swine genome will simplify the production of swine as a large animal biomedical model

PubMed Central

2012-01-01

Background Anatomic and physiological similarities to the human make swine an excellent large animal model for human health and disease. Methods Cloning from a modified somatic cell, which can be determined in cells prior to making the animal, is the only method available for the production of targeted modifications in swine. Results Since some strains of swine are similar in size to humans, technologies that have been developed for swine can be readily adapted to humans and vice versa. Here the importance of swine as a biomedical model, current technologies to produce genetically enhanced swine, current biomedical models, and how the completion of the swine genome will promote swine as a biomedical model are discussed. Conclusions The completion of the swine genome will enhance the continued use and development of swine as models of human health, syndromes and conditions. PMID:23151353

Cultural adaptation and validation of Stroke Impact Scale 3.0 version in Uganda: A small-scale study

PubMed Central

Kamwesiga, Julius T; von Koch, Lena; Kottorp, Anders; Guidetti, Susanne

2016-01-01

Background: Knowledge is scarce about the impact of stroke in Uganda, and culturally adapted, psychometrically tested patient-reported outcome measures are lacking. The Stroke Impact Scale 3.0 is recommended, but it has not been culturally adapted and validated in Uganda. Objective: To culturally adapt and determine the psychometric properties of the Stroke Impact Scale 3.0 in the Ugandan context on a small scale. Method: The Stroke Impact Scale 3.0 was culturally adapted to form Stroke Impact Scale 3.0 Uganda (in English) by involving 25 participants in three different expert committees. Subsequently, Stroke Impact Scale 3.0 Uganda from English to Luganda language was done in accordance with guidelines. The first language in Uganda is English and Luganda is the main spoken language in Kampala city and its surroundings. Translation of Stroke Impact Scale 3.0 Uganda (both in English and Luganda) was then tested psychometrically by applying a Rasch model on data collected from 95 participants with stroke. Results: Overall, 10 of 59 (17%) items in the eight domains of the Stroke Impact Scale 3.0 were culturally adapted. The majority were 6 of 10 items in the domain Activities of Daily Living, 2 of 9 items in the domain Mobility, and 2 of 5 items in the domain Hand function. Only in two domains, all items demonstrated acceptable goodness of fit to the Rasch model. There were also more than 5% person misfits in the domains Participation and Emotion, while the Communication, Mobility, and Hand function domains had the lowest proportions of person misfits. The reliability coefficient was equal or larger than 0.90 in all domains except the Emotion domain, which was below the set criterion of 0.80 (0.75). Conclusion: The cultural adaptation and translation of Stroke Impact Scale 3.0 Uganda provides initial evidence of validity of the Stroke Impact Scale 3.0 when used in this context. The results provide support for several aspects of validity and precision but also point out issues for further adaptation and improvement of the Stroke Impact Scale. PMID:27746913

Object tracking algorithm based on the color histogram probability distribution

NASA Astrophysics Data System (ADS)

Li, Ning; Lu, Tongwei; Zhang, Yanduo

2018-04-01

In order to resolve tracking failure resulted from target's being occlusion and follower jamming caused by objects similar to target in the background, reduce the influence of light intensity. This paper change HSV and YCbCr color channel correction the update center of the target, continuously updated image threshold self-adaptive target detection effect, Clustering the initial obstacles is roughly range, shorten the threshold range, maximum to detect the target. In order to improve the accuracy of detector, this paper increased the Kalman filter to estimate the target state area. The direction predictor based on the Markov model is added to realize the target state estimation under the condition of background color interference and enhance the ability of the detector to identify similar objects. The experimental results show that the improved algorithm more accurate and faster speed of processing.

RATES OF FITNESS DECLINE AND REBOUND SUGGEST PERVASIVE EPISTASIS

PubMed Central

Perfeito, L; Sousa, A; Bataillon, T; Gordo, I

2014-01-01

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS− E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models. PMID:24372601

Histone Deacetylase Adaptation in Single Ventricle Heart Disease and a Young Animal Model of Right Ventricular Hypertrophy

PubMed Central

Blakeslee, Weston W.; Demos-Davies, Kimberly M.; Lemon, Douglas D.; Lutter, Katharina M.; Cavasin, Maria A.; Payne, Sam; Nunley, Karin; Long, Carlin S.; McKinsey, Timothy A.; Miyamoto, Shelley D.

2017-01-01

Background Histone deacetylase (HDAC) inhibitors are promising therapeutics for various forms of cardiac disease. The purpose of this study was to assess cardiac HDAC catalytic activity and expression in children with single ventricle heart disease of right ventricular morphology (SV), as well as in a rodent model of right ventricular hypertrophy (RVH). Methods Homogenates of RV explants from non-failing controls and SV children were assayed for HDAC catalytic activity and HDAC isoform expression. Postnatal 1-day old rat pups were placed in hypoxic conditions and echocardiographic analysis, gene expression, HDAC catalytic activity and isoform expression studies of the RV were performed. Results Class I, IIa, and IIb HDAC catalytic activity and protein expression were elevated in hearts of SV children. Hypoxic neonatal rats demonstrated RVH, abnormal gene expression and elevated class I and class IIb HDAC catalytic activity and protein expression in the RV compared to control. Conclusions These data suggest that myocardial HDAC adaptations occur in the SV heart and could represent a novel therapeutic target. While further characterization of the hypoxic neonatal rat is needed, this animal model may be suitable for pre-clinical investigations of pediatric RV disease and could serve as a useful model for future mechanistic studies. PMID:28549058

Output-Adaptive Tetrahedral Cut-Cell Validation for Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Darmofal, David L.

2008-01-01

A cut-cell approach to Computational Fluid Dynamics (CFD) that utilizes the median dual of a tetrahedral background grid is described. The discrete adjoint is also calculated, which permits adaptation based on improving the calculation of a specified output (off-body pressure signature) in supersonic inviscid flow. These predicted signatures are compared to wind tunnel measurements on and off the configuration centerline 10 body lengths below the model to validate the method for sonic boom prediction. Accurate mid-field sonic boom pressure signatures are calculated with the Euler equations without the use of hybrid grid or signature propagation methods. Highly-refined, shock-aligned anisotropic grids were produced by this method from coarse isotropic grids created without prior knowledge of shock locations. A heuristic reconstruction limiter provided stable flow and adjoint solution schemes while producing similar signatures to Barth-Jespersen and Venkatakrishnan limiters. The use of cut-cells with an output-based adaptive scheme completely automated this accurate prediction capability after a triangular mesh is generated for the cut surface. This automation drastically reduces the manual intervention required by existing methods.

Mosaic evolution and adaptive brain component alteration under domestication seen on the background of evolutionary theory.

PubMed

Rehkämper, Gerd; Frahm, Heiko D; Cnotka, Julia

2008-01-01

Brain sizes and brain component sizes of five domesticated pigeon breeds including homing (racing) pigeons are compared with rock doves (Columba livia) based on an allometric approach to test the influence of domestication on brain and brain component size. Net brain volume, the volumes of cerebellum and telencephalon as a whole are significantly smaller in almost all domestic pigeons. Inside the telencephalon, mesopallium, nidopallium (+ entopallium + arcopallium) and septum are smaller as well. The hippocampus is significantly larger, particularly in homing pigeons. This finding is in contrast to the predictions of the 'regression hypothesis' of brain alteration under domestication. Among the domestic pigeons homing pigeons have significantly larger olfactory bulbs. These data are interpreted as representing a functional adaptation to homing that is based on spatial cognition and sensory integration. We argue that domestication as seen in domestic pigeons is not principally different from evolution in the wild, but represents a heuristic model to understand the evolutionary process in terms of adaptation and optimization. Copyright 2007 S. Karger AG, Basel.

Holistic approach for automated background EEG assessment in asphyxiated full-term infants

NASA Astrophysics Data System (ADS)

Matic, Vladimir; Cherian, Perumpillichira J.; Koolen, Ninah; Naulaers, Gunnar; Swarte, Renate M.; Govaert, Paul; Van Huffel, Sabine; De Vos, Maarten

2014-12-01

Objective. To develop an automated algorithm to quantify background EEG abnormalities in full-term neonates with hypoxic ischemic encephalopathy. Approach. The algorithm classifies 1 h of continuous neonatal EEG (cEEG) into a mild, moderate or severe background abnormality grade. These classes are well established in the literature and a clinical neurophysiologist labeled 272 1 h cEEG epochs selected from 34 neonates. The algorithm is based on adaptive EEG segmentation and mapping of the segments into the so-called segments’ feature space. Three features are suggested and further processing is obtained using a discretized three-dimensional distribution of the segments’ features represented as a 3-way data tensor. Further classification has been achieved using recently developed tensor decomposition/classification methods that reduce the size of the model and extract a significant and discriminative set of features. Main results. Effective parameterization of cEEG data has been achieved resulting in high classification accuracy (89%) to grade background EEG abnormalities. Significance. For the first time, the algorithm for the background EEG assessment has been validated on an extensive dataset which contained major artifacts and epileptic seizures. The demonstrated high robustness, while processing real-case EEGs, suggests that the algorithm can be used as an assistive tool to monitor the severity of hypoxic insults in newborns.

Considerations for forest adaptation to climate change in sustainable production of wood/fiber/biomass and ecosystem services

Treesearch

Roger A. Sedjo

2014-01-01

Climate change is expected to affect forests into the future. Although forests have an inherent resiliency that allows them to adapt to various disturbances, including past climate change, concerns are expressed that the rate of change of current and future climate may be more rapid than the ability of many forests to adapt. This paper examines the background of forest...

One Decade Later: KF Canadian Adaptation Scheme.

ERIC Educational Resources Information Center

Rashid, H.

1984-01-01

Provides background and rationale for formulation and use of the KF Canadian Adaptation Scheme in Canadian law libraries and describes methodological approaches and applications of the scheme to diverse and specific situations. Recent developments in its maintenance and updating and suggestions for its potential use are highlighted. (EJS)

Longitudinal Trajectories of Intellectual and Adaptive Functioning in Adolescents and Adults with Williams Syndrome

ERIC Educational Resources Information Center

Fisher, M. H.; Lense, M. D.; Dykens, E. M.

2016-01-01

Background: Williams syndrome (WS) is associated with a distinct cognitive-behavioural phenotype including mild to moderate intellectual disability, visual-spatial deficits, hypersociability, inattention and anxiety. Researchers typically characterise samples of individuals with WS by their intellectual functioning and adaptive behaviour. Because…

ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS

EPA Science Inventory

A contaminant detection technique and its optimization algorithms have two principal functions. One is the adaptive signal treatment that suppresses background noise and enhances contaminant signals, leading to a promising detection of water quality changes at a false rate as low...

Wavelet-based adaptive thresholding method for image segmentation

NASA Astrophysics Data System (ADS)

Chen, Zikuan; Tao, Yang; Chen, Xin; Griffis, Carl

2001-05-01

A nonuniform background distribution may cause a global thresholding method to fail to segment objects. One solution is using a local thresholding method that adapts to local surroundings. In this paper, we propose a novel local thresholding method for image segmentation, using multiscale threshold functions obtained by wavelet synthesis with weighted detail coefficients. In particular, the coarse-to- fine synthesis with attenuated detail coefficients produces a threshold function corresponding to a high-frequency- reduced signal. This wavelet-based local thresholding method adapts to both local size and local surroundings, and its implementation can take advantage of the fast wavelet algorithm. We applied this technique to physical contaminant detection for poultry meat inspection using x-ray imaging. Experiments showed that inclusion objects in deboned poultry could be extracted at multiple resolutions despite their irregular sizes and uneven backgrounds.

Estimating Time to the Common Ancestor for a Beneficial Allele

PubMed Central

Smith, Joel; Coop, Graham; Stephens, Matthew; Novembre, John

2018-01-01

Abstract The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele’s age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the surrounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to approaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans. PMID:29361025

Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Zuo, Ming J.; Lin, Jianhui; Liu, Jianxin

2017-02-01

This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.

When noise is beneficial for sensory encoding: Noise adaptation can improve face processing.

PubMed

Menzel, Claudia; Hayn-Leichsenring, Gregor U; Redies, Christoph; Németh, Kornél; Kovács, Gyula

2017-10-01

The presence of noise usually impairs the processing of a stimulus. Here, we studied the effects of noise on face processing and show, for the first time, that adaptation to noise patterns has beneficial effects on face perception. We used noiseless faces that were either surrounded by random noise or presented on a uniform background as stimuli. In addition, the faces were either preceded by noise adaptors or not. Moreover, we varied the statistics of the noise so that its spectral slope either matched that of the faces or it was steeper or shallower. Results of parallel ERP recordings showed that the background noise reduces the amplitude of the face-evoked N170, indicating less intensive face processing. Adaptation to a noise pattern, however, led to reduced P1 and enhanced N170 amplitudes as well as to a better behavioral performance in two of the three noise conditions. This effect was also augmented by the presence of background noise around the target stimuli. Additionally, the spectral slope of the noise pattern affected the size of the P1, N170 and P2 amplitudes. We reason that the observed effects are due to the selective adaptation of noise-sensitive neurons present in the face-processing cortical areas, which may enhance the signal-to-noise-ratio. Copyright © 2017 Elsevier Inc. All rights reserved.

Candidate genes that have facilitated freshwater adaptation by palaemonid prawns in the genus Macrobrachium: identification and expression validation in a model species (M. koombooloomba)

PubMed Central

Amin, Shorash; Mather, Peter B.; Hurwood, David A.

2017-01-01

Background The endemic Australian freshwater prawn, Macrobrachium koombooloomba, provides a model for exploring genes involved with freshwater adaptation because it is one of the relatively few Macrobrachium species that can complete its entire life cycle in freshwater. Methods The present study was conducted to identify potential candidate genes that are likely to contribute to effective freshwater adaptation by M. koombooloomba using a transcriptomics approach. De novo assembly of 75 bp paired end 227,564,643 high quality Illumina raw reads from 6 different cDNA libraries revealed 125,917 contigs of variable lengths (200–18,050 bp) with an N50 value of 1597. Results In total, 31,272 (24.83%) of the assembled contigs received significant blast hits, of which 27,686 and 22,560 contigs were mapped and functionally annotated, respectively. CEGMA (Core Eukaryotic Genes Mapping Approach) based transcriptome quality assessment revealed 96.37% completeness. We identified 43 different potential genes that are likely to be involved with freshwater adaptation in M. koombooloomba. Identified candidate genes included: 25 genes for osmoregulation, five for cell volume regulation, seven for stress tolerance, three for body fluid (haemolymph) maintenance, eight for epithelial permeability and water channel regulation, nine for egg size control and three for larval development. RSEM (RNA-Seq Expectation Maximization) based abundance estimation revealed that 6,253, 5,753 and 3,795 transcripts were expressed (at TPM value ≥10) in post larvae, juveniles and adults, respectively. Differential gene expression (DGE) analysis showed that 15 genes were expressed differentially in different individuals but these genes apparently were not involved with freshwater adaptation but rather were involved in growth, development and reproductive maturation. Discussion The genomic resources developed here will be useful for better understanding the molecular basis of freshwater adaptation in Macrobrachium prawns and other crustaceans more broadly. PMID:28194319

Are winter and summer dormancy symmetrical seasonal adaptive strategies? The case of temperate herbaceous perennials

PubMed Central

Gillespie, Lauren M.; Volaire, Florence A.

2017-01-01

Background Dormancy in higher plants is an adaptive response enabling plant survival during the harshest seasons and has been more explored in woody species than in herbaceous species. Nevertheless, winter and summer shoot meristem dormancy are adaptive strategies that could play a major role in enhancing seasonal stress tolerance and resilience of widespread herbaceous plant communities. Scope This review outlines the symmetrical aspects of winter and summer dormancy in order to better understand plant adaptation to severe stress, and highlight research priorities in a changing climate. Seasonal dormancy is a good model to explore the growth–stress survival trade-off and unravel the relationships between growth potential and stress hardiness. Although photoperiod and temperature are known to play a crucial, though reversed, role in the induction and release of both types of dormancy, the thresholds and combined effects of these environmental factors remain to be identified. The biochemical compounds involved in induction or release in winter dormancy (abscisic acid, ethylene, sugars, cytokinins and gibberellins) could be a priority research focus for summer dormancy. To address these research priorities, herbaceous species, being more tractable than woody species, are excellent model plants for which both summer and winter dormancy have been clearly identified. Conclusions Summer and winter dormancy, although responding to inverse conditions, share many characteristics. This analogous nature can facilitate research as well as lead to insight into plant adaptations to extreme conditions and the evolution of phenological patterns of species and communities under climate change. The development of phenotypes showing reduced winter and/or enhanced summer dormancy may be expected and could improve adaptation to less predictable environmental stresses correlated with future climates. To this end, it is suggested to explore the inter- and intraspecific genotypic variability of dormancy and its plasticity according to environmental conditions to contribute to predicting and mitigating global warming. PMID:28087658

The Ethnocultural Adaptation of Children of Migrants in the Schools of Moscow

ERIC Educational Resources Information Center

Makarov, A. I.

2012-01-01

Research data on the dynamics of ethnocultural adaptation of migrant family students in Moscow schools shows a tension between assimilation and retention of one's cultural background. Ethnic differences create barriers between those of Russian and non-Russian ethnicity, including difficulties with language and the widespread phenomenon of…

Cultural Orientation and Social Capital as Predictors of Condom Use among Internal Migrants in China

ERIC Educational Resources Information Center

Du, Hongfei; Li, Xiaoming; Lin, Danhua; Tam, Cheuk Chi

2016-01-01

Background: The global literature has revealed that cultural orientation, adaptation and social capital may influence HIV-related sexual behaviours among migrants. However, whether cultural orientations influence adaptation and social capital and thereby affect sexual behaviour is not well understood. Method: This study examined whether…

The GO4KIDDS Brief Adaptive Scale

ERIC Educational Resources Information Center

Perry, Adrienne; Taheri, Azin; Ting, Victoria; Weiss, Jonathan

2015-01-01

Background: Accurate measurement of adaptive behaviour is important in both clinical and research contexts. While several good clinical measures exist, as well as brief research measures for adults with intellectual disability, there is need for a brief and efficient measure for research with children and youth. We present preliminary psychometric…

Effectiveness of a Culturally Adapted Strengthening Families Program 12-16-Years for High-Risk Irish Families

ERIC Educational Resources Information Center

Kumpfer, Karol L.; Xie, Jing; O'Driscoll, Robert

2012-01-01

Background: Evidence-based programs (EBPs) targeting effective family skills are the most cost effective for improving adolescent behavioural health. Cochrane Reviews have found the "Strengthening Families Program" (SFP) to be the most effective substance abuse prevention intervention. Standardized cultural adaptation processes resulted…

PERSO: Towards an Adaptive e-Learning System

ERIC Educational Resources Information Center

Chorfi, Henda; Jemni, Mohamed

2004-01-01

In today's information technology society, members are increasingly required to be up to date on new technologies, particularly for computers, regardless of their background social situation. In this context, our aim is to design and develop an adaptive hypermedia e-learning system, called PERSO (PERSOnalizing e-learning system), where learners…

Easy-To-Make Costumes for Stage and School.

ERIC Educational Resources Information Center

Tompkins, Julia

This book offers patterns and instructions that will enable amateurs to turn out authentic costumes for school plays. Step-by-step guidance is provided for the adaptation and design of dress for period plays with Egyptian, biblical, Greek, Roman, and Renaissance backgrounds. Materials suggested for further adaptations are inexpensive and easily…

Using Mental Health Consultation to Decrease Disruptive Behaviors in Preschoolers: Adapting an Empirically-Supported Intervention

ERIC Educational Resources Information Center

Williford, Amanda P.; Shelton, Terri L.

2008-01-01

Background: This study examined the effectiveness of an adaptation of an empirically-supported intervention delivered using mental health consultation to preschoolers who displayed elevated disruptive behaviors. Method: Ninety-six preschoolers, their teachers, and their primary caregivers participated. Children in the intervention group received…

Making Mistakes: Emotional Adaptation and Classroom Learning

ERIC Educational Resources Information Center

McCaslin, Mary; Vriesema, Christine C.; Burggraf, Susan

2016-01-01

Background: We studied how students in Grades 4-6 participate in and emotionally adapt to the give-and-take of learning in classrooms, particularly when making mistakes. Our approach is consistent with researchers who (a) include cognitive appraisals in the study of emotional experiences, (b) consider how personal concerns might mediate…

The Role of Decision Support in Adapting to Climate Change: Findings from Three Place-based Regional Assessments

EPA Science Inventory

This report summarizes the methodologies and findings of three regional assessments and considers the role of decision support in assisting adaptation to climate change. Background. In conjunction with the US Global Change Research Program’s (USGCRP’s) National Assessment of ...

Development of Semantic Description for Multiscale Models of Thermo-Mechanical Treatment of Metal Alloys

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Regulski, Krzysztof

2016-08-01

We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.

Seismic hazard in the eastern United States

USGS Publications Warehouse

Mueller, Charles; Boyd, Oliver; Petersen, Mark D.; Moschetti, Morgan P.; Rezaeian, Sanaz; Shumway, Allison

2015-01-01

The U.S. Geological Survey seismic hazard maps for the central and eastern United States were updated in 2014. We analyze results and changes for the eastern part of the region. Ratio maps are presented, along with tables of ground motions and deaggregations for selected cities. The Charleston fault model was revised, and a new fault source for Charlevoix was added. Background seismicity sources utilized an updated catalog, revised completeness and recurrence models, and a new adaptive smoothing procedure. Maximum-magnitude models and ground motion models were also updated. Broad, regional hazard reductions of 5%–20% are mostly attributed to new ground motion models with stronger near-source attenuation. The revised Charleston fault geometry redistributes local hazard, and the new Charlevoix source increases hazard in northern New England. Strong increases in mid- to high-frequency hazard at some locations—for example, southern New Hampshire, central Virginia, and eastern Tennessee—are attributed to updated catalogs and/or smoothing.

A model for homeopathic remedy effects: low dose nanoparticles, allostatic cross-adaptation, and time-dependent sensitization in a complex adaptive system

PubMed Central

2012-01-01

Background This paper proposes a novel model for homeopathic remedy action on living systems. Research indicates that homeopathic remedies (a) contain measurable source and silica nanoparticles heterogeneously dispersed in colloidal solution; (b) act by modulating biological function of the allostatic stress response network (c) evoke biphasic actions on living systems via organism-dependent adaptive and endogenously amplified effects; (d) improve systemic resilience. Discussion The proposed active components of homeopathic remedies are nanoparticles of source substance in water-based colloidal solution, not bulk-form drugs. Nanoparticles have unique biological and physico-chemical properties, including increased catalytic reactivity, protein and DNA adsorption, bioavailability, dose-sparing, electromagnetic, and quantum effects different from bulk-form materials. Trituration and/or liquid succussions during classical remedy preparation create “top-down” nanostructures. Plants can biosynthesize remedy-templated silica nanostructures. Nanoparticles stimulate hormesis, a beneficial low-dose adaptive response. Homeopathic remedies prescribed in low doses spaced intermittently over time act as biological signals that stimulate the organism’s allostatic biological stress response network, evoking nonlinear modulatory, self-organizing change. Potential mechanisms include time-dependent sensitization (TDS), a type of adaptive plasticity/metaplasticity involving progressive amplification of host responses, which reverse direction and oscillate at physiological limits. To mobilize hormesis and TDS, the remedy must be appraised as a salient, but low level, novel threat, stressor, or homeostatic disruption for the whole organism. Silica nanoparticles adsorb remedy source and amplify effects. Properly-timed remedy dosing elicits disease-primed compensatory reversal in direction of maladaptive dynamics of the allostatic network, thus promoting resilience and recovery from disease. Summary Homeopathic remedies are proposed as source nanoparticles that mobilize hormesis and time-dependent sensitization via non-pharmacological effects on specific biological adaptive and amplification mechanisms. The nanoparticle nature of remedies would distinguish them from conventional bulk drugs in structure, morphology, and functional properties. Outcomes would depend upon the ability of the organism to respond to the remedy as a novel stressor or heterotypic biological threat, initiating reversals of cumulative, cross-adapted biological maladaptations underlying disease in the allostatic stress response network. Systemic resilience would improve. This model provides a foundation for theory-driven research on the role of nanomaterials in living systems, mechanisms of homeopathic remedy actions and translational uses in nanomedicine. PMID:23088629

Observations and modeling of magnetized plasma jets and bubbles launched into a transverse B-field

NASA Astrophysics Data System (ADS)

Fisher, Dustin M.; Zhang, Yue; Wallace, Ben; Gilmore, Mark; Manchester, Ward B., IV; van der Holst, Bart; Rogers, Barrett N.; Hsu, Scott C.

2017-10-01

Hot, dense, plasma structures launched from a coaxial plasma gun on the HelCat dual-source plasma device at the University of New Mexico drag frozen-in magnetic flux into the chamber's background magnetic field providing a rich set of dynamics to study magnetic turbulence, force-free magnetic spheromaks, shocks, as well as CME-like dynamics possibly relevant to the solar corona. Vector magnetic field data from an eleven-tipped B-dot rake probe and images from an ultra-fast camera will be presented in comparison with ongoing MHD modeling using the 3-D MHD BATS-R-US code developed at the University of Michigan. BATS-R-US employs an adaptive mesh refinement grid (AMR) that enables the capture and resolution of shock structures and current sheets and is uniquely suited for flux-rope expansion modeling. Recent experiments show a possible magnetic Rayleigh-Taylor (MRT) instability that appears asymmetrically at the interface between launched spheromaks (bubbles) and their entraining background magnetic field. Efforts to understand this instability using in situ measurements, new chamber boundary conditions, and ultra-fast camera data will be presented. Work supported by the Army Research Office Award No. W911NF1510480.

Low-mAs X-ray CT image reconstruction by adaptive-weighted TV-constrained penalized re-weighted least-squares

PubMed Central

Liu, Yan; Ma, Jianhua; Zhang, Hao; Wang, Jing; Liang, Zhengrong

2014-01-01

Background The negative effects of X-ray exposure, such as inducing genetic and cancerous diseases, has arisen more attentions. Objective This paper aims to investigate a penalized re-weighted least-square (PRWLS) strategy for low-mAs X-ray computed tomography image reconstruction by incorporating an adaptive weighted total variation (AwTV) penalty term and a noise variance model of projection data. Methods An AwTV penalty is introduced in the objective function by considering both piecewise constant property and local nearby intensity similarity of the desired image. Furthermore, the weight of data fidelity term in the objective function is determined by our recent study on modeling variance estimation of projection data in the presence of electronic background noise. Results The presented AwTV-PRWLS algorithm can achieve the highest full-width-at-half-maximum (FWHM) measurement, for data conditions of (1) full-view 10mA acquisition and (2) sparse-view 80mA acquisition. In comparison between the AwTV/TV-PRWLS strategies and the previous reported AwTV/TV-projection onto convex sets (AwTV/TV-POCS) approaches, the former can gain in terms of FWHM for data condition (1), but cannot gain for the data condition (2). Conclusions In the case of full-view 10mA projection data, the presented AwTV-PRWLS shows potential improvement. However, in the case of sparse-view 80mA projection data, the AwTV/TV-POCS shows advantage over the PRWLS strategies. PMID:25080113

Plants Modify Biological Processes to Ensure Survival following Carbon Depletion: A Lolium perenne Model

PubMed Central

Lee, Julia M.; Sathish, Puthigae; Donaghy, Daniel J.; Roche, John R.

2010-01-01

Background Plants, due to their immobility, have evolved mechanisms allowing them to adapt to multiple environmental and management conditions. Short-term undesirable conditions (e.g. moisture deficit, cold temperatures) generally reduce photosynthetic carbon supply while increasing soluble carbohydrate accumulation. It is not known, however, what strategies plants may use in the long-term to adapt to situations resulting in net carbon depletion (i.e. reduced photosynthetic carbon supply and carbohydrate accumulation). In addition, many transcriptomic experiments have typically been undertaken under laboratory conditions; therefore, long-term acclimation strategies that plants use in natural environments are not well understood. Methodology/Principal Findings Perennial ryegrass (Lolium perenne L.) was used as a model plant to define whether plants adapt to repetitive carbon depletion and to further elucidate their long-term acclimation mechanisms. Transcriptome changes in both lamina and stubble tissues of field-grown plants with depleted carbon reserves were characterised using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The RT-qPCR data for select key genes indicated that plants reduced fructan degradation, and increased photosynthesis and fructan synthesis capacities following carbon depletion. This acclimatory response was not sufficient to prevent a reduction (P<0.001) in net biomass accumulation, but ensured that the plant survived. Conclusions Adaptations of plants with depleted carbon reserves resulted in reduced post-defoliation carbon mobilization and earlier replenishment of carbon reserves, thereby ensuring survival and continued growth. These findings will help pave the way to improve plant biomass production, for either grazing livestock or biofuel purposes. PMID:20808836

Landscape genomic analysis of candidate genes for climate adaptation in a California endemic oak, Quercus lobata.

PubMed

Sork, Victoria L; Squire, Kevin; Gugger, Paul F; Steele, Stephanie E; Levy, Eric D; Eckert, Andrew J

2016-01-01

The ability of California tree populations to survive anthropogenic climate change will be shaped by the geographic structure of adaptive genetic variation. Our goal is to test whether climate-associated candidate genes show evidence of spatially divergent selection in natural populations of valley oak, Quercus lobata, as preliminary indication of local adaptation. Using DNA from 45 individuals from 13 localities across the species' range, we sequenced portions of 40 candidate genes related to budburst/flowering, growth, osmotic stress, and temperature stress. Using 195 single nucleotide polymorphisms (SNPs), we estimated genetic differentiation across populations and correlated allele frequencies with climate gradients using single-locus and multivariate models. The top 5% of FST estimates ranged from 0.25 to 0.68, yielding loci potentially under spatially divergent selection. Environmental analyses of SNP frequencies with climate gradients revealed three significantly correlated SNPs within budburst/flowering genes and two SNPs within temperature stress genes with mean annual precipitation, after controlling for multiple testing. A redundancy model showed a significant association between SNPs and climate variables and revealed a similar set of SNPs with high loadings on the first axis. In the RDA, climate accounted for 67% of the explained variation, when holding climate constant, in contrast to a putatively neutral SSR data set where climate accounted for only 33%. Population differentiation and geographic gradients of allele frequencies in climate-associated functional genes in Q. lobata provide initial evidence of adaptive genetic variation and background for predicting population response to climate change. © 2016 Botanical Society of America.

Unique pattern of dietary adaptation in the dentition of Carnivora: its advantage and developmental origin

PubMed Central

Saito, Kazuyuki; Kishida, Takushi; Takahashi, Katsu; Bessho, Kazuhisa

2016-01-01

Carnivora is a successful taxon in terms of dietary diversity. We investigated the dietary adaptations of carnivoran dentition and the developmental background of their dental diversity, which may have contributed to the success of the lineage. A developmental model was tested and extended to explain the unique variability and exceptional phenotypes observed in carnivoran dentition. Carnivorous mammalian orders exhibited two distinct patterns of dietary adaptation in molars and only Carnivora evolved novel variability, exhibiting a high correlation between relative molar size and the shape of the first molar. Studies of Bmp7-hetero-deficient mice, which may exhibit lower Bmp7 expression, suggested that Bmp7 has pleiotropic effects on these two dental traits. Its effects are consistent with the pattern of dietary adaptation observed in Carnivora, but not that observed in other carnivorous mammals. A molecular evolutionary analysis revealed that Bmp7 sequence evolved by natural selection during ursid evolution, suggesting that it plays an evolutionary role in the variation of carnivoran dentition. Using mouse experiments and a molecular evolutionary analysis, we extrapolated the causal mechanism of the hitherto enigmatic ursid dentition (larger M2 than M1 and M3). Our results demonstrate how carnivorans acquired novel dental variability that benefits their dietary divergence.

Sustainability of the integrated chronic disease management model at primary care clinics in South Africa

PubMed Central

Asmall, Shaidah

2016-01-01

Background An integrated chronic disease management (ICDM) model consisting of four components (facility reorganisation, clinical supportive management, assisted self-supportive management and strengthening of support systems and structures outside the facility) has been implemented across 42 primary health care clinics in South Africa with a view to improve the operational efficiency and patient clinical outcomes. Aim The aim of this study was to assess the sustainability of the facility reorganisation and clinical support components 18 months after the initiation. Setting The study was conducted at 37 of the initiating clinics across three districts in three provinces of South Africa. Methods The National Health Service (NHS) Institute for Innovation and Improvement Sustainability Model (SM) self-assessment tool was used to assess sustainability. Results Bushbuckridge had the highest mean sustainability score of 71.79 (95% CI: 63.70–79.89) followed by West Rand Health District (70.25 (95% CI: 63.96–76.53)) and Dr Kenneth Kaunda District (66.50 (95% CI: 55.17–77.83)). Four facilities (11%) had an overall sustainability score of less than 55. Conclusion The less than optimal involvement of clinical leadership (doctors), negative staff behaviour towards the ICDM, adaptability or flexibility of the model to adapt to external factors and infrastructure limitation have the potential to negatively affect the sustainability and scale-up of the model. PMID:28155314

Spiny Mice Modulate Eumelanin to Pheomelanin Ratio to Achieve Cryptic Coloration in “Evolution Canyon,” Israel

PubMed Central

Singaravelan, Natarajan; Pavlicek, Tomas; Beharav, Alex; Wakamatsu, Kazumasa; Ito, Shosuke; Nevo, Eviatar

2010-01-01

Background Coat coloration in mammals is an explicit adaptation through natural selection. Camouflaging with the environment is the foremost evolutionary drive in explaining overall coloration. Decades of enquiries on this topic have been limited to repetitive coat color measurements to correlate the morphs with background/habitat blending. This led to an overwhelming endorsement of concealing coloration as a local phenotypic adaptation in animals, primarily rodents to evade predators. However, most such studies overlooked how rodents actually achieve such cryptic coloration. Cryptic coloration could be attained only through optimization between the yellow- to brown-colored “pheomelanin” and gray to black-colored “eumelanin” in the hairs. However, no study has explored this conjecture yet. “Evolution Canyon” (EC) in Israel is a natural microscale laboratory where the relationship between organism and environment can be explored. EC is comprised of an “African” slope (AS), which exhibits a yellow-brownish background habitat, and a “European” slope (ES), exhibiting a dark grayish habitat; both slopes harbor spiny mice (Acomys cahirinus). Here, we examine how hair melanin content of spiny mice living in the opposing slopes of EC evolves toward blending with their respective background habitat. Methodology/Principal Findings We measured hair-melanin (both eumelanin and pheomelanin) contents of 30 spiny mice from the EC using high-performance liquid chromatography (HPLC) that detects specific degradation products of eumelanin and pheomelanin. The melanin pattern of A. cahirinus approximates the background color of the slope on which they dwell. Pheomelanin is slightly (insignificantly) higher in individuals found on the AS to match the brownish background, whereas individuals of the ES had significantly greater eumelanin content to mimic the dark grayish background. This is further substantiated by a significantly higher eumelanin and pheomelanin ratio on the ES than on the AS. Conclusion/Significance It appears that rodents adaptively modulate eumelanin and pheomelanin contents to achieve cryptic coloration in contrasting habitats even at a microscale. PMID:20090935

A culturally adapted lifestyle intervention addressing a Middle Eastern immigrant population at risk of diabetes, the MEDIM (impact of Migration and Ethnicity on Diabetes In Malmö): study protocol for a randomized controlled trial

PubMed Central

2013-01-01

Background Studies have shown that lifestyle interventions are effective in preventing or delaying the onset of type 2 diabetes in high-risk patients. However, research on the effectiveness of lifestyle interventions in high-risk immigrant populations with different cultural and socioeconomic backgrounds is scarce. The aim was to design a culturally adapted lifestyle intervention for an immigrant population and to evaluate its effectiveness and cost-effectiveness. Methods/design In this randomized controlled trial, 308 participants (born in Iraq, living in Malmö, Sweden and at high risk of type 2 diabetes) will be allocated to either a culturally adapted intervention or a control group. The intervention will consist of 10 group counseling sessions focusing on diet, physical activity and behavioral change over 6 months, and the offer of exercise sessions. Cultural adaptation includes gender-specific exercise sessions, and counseling by a health coach community member. The control group will receive the information about healthy lifestyle habits provided by the primary health care center. The primary outcome is change in fasting glucose level. Secondary outcomes are changes in body mass index, insulin sensitivity, physical activity, food habits and health-related quality of life. Measurements will be taken at baseline, after 3 and 6 months. Data will be analyzed by the intention-to-treat approach. The cost-effectiveness during the trial period and over the longer term will be assessed by simulation modeling from patient, health care and societal perspectives. Discussion This study will provide a basis to measure the effectiveness of a lifestyle intervention designed for immigrants from the Middle East in terms of improvement in glucose metabolism, and will also assess its cost-effectiveness. Results from this trial may help health care providers and policy makers to adapt and implement lifestyle interventions suitable for this population group that can be conducted in the community. Trial registration ClinicalTrials.gov, NCT01420198 PMID:24006857

Large- and small-scale environmental factors drive distributions of cool-adapted plants in karstic microrefugia

PubMed Central

Vojtkó, András; Farkas, Tünde; Szabó, Anna; Havadtői, Krisztina; Vojtkó, Anna E.; Tölgyesi, Csaba; Cseh, Viktória; Erdős, László; Maák, István Elek; Keppel, Gunnar

2017-01-01

Background and aims Dolines are small- to large-sized bowl-shaped depressions of karst surfaces. They may constitute important microrefugia, as thermal inversion often maintains cooler conditions within them. This study aimed to identify the effects of large- (macroclimate) and small-scale (slope aspect and vegetation type) environmental factors on cool-adapted plants in karst dolines of East-Central Europe. We also evaluated the potential of these dolines to be microrefugia that mitigate the effects of climate change on cool-adapted plants in both forest and grassland ecosystems. Methods We compared surveys of plant species composition that were made between 2007 and 2015 in 21 dolines distributed across four mountain ranges (sites) in Hungary and Romania. We examined the effects of environmental factors on the distribution and number of cool-adapted plants on three scales: (1) regional (all sites); (2) within sites and; (3) within dolines. Generalized linear models and non-parametric tests were used for the analyses. Key Results Macroclimate, vegetation type and aspect were all significant predictors of the diversity of cool-adapted plants. More cool-adapted plants were recorded in the coolest site, with only few found in the warmest site. At the warmest site, the distribution of cool-adapted plants was restricted to the deepest parts of dolines. Within sites of intermediate temperature and humidity, the effect of vegetation type and aspect on the diversity of cool-adapted plants was often significant, with more taxa being found in grasslands (versus forests) and on north-facing slopes (versus south-facing slopes). Conclusions There is large variation in the number and spatial distribution of cool-adapted plants in karst dolines, which is related to large- and small-scale environmental factors. Both macro- and microrefugia are therefore likely to play important roles in facilitating the persistence of cool-adapted plants under global warming. PMID:28025290

Fast Compressive Tracking.

PubMed

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

Olfactory cortical adaptation facilitates detection of odors against background.

PubMed

Kadohisa, Mikiko; Wilson, Donald A

2006-03-01

Detection and discrimination of odors generally, if not always, occurs against an odorous background. On any given inhalation, olfactory receptor neurons will be activated by features of both the target odorant and features of background stimuli. To identify a target odorant against a background therefore, the olfactory system must be capable of grouping a subset of features into an odor object distinct from the background. Our previous work has suggested that rapid homosynaptic depression of afferents to the anterior piriform cortex (aPCX) contributes to both cortical odor adaptation to prolonged stimulation and habituation of simple odor-evoked behaviors. We hypothesize here that this process may also contribute to figure-ground separation of a target odorant from background stimulation. Single-unit recordings were made from both mitral/tufted cells and aPCX neurons in urethan-anesthetized rats and mice. Single-unit responses to odorant stimuli and their binary mixtures were determined. One of the odorants was randomly selected as the background and presented for 50 s. Forty seconds after the onset of the background stimulus, the second target odorant was presented, producing a binary mixture. The results suggest that mitral/tufted cells continue to respond to the background odorant and, when the target odorant is presented, had response magnitudes similar to that evoked by the binary mixture. In contrast, aPCX neurons filter out the background stimulus while maintaining responses to the target stimulus. Thus the aPCX acts as a filter driven most strongly by changing stimuli, providing a potential mechanism for olfactory figure-ground separation and selective reading of olfactory bulb output.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modelling and regulating of cardio-respiratory response for the enhancement of interval training

PubMed Central

2014-01-01

Background The interval training method has been a well known exercise protocol which helps strengthen and improve one’s cardiovascular fitness. Purpose To develop an effective training protocol to improve cardiovascular fitness based on modelling and analysis of Heart Rate (HR) and Oxygen Uptake (VO2) dynamics. Methods In order to model the cardiorespiratory response to the onset and offset exercises, the (K4b2, Cosmed) gas analyzer was used to monitor and record the heart rate and oxygen uptake for ten healthy male subjects. An interval training protocol was developed for young health users and was simulated using a proposed RC switching model which was presented to accommodate the variations of the cardiorespiratory dynamics to running exercises. A hybrid system model was presented to describe the adaptation process and a multi-loop PI control scheme was designed for the tuning of interval training regime. Results By observing the original data for each subject, we can clearly identify that all subjects have similar HR and VO2 profiles. The proposed model is capable to simulate the exercise responses during onset and offset exercises; it ensures the continuity of the outputs within the interval training protocol. Under some mild assumptions, a hybrid system model can describe the adaption process and accordingly a multi-loop PI controller can be designed for the tuning of interval training protocol. The self-adaption feature of the proposed controller gives the exerciser the opportunity to reach his desired setpoints after a certain number of training sessions. Conclusions The established interval training protocol targets a range of 70-80% of HRmax which is mainly a training zone for the purpose of cardiovascular system development and improvement. Furthermore, the proposed multi-loop feedback controller has the potential to tune the interval training protocol according to the feedback from an individual exerciser. PMID:24499131

Cosmology of f(R) gravity in the metric variational approach

NASA Astrophysics Data System (ADS)

Li, Baojiu; Barrow, John D.

2007-04-01

We consider the cosmologies that arise in a subclass of f(R) gravity with f(R)=R+μ2n+2/(-R)n and n∈(-1,0) in the metric (as opposed to the Palatini) variational approach to deriving the gravitational field equations. The calculations of the isotropic and homogeneous cosmological models are undertaken in the Jordan frame and at both the background and the perturbation levels. For the former, we also discuss the connection to the Einstein frame in which the extra degree of freedom in the theory is associated with a scalar field sharing some of the properties of a “chameleon” field. For the latter, we derive the cosmological perturbation equations in general theories of f(R) gravity in covariant form and implement them numerically to calculate the cosmic microwave background (CMB) temperature and matter power spectra of the cosmological model. The CMB power is shown to reduce at low l’s, and the matter power spectrum is almost scale independent at small scales, thus having a similar shape to that in standard general relativity. These are in stark contrast with what was found in the Palatini f(R) gravity, where the CMB power is largely amplified at low l’s and the matter spectrum is strongly scale dependent at small scales. These features make the present model more adaptable than that arising from the Palatini f(R) field equations, and none of the data on background evolution, CMB power spectrum, or matter power spectrum currently rule it out.

A review of visual perception mechanisms that regulate rapid adaptive camouflage in cuttlefish.

PubMed

Chiao, Chuan-Chin; Chubb, Charles; Hanlon, Roger T

2015-09-01

We review recent research on the visual mechanisms of rapid adaptive camouflage in cuttlefish. These neurophysiologically complex marine invertebrates can camouflage themselves against almost any background, yet their ability to quickly (0.5-2 s) alter their body patterns on different visual backgrounds poses a vexing challenge: how to pick the correct body pattern amongst their repertoire. The ability of cuttlefish to change appropriately requires a visual system that can rapidly assess complex visual scenes and produce the motor responses-the neurally controlled body patterns-that achieve camouflage. Using specifically designed visual backgrounds and assessing the corresponding body patterns quantitatively, we and others have uncovered several aspects of scene variation that are important in regulating cuttlefish patterning responses. These include spatial scale of background pattern, background intensity, background contrast, object edge properties, object contrast polarity, object depth, and the presence of 3D objects. Moreover, arm postures and skin papillae are also regulated visually for additional aspects of concealment. By integrating these visual cues, cuttlefish are able to rapidly select appropriate body patterns for concealment throughout diverse natural environments. This sensorimotor approach of studying cuttlefish camouflage thus provides unique insights into the mechanisms of visual perception in an invertebrate image-forming eye.

Local adaptation within a hybrid species

PubMed Central

Eroukhmanoff, F; Hermansen, J S; Bailey, R I; Sæther, S A; Sætre, G-P

2013-01-01

Ecological divergence among populations may be strongly influenced by their genetic background. For instance, genetic admixture through introgressive hybridization or hybrid speciation is likely to affect the genetic variation and evolvability of phenotypic traits. We studied geographic variation in two beak dimensions and three other phenotypic traits of the Italian sparrow (Passer italiae), a young hybrid species formed through interbreeding between house sparrows (P. domesticus) and Spanish sparrows (P. hispaniolensis). We found that beak morphology was strongly influenced by precipitation regimes and that it appeared to be the target of divergent selection within Italian sparrows. Interestingly, however, the degree of parental genetic contribution in the hybrid species had no effect on phenotypic beak variation. Moreover, beak height divergence may mediate genetic differentiation between populations, consistent with isolation-by-adaptation within this hybrid species. The study illustrates how hybrid species may be relatively unconstrained by their admixed genetic background, allowing them to adapt rapidly to environmental variation. PMID:23695379

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.

Controlling gain one photon at a time

PubMed Central

Schwartz, Gregory W; Rieke, Fred

2013-01-01

Adaptation is a salient property of sensory processing. All adaptational or gain control mechanisms face the challenge of obtaining a reliable estimate of the property of the input to be adapted to and obtaining this estimate sufficiently rapidly to be useful. Here, we explore how the primate retina balances the need to change gain rapidly and reliably when photons arrive rarely at individual rod photoreceptors. We find that the weakest backgrounds that decrease the gain of the retinal output signals are similar to those that increase human behavioral threshold, and identify a novel site of gain control in the retinal circuitry. Thus, surprisingly, the gain of retinal signals begins to decrease essentially as soon as background lights are detectable; under these conditions, gain control does not rely on a highly averaged estimate of the photon count, but instead signals from individual photon absorptions trigger changes in gain. DOI: http://dx.doi.org/10.7554/eLife.00467.001 PMID:23682314

Impact of Sociocultural Background and Assessment Data Upon School Psychologists' Decisions.

ERIC Educational Resources Information Center

Huebner, E. Scott; Cummings, Jack A.

1985-01-01

Psychologists (N=56) participated in an adapted version of Algozzine and Ysseldyke's (1981) diagnostic simulation to investigate the effects of sociocultural background (rural vs. suburban) and assessment data (normal vs. learning disabled) on educational decisions. Findings suggest school psychologists utilize multiple sources of information but…

Establishing Positive Learning Environments for Students of Chinese American and Latino Backgrounds

ERIC Educational Resources Information Center

Wong-Lo, Mickie; Cortez, Gabriel A.

2014-01-01

Cultivating positive learning environments for underrepresented groups such as students of Chinese American and Latino backgrounds require careful planning and consideration. As our society strives to embrace individual differences of all cultures, educators must equip themselves with effective tools to adapt to the ever-changing dynamics within…

Adaptive Competency Acquisition: Whey LPN-to-AND Career Mobility Education Programs Work.

ERIC Educational Resources Information Center

Coyle-Rogers, Patricia G.

2001-01-01

Scores on an adaptive competency profile for 30 Licensed Practical Nurse graduate candidates and 41 second-level Associate Degree in Nursing candidates indicated that there was no significant difference between the two groups. Results suggest that a variety of educational backgrounds foster development of nursing competence. (Contains 23…

Adapting Individual Psychotherapy for Adults with Intellectual Disabilities: A Comparative Review of the Cognitive-Behavioural and Psychodynamic Literature

ERIC Educational Resources Information Center

Whitehouse, Richard M.; Tudway, Jeremy A.; Look, Roger; Kroese, Biza Stenfert

2006-01-01

Background: Historically, adults with intellectual disabilities have had little access to individual psychotherapy. Over the last 20 years an increasing body of literature has described psychotherapy with this client group and reported methods for adapting traditional psychotherapeutic techniques. Method: The current review identified the…

Adaptive Physical Education and Aquatics for Students with Disabilities: A Teacher's Unique Experience

ERIC Educational Resources Information Center

Blassingame, Jennifer Cheryl

2011-01-01

Students with the most severe disabilities have special needs that cannot be addressed with general education curriculum modifications in a traditional prekindergarten-12th grade environment (Heward, 2006). It is essential that expert teachers with specialized educational background and training are prepared to adapt daily lessons to accommodate…

Conflict Adaptation and Congruency Sequence Effects to Social-Emotional Stimuli in Individuals with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Worsham, Whitney; Gray, Whitney E.; Larson, Michael J.; South, Mikle

2015-01-01

Background: The modification of performance following conflict can be measured using conflict adaptation tasks thought to measure the change in the allocation of cognitive resources in order to reduce conflict interference and improve performance. While previous studies have suggested atypical processing during nonsocial cognitive control tasks,…

A Tale of 2 Teachers: A Preschool Physical Activity Intervention Case Study

ERIC Educational Resources Information Center

Howie, Erin K.; Brewer, Alisa E.; Dowda, Marsha; McIver, Kerry L.; Saunders, Ruth P.; Pate, Russell R.

2016-01-01

Background: Preschool settings vary greatly, and research has shown that interventions are more successful when they can be adapted to individual settings. This is a descriptive case study of how 2 teachers successfully adapted and implemented a preschool physical activity intervention. Methods: The Study of Health and Activity in Preschool…

RASCAL: A Rudimentary Adaptive System for Computer-Aided Learning.

ERIC Educational Resources Information Center

Stewart, John Christopher

Both the background of computer-assisted instruction (CAI) systems in general and the requirements of a computer-aided learning system which would be a reasonable assistant to a teacher are discussed. RASCAL (Rudimentary Adaptive System for Computer-Aided Learning) is a first attempt at defining a CAI system which would individualize the learning…

The Prevalence of Low Self-Esteem in an Intellectually Disabled Forensic Population

ERIC Educational Resources Information Center

Johnson, P.

2012-01-01

Background: This was a quantitative study to measure the prevalence low self-esteem in an intellectually disabled forensic population. The dependent variables used were the adapted six-item Rosenberg Self-Esteem Scale and the adapted Evaluative Beliefs Scale. It had a repeated measures design with independent variables including consideration of…

Adapting Compassion Focused Therapy for an Adult with a Learning Disability--A Case Study

ERIC Educational Resources Information Center

Cooper, Rosalind; Frearson, Julia

2017-01-01

Background: Joe was referred to the Community Learning Disabilities Team (CLDT) for support around low mood and overeating. Initial formulation suggested compassion focused therapy (CFT) as an intervention. The evidence base for using CFT with people with learning disabilities is currently limited. Materials and Methods: Adaptations were made to…

Using Repertory Grid Techniques to Measure Change Following Dialectical Behaviour Therapy with Adults with Learning Disabilities: Two Case Studies

ERIC Educational Resources Information Center

McNair, Louisa; Woodrow, Ceri; Hare, Dougal

2016-01-01

Background: Government strategy indicates that individuals with learning disabilities should have access to adapted psychological therapies. Dialectical behaviour therapy (DBT) is recommended for the treatment of borderline personality disorder (BPD); however, there is little published research regarding whether it can be appropriately adapted for…

Adaptive Force Control in Grasping as a Function of Level of Developmental Disability

ERIC Educational Resources Information Center

Sprague, R. L.; Deutsch, K. M.; Newell, K. M.

2009-01-01

Background: The adaptation to the task demands of grasping (grip mode and object mass) was investigated as a function of level of developmental disability. Methods: Subjects grasped objects of different grip widths and masses that were instrumented to record grip forces. Results: Proportionally, fewer participants from the profound compared with…

Towards More Comprehensive Projections of Urban Heat-Related Mortality: Estimates for New York City under Multiple Population, Adaptation, and Climate Scenarios

PubMed Central

Petkova, Elisaveta P.; Vink, Jan K.; Horton, Radley M.; Gasparrini, Antonio; Bader, Daniel A.; Francis, Joe D.; Kinney, Patrick L.

2016-01-01

Background: High temperatures have substantial impacts on mortality and, with growing concerns about climate change, numerous studies have developed projections of future heat-related deaths around the world. Projections of temperature-related mortality are often limited by insufficient information to formulate hypotheses about population sensitivity to high temperatures and future demographics. Objectives: The present study derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound influences on future health burdens. Methods: We adopted a novel approach to modeling heat adaptation by incorporating an analysis of the observed population response to heat in New York City over the course of eight decades. This approach projected heat-related mortality until the end of the 21st century based on observed trends in adaptation over a substantial portion of the 20th century. In addition, we incorporated a range of new scenarios for population change until the end of the 21st century. We then estimated future heat-related deaths in New York City by combining the changing temperature–mortality relationship and population scenarios with downscaled temperature projections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCPs). Results: The median number of projected annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population change scenario, ranging from 167 to 3,331 in the 2080s compared with 638 heat-related deaths annually between 2000 and 2006. Conclusions: These findings provide a more complete picture of the range of potential future heat-related mortality risks across the 21st century in New York City, and they highlight the importance of both demographic change and adaptation responses in modifying future risks. Citation: Petkova EP, Vink JK, Horton RM, Gasparrini A, Bader DA, Francis JD, Kinney PL. 2017. Towards more comprehensive projections of urban heat-related mortality: estimates for New York City under multiple population, adaptation, and climate scenarios. Environ Health Perspect 125:47–55; http://dx.doi.org/10.1289/EHP166 PMID:27337737

Prediction of adaptive self-regulatory responses to arthritis pain anxiety in exercising adults: Does pain acceptance matter?

PubMed Central

Cary, Miranda A; Gyurcsik, Nancy C; Brawley, Lawrence R

2015-01-01

BACKGROUND: Exercising for ≥150 min/week is a recommended strategy for self-managing arthritis. However, exercise nonadherence is a problem. Arthritis pain anxiety may interfere with regular exercise. According to the fear-avoidance model, individuals may confront their pain anxiety by using adaptive self-regulatory responses (eg, changing exercise type or duration). Furthermore, the anxiety-self-regulatory responses relationship may vary as a function of individuals’ pain acceptance levels. OBJECTIVES: To investigate pain acceptance as a moderator of the pain anxiety-adaptive self-regulatory responses relationship. The secondary objective was to examine whether groups of patients who differed in meeting exercise recommendations also differed in pain-related and self-regulatory responses. METHODS: Adults (mean [± SD] age 49.75±13.88 years) with medically diagnosed arthritis completed online measures of arthritis pain-related variables and self-regulatory responses at baseline, and exercise participation two weeks later. Individuals meeting (n=87) and not meeting (n=49) exercise recommendations were identified. RESULTS: Hierarchical multiple regression analysis revealed that pain acceptance moderated the anxiety-adaptive self-regulatory responses relationship. When pain anxiety was lower, greater pain acceptance was associated with less frequent use of adaptive responses. When anxiety was higher, adaptive responses were used regardless of pain acceptance level. MANOVA findings revealed that participants meeting the recommended exercise dose reported significantly lower pain and pain anxiety, and greater pain acceptance (P<0.05) than those not meeting the dose. CONCLUSIONS: Greater pain acceptance may help individuals to focus their efforts to adapt to their pain anxiety only when it is higher, leaving self-regulatory capacity to cope with additional challenges to exercise adherence (eg, busy schedule). PMID:25621990

Irregular and adaptive sampling for automatic geophysic measure systems

NASA Astrophysics Data System (ADS)

Avagnina, Davide; Lo Presti, Letizia; Mulassano, Paolo

2000-07-01

In this paper a sampling method, based on an irregular and adaptive strategy, is described. It can be used as automatic guide for rovers designed to explore terrestrial and planetary environments. Starting from the hypothesis that a explorative vehicle is equipped with a payload able to acquire measurements of interesting quantities, the method is able to detect objects of interest from measured points and to realize an adaptive sampling, while badly describing the not interesting background.

Approaches to enhance the teaching quality of experimental biochemistry for MBBS students in TSMU, China.

PubMed

Yu, Lijuan; Yi, Shuying; Zhai, Jing; Wang, Zhaojin

2017-07-08

With the internationalization of medical education in China, the importance of international students' education in medical schools is also increasing. Except foreign students majoring in Chinese language, English Bachelor of Medicine, Bachelor of Surgery (MBSS) students are the largest group of international students. Based on problems in the teaching process for experimental biochemistry, we designed teaching models adapted to the background of international students and strengthened teachers' teaching ability at Taishan Medical University. Several approaches were used in combination to promote teaching effects and increase the benefit of teaching to teachers. The primary data showed an increased passion for basic medical biochemistry and an improved theoretical background for MBSS students, which will be helpful for their later clinical medicine studies. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):360-364, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

Floral pathway integrator gene expression mediates gradual transmission of environmental and endogenous cues to flowering time.

PubMed

van Dijk, Aalt D J; Molenaar, Jaap

2017-01-01

The appropriate timing of flowering is crucial for the reproductive success of plants. Hence, intricate genetic networks integrate various environmental and endogenous cues such as temperature or hormonal statues. These signals integrate into a network of floral pathway integrator genes. At a quantitative level, it is currently unclear how the impact of genetic variation in signaling pathways on flowering time is mediated by floral pathway integrator genes. Here, using datasets available from literature, we connect Arabidopsis thaliana flowering time in genetic backgrounds varying in upstream signalling components with the expression levels of floral pathway integrator genes in these genetic backgrounds. Our modelling results indicate that flowering time depends in a quite linear way on expression levels of floral pathway integrator genes. This gradual, proportional response of flowering time to upstream changes enables a gradual adaptation to changing environmental factors such as temperature and light.

Application of Adaptive Design Methodology in Development of a Long-Acting Glucagon-Like Peptide-1 Analog (Dulaglutide): Statistical Design and Simulations

PubMed Central

Skrivanek, Zachary; Berry, Scott; Berry, Don; Chien, Jenny; Geiger, Mary Jane; Anderson, James H.; Gaydos, Brenda

2012-01-01

Background Dulaglutide (dula, LY2189265), a long-acting glucagon-like peptide-1 analog, is being developed to treat type 2 diabetes mellitus. Methods To foster the development of dula, we designed a two-stage adaptive, dose-finding, inferentially seamless phase 2/3 study. The Bayesian theoretical framework is used to adaptively randomize patients in stage 1 to 7 dula doses and, at the decision point, to either stop for futility or to select up to 2 dula doses for stage 2. After dose selection, patients continue to be randomized to the selected dula doses or comparator arms. Data from patients assigned the selected doses will be pooled across both stages and analyzed with an analysis of covariance model, using baseline hemoglobin A1c and country as covariates. The operating characteristics of the trial were assessed by extensive simulation studies. Results Simulations demonstrated that the adaptive design would identify the correct doses 88% of the time, compared to as low as 6% for a fixed-dose design (the latter value based on frequentist decision rules analogous to the Bayesian decision rules for adaptive design). Conclusions This article discusses the decision rules used to select the dula dose(s); the mathematical details of the adaptive algorithm—including a description of the clinical utility index used to mathematically quantify the desirability of a dose based on safety and efficacy measurements; and a description of the simulation process and results that quantify the operating characteristics of the design. PMID:23294775

Modified Multiple Model Adaptive Estimation (M3AE) for Simultaneous Parameter and State Estimation

DTIC Science & Technology

1998-03-01

Contents Page Dedication : iv Acknowledgments v Table Of Contents vi List of Figures . . ; x List of Tables xv Abstract xvii Chapter 1 ...INTRODUCTION 1 1.1 Overview 1 1.2 Background 7 1.2.1 The Chi-Square Test 9 1.2.2 Generalized Likelihood Ratio (GLR) Testing 10 1.2.3 Multiple...M3AE Covariance Analysis 115 4.1.3 Simulations and Performance Analysis 121 4.1.3.1 Test Case 1 : aT = 32.0 124 4.1.3.2 Test Case 2: aT = 37.89, and

VizieR Online Data Catalog: Optical/NIR photometry of OGLE-2012-SN-006 (Pastorello+, 2015)

NASA Astrophysics Data System (ADS)

Pastorello, A.; Wyrzykowski, L.; Valenti, S.; Prieto, J. L.; Kozlowski, S.; Udalski, A.; Elias-Rosa, N.; Morales-Garoffolo, A.; Anderson, J. P.; Benetti, S.; Bersten, M.; Botticella, M. T.; Cappellaro, E.; Fasano, G.; Fraser, M.; Gal-Yam, A.; Gillone, M.; Graham, M. L.; Greiner, J.; Hachinger, S.; Howell, D. A.; Inserra, C.; Parrent, J.; Rau, A.; Schulze, S.; Smartt, S. J.; Smith, K. W.; Turatto, M.; Yaron, O.; Young, D. R.; Kubiak, M.; Szymanski, M. K.; Pietrzynski, G.; Soszynski, I.; Ulaczyk, K.; Poleski, R.; Pietrukowicz, P.; Skowron, J.; Mroz, P.

2017-11-01

Photometric measurements in the optical and NIR bands were obtained through the PSF-fitting technique. A template PSF was built using stars in the SN field. With this PSF model along with a low-order polynomial surface, we finally performed a fit to the SN and the underlying background. OGLE-IV photometry was obtained using the difference imaging analysis, which is a template subtraction method adapted to the OGLE data and detailed in Wyrzykowski et al. 2014, J/AcA/64/197 (see also Wozniak 2000, J/AcA/50/421). (2 data files).

Neither fish nor fowl: A perceived mismatch in norms and values between oneself, other students, and people back home undermines adaptation to university.

PubMed

de Vreeze, Jort; Matschke, Christina; Cress, Ulrike

2018-03-12

Students from low social-class background often struggle to adapt to university. Previous research shows that perceived incompatibility between social-class background identity and student identity is one reason, but little is known about the underlying causes of identity incompatibility. In three studies, we expected and found that students with low subjective social-class background perceived their values differently from other students, but also differently from people back home, and both increased identity incompatibility. Identity incompatibility negatively affected the student identity. Additionally, the current research also identifies specific patterns of norm and value differences that are prone to perceived identity incompatibility. The findings demonstrate that perceived differences in values from both groups are important mechanisms for identity incompatibility induced by the transition to university that may affect student identities and potentially their university trajectories. © 2018 The British Psychological Society.

Reaction to background stimulation of preschool children who do and do not stutter.

PubMed

Schwenk, Krista A; Conture, Edward G; Walden, Tedra A

2007-01-01

This study investigated the maintenance of attention and adaptation to background stimuli of preschool children who do (CWS) and do not stutter (CWNS). Participants were 13 monolingual, Standard American English speaking, 3-5-year-old CWS and 14 CWNS. Results indicated that CWS were significantly more apt than CWNS to attend to or look at changes in background stimuli, although there were no significant differences between groups in duration and latency of these looks. Findings suggest that preschool CWS are more reactive to, distracted by, and slower to adapt and habituate to environmental stimuli than their CWNS counterparts. The reader should be able to: (1) recognize the temperamental differences between CWS and CWNS, (2) define attention reactivity and regulation, (3) explain how attention reactivity and regulation are associated with preschool stuttering, and (4) understand recent empirical evidence relating reactivity and regulation to preschool stuttering.

Target Recognition Using Neural Networks for Model Deformation Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hibler, David L.

1999-01-01

Optical measurements provide a non-invasive method for measuring deformation of wind tunnel models. Model deformation systems use targets mounted or painted on the surface of the model to identify known positions, and photogrammetric methods are used to calculate 3-D positions of the targets on the model from digital 2-D images. Under ideal conditions, the reflective targets are placed against a dark background and provide high-contrast images, aiding in target recognition. However, glints of light reflecting from the model surface, or reduced contrast caused by light source or model smoothness constraints, can compromise accurate target determination using current algorithmic methods. This paper describes a technique using a neural network and image processing technologies which increases the reliability of target recognition systems. Unlike algorithmic methods, the neural network can be trained to identify the characteristic patterns that distinguish targets from other objects of similar size and appearance and can adapt to changes in lighting and environmental conditions.

Verifying Three-Dimensional Skull Model Reconstruction Using Cranial Index of Symmetry

PubMed Central

Kung, Woon-Man; Chen, Shuo-Tsung; Lin, Chung-Hsiang; Lu, Yu-Mei; Chen, Tzu-Hsuan; Lin, Muh-Shi

2013-01-01

Background Difficulty exists in scalp adaptation for cranioplasty with customized computer-assisted design/manufacturing (CAD/CAM) implant in situations of excessive wound tension and sub-cranioplasty dead space. To solve this clinical problem, the CAD/CAM technique should include algorithms to reconstruct a depressed contour to cover the skull defect. Satisfactory CAM-derived alloplastic implants are based on highly accurate three-dimensional (3-D) CAD modeling. Thus, it is quite important to establish a symmetrically regular CAD/CAM reconstruction prior to depressing the contour. The purpose of this study is to verify the aesthetic outcomes of CAD models with regular contours using cranial index of symmetry (CIS). Materials and methods From January 2011 to June 2012, decompressive craniectomy (DC) was performed for 15 consecutive patients in our institute. 3-D CAD models of skull defects were reconstructed using commercial software. These models were checked in terms of symmetry by CIS scores. Results CIS scores of CAD reconstructions were 99.24±0.004% (range 98.47–99.84). CIS scores of these CAD models were statistically significantly greater than 95%, identical to 99.5%, but lower than 99.6% (p<0.001, p = 0.064, p = 0.021 respectively, Wilcoxon matched pairs signed rank test). These data evidenced the highly accurate symmetry of these CAD models with regular contours. Conclusions CIS calculation is beneficial to assess aesthetic outcomes of CAD-reconstructed skulls in terms of cranial symmetry. This enables further accurate CAD models and CAM cranial implants with depressed contours, which are essential in patients with difficult scalp adaptation. PMID:24204566

High contrast imaging through adaptive transmittance control in the focal plane

NASA Astrophysics Data System (ADS)

Dhadwal, Harbans S.; Rastegar, Jahangir; Feng, Dake

2016-05-01

High contrast imaging, in the presence of a bright background, is a challenging problem encountered in diverse applications ranging from the daily chore of driving into a sun-drenched scene to in vivo use of biomedical imaging in various types of keyhole surgeries. Imaging in the presence of bright sources saturates the vision system, resulting in loss of scene fidelity, corresponding to low image contrast and reduced resolution. The problem is exacerbated in retro-reflective imaging systems where the light sources illuminating the object are unavoidably strong, typically masking the object features. This manuscript presents a novel theoretical framework, based on nonlinear analysis and adaptive focal plane transmittance, to selectively remove object domain sources of background light from the image plane, resulting in local and global increases in image contrast. The background signal can either be of a global specular nature, giving rise to parallel illumination from the entire object surface or can be represented by a mosaic of randomly orientated, small specular surfaces. The latter is more representative of real world practical imaging systems. Thus, the background signal comprises of groups of oblique rays corresponding to distributions of the mosaic surfaces. Through the imaging system, light from group of like surfaces, converges to a localized spot in the focal plane of the lens and then diverges to cast a localized bright spot in the image plane. Thus, transmittance of a spatial light modulator, positioned in the focal plane, can be adaptively controlled to block a particular source of background light. Consequently, the image plane intensity is entirely due to the object features. Experimental image data is presented to verify the efficacy of the methodology.

Learner Identities in the Context of Undergraduates: A Case Study

ERIC Educational Resources Information Center

Lawson, Alison

2014-01-01

Background: A "learner identity" can be broadly defined as how an individual feels about himself/herself as a learner and the extent to which he/she describes himself/herself as a "learner." The literature suggests that those from non-traditional backgrounds may struggle to adapt to a university environment with all its related…

Daytime adaptive optics for deep space optical communications

NASA Technical Reports Server (NTRS)

Wilson, Keith; Troy, M.; Srinivasan, M.; Platt, B.; Vilnrotter, V.; Wright, M.; Garkanian, V.; Hemmati, H.

2003-01-01

The deep space optical communications subsystem offers a higher bandwidth communications link in smaller size, lower mass, and lower power consumption subsystem than does RF. To demonstrate the benefit of this technology to deep space communications NASA plans to launch an optical telecommunications package on the 2009 Mars Telecommunications orbiter spacecraft. Current performance goals are 30-Mbps from opposition, and 1-Mbps near conjunction (-3 degrees Sun-Earth-Probe angle). Yet, near conjunction the background noise from the day sky will degrade the performance of the optical link. Spectral and spatial filtering and higher modulation formats can mitigate the effects of background sky. Narrowband spectral filters can result in loss of link margin, and higher modulation formats require higher transmitted peak powers. In contrast, spatial filtering at the receiver has the potential of being lossless while providing the required sky background rejection. Adaptive optics techniques can correct wave front aberrations caused by atmospheric turbulence and enable near-diffraction-limited performance of the receiving telescope. Such performance facilitates spatial filtering, and allows the receiver field-of-view and hence the noise from the sky background to be reduced.

Chlorophyll fluorescence analysis revealed essential roles of FtsH 11 protease in regulation of the adaptive responses of photosynthetic systems to high temperature

USDA-ARS?s Scientific Manuscript database

Background: Photosynthetic systems are known to be sensitive to high temperature stress. To maintain a relatively “normal” level of photosynthetic activities, plants employ a variety of adaptive mechanisms in response to environmental temperature fluctuations. Previously, we reported that the chloro...

Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values

ERIC Educational Resources Information Center

Storey, Brian; Butler, Joy

2013-01-01

Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title "complexity thinking"…

Mindfulness Training Improves Problem-Focused Coping in Psychology and Medical Students: Results from a Randomized Controlled Trial

ERIC Educational Resources Information Center

Halland, E.; De Vibe, M.; Solhaug, I.; Friborg, O.; Rosenvinge, J. H.; Tyssen, R.; Sørlie, T.; Bjørndal, A.

2015-01-01

Background: Students of clinical psychology and medicine experience high levels of mental distress and low levels of life satisfaction. Using adaptive coping strategies can modify the negative effect of stressors on health. Mindfulness, it has been claimed, more adaptive coping with stress, yet few studies have investigated whether mindfulness…

SKOPE-IT (Shareable Knowledge Objects as Portable Intelligent Tutors): Overlaying Natural Language Tutoring on an Adaptive Learning System for Mathematics

ERIC Educational Resources Information Center

Nye, Benjamin D.; Pavlik, Philip I., Jr.; Windsor, Alistair; Olney, Andrew M.; Hajeer, Mustafa; Hu, Xiangen

2018-01-01

Background: This study investigated learning outcomes and user perceptions from interactions with a hybrid intelligent tutoring system created by combining the AutoTutor conversational tutoring system with the Assessment and Learning in Knowledge Spaces (ALEKS) adaptive learning system for mathematics. This hybrid intelligent tutoring system (ITS)…

Outcomes and Experiences of an Adapted Dialectic Behaviour Therapy Skills Training Group for People with Intellectual Disabilities

ERIC Educational Resources Information Center

Crossland, Tom; Hewitt, Olivia; Walden, Sarah

2017-01-01

Background: A growing body of evidence supports the use of Dialectic Behaviour Therapy with people with an intellectual disability. Various adaptation have been used in studies exploring the efficacy of this intervention. Method: A Dialectic Behaviour Therapy DBT skills training group was attended by people with an intellectual disability and…

Adapting and Evaluating a Tree of Life Group for Women with Learning Disabilities

ERIC Educational Resources Information Center

Randle-Phillips, Cathy; Farquhar, Sarah; Thomas, Sally

2016-01-01

Background: This study describes how a specific narrative therapy approach called 'the tree of life' was adapted to run a group for women with learning disabilities. The group consisted of four participants and ran for five consecutive weeks. Materials and Methods: Participants each constructed a tree to represent their lives and presented their…

Social Contextual Links to Emotion Regulation in an Adolescent Psychiatric Inpatient Population: Do Gender and Symptomatology Matter?

ERIC Educational Resources Information Center

Adrian, Molly; Zeman, Janice; Erdley, Cynthia; Lisa, Ludmila; Homan, Kendra; Sim, Leslie

2009-01-01

Background: The regulation of emotion is essential for adaptive functioning. However, delineating the pathways of emotion regulation (ER) processes that lead to psychological adaptation remains under-studied, with mixed evidence for the specificity vs. generality of ER deficits in relation to specific forms of psychopathology. To examine this…

Academic Adaptation Amid Internationalisation: The Challenges for Local, Mainland Chinese, and International Students at Hong Kong's Universities

ERIC Educational Resources Information Center

Yu, Baohua; Wright, Ewan

2017-01-01

Internationalisation has been actively pursued by Hong Kong's universities. Recent years have witnessed quantitative growth in non-local students. To ensure a qualitative success of internationalisation, it is crucial that universities cater for students with diverse academic backgrounds. This research explored challenges to academic adaptation.…

What Can the Semantic Web Do for Adaptive Educational Hypermedia?

ERIC Educational Resources Information Center

Cristea, Alexandra I.

2004-01-01

Semantic Web and Adaptive Hypermedia come from different backgrounds, but it turns out that actually, they can benefit from each other, and that their confluence can lead to synergistic effects. This encounter can influence several fields, among which an important one is Education. This paper presents an analysis of this encounter, first from a…

Is local best? Examining the evidence for local adaptation in trees and its scale

Treesearch

David Boshier; Linda Broadhurst; Jonathan Cornelius; Leonardo Gallo; Jarkko Koskela; Judy Loo; Gillian Petrokofsky; Brad St. Clair

2015-01-01

Background: Although the importance of using local provenance planting stock for woodland production, habitat conservation and restoration remains contentious, the concept is easy to understand, attractive and easy to ‘sell’. With limited information about the extent and scale of adaptive variation in native trees, discussion about suitable...

Rasch analysis of the Mini-Mental Adjustment to Cancer Scale (mini-MAC) among a heterogeneous sample of long-term cancer survivors: A cross-sectional study

PubMed Central

2012-01-01

Background The mini-Mental Adjustment to Cancer Scale (mini-MAC) is a well-recognised, popular measure of coping in psycho-oncology and assesses five cancer-specific coping strategies. It has been suggested that these five subscales could be grouped to form the over-arching adaptive and maladptive coping subscales to facilitate the interpretation and clinical application of the scale. Despite the popularity of the mini-MAC, few studies have examined its psychometric properties among long-term cancer survivors, and further validation of the mini-MAC is needed to substantiate its use with the growing population of survivors. Therefore, this study examined the psychometric properties and dimensionality of the mini-MAC in a sample of long-term cancer survivors using Rasch analysis. Methods RUMM 2030 was used to analyse the mini-MAC data (n=851). Separate Rasch analyses were conducted for each of the original mini-MAC subscales as well as the over-arching adaptive and maladaptive coping subscales to examine summary and individual model fit statistics, person separation index (PSI), response format, local dependency, targeting, item bias (or differential item functioning -DIF), and dimensionality. Results For the fighting spirit, fatalism, and helplessness-hopelessness subscales, a revised three-point response format seemed more optimal than the original four-point response. To achieve model fit, items were deleted from four of the five subscales – Anxious Preoccupation items 7, 25, and 29; Cognitive Avoidance items 11 and 17; Fighting Spirit item 18; and Helplessness-Hopelessness items 16 and 20. For those subscales with sufficient items, analyses supported unidimensionality. Combining items to form the adaptive and maladaptive subscales was partially supported. Conclusions The original five subscales required item deletion and/or rescaling to improve goodness of fit to the Rasch model. While evidence was found for overarching subscales of adaptive and maladaptive coping, extensive modifications were necessary to achieve this result. Further exploration and validation of over-arching subscales assessing adaptive and maladaptive coping is necessary with cancer survivors. PMID:22607052

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

Stroeer, Alexander; Veitch, John

The Laser Interferometer Space Antenna (LISA) defines new demands on data analysis efforts in its all-sky gravitational wave survey, recording simultaneously thousands of galactic compact object binary foreground sources and tens to hundreds of background sources like binary black hole mergers and extreme-mass ratio inspirals. We approach this problem with an adaptive and fully automatic Reversible Jump Markov Chain Monte Carlo sampler, able to sample from the joint posterior density function (as established by Bayes theorem) for a given mixture of signals ''out of the box'', handling the total number of signals as an additional unknown parameter beside the unknownmore » parameters of each individual source and the noise floor. We show in examples from the LISA Mock Data Challenge implementing the full response of LISA in its TDI description that this sampler is able to extract monochromatic Double White Dwarf signals out of colored instrumental noise and additional foreground and background noise successfully in a global fitting approach. We introduce 2 examples with fixed number of signals (MCMC sampling), and 1 example with unknown number of signals (RJ-MCMC), the latter further promoting the idea behind an experimental adaptation of the model indicator proposal densities in the main sampling stage. We note that the experienced runtimes and degeneracies in parameter extraction limit the shown examples to the extraction of a low but realistic number of signals.« less

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

PubMed

Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

2016-02-01

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

Agenda Setting for Health Promotion: Exploring an Adapted Model for the Social Media Era

PubMed Central

2015-01-01

Background The foundation of best practice in health promotion is a robust theoretical base that informs design, implementation, and evaluation of interventions that promote the public’s health. This study provides a novel contribution to health promotion through the adaptation of the agenda-setting approach in response to the contribution of social media. This exploration and proposed adaptation is derived from a study that examined the effectiveness of Twitter in influencing agenda setting among users in relation to road traffic accidents in Saudi Arabia. Objective The proposed adaptations to the agenda-setting model to be explored reflect two levels of engagement: agenda setting within the social media sphere and the position of social media within classic agenda setting. This exploratory research aims to assess the veracity of the proposed adaptations on the basis of the hypotheses developed to test these two levels of engagement. Methods To validate the hypotheses, we collected and analyzed data from two primary sources: Twitter activities and Saudi national newspapers. Keyword mentions served as indicators of agenda promotion; for Twitter, interactions were used to measure the process of agenda setting within the platform. The Twitter final dataset comprised 59,046 tweets and 38,066 users who contributed by tweeting, replying, or retweeting. Variables were collected for each tweet and user. In addition, 518 keyword mentions were recorded from six popular Saudi national newspapers. Results The results showed significant ratification of the study hypotheses at both levels of engagement that framed the proposed adaptions. The results indicate that social media facilitates the contribution of individuals in influencing agendas (individual users accounted for 76.29%, 67.79%, and 96.16% of retweet impressions, total impressions, and amplification multipliers, respectively), a component missing from traditional constructions of agenda-setting models. The influence of organizations on agenda setting is also highlighted (in the data of user interactions, organizational accounts registered 17% and 14.74% as source and target of interactions, respectively). In addition, 13 striking similarities showed the relationship between newspapers and Twitter on the mentions trends line. Conclusions The effective use of social media platforms in health promotion intervention programs requires new strategies that consider the limitations of traditional communication channels. Conducting research is vital to establishing a strong basis for modifying, designing, and developing new health promotion strategies and approaches. PMID:27227139

A model-based exploration of the role of pattern generating circuits during locomotor adaptation.

PubMed

Marjaninejad, Ali; Finley, James M

2016-08-01

In this study, we used a model-based approach to explore the potential contributions of central pattern generating circuits (CPGs) during adaptation to external perturbations during locomotion. We constructed a neuromechanical modeled of locomotion using a reduced-phase CPG controller and an inverted pendulum mechanical model. Two different forms of locomotor adaptation were examined in this study: split-belt treadmill adaptation and adaptation to a unilateral, elastic force field. For each simulation, we first examined the effects of phase resetting and varying the model's initial conditions on the resulting adaptation. After evaluating the effect of phase resetting on the adaptation of step length symmetry, we examined the extent to which the results from these simple models could explain previous experimental observations. We found that adaptation of step length symmetry during split-belt treadmill walking could be reproduced using our model, but this model failed to replicate patterns of adaptation observed in response to force field perturbations. Given that spinal animal models can adapt to both of these types of perturbations, our findings suggest that there may be distinct features of pattern generating circuits that mediate each form of adaptation.

Measurement of a model of implementation for health care: toward a testable theory

PubMed Central

2012-01-01

Background Greenhalgh et al. used a considerable evidence-base to develop a comprehensive model of implementation of innovations in healthcare organizations [1]. However, these authors did not fully operationalize their model, making it difficult to test formally. The present paper represents a first step in operationalizing Greenhalgh et al.’s model by providing background, rationale, working definitions, and measurement of key constructs. Methods A systematic review of the literature was conducted for key words representing 53 separate sub-constructs from six of the model’s broad constructs. Using an iterative process, we reviewed existing measures and utilized or adapted items. Where no one measure was deemed appropriate, we developed other items to measure the constructs through consensus. Results The review and iterative process of team consensus identified three types of data that can been used to operationalize the constructs in the model: survey items, interview questions, and administrative data. Specific examples of each of these are reported. Conclusion Despite limitations, the mixed-methods approach to measurement using the survey, interview measure, and administrative data can facilitate research on implementation by providing investigators with a measurement tool that captures most of the constructs identified by the Greenhalgh model. These measures are currently being used to collect data concerning the implementation of two evidence-based psychotherapies disseminated nationally within Department of Veterans Affairs. Testing of psychometric properties and subsequent refinement should enhance the utility of the measures. PMID:22759451

MRSA model of learning and adaptation: a qualitative study among the general public

PubMed Central

2012-01-01

Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA) infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1) a common model of MRSA learning and adaptation; 2) the self-directed nature of adult learning; 3) the focus on general MRSA information, care and prevention, and antibiotic resistance; 4) the interconnected nature of adaptation; and, 5) the need for a consistent step by step plan to deal with MRSA provided at the time of diagnosis. PMID:22469420

Emergence of Adaptive Computation by Single Neurons in the Developing Cortex

PubMed Central

Famulare, Michael; Gjorgjieva, Julijana; Moody, William J.

2013-01-01

Adaptation is a fundamental computational motif in neural processing. To maintain stable perception in the face of rapidly shifting input, neural systems must extract relevant information from background fluctuations under many different contexts. Many neural systems are able to adjust their input–output properties such that an input's ability to trigger a response depends on the size of that input relative to its local statistical context. This “gain-scaling” strategy has been shown to be an efficient coding strategy. We report here that this property emerges during early development as an intrinsic property of single neurons in mouse sensorimotor cortex, coinciding with the disappearance of spontaneous waves of network activity, and can be modulated by changing the balance of spike-generating currents. Simultaneously, developing neurons move toward a common intrinsic operating point and a stable ratio of spike-generating currents. This developmental trajectory occurs in the absence of sensory input or spontaneous network activity. Through a combination of electrophysiology and modeling, we demonstrate that developing cortical neurons develop the ability to perform nearly perfect gain scaling by virtue of the maturing spike-generating currents alone. We use reduced single neuron models to identify the conditions for this property to hold. PMID:23884925

Neuro- and sensoriphysiological Adaptations to Microgravity using Fish as Model System

NASA Astrophysics Data System (ADS)

Anken, R.

The phylogenetic development of all organisms took place under constant gravity conditions, against which they achieved specific countermeasures for compensation and adaptation. On this background, it is still an open question to which extent altered gravity such as hyper- or microgravity (centrifuge/spaceflight) affects the normal individual development, either on the systemic level of the whole organism or on the level of individual organs or even single cells. The present review provides information on this topic, focusing on the effects of altered gravity on developing fish as model systems even for higher vertebrates including humans, with special emphasis on the effect of altered gravity on behaviour and particularly on the developing brain and vestibular system. Overall, the results speak in favour of the following concept: Short-term altered gravity (˜ 1 day) can induce transient sensorimotor disorders (kinetoses) due to malfunctions of the inner ear, originating from asymmetric otoliths. The regain of normal postural control is likely due to a reweighing of sensory inputs. During long-term altered gravity (several days and more), complex adptations on the level of the central and peripheral vestibular system occur. This work was financially supported by the German Aerospace Center (DLR) e.V. (FKZ: 50 WB 9997).

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Rapid perceptual adaptation to high gravitoinertial force levels Evidence for context-specific adaptation

NASA Technical Reports Server (NTRS)

Lackner, J. R.; Graybiel, A.

1982-01-01

Subjects exposed to periodic variations in gravitoinertial force (2-G peak) in parabolic flight maneuvers quickly come to perceive the peak force level as having decreased in intensity. By the end of a 40-parabola flight, the decrease in apparent force is approximately 40%. On successive flight days, the apparent intensity of the force loads seems to decrease as well, indicating a cumulative adaptive effect. None of the subjects reported feeling abnormally 'light' for more than a minute or two after return to 1-G background force levels. The pattern of findings suggests a context-specific adaptation to high-force levels.

A Comparative Study of Backgrounds and Attitudes of Community College Academic Staff.

ERIC Educational Resources Information Center

Melone, Rudolph Joseph

Community colleges should be responsive to the shifting needs of society. As in the case of other organizations, however, the ability to initiate and adapt to the necessary changes is dependent on the attitudes and backgrounds of the people in the institution. A primary concern of this study was determining whether junior colleges accept the…

Adapted Physical Activity Programme and Self-Perception in Obese Adolescents with Intellectual Disability: Between Morphological Awareness and Positive Illusory Bias

ERIC Educational Resources Information Center

Salaun, Laureline; Reynes, Eric; Berthouze-Aranda, Sophie E.

2014-01-01

Background: In adolescents with intellectual disability, the management of obesity is a crucial issue, yet also quite complex because of their particular perception of themselves. This study investigated the relationship between self-perception variables and morphological variables and their changes after a 9-month Adapted Physical Activity (APA)…

Adapted Intervention Mapping: A Strategic Planning Process for Increasing Physical Activity and Healthy Eating Opportunities in Schools via Environment and Policy Change

ERIC Educational Resources Information Center

Belansky, Elaine S.; Cutforth, Nick; Chavez, Robert; Crane, Lori A.; Waters, Emily; Marshall, Julie A.

2013-01-01

Background: School environment and policy changes have increased healthy eating and physical activity; however, there has been modest success in translating research ?ndings to practice. The School Environment Project tested whether an adapted version of Intervention Mapping (AIM) resulted in school change. Methods: Using a pair randomized design,…

Comparison of self-reported weight status among followers of popular diets: data from the ADAPT (adhering to dietary approaches for personal taste) feasibility survey

USDA-ARS?s Scientific Manuscript database

Background: Public interest in nutrition is at the forefront of health and wellness and a major driver of popular diet adoption. Cohort studies lack specific data from followers of popular diets. Adhering to Dietary Approaches for Personal Taste (ADAPT) Feasibility Survey (FS) assessed the practical...

The Adaptation of a School-Based Health Promotion Programme for Youth with Intellectual and Developmental Disabilities: A Community-Engaged Research Process

ERIC Educational Resources Information Center

Hubbard, Kristie L.; Bandini, Linda G.; Folta, Sara C.; Wansink, Brian; Must, Aviva

2014-01-01

Background: Evidenced-based health promotion programmes for youth with intellectual and developmental disabilities (I/DD) are notably absent. Barriers include a lack of understanding of how to adapt existing evidence-based programmes to their needs, maximize inclusion and support mutual goals of health and autonomy. Methods: We undertook a…

The Psychometric Analysis of the Persian Version of the Strategy Inventory for Language Learning of Rebecca L. Oxford

ERIC Educational Resources Information Center

Fazeli, Seyed Hossein

2012-01-01

The current study aims to analyze the psychometric qualities of the Persian adapted version of Strategy Inventory for Language Learning (SILL) developed by Rebecca L. Oxford (1990). Three instruments were used: Persian adapted version of SILL, a Background Questionnaire, and Test of English as a Foreign Language. Two hundred and thirteen Iranian…

Emotional Stability as a Condition of Students' Adaptation to Studying in a Higher Educational Institution

ERIC Educational Resources Information Center

Serebryakova, Tat'yana A.; Morozova, Lyudmila B.; Kochneva, Elena M.; Zharova, Darya V.; Kostyleva, Elena A.; Kolarkova, Oxana G.

2016-01-01

Background/Objectives: The objective of the paper is analysis and description of findings of an empiric study on the issue of social and psychological adaptation of first year students to studying in a higher educational institution. Methods/Statistical analysis: Using the methods of theoretical analysis the paper's authors plan and carry out an…

Family Quality of Life: Adaptation to Spanish Population of Several Family Support Questionnaires

ERIC Educational Resources Information Center

Balcells-Balcells, A.; Gine, C.; Guardia-Olmos, J.; Summers, J. A.

2011-01-01

Background: The concept of family quality of life has emerged as a decisive construct in the last decades to improve the capabilities of families and to assess the outcomes of the services and supports they get. The goal of this research is to adapt three instruments to the Spanish population: the "Beach Center Family Quality of Life…

Cell culture-adaptive mutations of NS5A affect replication of hepatitis C virus differentially depending on the viral genotypes.

PubMed

Chung, Aeri; Jin, Bora; Han, Kwang-Hyub; Ahn, Sang Hoon; Kim, Seungtaek

2017-01-01

Most of HCV RNAs require cell culture-adaptive mutations for efficient replication in cell culture and a number of such mutations have been described including a well-known S2204I substitution mutation in NS5A protein. In contrast, the replication of genotype 2a JFH1 RNA in cell culture does not require any cell culture-adaptive mutation. Rather, the presence of S2204I mutation impaired the JFH1 RNA replication. In this study, we examined the effect of reversions and substitutions of NS5A cell culture-adaptive mutations on virus replication in different genotypic backgrounds after either placing genotype 1a NS5A in the genotype 2a JFH1 or vice versa. The results from this investigation suggest that the S2204I mutation affects HCV RNA replication differentially depending on the viral genotypes but that the effect was not simply explained by the genotypic background. Perhaps, the effect of the S2204I mutation on HCV replication reflects both intra- and intergenic interactions of NS5A protein. J. Med. Virol. 89:146-152, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A diversified portfolio model of adaptability.

PubMed

Chandra, Siddharth; Leong, Frederick T L

2016-12-01

A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Opinion dynamics in a group-based society

NASA Astrophysics Data System (ADS)

Gargiulo, F.; Huet, S.

2010-09-01

Many models have been proposed to analyze the evolution of opinion structure due to the interaction of individuals in their social environment. Such models analyze the spreading of ideas both in completely interacting backgrounds and on social networks, where each person has a finite set of interlocutors. In this paper we analyze the reciprocal feedback between the opinions of the individuals and the structure of the interpersonal relationships at the level of community structures. For this purpose we define a group-based random network and we study how this structure co-evolves with opinion dynamics processes. We observe that the adaptive network structure affects the opinion dynamics process helping the consensus formation. The results also show interesting behaviors in regards to the size distribution of the groups and their correlation with opinion structure.

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

NASA Astrophysics Data System (ADS)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

Wind profiling for a coherent wind Doppler lidar by an auto-adaptive background subtraction approach.

PubMed

Wu, Yanwei; Guo, Pan; Chen, Siying; Chen, He; Zhang, Yinchao

2017-04-01

Auto-adaptive background subtraction (AABS) is proposed as a denoising method for data processing of the coherent Doppler lidar (CDL). The method is proposed specifically for a low-signal-to-noise-ratio regime, in which the drifting power spectral density of CDL data occurs. Unlike the periodogram maximum (PM) and adaptive iteratively reweighted penalized least squares (airPLS), the proposed method presents reliable peaks and is thus advantageous in identifying peak locations. According to the analysis results of simulated and actually measured data, the proposed method outperforms the airPLS method and the PM algorithm in the furthest detectable range. The proposed method improves the detection range approximately up to 16.7% and 40% when compared to the airPLS method and the PM method, respectively. It also has smaller mean wind velocity and standard error values than the airPLS and PM methods. The AABS approach improves the quality of Doppler shift estimates and can be applied to obtain the whole wind profiling by the CDL.

Small Infrared Target Detection by Region-Adaptive Clutter Rejection for Sea-Based Infrared Search and Track

PubMed Central

Kim, Sungho; Lee, Joohyoung

2014-01-01

This paper presents a region-adaptive clutter rejection method for small target detection in sea-based infrared search and track. In the real world, clutter normally generates many false detections that impede the deployment of such detection systems. Incoming targets (missiles, boats, etc.) can be located in the sky, horizon and sea regions, which have different types of clutters, such as clouds, a horizontal line and sea-glint. The characteristics of regional clutter were analyzed after the geometrical analysis-based region segmentation. The false detections caused by cloud clutter were removed by the spatial attribute-based classification. Those by the horizontal line were removed using the heterogeneous background removal filter. False alarms by sun-glint were rejected using the temporal consistency filter, which is the most difficult part. The experimental results of the various cluttered background sequences show that the proposed region adaptive clutter rejection method produces fewer false alarms than that of the mean subtraction filter (MSF) with an acceptable degradation detection rate. PMID:25054633

High Strain Rate Deformation Modeling of a Polymer Matrix Composite. Part 1; Matrix Constitutive Equations

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Stouffer, Donald C.

1998-01-01

Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this first paper of a two part report, background information is presented, along with the constitutive equations which will be used to model the rate dependent nonlinear deformation response of the polymer matrix. Strain rate dependent inelastic constitutive models which were originally developed to model the viscoplastic deformation of metals have been adapted to model the nonlinear viscoelastic deformation of polymers. The modified equations were correlated by analyzing the tensile/ compressive response of both 977-2 toughened epoxy matrix and PEEK thermoplastic matrix over a variety of strain rates. For the cases examined, the modified constitutive equations appear to do an adequate job of modeling the polymer deformation response. A second follow-up paper will describe the implementation of the polymer deformation model into a composite micromechanical model, to allow for the modeling of the nonlinear, rate dependent deformation response of polymer matrix composites.

Characterization of the transcriptome of an ecologically important avian species, the Vinous-throated Parrotbill Paradoxornis webbianus bulomachus (Paradoxornithidae; Aves)

PubMed Central

2012-01-01

Background Adaptive divergence driven by environmental heterogeneity has long been a fascinating topic in ecology and evolutionary biology. The study of the genetic basis of adaptive divergence has, however, been greatly hampered by a lack of genomic information. The recent development of transcriptome sequencing provides an unprecedented opportunity to generate large amounts of genomic data for detailed investigations of the genetics of adaptive divergence in non-model organisms. Herein, we used the Illumina sequencing platform to sequence the transcriptome of brain and liver tissues from a single individual of the Vinous-throated Parrotbill, Paradoxornis webbianus bulomachus, an ecologically important avian species in Taiwan with a wide elevational range of sea level to 3100 m. Results Our 10.1 Gbp of sequences were first assembled based on Zebra Finch (Taeniopygia guttata) and chicken (Gallus gallus) RNA references. The remaining reads were then de novo assembled. After filtering out contigs with low coverage (<10X), we retained 67,791 of 487,336 contigs, which covered approximately 5.3% of the P. w. bulomachus genome. Of 7,779 contigs retained for a top-hit species distribution analysis, the majority (about 86%) were matched to known Zebra Finch and chicken transcripts. We also annotated 6,365 contigs to gene ontology (GO) terms: in total, 122 GO-slim terms were assigned, including biological process (41%), molecular function (32%), and cellular component (27%). Many potential genetic markers for future adaptive genomic studies were also identified: 8,589 single nucleotide polymorphisms, 1,344 simple sequence repeats and 109 candidate genes that might be involved in elevational or climate adaptation. Conclusions Our study shows that transcriptome data can serve as a rich genetic resource, even for a single run of short-read sequencing from a single individual of a non-model species. This is the first study providing transcriptomic information for species in the avian superfamily Sylvioidea, which comprises more than 1,000 species. Our data can be used to study adaptive divergence in heterogeneous environments and investigate other important ecological and evolutionary questions in parrotbills from different populations and even in other species in the Sylvioidea. PMID:22530590

Real-Time State Estimation and Long-Term Model Adaptation: A Two-Sided Approach toward Personalized Diagnosis of Glucose and Insulin Levels

PubMed Central

Eberle, Claudia; Ament, Christoph

2012-01-01

Background With continuous glucose sensors (CGSs), it is possible to obtain a dynamical signal of the patient’s subcutaneous glucose concentration in real time. How could that information be exploited? We suggest a model-based diagnosis system with a twofold objective: real-time state estimation and long-term model parameter identification. Methods To obtain a dynamical model, Bergman’s nonlinear minimal model (considering plasma glucose G, insulin I, and interstitial insulin X) is extended by two states describing first and second insulin response. Furthermore, compartments for oral glucose and subcutaneous insulin inputs as well as for subcutaneous glucose measurement are added. The observability of states and external inputs as well as the identifiability of model parameters are assessed using the empirical observability Gramian. Signals are estimated for different nondiabetic and diabetic scenarios by unscented Kalman filter. Results (1) Observability of different state subsets is evaluated, e.g., from CGSs, {G, I} or {G, X} can be observed and the set {G, I, X} cannot. (2) Model parameters are included, e.g., it is possible to estimate the second-phase insulin response gain kG2 additionally. This can be used for model adaptation and as a diagnostic parameter that is almost zero for diabetes patients. (3) External inputs are considered, e.g., oral glucose is theoretically observable for nondiabetic patients, but estimation scenarios show that the time delay of 1 h limits application. Conclusions A real-time estimation of states (such as plasma insulin I) and parameters (such as kG2) is possible, which allows an improved real-time state prediction and a personalized model. PMID:23063042

Adaptive color artwork

NASA Astrophysics Data System (ADS)

Beretta, Giordano

2007-01-01

The words in a document are often supported, illustrated, and enriched by visuals. When color is used, some of it is used to define the document's identity and is therefore strictly controlled in the design process. The result of this design process is a "color specification sheet," which must be created for every background color. While in traditional publishing there are only a few backgrounds, in variable data publishing a larger number of backgrounds can be used. We present an algorithm that nudges the colors in a visual to be distinct from a background while preserving the visual's general color character.

Genetic Background and Environment Influence the Effects of Mutations in pykF and Help Reveal Mechanisms Underlying Their Benefit

DTIC Science & Technology

2015-08-01

another trait (Losos 2011). All of these factors make it hard to identify adaptations. Mutations are the ultimate source of genetic variation that is...effects when added to the same evolved background (See Table 2.2 for results of one-way ANOVAs). Genetic background explains most (~ 88%) of the variation ...in fitness whereas the variation explained by different pykF alleles is negligible (~2%) compared to statistical noise (~8%) (Table 2.3). These

Adapting services to the needs of children and families with complex migration experiences: The Toulouse University Hospital's intercultural consultation.

PubMed

Sturm, Gesine; Guerraoui, Zohra; Bonnet, Sylvie; Gouzvinski, Françoise; Raynaud, Jean-Philippe

2017-08-01

This article presents the recently created intercultural consultation at the Medical and Psychological Health Care Service (CMP) of the University Hospital la Grave at Toulouse. The approach of the intercultural consultation was elaborated in response to the increasing diversity of children and families using the service in Toulouse. It is also based on local research that indicates the difficulties service providers encounter when trying to establish a solid therapeutic alliance with families with complex migration backgrounds who accumulate different disadvantaging factors. The intercultural consultation adapts existing models of culture-sensitive consultations in child mental health care in France and Canada to the local context in Toulouse. We describe the underlying principles of the intercultural consultation work, the therapeutic and mediation techniques used, and the way the work is integrated into the global service provision of the CMP. The process is illustrated with a case study followed by a discussion of the innovations.

The Active Side of Stereopsis: Fixation Strategy and Adaptation to Natural Environments.

PubMed

Gibaldi, Agostino; Canessa, Andrea; Sabatini, Silvio P

2017-03-20

Depth perception in near viewing strongly relies on the interpretation of binocular retinal disparity to obtain stereopsis. Statistical regularities of retinal disparities have been claimed to greatly impact on the neural mechanisms that underlie binocular vision, both to facilitate perceptual decisions and to reduce computational load. In this paper, we designed a novel and unconventional approach in order to assess the role of fixation strategy in conditioning the statistics of retinal disparity. We integrated accurate realistic three-dimensional models of natural scenes with binocular eye movement recording, to obtain accurate ground-truth statistics of retinal disparity experienced by a subject in near viewing. Our results evidence how the organization of human binocular visual system is finely adapted to the disparity statistics characterizing actual fixations, thus revealing a novel role of the active fixation strategy over the binocular visual functionality. This suggests an ecological explanation for the intrinsic preference of stereopsis for a close central object surrounded by a far background, as an early binocular aspect of the figure-ground segregation process.

Face-space: A unifying concept in face recognition research.

PubMed

Valentine, Tim; Lewis, Michael B; Hills, Peter J

2016-10-01

The concept of a multidimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to the development of face-space is explained, and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms, is reviewed. Face-space as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally, two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion, and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception.

From Spiking Neuron Models to Linear-Nonlinear Models

PubMed Central

Ostojic, Srdjan; Brunel, Nicolas

2011-01-01

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates. PMID:21283777

From spiking neuron models to linear-nonlinear models.

PubMed

Ostojic, Srdjan; Brunel, Nicolas

2011-01-20

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

PubMed Central

2011-01-01

Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases. PMID:21385459

A proof for loop-law constraints in stoichiometric metabolic networks

PubMed Central

2012-01-01

Background Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. Results Here we apply Gordan’s theorem from linear algebra to prove for the first time that the constraints added in loopless-COBRA do not over-constrain the problem beyond the elimination of the loops themselves. Conclusions The loopless-COBRA constraints can be reliably applied. Furthermore, this proof may be adapted to evaluate the theoretical soundness for other methods in constraint-based modeling. PMID:23146116

Public Health and Climate Change Adaptation at the Federal Level: One Agency’s Response to Executive Order 13514

PubMed Central

Schramm, Paul J.; Luber, George

2014-01-01

Climate change will likely have adverse human health effects that require federal agency involvement in adaptation activities. In 2009, President Obama issued Executive Order 13514, Federal Leadership in Environmental, Energy, and Economic Performance. The order required federal agencies to develop and implement climate change adaptation plans. The Centers for Disease Control and Prevention (CDC), as part of a larger Department of Health and Human Services response to climate change, is developing such plans. We provide background on Executive Orders, outline tenets of climate change adaptation, discuss public health adaptation planning at both the Department of Health and Human Services and the CDC, and outline possible future CDC efforts. We also consider how these activities may be better integrated with other adaptation activities that manage emerging health threats posed by climate change. PMID:24432931

Public health and climate change adaptation at the federal level: one agency's response to Executive Order 13514.

PubMed

Hess, Jeremy J; Schramm, Paul J; Luber, George

2014-03-01

Climate change will likely have adverse human health effects that require federal agency involvement in adaptation activities. In 2009, President Obama issued Executive Order 13514, Federal Leadership in Environmental, Energy, and Economic Performance. The order required federal agencies to develop and implement climate change adaptation plans. The Centers for Disease Control and Prevention (CDC), as part of a larger Department of Health and Human Services response to climate change, is developing such plans. We provide background on Executive Orders, outline tenets of climate change adaptation, discuss public health adaptation planning at both the Department of Health and Human Services and the CDC, and outline possible future CDC efforts. We also consider how these activities may be better integrated with other adaptation activities that manage emerging health threats posed by climate change.

The case of a city where 1 in 6 residents is a refugee: ecological factors and host community adaptation in successful resettlement.

PubMed

Smith, R Scott

2008-12-01

The notable success of an upstate New York community in resettling refugees raises the question of whether multiple waves of resettlement over a 15-year period have resulted in greater accommodation to refugees. Structured interviews based on transactional models of acculturation were used along with archival data to explore ecological factors supporting a host community's behavioral flexibility and perseverance in response to the influx of refugees. Evidence suggests that socioeconomic climate, historical background/social norms, and the organizational structure of agencies involved in resettlement moderate successful inclusion of refugees into a host community in a bidirectional process.

Shift Work in Nurses: Contribution of Phenotypes and Genotypes to Adaptation

PubMed Central

Gamble, Karen L.; Motsinger-Reif, Alison A.; Hida, Akiko; Borsetti, Hugo M.; Servick, Stein V.; Ciarleglio, Christopher M.; Robbins, Sam; Hicks, Jennifer; Carver, Krista; Hamilton, Nalo; Wells, Nancy; Summar, Marshall L.; McMahon, Douglas G.; Johnson, Carl Hirschie

2011-01-01

Background Daily cycles of sleep/wake, hormones, and physiological processes are often misaligned with behavioral patterns during shift work, leading to an increased risk of developing cardiovascular/metabolic/gastrointestinal disorders, some types of cancer, and mental disorders including depression and anxiety. It is unclear how sleep timing, chronotype, and circadian clock gene variation contribute to adaptation to shift work. Methods Newly defined sleep strategies, chronotype, and genotype for polymorphisms in circadian clock genes were assessed in 388 hospital day- and night-shift nurses. Results Night-shift nurses who used sleep deprivation as a means to switch to and from diurnal sleep on work days (∼25%) were the most poorly adapted to their work schedule. Chronotype also influenced efficacy of adaptation. In addition, polymorphisms in CLOCK, NPAS2, PER2, and PER3 were significantly associated with outcomes such as alcohol/caffeine consumption and sleepiness, as well as sleep phase, inertia and duration in both single- and multi-locus models. Many of these results were specific to shift type suggesting an interaction between genotype and environment (in this case, shift work). Conclusions Sleep strategy, chronotype, and genotype contribute to the adaptation of the circadian system to an environment that switches frequently and/or irregularly between different schedules of the light-dark cycle and social/workplace time. This study of shift work nurses illustrates how an environmental “stress” to the temporal organization of physiology and metabolism can have behavioral and health-related consequences. Because nurses are a key component of health care, these findings could have important implications for health-care policy. PMID:21533241

Divergent and convergent evolution in metastases suggest treatment strategies based on specific metastatic sites

PubMed Central

Cunningham, Jessica J.; Brown, Joel S.; Vincent, Thomas L.

2015-01-01

Background and objective: Systemic therapy for metastatic cancer is currently determined exclusively by the site of tumor origin. Yet, there is increasing evidence that the molecular characteristics of metastases significantly differ from the primary tumor. We define the evolutionary dynamics of metastases that govern this molecular divergence and examine their potential contribution to variations in response to targeted therapies. Methodology: Darwinian interactions of transformed cells with the tissue microenvironments at primary and metastatic sites are analyzed using evolutionary game theory. Computational models simulate responses to targeted therapies in different organs within the same patient. Results: Tumor cells, although maximally fit at their primary site, typically have lower fitness on the adaptive landscapes offered by the metastatic sites due to organ-specific variations in mesenchymal properties and signaling pathways. Clinically evident metastases usually exhibit time-dependent divergence from the phenotypic mean of the primary population as the tumor cells evolve and adapt to their new circumstances. In contrast, tumors from different primary sites evolving on identical metastatic adaptive landscapes exhibit phenotypic convergence. Thus, metastases in the liver from different primary tumors and even in different hosts will evolve toward similar adaptive phenotypes. The combination of evolutionary divergence from the primary cancer phenotype and convergence towards similar adaptive strategies in the same tissue cause significant variations in treatment responses particularly for highly targeted therapies. Conclusion and implications: The results suggest that optimal therapies for disseminated cancer must take into account the site(s) of metastatic growth as well as the primary organ. PMID:25794501

RSAT: regulatory sequence analysis tools.

PubMed

Thomas-Chollier, Morgane; Sand, Olivier; Turatsinze, Jean-Valéry; Janky, Rekin's; Defrance, Matthieu; Vervisch, Eric; Brohée, Sylvain; van Helden, Jacques

2008-07-01

The regulatory sequence analysis tools (RSAT, http://rsat.ulb.ac.be/rsat/) is a software suite that integrates a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. The suite includes programs for sequence retrieval, pattern discovery, phylogenetic footprint detection, pattern matching, genome scanning and feature map drawing. Random controls can be performed with random gene selections or by generating random sequences according to a variety of background models (Bernoulli, Markov). Beyond the original word-based pattern-discovery tools (oligo-analysis and dyad-analysis), we recently added a battery of tools for matrix-based detection of cis-acting elements, with some original features (adaptive background models, Markov-chain estimation of P-values) that do not exist in other matrix-based scanning tools. The web server offers an intuitive interface, where each program can be accessed either separately or connected to the other tools. In addition, the tools are now available as web services, enabling their integration in programmatic workflows. Genomes are regularly updated from various genome repositories (NCBI and EnsEMBL) and 682 organisms are currently supported. Since 1998, the tools have been used by several hundreds of researchers from all over the world. Several predictions made with RSAT were validated experimentally and published.

Optimizing countershading camouflage.

PubMed

Cuthill, Innes C; Sanghera, N Simon; Penacchio, Olivier; Lovell, Paul George; Ruxton, Graeme D; Harris, Julie M

2016-11-15

Countershading, the widespread tendency of animals to be darker on the side that receives strongest illumination, has classically been explained as an adaptation for camouflage: obliterating cues to 3D shape and enhancing background matching. However, there have only been two quantitative tests of whether the patterns observed in different species match the optimal shading to obliterate 3D cues, and no tests of whether optimal countershading actually improves concealment or survival. We use a mathematical model of the light field to predict the optimal countershading for concealment that is specific to the light environment and then test this prediction with correspondingly patterned model "caterpillars" exposed to avian predation in the field. We show that the optimal countershading is strongly illumination-dependent. A relatively sharp transition in surface patterning from dark to light is only optimal under direct solar illumination; if there is diffuse illumination from cloudy skies or shade, the pattern provides no advantage over homogeneous background-matching coloration. Conversely, a smoother gradation between dark and light is optimal under cloudy skies or shade. The demonstration of these illumination-dependent effects of different countershading patterns on predation risk strongly supports the comparative evidence showing that the type of countershading varies with light environment.

Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation.

PubMed

Zana, F; Klein, J C

2001-01-01

This paper presents an algorithm based on mathematical morphology and curvature evaluation for the detection of vessel-like patterns in a noisy environment. Such patterns are very common in medical images. Vessel detection is interesting for the computation of parameters related to blood flow. Its tree-like geometry makes it a usable feature for registration between images that can be of a different nature. In order to define vessel-like patterns, segmentation is performed with respect to a precise model. We define a vessel as a bright pattern, piece-wise connected, and locally linear, mathematical morphology is very well adapted to this description, however other patterns fit such a morphological description. In order to differentiate vessels from analogous background patterns, a cross-curvature evaluation is performed. They are separated out as they have a specific Gaussian-like profile whose curvature varies smoothly along the vessel. The detection algorithm that derives directly from this modeling is based on four steps: (1) noise reduction; (2) linear pattern with Gaussian-like profile improvement; (3) cross-curvature evaluation; (4) linear filtering. We present its theoretical background and illustrate it on real images of various natures, then evaluate its robustness and its accuracy with respect to noise.

Model observer design for multi-signal detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Park, Subok

2017-02-01

As psychophysical studies are resource-intensive to conduct, model observers are commonly used to assess and optimize medical imaging quality. Model observers are typically designed to detect at most one signal. However, in clinical practice, there may be multiple abnormalities in a single image set (e.g. multifocal multicentric (MFMC) breast cancer), which can impact treatment planning. Prevalence of signals can be different across anatomical regions, and human observers do not know the number or location of signals a priori. As new imaging techniques have the potential to improve multiple-signal detection (e.g. digital breast tomosynthesis may be more effective for diagnosis of MFMC than mammography), image quality assessment approaches addressing such tasks are needed. In this study, we present a model observer to detect multiple signals in an image dataset. A novel implementation of partial least squares (PLS) was developed to estimate different sets of efficient channels directly from the images. The PLS channels are adaptive to the characteristics of signals and the background, and they capture the interactions among signal locations. Corresponding linear decision templates are employed to generate both image-level and location-specific scores on the presence of signals. Our results show that: (1) the model observer can achieve high performance with a reasonably small number of channels; (2) the model observer with PLS channels outperforms that with benchmark modified Laguerre-Gauss channels, especially when realistic signal shapes and complex background statistics are involved; (3) the tasks of clinical interest, and other constraints such as sample size would alter the optimal design of the model observer.

Contribution of silent mutations to thermal adaptation of RNA bacteriophage Qβ.

PubMed

Kashiwagi, Akiko; Sugawara, Ryu; Sano Tsushima, Fumie; Kumagai, Tomofumi; Yomo, Tetsuya

2014-10-01

Changes in protein function and other biological properties, such as RNA structure, are crucial for adaptation of organisms to novel or inhibitory environments. To investigate how mutations that do not alter amino acid sequence may be positively selected, we performed a thermal adaptation experiment using the single-stranded RNA bacteriophage Qβ in which the culture temperature was increased from 37.2°C to 41.2°C and finally to an inhibitory temperature of 43.6°C in a stepwise manner in three independent lines. Whole-genome analysis revealed 31 mutations, including 14 mutations that did not result in amino acid sequence alterations, in this thermal adaptation. Eight of the 31 mutations were observed in all three lines. Reconstruction and fitness analyses of Qβ strains containing only mutations observed in all three lines indicated that five mutations that did not result in amino acid sequence changes but increased the amplification ratio appeared in the course of adaptation to growth at 41.2°C. Moreover, these mutations provided a suitable genetic background for subsequent mutations, altering the fitness contribution from deleterious to beneficial. These results clearly showed that mutations that do not alter the amino acid sequence play important roles in adaptation of this single-stranded RNA virus to elevated temperature. Recent studies using whole-genome analysis technology suggested the importance of mutations that do not alter the amino acid sequence for adaptation of organisms to novel environmental conditions. It is necessary to investigate how these mutations may be positively selected and to determine to what degree such mutations that do not alter amino acid sequences contribute to adaptive evolution. Here, we report the roles of these silent mutations in thermal adaptation of RNA bacteriophage Qβ based on experimental evolution during which Qβ showed adaptation to growth at an inhibitory temperature. Intriguingly, four synonymous mutations and one mutation in the untranslated region that spread widely in the Qβ population during the adaptation process at moderately high temperature provided a suitable genetic background to alter the fitness contribution of subsequent mutations from deleterious to beneficial at a higher temperature. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

[Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

PubMed

Cao, Wu; Li, Wei-jun; Wang, Ping; Zhang, Li-ping

2014-06-01

The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

A low-background piston-cylinder-type hybrid high pressure cell for muon-spin rotation/relaxation experiments

NASA Astrophysics Data System (ADS)

Shermadini, Z.; Khasanov, R.; Elender, M.; Simutis, G.; Guguchia, Z.; Kamenev, K. V.; Amato, A.

2017-10-01

A low background double-wall piston-cylinder-type pressure cell is developed at the Paul Scherrer Institute. The cell is made from BERYLCO-25 (beryllium copper) and MP35N nonmagnetic alloys with the design and dimensions which are specifically adapted to muon-spin rotation/relaxation (μSR) measurements. The mechanical design and performance of the pressure cell are evaluated using finite-element analysis (FEA). By including the measured stress-strain characteristics of the materials into the finite-element model, the cell dimensions are optimized with the aim to reach the highest possible pressure while maintaining the sample space large (6 mm in diameter and 12 mm high). The presented unconventional design of the double-wall piston-cylinder pressure cell with a harder outer MP35N sleeve and a softer inner CuBe cylinder enables pressures of up to 2.6 GPa to be reached at ambient temperature, corresponding to 2.2 GPa at low temperatures without any irreversible damage to the pressure cell. The nature of the muon stopping distribution, mainly in the sample and in the CuBe cylinder, results in a low-background μSR signal.

Adaptation and Validation of the Tower of London Test of Planning and Problem Solving in People with Intellectual Disabilities

ERIC Educational Resources Information Center

Masson, J. D.; Dagnan, D.; Evans, J.

2010-01-01

Background: There is a need for validated, standardised tools for the assessment of executive functions in adults with intellectual disabilities (ID). This study examines the validity of a test of planning and problem solving (Tower of London) with adults with ID. Method: Participants completed an adapted version of the Tower of London (ToL) while…

Cultural Continuity in an Educational Institution: A Case Study of the Suzuki Method of Music Instruction.

ERIC Educational Resources Information Center

Taniuchi, Lois

As the Suzuki method of music instruction has spread from Japan to other countries, its methods have been modified to adapt to the culture of those countries. In this paper the Japanese cultural background, and the principles and methods developed in Japan are discussed and compared with the adaptations made in the United States. The Suzuki method…

Analysis and research on thermal infrared properties and adaptability of the camouflage net

NASA Astrophysics Data System (ADS)

Cui, Guangzhen; Hu, Jianghua; Jian, Chaochao; Yang, Juntang

2016-10-01

As camouflage equipment, camouflage net which covers or obstruct the enemy reconnaissance and attack, have the compatibility such as optics, infrared, radar wave band performance. To improve the adaptive between the camouflage net with background in infrared wavelengths, the heat shield and heat integration requirements on the surface of the camouflage net was analyzed. The condition that satisfied the heat shield was when the average thermal infrared transmittance was less than 25.38% on camouflage screen surface. Studies have shown that camouflage nets and the background field fused together when infrared radiation temperature difference control is within the scope of ± 4K . Experiment on temperature contrast was tested in situ background, thermal camouflage spots and camouflage net with sponge material, the infrared heat maps was recorded in the period of experiment through the thermal imager. Results showed that the thermal inertia of camouflage net was markedly lower than the background and the exposed signs were obvious. It was difficult to reach camouflage thermal infrared fusion requirements by relying on camouflage spot emissivity, but sponge which mix with polymer resin can reduce target significance in the context of mottled and realize the fusion effect.

Rise of the First Super-Massive Stars

NASA Astrophysics Data System (ADS)

Regan, John A.; Downes, Turlough P.

2018-05-01

We use high resolution adaptive mesh refinement simulations to model the formation of massive metal-free stars in the early Universe. By applying Lyman-Werner (LW) backgrounds of 100 J21 and 1000 J21 respectively we construct environments conducive to the formation of massive stars. We find that only in the case of the higher LW backgrounds are super-critical accretion rates realised that are necessary for super-massive star (SMS) formation. Mild fragmentation is observed for both backgrounds. Violent dynamical interactions between the stars that form in the more massive halo formed (1000 J21 background) results in the eventual expulsion of the two most massive stars from the halo. In the smaller mass halo (100 J21 background) mergers of stars occur before any multibody interactions and a single massive Pop III star is left at the centre of the halo at the end of our simulation. Feedback from the very massive Pop III stars is not effective in generating a large HII region with ionising photons absorbed within a few thousand AU of the star. In all cases a massive black hole seed is the expected final fate of the most massive objects. The seed of the massive Pop III star which remained at the centre of the less massive halo experiences steady accretion rates of almost 10-2M_{⊙}/yr and if these rates continue could potentially experience super-Eddington accretion rates in the immediate aftermath of collapsing into a black hole.

Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

PubMed Central

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-01-01

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively. PMID:24871988

Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

PubMed

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-05-27

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

Speech understanding in background noise with the two-microphone adaptive beamformer BEAM in the Nucleus Freedom Cochlear Implant System.

PubMed

Spriet, Ann; Van Deun, Lieselot; Eftaxiadis, Kyriaky; Laneau, Johan; Moonen, Marc; van Dijk, Bas; van Wieringen, Astrid; Wouters, Jan

2007-02-01

This paper evaluates the benefit of the two-microphone adaptive beamformer BEAM in the Nucleus Freedom cochlear implant (CI) system for speech understanding in background noise by CI users. A double-blind evaluation of the two-microphone adaptive beamformer BEAM and a hardware directional microphone was carried out with five adult Nucleus CI users. The test procedure consisted of a pre- and post-test in the lab and a 2-wk trial period at home. In the pre- and post-test, the speech reception threshold (SRT) with sentences and the percentage correct phoneme scores for CVC words were measured in quiet and background noise at different signal-to-noise ratios. Performance was assessed for two different noise configurations (with a single noise source and with three noise sources) and two different noise materials (stationary speech-weighted noise and multitalker babble). During the 2-wk trial period at home, the CI users evaluated the noise reduction performance in different listening conditions by means of the SSQ questionnaire. In addition to the perceptual evaluation, the noise reduction performance of the beamformer was measured physically as a function of the direction of the noise source. Significant improvements of both the SRT in noise (average improvement of 5-16 dB) and the percentage correct phoneme scores (average improvement of 10-41%) were observed with BEAM compared to the standard hardware directional microphone. In addition, the SSQ questionnaire and subjective evaluation in controlled and real-life scenarios suggested a possible preference for the beamformer in noisy environments. The evaluation demonstrates that the adaptive noise reduction algorithm BEAM in the Nucleus Freedom CI-system may significantly increase the speech perception by cochlear implantees in noisy listening conditions. This is the first monolateral (adaptive) noise reduction strategy actually implemented in a mainstream commercial CI.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

PubMed

Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-08-16

Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

MRI Brain Tumor Segmentation and Necrosis Detection Using Adaptive Sobolev Snakes.

PubMed

Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

2014-03-21

Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at different points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D diffusion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

MRI brain tumor segmentation and necrosis detection using adaptive Sobolev snakes

NASA Astrophysics Data System (ADS)

Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

2014-03-01

Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at di erent points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D di usion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

Docking-based classification models for exploratory toxicology ...

EPA Pesticide Factsheets

Background: Exploratory toxicology is a new emerging research area whose ultimate mission is that of protecting human health and environment from risks posed by chemicals. In this regard, the ethical and practical limitation of animal testing has encouraged the promotion of computational methods for the fast screening of huge collections of chemicals available on the market. Results: We derived 24 reliable docking-based classification models able to predict the estrogenic potential of a large collection of chemicals having high quality experimental data, kindly provided by the U.S. Environmental Protection Agency (EPA). The predictive power of our docking-based models was supported by values of AUC, EF1% (EFmax = 7.1), -LR (at SE = 0.75) and +LR (at SE = 0.25) ranging from 0.63 to 0.72, from 2.5 to 6.2, from 0.35 to 0.67 and from 2.05 to 9.84, respectively. In addition, external predictions were successfully made on some representative known estrogenic chemicals. Conclusion: We show how structure-based methods, widely applied to drug discovery programs, can be adapted to meet the conditions of the regulatory context. Importantly, these methods enable one to employ the physicochemical information contained in the X-ray solved biological target and to screen structurally-unrelated chemicals. Shows how structure-based methods, widely applied to drug discovery programs, can be adapted to meet the conditions of the regulatory context. Evaluation of 24 reliable dockin

SuBSENSE: a universal change detection method with local adaptive sensitivity.

PubMed

St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses

PubMed Central

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-01-01

Background Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. Methods A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Results Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12–0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Conclusion Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ. PMID:27660543

Prediction of adaptation difficulties by country of origin, cumulate psychosocial stressors and attitude toward integrating: A Swedish study of first-generation immigrants from Somalia, Vietnam and China

PubMed Central

Zolkowska, Krystyna; McNeil, Thomas F

2015-01-01

Background: Different types of accumulated stress have been found to have negative consequences for immigrants’ capacity to adapt to the new environment. It remains unclear which factors have the greatest influence. Aims: The study investigated whether immigrants’ experience of great difficulty in adapting to a new country could best be explained by (1) country of origin, (2) exposure to accumulated stressors before arrival or (3) after arrival in the new country and/or (4) reserved attitude toward integrating into the new society. Methods: The 119 first-generation immigrants from Somalia, Vietnam and China, living in Malmö, Sweden, were interviewed in a standardized manner. Results: Experiencing great difficulty in adapting to Sweden was independent of length of residence, but significantly related to all four influences, studied one at a time. Country of origin was also related to stressors and attitude. When the effects of the other influences were mutually controlled for, only exposure to accumulated stressors in Sweden (and especially experiencing discrimination/xenophobia/racism) accounted for great adaptation difficulty. Stressors in Sweden had a greater effect if the immigrant had been exposed to stressors earlier. Conclusions: Immigrants’ long-term experiences of great difficulty in adapting to a new country were explained primarily by exposure to accumulated stressors while moving to and living in the new country, rather than by their backgrounds or attitudes toward integrating. This suggests promoting strategies to avoid discrimination and other stressors in the host country. PMID:24927925

An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

2008-01-01

This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

The Family Adaptation Model: A Life Course Perspective. Technical Report 880.

ERIC Educational Resources Information Center

Bowen, Gary L.

This conceptual model for explaining the factors and processes that underlie family adaptation in the Army relies heavily upon two traditions: the "Double ABCX" model of family stress and adaptation and the "Person-Environment Fit" model. The new model has three major parts: the environmental system, the personal system, and family adaptation.…

Light adaptation and dark adaptation of human rod photoreceptors measured from the a-wave of the electroretinogram

PubMed Central

Thomas, M M; Lamb, T D

1999-01-01

We recorded the a-wave of the human electroretinogram from subjects with normal vision, using a corneal electrode and ganzfeld (full-field) light stimulation. From analysis of the rising phase of rod-isolated flash responses we determined the maximum size (amax) of the a-wave, a measure of the massed circulating current of the rods, and the amplification constant (A) of transduction within the rod photoreceptors.During light adaptation by steady backgrounds the maximal response was reduced, as reported previously. amax declined approximately as I0/(I0+IB), where IB is retinal illuminance and I0 is a constant. In different subjects I0 ranged from 40 to 100 trolands, with a mean of 70 trolands, corresponding to about 600 photoisomerizations s−1 per rod. (1 troland is the retinal illuminance that results when a surface luminance of 1 cd m−2 is viewed through a pupil area of 1 mm2.) The amplification constant A decreased only slightly in the presence of steady backgrounds.Following a full bleach amax recovered along an S-shaped curve over a period of 30 min. There was no detectable response for the first 5 min, and half-maximal recovery took 13-17 min.The apparent amplification constant decreased at early times after large bleaches. However, upon correction for reduced light absorption due to loss of pigment, with regeneration of rhodopsin occurring with a time constant of 9-15 min in different subjects, it appeared that the true value of A was probably unchanged by bleaching.The recovery of amax following a bleach could be converted into recovery of equivalent background intensity, using a ‘Crawford transformation’ derived from the light adaptation results. Following bleaches ranging from 10 to > 99 %, the equivalent background intensity decayed approximately exponentially, with a time constant of about 3 min.The time taken for amax to recover to a fixed proportion of its original level increased approximately linearly (rather than logarithmically) with fractional bleach, with a slope of about 12 min per 100 % bleach. Similar behaviour has previously been seen in psychophysical dark adaptation experiments, for the dependence of the ‘second component’ of recovery on the level of bleaching. PMID:10381594

Effects of ocular aberrations on contrast detection in noise.

PubMed

Liang, Bo; Liu, Rong; Dai, Yun; Zhou, Jiawei; Zhou, Yifeng; Zhang, Yudong

2012-08-06

We use adaptive optics (AO) techniques to manipulate the ocular aberrations and elucidate the effects of these ocular aberrations on contrast detection in a noisy background. The detectability of sine wave gratings at frequencies of 4, 8, and 16 circles per degree (cpd) was measured in a standard two-interval force-choice staircase procedure against backgrounds of various levels of white noise. The observer's ocular aberrations were either corrected with AO or left uncorrected. In low levels of external noise, contrast detection thresholds are always lowered by AO correction, whereas in high levels of external noise, they are generally elevated by AO correction. Higher levels of external noise are required to make this threshold elevation observable when signal spatial frequencies increase from 4 to 16 cpd. The linear-amplifier-model fit shows that mostly sampling efficiency and equivalent noise both decrease with AO correction. Our findings indicate that ocular aberrations could be beneficial for contrast detection in high-level noises. The implications of these findings are discussed.

Sensorimotor adaptation is influenced by background music.

PubMed

Bock, Otmar

2010-06-01

It is well established that listening to music can modify subjects' cognitive performance. The present study evaluates whether this so-called Mozart Effect extends beyond cognitive tasks and includes sensorimotor adaptation. Three subject groups listened to musical pieces that in the author's judgment were serene, neutral, or sad, respectively. This judgment was confirmed by the subjects' introspective reports. While listening to music, subjects engaged in a pointing task that required them to adapt to rotated visual feedback. All three groups adapted successfully, but the speed and magnitude of adaptive improvement was more pronounced with serene music than with the other two music types. In contrast, aftereffects upon restoration of normal feedback were independent of music type. These findings support the existence of a "Mozart effect" for strategic movement control, but not for adaptive recalibration. Possibly, listening to music modifies neural activity in an intertwined cognitive-emotional network.

Associations between risk perception, spontaneous adaptation behavior to heat waves and heatstroke in Guangdong province, China

PubMed Central

2013-01-01

Background In many parts of the world, including in China, extreme heat events or heat waves are likely to increase in intensity, frequency, and duration in light of climate change in the next decades. Risk perception and adaptation behaviors are two important components in reducing the health impacts of heat waves, but little is known about their relationships in China. This study aimed to examine the associations between risk perception to heat waves, adaptation behaviors, and heatstroke among the public in Guangdong province, China. Methods A total of 2,183 adult participants were selected using a four-stage sampling method in Guangdong province. From September to November of 2010 each subject was interviewed at home by a well-trained investigator using a structured questionnaire. The information collected included socio-demographic characteristics, risk perception and spontaneous adaptation behaviors during heat wave periods, and heatstroke experience in the last year. Chi-square tests and unconditional logistic regression models were employed to analyze the data. Results This study found that 14.8%, 65.3% and 19.9% of participants perceived heat waves as a low, moderate or high health risk, respectively. About 99.1% participants employed at least one spontaneous adaptation behavior, and 26.2%, 51.2% and 22.6% respondents employed <4, 4–7, and >7 adaptation behaviors during heat waves, respectively. Individuals with moderate (OR=2.93, 95% CI: 1.38-6.22) or high (OR=10.58, 95% CI: 4.74-23.63) risk perception experienced more heatstroke in the past year than others. Drinking more water and wearing light clothes in urban areas, while decreasing activity as well as wearing light clothes in rural areas were negatively associated with heatstroke. Individuals with high risk perception and employing <4 adaptation behaviors during heat waves had the highest risks of heatstroke (OR=47.46, 95% CI: 12.82-175.73). Conclusions There is a large room for improving health risk perception and adaptation capacity to heat waves among the public of Guangdong province. People with higher risk perception and fewer adaptation behaviors during heat waves may be more vulnerable to heat waves. PMID:24088302

Systems analysis of the single photon response in invertebrate photoreceptors.

PubMed

Pumir, Alain; Graves, Jennifer; Ranganathan, Rama; Shraiman, Boris I

2008-07-29

Photoreceptors of Drosophila compound eye employ a G protein-mediated signaling pathway that transduces single photons into transient electrical responses called "quantum bumps" (QB). Although most of the molecular components of this pathway are already known, the system-level understanding of the mechanism of QB generation has remained elusive. Here, we present a quantitative model explaining how QBs emerge from stochastic nonlinear dynamics of the signaling cascade. The model shows that the cascade acts as an "integrate and fire" device and explains how photoreceptors achieve reliable responses to light although keeping low background in the dark. The model predicts the nontrivial behavior of mutants that enhance or suppress signaling and explains the dependence on external calcium, which controls feedback regulation. The results provide insight into physiological questions such as single-photon response efficiency and the adaptation of response to high incident-light level. The system-level analysis enabled by modeling phototransduction provides a foundation for understanding G protein signaling pathways less amenable to quantitative approaches.

Handwritten word preprocessing for database adaptation

NASA Astrophysics Data System (ADS)

Oprean, Cristina; Likforman-Sulem, Laurence; Mokbel, Chafic

2013-01-01

Handwriting recognition systems are typically trained using publicly available databases, where data have been collected in controlled conditions (image resolution, paper background, noise level,...). Since this is not often the case in real-world scenarios, classification performance can be affected when novel data is presented to the word recognition system. To overcome this problem, we present in this paper a new approach called database adaptation. It consists of processing one set (training or test) in order to adapt it to the other set (test or training, respectively). Specifically, two kinds of preprocessing, namely stroke thickness normalization and pixel intensity normalization are considered. The advantage of such approach is that we can re-use the existing recognition system trained on controlled data. We conduct several experiments with the Rimes 2011 word database and with a real-world database. We adapt either the test set or the training set. Results show that training set adaptation achieves better results than test set adaptation, at the cost of a second training stage on the adapted data. Accuracy of data set adaptation is increased by 2% to 3% in absolute value over no adaptation.

Null mutation in the rhodopsin kinase gene slows recovery kinetics of rod and cone phototransduction in man

PubMed Central

Cideciyan, Artur V.; Zhao, Xinyu; Nielsen, Lori; Khani, Shahrokh C.; Jacobson, Samuel G.; Palczewski, Krzysztof

1998-01-01

Rhodopsin kinase (RK), a specialized G-protein-coupled receptor kinase expressed in retina, is involved in quenching of light-induced signal transduction in photoreceptors. The role of RK in recovery after photoactivation has been explored in vitro and in vivo experimentally but has not been specifically defined in humans. We investigated the effects on human vision of a mutation in the RK gene causing Oguchi disease, a recessively inherited retinopathy. In vitro experiments demonstrated that the mutation, a deletion of exon 5, abolishes the enzymatic activity of RK and is likely a null. Both a homozygote and heterozygote with this RK mutation had recovery phase abnormalities of rod-isolated photoresponses by electroretinography (ERG); photoactivation was normal. Kinetics of rod bleaching adaptation by psychophysics were dramatically slowed in the homozygote but normal final thresholds were attained. Light adaptation was normal at low backgrounds but became abnormal at higher backgrounds. A slight slowing of cone deactivation kinetics in the homozygote was detected by ERG. Cone bleaching adaptation and background adaptation were normal. In this human in vivo condition without a functional RK and probable lack of phosphorylation and arrestin binding to activated rhodopsin, reduction of photolyzed chromophore and regeneration processes with 11-cis-retinal probably constitute the sole pathway for recovery of rod sensitivity. The role of RK in rods would thus be to accelerate inactivation of activated rhodopsin molecules that in concert with regeneration leads to the normal rate of recovery of sensitivity. Cones may rely mainly on regeneration for the inactivation of photolyzed visual pigment, but RK also contributes to cone recovery. PMID:9419375

Prediction models for clustered data: comparison of a random intercept and standard regression model

PubMed Central

2013-01-01

Background When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Methods Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. Results The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. Conclusion The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters. PMID:23414436

A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying

PubMed Central

2014-01-01

Background In-silico models that attempt to capture and describe the physiological behavior of biological organisms, including humans, are intrinsically complex and time consuming to build and simulate in a computing environment. The level of detail of description incorporated in the model depends on the knowledge of the system’s behavior at that level. This knowledge is gathered from the literature and/or improved by knowledge obtained from new experiments. Thus model development is an iterative developmental procedure. The objective of this paper is to describe a new plug and play scheme that offers increased flexibility and ease-of-use for modeling and simulating physiological behavior of biological organisms. Methods This scheme requires the modeler (user) first to supply the structure of the interacting components and experimental data in a tabular format. The behavior of the components described in a mathematical form, also provided by the modeler, is externally linked during simulation. The advantage of the plug and play scheme for modeling is that it requires less programming effort and can be quickly adapted to newer modeling requirements while also paving the way for dynamic model building. Results As an illustration, the paper models the dynamics of gastric emptying behavior experienced by humans. The flexibility to adapt the model to predict the gastric emptying behavior under varying types of nutrient infusion in the intestine (ileum) is demonstrated. The predictions were verified with a human intervention study. The error in predicting the half emptying time was found to be less than 6%. Conclusions A new plug-and-play scheme for biological systems modeling was developed that allows changes to the modeled structure and behavior with reduced programming effort, by abstracting the biological system into a network of smaller sub-systems with independent behavior. In the new scheme, the modeling and simulation becomes an automatic machine readable and executable task. PMID:24917054

Development and testing of culturally sensitive patient information material for Turkish, Polish, Russian and Italian migrants with depression or chronic low back pain (KULTINFO): study protocol for a double-blind randomized controlled trial.

PubMed

Hölzel, Lars P; Ries, Zivile; Zill, Jördis M; Kriston, Levente; Dirmaier, Jörg; Härter, Martin; Bermejo, Isaac

2014-07-04

Many of the approximately 15 million people with a migration background living in Germany (19% of the population) are inadequately reached by existing healthcare provision. In the literature, the necessity for cultural adaptation of information material for patients with a migration background is often cited as a measure for improving healthcare.In this study, culturally sensitive information material will be developed and evaluated for patients with a migration background and depression or chronic low back pain. In this respect, it will be examined whether culturally sensitive information material is judged as more useful by the patients than standard translated patient information without cultural adaptation. The implementation and evaluation of culturally sensitive patient information material will occur in the framework of a double-blind randomized controlled parallel-group study in four study centres in Germany. Primary care patients with a Turkish, Polish, Russian or Italian migration background with a diagnosis of depressive disorder or chronic low back pain will be included and randomly allocated to the intervention group or the control group. In the intervention group, culturally sensitive patient information will be handed to the patient at the end of the physician consultation, while in the control group, standard translated patient information material will be provided. The patients will be surveyed by means of questionnaires following the consultation as well as after 8 weeks and 6 months. In addition to the primary outcome (subjective usefulness), several patient- and physician-rated secondary outcomes will be considered. The study will provide an empirical answer to the question of whether persons with a migration background perceive culturally sensitive patient information material as more useful than translated information material without cultural adaptation. Deutsches Register Klinischer Studien (DRKS-ID) DRKS00004241 and Universal Trial Number (UTN) U1111-1135-8043.

Data-driven approach for creating synthetic electronic medical records.

PubMed

Buczak, Anna L; Babin, Steven; Moniz, Linda

2010-10-14

New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed. This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population. We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified. A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

A Roy model study of adapting to being HIV positive.

PubMed

Perrett, Stephanie E; Biley, Francis C

2013-10-01

Roy's adaptation model outlines a generic process of adaptation useful to nurses in any situation where a patient is facing change. To advance nursing practice, nursing theories and frameworks must be constantly tested and developed through research. This article describes how the results of a qualitative grounded theory study have been used to test components of the Roy adaptation model. A framework for "negotiating uncertainty" was the result of a grounded theory study exploring adaptation to HIV. This framework has been compared to the Roy adaptation model, strengthening concepts such as focal and contextual stimuli, Roy's definition of adaptation and her description of adaptive modes, while suggesting areas for further development including the role of perception. The comparison described in this article demonstrates the usefulness of qualitative research in developing nursing models, specifically highlighting opportunities to continue refining Roy's work.

Identifying traits for genotypic adaptation using crop models.

PubMed

Ramirez-Villegas, Julian; Watson, James; Challinor, Andrew J

2015-06-01

Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Convergent evolution and divergent selection: lizards at the White Sands ecotone.

PubMed

Rosenblum, Erica Bree

2006-01-01

Ecological transition zones, where organismal phenotypes result from a delicate balance between selection and migration, highlight the interplay of local adaptation and gene flow. Here, I study the response of an entire species assemblage to natural selection across a common ecotone. Three lizard species, distributed along a dramatic environmental gradient in substrate color, display convergent adaptation of blanched coloration on the gypsum dunes of White Sands National Monument. I investigate the role of gene flow in modulating phenotypic response to selection by quantifying color variation and genetic variation across the ecotone. I find species differences in degree of background matching and in genetic connectivity of populations across the ecotone. Differences among species in phenotypic response to selection scale precisely to levels of genetic isolation. Species with higher levels of gene flow across the ecotone exhibit less dramatic responses to selection. Results also reveal a strong signal of ecologically mediated divergence for White Sands lizards. For all species, phenotypic variation is better explained by habitat similarity than genetic similarity. Convergent evolution of blanched coloration at White Sands clearly reflects the action of strong divergent selection; however, adaptive response appears to be modulated by gene flow and demographic history and can be predicted by divergence-with-gene-flow models.

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.

Studies on the Time Course of Salinity and Temperature Adaptation in the Commercial Brown Shrimp Penaeus aztecus Ives.

DTIC Science & Technology

1977-09-01

Effect of temperature background 52 Effect of salinity and temperature change 53 Blood Osmoregulation During the Time Course of Adaptation... Osmoregulators Osmotic concentration Salinity Serum Standard metabolism Weight specific metabolic rate APPENDIX B: Tables I-IX. Mean... Effect of salinity and temperature change on the blood osmoregulation of Penaeus aztecus in relation to the isosmotic line 153 81

Intelligence Dissemination to the Warfighter

DTIC Science & Technology

2007-12-01

that prevent other JWICS users from exchanging data. The CIA conducts most of their business on the CIAnet , which can pull data from JWICS but...data. Spreadsheets and word processors, in order to retain a high level of user- friendliness, handle several complex background processes that...the “ complex adaptive systems”, where the onus is placed equally on the analyst and on the tools to be receptive and adaptable. It is the

Complex interplay between neutral and adaptive evolution shaped differential genomic background and disease susceptibility along the Italian peninsula.

PubMed

Sazzini, Marco; Gnecchi Ruscone, Guido Alberto; Giuliani, Cristina; Sarno, Stefania; Quagliariello, Andrea; De Fanti, Sara; Boattini, Alessio; Gentilini, Davide; Fiorito, Giovanni; Catanoso, Mariagrazia; Boiardi, Luigi; Croci, Stefania; Macchioni, Pierluigi; Mantovani, Vilma; Di Blasio, Anna Maria; Matullo, Giuseppe; Salvarani, Carlo; Franceschi, Claudio; Pettener, Davide; Garagnani, Paolo; Luiselli, Donata

2016-09-01

The Italian peninsula has long represented a natural hub for human migrations across the Mediterranean area, being involved in several prehistoric and historical population movements. Coupled with a patchy environmental landscape entailing different ecological/cultural selective pressures, this might have produced peculiar patterns of population structure and local adaptations responsible for heterogeneous genomic background of present-day Italians. To disentangle this complex scenario, genome-wide data from 780 Italian individuals were generated and set into the context of European/Mediterranean genomic diversity by comparison with genotypes from 50 populations. To maximize possibility of pinpointing functional genomic regions that have played adaptive roles during Italian natural history, our survey included also ~250,000 exomic markers and ~20,000 coding/regulatory variants with well-established clinical relevance. This enabled fine-grained dissection of Italian population structure through the identification of clusters of genetically homogeneous provinces and of genomic regions underlying their local adaptations. Description of such patterns disclosed crucial implications for understanding differential susceptibility to some inflammatory/autoimmune disorders, coronary artery disease and type 2 diabetes of diverse Italian subpopulations, suggesting the evolutionary causes that made some of them particularly exposed to the metabolic and immune challenges imposed by dietary and lifestyle shifts that involved western societies in the last centuries.

A whole genome Bayesian scan for adaptive genetic divergence in West African cattle

PubMed Central

2009-01-01

Background The recent settlement of cattle in West Africa after several waves of migration from remote centres of domestication has imposed dramatic changes in their environmental conditions, in particular through exposure to new pathogens. West African cattle populations thus represent an appealing model to unravel the genome response to adaptation to tropical conditions. The purpose of this study was to identify footprints of adaptive selection at the whole genome level in a newly collected data set comprising 36,320 SNPs genotyped in 9 West African cattle populations. Results After a detailed analysis of population structure, we performed a scan for SNP differentiation via a previously proposed Bayesian procedure including extensions to improve the detection of loci under selection. Based on these results we identified 53 genomic regions and 42 strong candidate genes. Their physiological functions were mainly related to immune response (MHC region which was found under strong balancing selection, CD79A, CXCR4, DLK1, RFX3, SEMA4A, TICAM1 and TRIM21), nervous system (NEUROD6, OLFM2, MAGI1, SEMA4A and HTR4) and skin and hair properties (EDNRB, TRSP1 and KRTAP8-1). Conclusion The main possible underlying selective pressures may be related to climatic conditions but also to the host response to pathogens such as Trypanosoma(sp). Overall, these results might open the way towards the identification of important variants involved in adaptation to tropical conditions and in particular to resistance to tropical infectious diseases. PMID:19930592

Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

NASA Astrophysics Data System (ADS)

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-05-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

Spinorial Geometry and Branes

NASA Astrophysics Data System (ADS)

Sloane, Peter

2007-09-01

We adapt the spinorial geometry method introduced in [J. Gillard, U. Gran and G. Papadopoulos, "The spinorial geometry of supersymmetric backgrounds," Class. Quant. Grav. 22 (2005) 1033 [ arXiv:hep-th/0410155

Academic Radiology in the New Healthcare Delivery Environment

PubMed Central

Qayyum, Aliya; Yu, John-Paul J.; Kansagra, Akash P.; von Fischer, Nathaniel; Costa, Daniel; Heller, Matthew; Kantartzis, Stamatis; Plowman, R. Scooter; Itri, Jason

2014-01-01

Ongoing concerns over the rising cost of health care are driving large-scale changes in the way that health care is practiced and reimbursed in the United States. To effectively implement and thrive within this new health care delivery environment, academic medical institutions will need to modify financial and business models and adapt institutional cultures. In this paper, we review the expected features of the new health care environment from the perspective of academic radiology departments. Our review will include background on Accountable Care Organizations, identify challenges associated with the new managed care model, and outline key strategies—including expanding the use of existing information technology infrastructure, promoting continued medical innovation, balancing academic research with clinical care, and exploring new roles for radiologists in efficient patient management—that will ensure continued success for academic radiology. PMID:24200477

[Debating disease: the risk factor concept in political economic and scientific consideration, 1968 to 1986].

PubMed

Madarász, Jeannette

2009-01-01

The risk factor concept was developed in American epidemiological studies ongoing since the 1940s researching the causes of chronic cardiovascular diseases. By looking at the depiction of this model in a variety of media in Germany between 1968 and 1986 we can put its close interaction with contemporary socio-political debates under scrutiny. Thereby, a strong connection between the various agents' political and economic interests on the one hand and the incorporation of the risk factor concept into their specific agendas will become apparent. The risk factor concept was not fundamentally changed in the process but it was adapted to contemporary conditions and political constellations. Thereby, so it will be argued, the medical uses of the model, especially regarding the prevention of chronic cardiovascular disease, were forced into the background of public debates.

Adaptive adjustment of the randomization ratio using historical control data

PubMed Central

Hobbs, Brian P.; Carlin, Bradley P.; Sargent, Daniel J.

2013-01-01

Background Prospective trial design often occurs in the presence of “acceptable” [1] historical control data. Typically this data is only utilized for treatment comparison in a posteriori retrospective analysis to estimate population-averaged effects in a random-effects meta-analysis. Purpose We propose and investigate an adaptive trial design in the context of an actual randomized controlled colorectal cancer trial. This trial, originally reported by Goldberg et al. [2], succeeded a similar trial reported by Saltz et al. [3], and used a control therapy identical to that tested (and found beneficial) in the Saltz trial. Methods The proposed trial implements an adaptive randomization procedure for allocating patients aimed at balancing total information (concurrent and historical) among the study arms. This is accomplished by assigning more patients to receive the novel therapy in the absence of strong evidence for heterogeneity among the concurrent and historical controls. Allocation probabilities adapt as a function of the effective historical sample size (EHSS) characterizing relative informativeness defined in the context of a piecewise exponential model for evaluating time to disease progression. Commensurate priors [4] are utilized to assess historical and concurrent heterogeneity at interim analyses and to borrow strength from the historical data in the final analysis. The adaptive trial’s frequentist properties are simulated using the actual patient-level historical control data from the Saltz trial and the actual enrollment dates for patients enrolled into the Goldberg trial. Results Assessing concurrent and historical heterogeneity at interim analyses and balancing total information with the adaptive randomization procedure leads to trials that on average assign more new patients to the novel treatment when the historical controls are unbiased or slightly biased compared to the concurrent controls. Large magnitudes of bias lead to approximately equal allocation of patients among the treatment arms. Using the proposed commensurate prior model to borrow strength from the historical data, after balancing total information with the adaptive randomization procedure, provides admissible estimators of the novel treatment effect with desirable bias-variance trade-offs. Limitations Adaptive randomization methods in general are sensitive to population drift and more suitable for trials that initiate with gradual enrollment. Balancing information among study arms in time-to-event analyses is difficult in the presence of informative right-censoring. Conclusions The proposed design could prove important in trials that follow recent evaluations of a control therapy. Efficient use of the historical controls is especially important in contexts where reliance on pre-existing information is unavoidable because the control therapy is exceptionally hazardous, expensive, or the disease is rare. PMID:23690095

Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.

PubMed

de Bruijne, Marleen; van Ginneken, Bram; Viergever, Max A; Niessen, Wiro J

2003-07-01

Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. The methods are evaluated on the complex task of segmenting thrombus in abdominal aortic aneurysms (AAA). Shape approximation errors were successfully reduced using the two shape model extensions. Segmentation using the new appearance model significantly outperformed the original ASM scheme; average volume errors are 5.1% and 45% respectively.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Resolving z ~2 galaxy using adaptive coadded source plane reconstruction

NASA Astrophysics Data System (ADS)

Sharma, Soniya; Richard, Johan; Kewley, Lisa; Yuan, Tiantian

2018-06-01

Natural magnification provided by gravitational lensing coupled with Integral field spectrographic observations (IFS) and adaptive optics (AO) imaging techniques have become the frontier of spatially resolved studies of high redshift galaxies (z>1). Mass models of gravitational lenses hold the key for understanding the spatially resolved source–plane (unlensed) physical properties of the background lensed galaxies. Lensing mass models very sensitively control the accuracy and precision of source-plane reconstructions of the observed lensed arcs. Effective source-plane resolution defined by image-plane (observed) point spread function (PSF) makes it challenging to recover the unlensed (source-plane) surface brightness distribution.We conduct a detailed study to recover the source-plane physical properties of z=2 lensed galaxy using spatially resolved observations from two different multiple images of the lensed target. To deal with PSF’s from two data sets on different multiple images of the galaxy, we employ a forward (Source to Image) approach to merge these independent observations. Using our novel technique, we are able to present a detailed analysis of the source-plane dynamics at scales much better than previously attainable through traditional image inversion methods. Moreover, our technique is adapted to magnification, thus allowing us to achieve higher resolution in highly magnified regions of the source. We find that this lensed system is highly evident of a minor merger. In my talk, I present this case study of z=2 lensed galaxy and also discuss the applications of our algorithm to study plethora of lensed systems, which will be available through future telescopes like JWST and GMT.

Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity

PubMed Central

Yin, Xinyou

2013-01-01

Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883

Spectrophotometric Analysis of Pigments: A Critical Assessment of a High-Throughput Method for Analysis of Algal Pigment Mixtures by Spectral Deconvolution

PubMed Central

Thrane, Jan-Erik; Kyle, Marcia; Striebel, Maren; Haande, Sigrid; Grung, Merete; Rohrlack, Thomas; Andersen, Tom

2015-01-01

The Gauss-peak spectra (GPS) method represents individual pigment spectra as weighted sums of Gaussian functions, and uses these to model absorbance spectra of phytoplankton pigment mixtures. We here present several improvements for this type of methodology, including adaptation to plate reader technology and efficient model fitting by open source software. We use a one-step modeling of both pigment absorption and background attenuation with non-negative least squares, following a one-time instrument-specific calibration. The fitted background is shown to be higher than a solvent blank, with features reflecting contributions from both scatter and non-pigment absorption. We assessed pigment aliasing due to absorption spectra similarity by Monte Carlo simulation, and used this information to select a robust set of identifiable pigments that are also expected to be common in natural samples. To test the method’s performance, we analyzed absorbance spectra of pigment extracts from sediment cores, 75 natural lake samples, and four phytoplankton cultures, and compared the estimated pigment concentrations with concentrations obtained using high performance liquid chromatography (HPLC). The deviance between observed and fitted spectra was generally very low, indicating that measured spectra could successfully be reconstructed as weighted sums of pigment and background components. Concentrations of total chlorophylls and total carotenoids could accurately be estimated for both sediment and lake samples, but individual pigment concentrations (especially carotenoids) proved difficult to resolve due to similarity between their absorbance spectra. In general, our modified-GPS method provides an improvement of the GPS method that is a fast, inexpensive, and high-throughput alternative for screening of pigment composition in samples of phytoplankton material. PMID:26359659

Importance of the cutoff value in the quadratic adaptive integrate-and-fire model.

PubMed

Touboul, Jonathan

2009-08-01

The quadratic adaptive integrate-and-fire model (Izhikevich, 2003 , 2007 ) is able to reproduce various firing patterns of cortical neurons and is widely used in large-scale simulations of neural networks. This model describes the dynamics of the membrane potential by a differential equation that is quadratic in the voltage, coupled to a second equation for adaptation. Integration is stopped during the rise phase of a spike at a voltage cutoff value V(c) or when it blows up. Subsequently the membrane potential is reset, and the adaptation variable is increased by a fixed amount. We show in this note that in the absence of a cutoff value, not only the voltage but also the adaptation variable diverges in finite time during spike generation in the quadratic model. The divergence of the adaptation variable makes the system very sensitive to the cutoff: changing V(c) can dramatically alter the spike patterns. Furthermore, from a computational viewpoint, the divergence of the adaptation variable implies that the time steps for numerical simulation need to be small and adaptive. However, divergence of the adaptation variable does not occur for the quartic model (Touboul, 2008 ) and the adaptive exponential integrate-and-fire model (Brette & Gerstner, 2005 ). Hence, these models are robust to changes in the cutoff value.

PS1-41: Just Add Data: Implementing an Event-Based Data Model for Clinical Trial Tracking

PubMed Central

Fuller, Sharon; Carrell, David; Pardee, Roy

2012-01-01

Background/Aims Clinical research trials often have similar fundamental tracking needs, despite being quite variable in their specific logic and activities. A model tracking database that can be quickly adapted by a variety of studies has the potential to achieve significant efficiencies in database development and maintenance. Methods Over the course of several different clinical trials, we have developed a database model that is highly adaptable to a variety of projects. Rather than hard-coding each specific event that might occur in a trial, along with its logical consequences, this model considers each event and its parameters to be a data record in its own right. Each event may have related variables (metadata) describing its prerequisites, subsequent events due, associated mailings, or events that it overrides. The metadata for each event is stored in the same record with the event name. When changes are made to the study protocol, no structural changes to the database are needed. One has only to add or edit events and their metadata. Changes in the event metadata automatically determine any related logic changes. In addition to streamlining application code, this model simplifies communication between the programmer and other team members. Database requirements can be phrased as changes to the underlying data, rather than to the application code. The project team can review a single report of events and metadata and easily see where changes might be needed. In addition to benefitting from streamlined code, the front end database application can also implement useful standard features such as automated mail merges and to do lists. Results The event-based data model has proven itself to be robust, adaptable and user-friendly in a variety of study contexts. We have chosen to implement it as a SQL Server back end and distributed Access front end. Interested readers may request a copy of the Access front end and scripts for creating the back end database. Discussion An event-based database with a consistent, robust set of features has the potential to significantly reduce development time and maintenance expense for clinical trial tracking databases.

A conceptual model of childhood adaptation to type 1 diabetes.

PubMed

Whittemore, Robin; Jaser, Sarah; Guo, Jia; Grey, Margaret

2010-01-01

The Childhood Adaptation Model to Chronic Illness: Diabetes Mellitus was developed to identify factors that influence childhood adaptation to type 1 diabetes (T1D). Since this model was proposed, considerable research has been completed. The purpose of this article is to update the model on childhood adaptation to T1D using research conducted since the original model was proposed. The framework suggests that, in individuals and families, characteristics such as age and socioeconomic status as well as the individuals' and families' responses (self-management, coping, self-efficacy, family functioning, social competence) influence the level of adaptation; in children with T1D, characteristics such as treatment modality (pump vs injections) and psychosocial responses (depressive symptoms and anxiety) also influence the level of adaptation. Adaptation has both physiologic (metabolic control) and psychosocial (Quality of Life [QOL]) components. This revised model provides greater specificity to the factors that influence adaptation to chronic illness in children. Research and clinical implications are discussed. Copyright © 2010 Mosby, Inc. All rights reserved.

Beyond Risk and Protective Factors: An Adaptation-Based Approach to Resilience.

PubMed

Ellis, Bruce J; Bianchi, JeanMarie; Griskevicius, Vladas; Frankenhuis, Willem E

2017-07-01

How does repeated or chronic childhood adversity shape social and cognitive abilities? According to the prevailing deficit model, children from high-stress backgrounds are at risk for impairments in learning and behavior, and the intervention goal is to prevent, reduce, or repair the damage. Missing from this deficit approach is an attempt to leverage the unique strengths and abilities that develop in response to high-stress environments. Evolutionary-developmental models emphasize the coherent, functional changes that occur in response to stress over the life course. Research in birds, rodents, and humans suggests that developmental exposures to stress can improve forms of attention, perception, learning, memory, and problem solving that are ecologically relevant in harsh-unpredictable environments (as per the specialization hypothesis). Many of these skills and abilities, moreover, are primarily manifest in currently stressful contexts where they would provide the greatest fitness-relevant advantages (as per the sensitization hypothesis). This perspective supports an alternative adaptation-based approach to resilience that converges on a central question: "What are the attention, learning, memory, problem-solving, and decision-making strategies that are enhanced through exposures to childhood adversity?" At an applied level, this approach focuses on how we can work with, rather than against, these strengths to promote success in education, employment, and civic life.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

PubMed Central

Lindén, Henrik; Lansner, Anders

2016-01-01

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model’s feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison. PMID:27213810

Measurement of ultra-low power oscillators using adaptive drift cancellation with applications to nano-magnetic spin torque oscillators.

PubMed

Tamaru, S; Ricketts, D S

2013-05-01

This work presents a technique for measuring ultra-low power oscillator signals using an adaptive drift cancellation method. We demonstrate this technique through spectrum measurements of a sub-pW nano-magnet spin torque oscillator (STO). We first present a detailed noise analysis of the standard STO characterization apparatus to estimate the background noise level, then compare these results to the noise level of three measurement configurations. The first and second share the standard configuration but use different spectrum analyzers (SA), an older model and a state-of-the-art model, respectively. The third is the technique proposed in this work using the same old SA as for the first. Our results show that the first and second configurations suffer from a large drift that requires ~30 min to stabilize each time the SA changes the frequency band, even though the SA has been powered on for longer than 24 h. The third configuration introduced in this work, however, shows absolutely no drift as the SA changes frequency band, and nearly the same noise performance as with a state-of-the-art SA, thus providing a reliable method for measuring very low power signals for a wide variety of applications.

Work-Related Stress Risk Assessment in Italy: A Methodological Proposal Adapted to Regulatory Guidelines

PubMed Central

Persechino, Benedetta; Valenti, Antonio; Ronchetti, Matteo; Rondinone, Bruna Maria; Di Tecco, Cristina; Vitali, Sara; Iavicoli, Sergio

2013-01-01

Background Work-related stress is one of the major causes of occupational ill health. In line with the regulatory framework on occupational health and safety (OSH), adequate models for assessing and managing risk need to be identified so as to minimize the impact of this stress not only on workers' health, but also on productivity. Methods After close analysis of the Italian and European reference regulatory framework and work-related stress assessment and management models used in some European countries, we adopted the UK Health and Safety Executive's (HSE) Management Standards (MS) approach, adapting it to the Italian context in order to provide a suitable methodological proposal for Italy. Results We have developed a work-related stress risk assessment strategy, meeting regulatory requirements, now available on a specific web platform that includes software, tutorials, and other tools to assist companies in their assessments. Conclusion This methodological proposal is new on the Italian work-related stress risk assessment scene. Besides providing an evaluation approach using scientifically validated instruments, it ensures the active participation of occupational health professionals in each company. The assessment tools provided enable companies not only to comply with the law, but also to contribute to a database for monitoring and assessment and give access to a reserved area for data analysis and comparisons. PMID:23961332

Adaptive control system having hedge unit and related apparatus and methods

NASA Technical Reports Server (NTRS)

Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

2003-01-01

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

A Conceptual Model of Childhood Adaptation to Type 1 Diabetes

PubMed Central

Whittemore, Robin; Jaser, Sarah; Guo, Jia; Grey, Margaret

2010-01-01

The Childhood Adaptation Model to Chronic Illness: Diabetes Mellitus was developed to identify factors that influence childhood adaptation to type 1 diabetes (T1D). Since this model was proposed, considerable research has been completed. The purpose of this paper is to update the model on childhood adaptation to T1D using research conducted since the original model was proposed. The framework suggests that individual and family characteristics, such as age, socioeconomic status, and in children with T1D, treatment modality (pump vs. injections), psychosocial responses (depressive symptoms and anxiety), and individual and family responses (self-management, coping, self-efficacy, family functioning, social competence) influence the level of adaptation. Adaptation has both physiologic (metabolic control) and psychosocial (QOL) components. This revised model provides greater specificity to the factors that influence adaptation to chronic illness in children. Research and clinical implications are discussed. PMID:20934079

A Prototype Instrument for Adaptive SPECT Imaging

PubMed Central

Freed, Melanie; Kupinski, Matthew A.; Furenlid, Lars R.; Barrett, Harrison H.

2015-01-01

We have designed and constructed a small-animal adaptive SPECT imaging system as a prototype for quantifying the potential benefit of adaptive SPECT imaging over the traditional fixed geometry approach. The optical design of the system is based on filling the detector with the object for each viewing angle, maximizing the sensitivity, and optimizing the resolution in the projection images. Additional feedback rules for determining the optimal geometry of the system can be easily added to the existing control software. Preliminary data have been taken of a phantom with a small, hot, offset lesion in a flat background in both adaptive and fixed geometry modes. Comparison of the predicted system behavior with the actual system behavior is presented along with recommendations for system improvements. PMID:26346820

The new approach for infrared target tracking based on the particle filter algorithm

NASA Astrophysics Data System (ADS)

Sun, Hang; Han, Hong-xia

2011-08-01

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring, precision, and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection, the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure, but in order to capture the change of the state space, it need a certain amount of particles to ensure samples is enough, and this number will increase in accompany with dimension and increase exponentially, this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining", we expand the classic Mean Shift tracking framework .Based on the previous perspective, we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis, Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism, used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation, and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value .Last because of the gray and fusion target motion information, this approach also inhibit interference from the background, ultimately improve the stability and the real-time of the target track.

Assessing Multivariate Constraints to Evolution across Ten Long-Term Avian Studies

PubMed Central

Teplitsky, Celine; Tarka, Maja; Møller, Anders P.; Nakagawa, Shinichi; Balbontín, Javier; Burke, Terry A.; Doutrelant, Claire; Gregoire, Arnaud; Hansson, Bengt; Hasselquist, Dennis; Gustafsson, Lars; de Lope, Florentino; Marzal, Alfonso; Mills, James A.; Wheelwright, Nathaniel T.; Yarrall, John W.; Charmantier, Anne

2014-01-01

Background In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. Methodology/Principal Findings We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate selection coefficients to predict evolutionary responses to selection. Using Bayesian methods that facilitate the propagation of errors in estimates, we compare (1) the rate of adaptation based on predicted response to selection when including genetic correlations with predictions from models where these genetic correlations were set to zero and (2) the multivariate evolvability in the direction of current selection to the average evolvability in random directions of the phenotypic space. We show that genetic correlations on average decrease the predicted rate of adaptation by 28%. Multivariate evolvability in the direction of current selection was systematically lower than average evolvability in random directions of space. These significant reductions in the rate of adaptation and reduced evolvability were due to a general nonalignment of selection and genetic variance, notably orthogonality of directional selection with the size axis along which most (60%) of the genetic variance is found. Conclusions These results suggest that genetic correlations can impose significant constraints on the evolution of avian morphology in wild populations. This could have important impacts on evolutionary dynamics and hence population persistence in the face of rapid environmental change. PMID:24608111

Transatlantic invasion routes and adaptive potential in North American populations of the invasive glossy buckthorn, Frangula alnus

PubMed Central

De Kort, Hanne; Mergeay, Joachim; Jacquemyn, Hans; Honnay, Olivier

2016-01-01

Background and Aims Many invasive species severely threaten native biodiversity and ecosystem functioning. One of the most prominent questions in invasion genetics is how invasive populations can overcome genetic founder effects to establish stable populations after colonization of new habitats. High native genetic diversity and multiple introductions are expected to increase genetic diversity and adaptive potential in the invasive range. Our aim was to identify the European source populations of Frangula alnus (glossy buckthorn), an ornamental and highly invasive woody species that was deliberately introduced into North America at the end of the 18th century. A second aim of this study was to assess the adaptive potential as an explanation for the invasion success of this species. Methods Using a set of annotated single-nucleotide polymorphisms (SNPs) that were assigned a putative function based on sequence comparison with model species, a total of 38 native European and 21 invasive North American populations were subjected to distance-based structure and assignment analyses combined with population genomic tools. Genetic diversity at SNPs with ecologically relevant functions was considered as a proxy for adaptive potential. Key Results Patterns of invasion coincided with early modern transatlantic trading routes. Multiple introductions through transatlantic trade from a limited number of European port regions to American urban areas led to the establishment of bridgehead populations with high allelic richness and expected heterozygosity, allowing continuous secondary migration to natural areas. Conclusions Targeted eradication of the urban populations, where the highest genetic diversity and adaptive potential were observed, offers a promising strategy to arrest further invasion of native American prairies and forests. PMID:27539599

Nursing Approach Based on Roy Adaptation Model in a Patient Undergoing Breast Conserving Surgery for Breast Cancer.

PubMed

Ursavaş, Figen Erol; Karayurt, Özgül; İşeri, Özge

2014-07-01

The use of models in nursing provides nurses to focus on the role of nursing and its applications rather than medical practice. In addition, it helps patient care to be systematic, purposeful, controlled and effective. One of the commonly used models in nursing is Roy Adaptation Model. According to Roy adaptation model, the aim of nursing is to increase compliance and life expectancy. Roy Adaptation Model evaluates the patient in physiologic mode, self-concept mode, role function mode and interdependence mode aiming to provide holistic care. This article describes the use of Roy Adaptation Model in the care of a patient who has been diagnosed with breast cancer and had breast-conserving surgery. Patient data was evaluated in the four modes of Roy adaptation model (physiologic, self-concept, role function, and interdependence modes) and the nursing process was applied.

Adaptive control of bivalirudin in the cardiac intensive care unit.

PubMed

Zhao, Qi; Edrich, Thomas; Paschalidis, Ioannis Ch

2015-02-01

Bivalirudin is a direct thrombin inhibitor used in the cardiac intensive care unit when heparin is contraindicated due to heparin-induced thrombocytopenia. Since it is not a commonly used drug, clinical experience with its dosing is sparse. In earlier work [1], we developed a dynamic system model that accurately predicts the effect of bivalirudin given dosage over time and patient physiological characteristics. This paper develops adaptive dosage controllers that regulate its effect to desired levels. To that end, and in the case that bivalirudin model parameters are available, we develop a Model Reference Control law. In the case that model parameters are unknown, an indirect Model Reference Adaptive Control scheme is applied to estimate model parameters first and then adapt the controller. Alternatively, direct Model Reference Adaptive Control is applied to adapt the controller directly without estimating model parameters first. Our algorithms are validated using actual patient data from a large hospital in the Boston area.

Childhood Epilepsy and Asthma: A Test of an Extension of the Double ABCX Model.

ERIC Educational Resources Information Center

Austin, Joan Kessner

The Double ABCX Model of Family Adjustment and Adaptation, a model that predicts adaptation to chronic stressors on the family, was extended by dividing it into attitudes, coping, and adaptation of parents and child separately, and by including variables relevant to child adaptation to epilepsy or asthma. The extended model was tested on 246…

Sensitivity analysis of dynamic biological systems with time-delays.

PubMed

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2010-10-15

Mathematical modeling has been applied to the study and analysis of complex biological systems for a long time. Some processes in biological systems, such as the gene expression and feedback control in signal transduction networks, involve a time delay. These systems are represented as delay differential equation (DDE) models. Numerical sensitivity analysis of a DDE model by the direct method requires the solutions of model and sensitivity equations with time-delays. The major effort is the computation of Jacobian matrix when computing the solution of sensitivity equations. The computation of partial derivatives of complex equations either by the analytic method or by symbolic manipulation is time consuming, inconvenient, and prone to introduce human errors. To address this problem, an automatic approach to obtain the derivatives of complex functions efficiently and accurately is necessary. We have proposed an efficient algorithm with an adaptive step size control to compute the solution and dynamic sensitivities of biological systems described by ordinal differential equations (ODEs). The adaptive direct-decoupled algorithm is extended to solve the solution and dynamic sensitivities of time-delay systems describing by DDEs. To save the human effort and avoid the human errors in the computation of partial derivatives, an automatic differentiation technique is embedded in the extended algorithm to evaluate the Jacobian matrix. The extended algorithm is implemented and applied to two realistic models with time-delays: the cardiovascular control system and the TNF-α signal transduction network. The results show that the extended algorithm is a good tool for dynamic sensitivity analysis on DDE models with less user intervention. By comparing with direct-coupled methods in theory, the extended algorithm is efficient, accurate, and easy to use for end users without programming background to do dynamic sensitivity analysis on complex biological systems with time-delays.

Leuconostoc Mesenteroides Growth in Food Products: Prediction and Sensitivity Analysis by Adaptive-Network-Based Fuzzy Inference Systems

PubMed Central

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

Background An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. Methods The ANFIS and ANN models were compared in terms of six statistical indices calculated by comparing their prediction results with actual data: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R 2). Graphical plots were also used for model comparison. Conclusions The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. PMID:23705023

JPL Developments in Retrieval Algorithms for Geostationary Observations - Applications to H2CO

NASA Technical Reports Server (NTRS)

Kurosu, Thomas P.; Kulawik, Susan; Natraj, Vijay

2012-01-01

JPL has strong expertise in atmospheric retrievals from UV and thermal IR, and a wide range of tools to apply to observations and instrument characterization. Radiative Transfer, AMF, Inversion, Fitting, Assimilation. Tools were applied for a preliminary study of H2CO sensitivities from GEO. Results show promise for moderate/strong H2CO lading but also that low background conditions will prove a challenge. H2CO DOF are not too strongly dependent on FWHM. GEMS (Geostationary Environmental Monitoring Spectrometer) choice of 0.6 nm FWHM (?) spectral resolution is adequate for H2CO retrievals. Case study can easily be adapted to GEMS observations/instrument model for more in-depth sensitivity characterization.

[Wireless human body communication technology].

PubMed

Sun, Lei; Zhang, Xiaojuan

2014-12-01

The Wireless Body Area Network (WBAN) is a key part of the wearable monitoring technologies, which has many communication technologies to choose from, like Bluetooth, ZigBee, Ultra Wideband, and Wireless Human Body Communication (WHBC). As for the WHBC developed in recent years, it is worthy to be further studied. The WHBC has a strong momentum of growth and a natural advantage in the formation of WBAN. In this paper, we first briefly describe the technical background of WHBC, then introduce theoretical model of human-channel communication and digital transmission machine based on human channel. And finally we analyze various of the interference of the WHBC and show the AFH (Adaptive Frequency Hopping) technology which can effectively deal with the interference.

Preferential accumulation of sex and Bs chromosomes in biarmed karyotypes by meiotic drive and rates of chromosomal changes in fishes.

PubMed

Molina, Wagner F; Martinez, Pablo A; Bertollo, Luiz A C; Bidau, Claudio J

2014-12-01

Mechanisms of accumulation based on typical centromeric drive or of chromosomes carrying pericentric inversions are adjusted to the general karyotype differentiation in the principal Actinopterygii orders. Here, we show that meiotic drive in fish is also supported by preferential establishment of sex chromosome systems and B chromosomes in orders with predominantly bi-brachial chromosomes. The mosaic of trends acting at an infra-familiar level in fish could be explained as the interaction of the directional process of meiotic drive as background, modulated on a smaller scale by adaptive factors or specific karyotypic properties of each group, as proposed for the orthoselection model.

Preferential accumulation of sex and Bs chromosomes in biarmed karyotypes by meiotic drive and rates of chromosomal changes in fishes.

PubMed

Molina, Wagner F; Martinez, Pablo A; Bertollo, Luiz A C; Bidau, Claudio J

2014-11-14

Mechanisms of accumulation based on typical centromeric drive or of chromosomes carrying pericentric inversions are adjusted to the general karyotype differentiation in the principal Actinopterygii orders. Here, we show that meiotic drive in fish is also supported by preferential establishment of sex chromosome systems and B chromosomes in orders with predominantly bi-brachial chromosomes. The mosaic of trends acting at an infra-familiar level in fish could be explained as the interaction of the directional process of meiotic drive as background, modulated on a smaller scale by adaptive factors or specific karyotypic properties of each group, as proposed for the orthoselection model.

Phenological mismatch and the effectiveness of assisted gene flow.

PubMed

Wadgymar, Susana M; Weis, Arthur E

2017-06-01

The persistence of narrowly adapted species under climate change will depend on their ability to migrate apace with their historical climatic envelope or to adapt in place to maintain fitness. This second path to persistence can only occur if there is sufficient genetic variance for response to new selection regimes. Inadequate levels of genetic variation can be remedied through assisted gene flow (AGF), that is the intentional introduction of individuals genetically adapted to localities with historic climates similar to the current or future climate experienced by the resident population. However, the timing of reproduction is frequently adapted to local conditions. Phenological mismatch between residents and migrants can reduce resident × migrant mating frequencies, slowing the introgression of migrant alleles into the resident genetic background and impeding evolutionary rescue efforts. Focusing on plants, we devised a method to estimate the frequency of resident × migrant matings based on flowering schedules and applied it in an experiment that mimicked the first generation of an AGF program with Chamaecrista fasciculata, a prairie annual, under current and expected future temperature regimes. Phenological mismatch reduced the potential for resident × migrant matings by 40-90%, regardless of thermal treatment. The most successful migrant sires were the most resident like in their flowering time, further biasing the genetic admixture between resident and migrant populations. Other loci contributing to local adaptation-heat-tolerance genes, for instance-may be in linkage disequilibrium with phenology when residents and migrants are combined into a single mating pool. Thus, introgression of potentially adaptive migrant alleles into the resident genetic background is slowed when selection acts against migrant phenology. Successful AGF programs may require sustained high immigration rates or preliminary breeding programs when phenologically matched migrant source populations are unavailable. © 2016 Society for Conservation Biology.

Navy Aegis Ballistic Missile Defense (BMD) Program: Background and Issues for Congress

DTIC Science & Technology

2016-10-25

for European BMD On September 17, 2009, the Obama Administration announced a new approach for regional BMD operations called the Phased Adaptive...December 2010, the U.S. missile defense approach in Europe commits MDA to delivering systems and associated capabilities on a schedule that requires...announcement of the European Phased Adaptive Approach on September 17, 2009, stated, “This approach is based on an assessment of the Iranian missile

Adaptive method of recognition of signals for one and two-frequency signal system in the telephony on the background of speech

NASA Astrophysics Data System (ADS)

Kuznetsov, Michael V.

2006-05-01

For reliable teamwork of various systems of automatic telecommunication including transferring systems of optical communication networks it is necessary authentic recognition of signals for one- or two-frequency service signal system. The analysis of time parameters of an accepted signal allows increasing reliability of detection and recognition of the service signal system on a background of speech.

Single molecule fluorescence imaging as a technique for barium tagging in neutrinoless double beta decay

NASA Astrophysics Data System (ADS)

Jones, B. J. P.; McDonald, A. D.; Nygren, D. R.

2016-12-01

Background rejection is key to success for future neutrinoless double beta decay experiments. To achieve sensitivity to effective Majorana lifetimes of ~ 1028 years, backgrounds must be controlled to better than 0.1 count per ton per year, beyond the reach of any present technology. In this paper we propose a new method to identify the birth of the barium daughter ion in the neutrinoless double beta decay of 136Xe. The method adapts Single Molecule Fluorescent Imaging, a technique from biochemistry research with demonstrated single ion sensitivity. We explore possible SMFI dyes suitable for the problem of barium ion detection in high pressure xenon gas, and develop a fiber-coupled sensing system with which we can detect the presence of bulk Ba++ ions remotely. We show that our sensor produces signal-to-background ratios as high as 85 in response to Ba++ ions when operated in aqueous solution. We then describe the next stage of this R&D program, which will be to demonstrate chelation and fluorescence in xenon gas. If a successful barium ion tag can be developed using SMFI adapted for high pressure xenon gas detectors, the first essentially zero background, ton-scale neutrinoless double beta decay technology could be realized.

The Role of Scale and Model Bias in ADAPT's Photospheric Eatimation

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

Godinez Vazquez, Humberto C.; Hickmann, Kyle Scott; Arge, Charles Nicholas

2015-05-20

The Air Force Assimilative Photospheric flux Transport model (ADAPT), is a magnetic flux propagation based on Worden-Harvey (WH) model. ADAPT would be used to provide a global photospheric map of the Earth. A data assimilation method based on the Ensemble Kalman Filter (EnKF), a method of Monte Carlo approximation tied with Kalman filtering, is used in calculating the ADAPT models.

Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

NASA Astrophysics Data System (ADS)

Xiang, Wei; Ye, Feifan

Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors

PubMed Central

2014-01-01

Background Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. Methods We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Results Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min −1 (0.3 min −1) and -0.7 bpm (1.7 bpm) (compared to -0.2 min −1 (0.4 min −1) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed for the Kalman filters is under 25% of the total signal length rendering it possible to perform the filtering in real-time. Conclusions It is possible to measure in real-time heart and breathing rates using an adaptive Kalman filter approach. Adapting the Kalman filter matrices improves the estimation results and makes the filter universally deployable when measuring cardiorespiratory signals. PMID:24886253

A Non–Gas-Based Cryotherapy System for the Treatment of Cervical Intraepithelial Neoplasia: A Mixed-Methods Approach for Initial Development and Testing

PubMed Central

Cremer, Miriam; Paul, Proma; Bergman, Katie; Haas, Michael; Maza, Mauricio; Zevallos, Albert; Ossandon, Miguel; Garai, Jillian D; Winkler, Jennifer L

2017-01-01

ABSTRACT Background: Gas-based cryotherapy is the most widely used treatment strategy for cervical intraepithelial neoplasia (CIN) in low-resource settings, but reliance on gas presents challenges in low- and middle-income countries (LMICs). Our team adapted the original CryoPen Cryosurgical System, a cryotherapy device that does not require compressed gas and is powered by electricity, for use in LMICs. Methods: A mixed-methods approach was used involving both qualitative and quantitative methods. First, we used a user-centered design approach to identify priority features of the adapted device. U.S.-based and global potential users of the adapted CryoPen participated in discussion groups and a card sorting activity to rank 7 features of the adapted CryoPen: cost, durability, efficacy and safety, maintenance, no need for electricity, patient throughput, and portability. Mean and median rankings, overall rankings, and summary rankings by discussion group were generated. In addition, results of several quantitative tests were analyzed including bench testing to determine tip temperature and heat extraction capabilities; a pathology review of CIN grade 3 cases (N=107) to determine target depth of necrosis needed to achieve high efficacy; and a pilot study (N=5) investigating depth of necrosis achieved with the adapted device to assess efficacy. Results: Discussion groups revealed 4 priority themes for device development in addition to the need to ensure high efficacy and safety and low cost: improved portability, durability, ease of use, and potential for cure. Adaptions to the original CryoPen system included a single-core, single-tip model; rugged carrying case; custom circuit to allow car battery charging; and sterilization by high-level disinfection. In bench testing, there were no significant differences in tip temperature or heat extraction capability between the adapted CryoPen and the standard cryotherapy device. In 80% of the cases in the pilot study, the adapted CryoPen achieved the target depth of necrosis 3.5 mm established in the pathology review. Conclusion: The LMIC-adapted CryoPen overcomes barriers to standard gas-based cryotherapy by eliminating dependency on gas, increasing portability, and ensuring consistent freeze temperatures. Further testing and evaluation of the adapted CryoPen will be pursued to assess scalability and potential impact of this device in decreasing the cervical cancer burden in LMICs. PMID:28351879

Non-linear structure formation in the `Running FLRW' cosmological model

NASA Astrophysics Data System (ADS)

Bibiano, Antonio; Croton, Darren J.

2016-07-01

We present a suite of cosmological N-body simulations describing the `Running Friedmann-Lemaïtre-Robertson-Walker' (R-FLRW) cosmological model. This model is based on quantum field theory in a curved space-time and extends Lambda cold dark matter (ΛCDM) with a time-evolving vacuum density, Λ(z), and time-evolving gravitational Newton's coupling, G(z). In this paper, we review the model and introduce the necessary analytical treatment needed to adapt a reference N-body code. Our resulting simulations represent the first realization of the full growth history of structure in the R-FLRW cosmology into the non-linear regime, and our normalization choice makes them fully consistent with the latest cosmic microwave background data. The post-processing data products also allow, for the first time, an analysis of the properties of the halo and sub-halo populations. We explore the degeneracies of many statistical observables and discuss the steps needed to break them. Furthermore, we provide a quantitative description of the deviations of R-FLRW from ΛCDM, which could be readily exploited by future cosmological observations to test and further constrain the model.

Natural Selection Causes Adaptive Genetic Resistance in Wild Emmer Wheat against Powdery Mildew at “Evolution Canyon” Microsite, Mt. Carmel, Israel

PubMed Central

Yin, Huayan; Ben-Abu, Yuval; Wang, Hongwei; Li, Anfei; Nevo, Eviatar; Kong, Lingrang

2015-01-01

Background “Evolution Canyon” (ECI) at Lower Nahal Oren, Mount Carmel, Israel, is an optimal natural microscale model for unraveling evolution in action highlighting the basic evolutionary processes of adaptation and speciation. A major model organism in ECI is wild emmer, Triticum dicoccoides, the progenitor of cultivated wheat, which displays dramatic interslope adaptive and speciational divergence on the tropical-xeric “African” slope (AS) and the temperate-mesic “European” slope (ES), separated on average by 250 m. Methods We examined 278 single sequence repeats (SSRs) and the phenotype diversity of the resistance to powdery mildew between the opposite slopes. Furthermore, 18 phenotypes on the AS and 20 phenotypes on the ES, were inoculated by both Bgt E09 and a mixture of powdery mildew races. Results In the experiment of genetic diversity, very little polymorphism was identified intra-slope in the accessions from both the AS or ES. By contrast, 148 pairs of SSR primers (53.23%) amplified polymorphic products between the phenotypes of AS and ES. There are some differences between the two wild emmer wheat genomes and the inter-slope SSR polymorphic products between genome A and B. Interestingly, all wild emmer types growing on the south-facing slope (SFS=AS) were susceptible to a composite of Blumeria graminis, while the ones growing on the north-facing slope (NFS=ES) were highly resistant to Blumeria graminis at both seedling and adult stages. Conclusion/Significance Remarkable inter-slope evolutionary divergent processes occur in wild emmer wheat, T. dicoccoides at EC I, despite the shot average distance of 250 meters. The AS, a dry and hot slope, did not develop resistance to powdery mildew, whereas the ES, a cool and humid slope, did develop resistance since the disease stress was strong there. This is a remarkable demonstration in host-pathogen interaction on how resistance develops when stress causes an adaptive result at a micro-scale distance. PMID:25856164

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

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

2010-01-01

This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

Do Bayesian adaptive trials offer advantages for comparative effectiveness research? Protocol for the RE-ADAPT study

PubMed Central

Luce, Bryan R; Broglio, Kristine R; Ishak, K Jack; Mullins, C Daniel; Vanness, David J; Fleurence, Rachael; Saunders, Elijah; Davis, Barry R

2013-01-01

Background Randomized clinical trials, particularly for comparative effectiveness research (CER), are frequently criticized for being overly restrictive or untimely for health-care decision making. Purpose Our prospectively designed REsearch in ADAptive methods for Pragmatic Trials (RE-ADAPT) study is a ‘proof of concept’ to stimulate investment in Bayesian adaptive designs for future CER trials. Methods We will assess whether Bayesian adaptive designs offer potential efficiencies in CER by simulating a re-execution of the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) study using actual data from ALLHAT. Results We prospectively define seven alternate designs consisting of various combinations of arm dropping, adaptive randomization, and early stopping and describe how these designs will be compared to the original ALLHAT design. We identify the one particular design that would have been executed, which incorporates early stopping and information-based adaptive randomization. Limitations While the simulation realistically emulates patient enrollment, interim analyses, and adaptive changes to design, it cannot incorporate key features like the involvement of data monitoring committee in making decisions about adaptive changes. Conclusion This article describes our analytic approach for RE-ADAPT. The next stage of the project is to conduct the re-execution analyses using the seven prespecified designs and the original ALLHAT data. PMID:23983160

Climate adaptation policy, science and practice - Lessons for communication

NASA Astrophysics Data System (ADS)

Wolf, Johanna

2017-04-01

In climate change adaptation research, policy, and practice, institutional culture produces distinct conceptualizations of adaptation, which in turn affect how adaptation work is undertaken. This study examines institutional culture as the four domains of norms, values, knowledge, and beliefs that are held by adaptation scientists, policy- and decision-makers, and practitioners in Western Canada. Based on 31 semi-structured interviews, this article traces the ways in which these four domains interact, intersect, converge, and diverge among scientists, policy- and decision-makers, and practitioners. By exploring the knowledge, backgrounds, goals, approaches, assumptions, and behaviours of people working in adaptation, these interviews map the ways in which institutional culture shapes adaptation work being carried out by local, provincial, and federal governments, nongovernmental organizations, and an international community of scientists (including Canadian scientists). Findings suggest that institutional culture both limits and enables adaptation actions for these actors in important ways, significantly influencing how climate change adaptation is being planned for, and carried out on the ground. As a result, this paper asserts that there is an urgent need to better understand the role that institutional culture plays in order to advance climate change adaptation, both now and in the future. Important lessons for communicating about climate science, climate impacts and adaptation will be presented.

Effect of vergence adaptation on convergence-accommodation: model simulations.

PubMed

Sreenivasan, Vidhyapriya; Bobier, William R; Irving, Elizabeth L; Lakshminarayanan, Vasudevan

2009-10-01

Several theoretical control models depict the adaptation effects observed in the accommodation and vergence mechanisms of the human visual system. Two current quantitative models differ in their approach of defining adaptation and in identifying the effect of controller adaptation on their respective cross-links between the vergence and accommodative systems. Here, we compare the simulation results of these adaptation models with empirical data obtained from emmetropic adults when they performed sustained near task through + 2D lens addition. The results of our experimental study showed an initial increase in exophoria (a divergent open-loop vergence position) and convergence-accommodation (CA) when viewing through +2D lenses. Prolonged fixation through the near addition lenses initiated vergence adaptation, which reduced the lens-induced exophoria and resulted in a concurrent reduction of CA. Both models showed good agreement with empirical measures of vergence adaptation. However, only one model predicted the experimental time course of reduction in CA. The pattern of our empirical results seem to be best described by the adaptation model that indicates the total vergence response to be a sum of two controllers, phasic and tonic, with the output of phasic controller providing input to the cross-link interactions.

An adaptive observer for on-line tool wear estimation in turning, Part I: Theory

NASA Astrophysics Data System (ADS)

Danai, Kourosh; Ulsoy, A. Galip

1987-04-01

On-line sensing of tool wear has been a long-standing goal of the manufacturing engineering community. In the absence of any reliable on-line tool wear sensors, a new model-based approach for tool wear estimation has been proposed. This approach is an adaptive observer, based on force measurement, which uses both parameter and state estimation techniques. The design of the adaptive observer is based upon a dynamic state model of tool wear in turning. This paper (Part I) presents the model, and explains its use as the basis for the adaptive observer design. This model uses flank wear and crater wear as state variables, feed as the input, and the cutting force as the output. The suitability of the model as the basis for adaptive observation is also verified. The implementation of the adaptive observer requires the design of a state observer and a parameter estimator. To obtain the model parameters for tuning the adaptive observer procedures for linearisation of the non-linear model are specified. The implementation of the adaptive observer in turning and experimental results are presented in a companion paper (Part II).

Adaptive Noise Suppression of Pediatric Lung Auscultations With Real Applications to Noisy Clinical Settings in Developing Countries

PubMed Central

Emmanouilidou, Dimitra; McCollum, Eric D.; Park, Daniel E.

2015-01-01

Goal Chest auscultation constitutes a portable low-cost tool widely used for respiratory disease detection. Though it offers a powerful means of pulmonary examination, it remains riddled with a number of issues that limit its diagnostic capability. Particularly, patient agitation (especially in children), background chatter, and other environmental noises often contaminate the auscultation, hence affecting the clarity of the lung sound itself. This paper proposes an automated multiband denoising scheme for improving the quality of auscultation signals against heavy background contaminations. Methods The algorithm works on a simple two-microphone setup, dynamically adapts to the background noise and suppresses contaminations while successfully preserving the lung sound content. The proposed scheme is refined to offset maximal noise suppression against maintaining the integrity of the lung signal, particularly its unknown adventitious components that provide the most informative diagnostic value during lung pathology. Results The algorithm is applied to digital recordings obtained in the field in a busy clinic in West Africa and evaluated using objective signal fidelity measures and perceptual listening tests performed by a panel of licensed physicians. A strong preference of the enhanced sounds is revealed. Significance The strengths and benefits of the proposed method lie in the simple automated setup and its adaptive nature, both fundamental conditions for everyday clinical applicability. It can be simply extended to a real-time implementation, and integrated with lung sound acquisition protocols. PMID:25879837

General mental ability and two types of adaptation to unforeseen change: applying discontinuous growth models to the task-change paradigm.

PubMed

Lang, Jonas W B; Bliese, Paul D

2009-03-01

The present research provides new insights into the relationship between general mental ability (GMA) and adaptive performance by applying a discontinuous growth modeling framework to a study of unforeseen change on a complex decision-making task. The proposed framework provides a way to distinguish 2 types of adaptation (transition adaptation and reacquisition adaptation) from 2 common performance components (skill acquisition and basal task performance). Transition adaptation refers to an immediate loss of performance following a change, whereas reacquisition adaptation refers to the ability to relearn a changed task over time. Analyses revealed that GMA was negatively related to transition adaptation and found no evidence for a relationship between GMA and reacquisition adaptation. The results are integrated within the context of adaptability research, and implications of using the described discontinuous growth modeling framework to study adaptability are discussed. (c) 2009 APA, all rights reserved.

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

A Background Noise Reduction Technique Using Adaptive Noise Cancellation for Microphone Arrays

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Fuller, Christopher R.; Brooks, Thomas F.; Humphreys, William M., Jr.; Brooks, Thomas F.

2011-01-01

Background noise in wind tunnel environments poses a challenge to acoustic measurements due to possible low or negative Signal to Noise Ratios (SNRs) present in the testing environment. This paper overviews the application of time domain Adaptive Noise Cancellation (ANC) to microphone array signals with an intended application of background noise reduction in wind tunnels. An experiment was conducted to simulate background noise from a wind tunnel circuit measured by an out-of-flow microphone array in the tunnel test section. A reference microphone was used to acquire a background noise signal which interfered with the desired primary noise source signal at the array. The technique s efficacy was investigated using frequency spectra from the array microphones, array beamforming of the point source region, and subsequent deconvolution using the Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) algorithm. Comparisons were made with the conventional techniques for improving SNR of spectral and Cross-Spectral Matrix subtraction. The method was seen to recover the primary signal level in SNRs as low as -29 dB and outperform the conventional methods. A second processing approach using the center array microphone as the noise reference was investigated for more general applicability of the ANC technique. It outperformed the conventional methods at the -29 dB SNR but yielded less accurate results when coherence over the array dropped. This approach could possibly improve conventional testing methodology but must be investigated further under more realistic testing conditions.

Toward an effective field theory approach to reheating

NASA Astrophysics Data System (ADS)

Özsoy, Ogan; Giblin, John T.; Nesbit, Eva; Şengör, Gizem; Watson, Scott

2017-12-01

We investigate whether effective field theory (EFT) approaches, which have been useful in examining inflation and dark energy, can also be used to establish a systematic approach to inflationary reheating. We consider two methods. First, we extend Weinberg's background EFT to the end of inflation and reheating. We establish when parametric resonance and decay of the inflaton occurs, but also find intrinsic theoretical limitations, which make it difficult to capture some reheating models. This motivates us to next consider Cheung et al.'s EFT approach, which instead focuses on perturbations and the symmetry breaking induced by the cosmological background. Adapting the latter approach to reheating implies some new and important differences compared to the EFT of inflation. In particular, there are new hierarchical scales, and we must account for inflaton oscillations during reheating, which lead to discrete symmetry breaking. Guided by the fundamental symmetries, we construct the EFT of reheating, and as an example of its usefulness we establish a new class of reheating models and the corresponding predictions for gravity wave observations. In this paper we primarily focus on the first stages of preheating. We conclude by discussing challenges for the approach and future directions. This paper builds on ideas first proposed in the paper [O. Ozsoy, G. Sengor, K. Sinha, and S. Watson, arXiv:1507.06651.].

Ethnic Variations of Trajectories in Suicide Ideation and Attempt: From Middle School to High School.

PubMed

Kim, Jahun; Pike, Kenneth; McCauley, Elizabeth; Vander Stoep, Ann

2018-02-14

The purpose of this study was to compare patterns of suicide ideation and suicide attempt in three ethnic groups. We analyzed data from 463 students with ethnic backgrounds of African American (AA), Asian American (ASA), and European American (EA) for 6 years. The best fit model was a three-trajectory class model for all groups. The majority of adolescents belonged in the nonideators trajectory. The high level of ideation was found in the high ideators (4%), high-fluctuating ideators (8%), and high-decreasing ideators (4%) trajectory in AA, ASA, and EA, respectively. In the AA group, being a member of ideators was not a significant predictor of suicide attempt. In the ASA group, being a member of high-fluctuating ideators was a significant predictor. In the EA group, being a member of both ideators predicted suicide attempt. The timing of onset, patterns of change, and peak time in the ideators trajectories in the three ethnic groups were markedly different. The high level of attempts found in the ASA-AA group was not explained by having suicide ideation. Findings suggest the need for in-depth examination of suicide behaviors across ethnic groups and culturally adapted preventive efforts with distinct developmental timing for adolescents from different ethnic backgrounds. © 2018 The American Association of Suicidology.

Sector-Based Detection for Hands-Free Speech Enhancement in Cars

NASA Astrophysics Data System (ADS)

Lathoud, Guillaume; Bourgeois, Julien; Freudenberger, Jürgen

2006-12-01

Adaptation control of beamforming interference cancellation techniques is investigated for in-car speech acquisition. Two efficient adaptation control methods are proposed that avoid target cancellation. The "implicit" method varies the step-size continuously, based on the filtered output signal. The "explicit" method decides in a binary manner whether to adapt or not, based on a novel estimate of target and interference energies. It estimates the average delay-sum power within a volume of space, for the same cost as the classical delay-sum. Experiments on real in-car data validate both methods, including a case with[InlineEquation not available: see fulltext.] km/h background road noise.

More About Vector Adaptive/Predictive Coding Of Speech

NASA Technical Reports Server (NTRS)

Jedrey, Thomas C.; Gersho, Allen

1992-01-01

Report presents additional information about digital speech-encoding and -decoding system described in "Vector Adaptive/Predictive Encoding of Speech" (NPO-17230). Summarizes development of vector adaptive/predictive coding (VAPC) system and describes basic functions of algorithm. Describes refinements introduced enabling receiver to cope with errors. VAPC algorithm implemented in integrated-circuit coding/decoding processors (codecs). VAPC and other codecs tested under variety of operating conditions. Tests designed to reveal effects of various background quiet and noisy environments and of poor telephone equipment. VAPC found competitive with and, in some respects, superior to other 4.8-kb/s codecs and other codecs of similar complexity.

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

PubMed Central

Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Background and objectives Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. Methods The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. Results A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised. Conclusions Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality. PMID:28686743

Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System

PubMed Central

Velazquez-Pupo, Roxana; Sierra-Romero, Alberto; Torres-Roman, Deni; Shkvarko, Yuriy V.; Romero-Delgado, Misael

2018-01-01

This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. PMID:29382078

[Mutual guiding and following of movement - The interaction process in mobilisation based on the example of kinaesthetics: A qualitative study].

PubMed

Maurer, Carola; Vosseler, Birgit; Senn, Beate; Gattinger, Heidrun

2018-06-01

Background: Mobility impairment is often seen as a reason for needing long-term care. Thus, promoting mobility becomes increasingly significant in nursing homes. The kinaesthetic approach offers a way to support nursing home residents in using their own resources to maintain or improve their mobility. Aim: The present study intends to identify the characteristics of the interaction between nursing home residents with impaired mobility and kinaesthetic trainers during mobilisation. Methods: This secondary analysis comprises nine video sequences interpreted according to Grounded Theory-principles. The findings are described in a basic model. Results: The interaction with nursing home residents is focused on adapted movement support. This assistance shows a positive effect on residents’ self-activity in the tracking process and in the context of other strategies. Intervening conditions like residents’ daily constitution have an influence on nurses’ kinaesthetic strategies. Thereby, nurses have to be highly competent in self-perception. Conclusion: Adapted movement support proves to be a phenomenon basing on the nurse-resident-interaction and allowing residents to actively participate in collaborative action.

Walking backwards into the future: the need for a holistic evolutionary approach in Pacific health research.

PubMed

Matisoo-Smith, Elizabeth; Gosling, Anna L

2018-05-01

The Pacific region has had a complex human history. It has been subject to multiple major human dispersal and colonisation events, including some of the earliest Out-of-Africa migrations, the so-called Austronesian expansion of people out of Island Southeast Asia, and the more recent arrival of Europeans. Despite models of island isolation, evidence suggests significant levels of interconnectedness that vary in direction and frequency over time. The Pacific Ocean covers a vast area and its islands provide an array of different physical environments with variable pathogen loads and subsistence opportunities. These diverse environments likely caused Pacific peoples to adapt (both genetically and culturally) in unique ways. Differences in genetic background, in combination with adaptation, likely affect their susceptibility to non-communicable diseases. Here we provide an overview of some of the key issues in the natural and human history of the Pacific region which are likely to impact human health. We argue that understanding the evolutionary and cultural history of Pacific peoples is essential for the generation of testable hypotheses surrounding potential causes of elevated disease susceptibility among Pacific peoples.

Infrared images target detection based on background modeling in the discrete cosine domain

NASA Astrophysics Data System (ADS)

Ye, Han; Pei, Jihong

2018-02-01

Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.

Adaptation of occupants with its environment in the official residence (case study: Housing of TNI AD Gaperta)

NASA Astrophysics Data System (ADS)

Nirfalini Aulia, Dwira; Aritonang, Cindy

2018-03-01

An official residence is a housing provided by the state and used as a residence occupied by the official duties of officials and civil servants during their service in the city. The property rights of the official residence have limit, only valid while the residents serve in the city. The process of adaptation becomes indispensable because, in the early days of occupying the housing, residents will face a new social environment, which may be different from their previous environment. Furthermore, backgrounds such as economic, cultural, and social factors of each occupant will also determine the adaptation process that occurs. This research aims to find out and analyze adaptation process of the official residence’s dwellers to its environment. This study used the descriptive-qualitative method by interviewing ten occupants who selected by purposive sampling method. Results of research indicated that the most adaptation process occurs adaptation by the reaction such as adding the number of room and service area.

Computerized adaptive measurement of depression: A simulation study

PubMed Central

Gardner, William; Shear, Katherine; Kelleher, Kelly J; Pajer, Kathleen A; Mammen, Oommen; Buysse, Daniel; Frank, Ellen

2004-01-01

Background Efficient, accurate instruments for measuring depression are increasingly important in clinical practice. We developed a computerized adaptive version of the Beck Depression Inventory (BDI). We examined its efficiency and its usefulness in identifying Major Depressive Episodes (MDE) and in measuring depression severity. Methods Subjects were 744 participants in research studies in which each subject completed both the BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale. Results The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%, equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21 items). The adaptive latent depression score correlated r = .92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (r = .74) than the BDI total score did (r = .70). Conclusions Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity. PMID:15132755

Evolution of adaptation mechanisms: Adaptation energy, stress, and oscillating death.

PubMed

Gorban, Alexander N; Tyukina, Tatiana A; Smirnova, Elena V; Pokidysheva, Lyudmila I

2016-09-21

In 1938, Selye proposed the notion of adaptation energy and published 'Experimental evidence supporting the conception of adaptation energy.' Adaptation of an animal to different factors appears as the spending of one resource. Adaptation energy is a hypothetical extensive quantity spent for adaptation. This term causes much debate when one takes it literally, as a physical quantity, i.e. a sort of energy. The controversial points of view impede the systematic use of the notion of adaptation energy despite experimental evidence. Nevertheless, the response to many harmful factors often has general non-specific form and we suggest that the mechanisms of physiological adaptation admit a very general and nonspecific description. We aim to demonstrate that Selye׳s adaptation energy is the cornerstone of the top-down approach to modelling of non-specific adaptation processes. We analyze Selye׳s axioms of adaptation energy together with Goldstone׳s modifications and propose a series of models for interpretation of these axioms. Adaptation energy is considered as an internal coordinate on the 'dominant path' in the model of adaptation. The phenomena of 'oscillating death' and 'oscillating remission' are predicted on the base of the dynamical models of adaptation. Natural selection plays a key role in the evolution of mechanisms of physiological adaptation. We use the fitness optimization approach to study of the distribution of resources for neutralization of harmful factors, during adaptation to a multifactor environment, and analyze the optimal strategies for different systems of factors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Implementing Innovative Models of Dementia Care: The Healthy Aging Brain Center

PubMed Central

Boustani, Malaz A.; Sachs, Greg A.; Alder, Catherine A.; Munger, Stephanie; Schubert, Cathy C.; Guerriero Austrom, Mary; Hake, Ann; Unverzagt, Frederick W.; Farlow, Martin; Matthews, Brandy R.; Perkins, Anthony J.; Beck, Robin A.; Callahan, Christopher M.

2010-01-01

BACKGROUND Recent randomized controlled trials have demonstrated the effectiveness of the collaborative dementia care model targeting both patients suffering from dementia and their informal caregivers. OBJECTIVE To implement a sustainable collaborative dementia care program in a public health care system in Indianapolis. METHODS We used the framework of Complex Adaptive System and the tool of the Reflective Adaptive Process to translate the results of the dementia care trial into the Healthy Aging Brain Center (HABC). RESULTS Within its first year of operation, the HABC delivered 528 visits to serve 208 patients and 176 informal caregivers. The mean age of HABC patients was 73.8 (SD 9.5), 40% were African Americans, 42% had less than high school education, 14% had normal cognitive status, 39% received a diagnosis of mild cognitive impairment, and 46% were diagnosed with dementia. Within 12 months of the initial HABC visit, 28% of patients had at least one visit to an emergency room (ER) and 14% were hospitalized with a mean length of stay of five days. The rate of a one-week ER revisit was 14% and the 30-day re-hospitalization rate was 11%. Only 5% of HABC patients received an order for neuroleptics and only 16% had simultaneous orders for both definite anticholinergic and anti-dementia drugs. CONCLUSION The tools of “implementation science” can be utilized to translate a health care delivery model developed in the research laboratory to a practical, operational, health care delivery program. PMID:21271387

Dissecting Long-Term Glucose Metabolism Identifies New Susceptibility Period for Metabolic Dysfunction in Aged Mice

PubMed Central

Koch, Franziska; Ibrahim, Saleh M.; Vera, Julio; Wolkenhauer, Olaf; Tiedge, Markus

2015-01-01

Metabolic disorders, like diabetes and obesity, are pathogenic outcomes of imbalance in glucose metabolism. Nutrient excess and mitochondrial imbalance are implicated in dysfunctional glucose metabolism with age. We used conplastic mouse strains with defined mitochondrial DNA (mtDNA) mutations on a common nuclear genomic background, and administered a high-fat diet up to 18 months of age. The conplastic mouse strain B6-mtFVB, with a mutation in the mt-Atp8 gene, conferred β-cell dysfunction and impaired glucose tolerance after high-fat diet. To our surprise, despite of this functional deficit, blood glucose levels adapted to perturbations with age. Blood glucose levels were particularly sensitive to perturbations at the early age of 3 to 6 months. Overall the dynamics consisted of a peak between 3–6 months followed by adaptation by 12 months of age. With the help of mathematical modeling we delineate how body weight, insulin and leptin regulate this non-linear blood glucose dynamics. The model predicted a second rise in glucose between 15 and 21 months, which could be experimentally confirmed as a secondary peak. We therefore hypothesize that these two peaks correspond to two sensitive periods of life, where perturbations to the basal metabolism can mark the system for vulnerability to pathologies at later age. Further mathematical modeling may perspectively allow the design of targeted periods for therapeutic interventions and could predict effects on weight loss and insulin levels under conditions of pre-diabetic obesity. PMID:26540285

Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso; Elena, Santiago F

2009-01-01

Background Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes. Results We show that the A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feed-forward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures. Conclusions These data suggest that A. thaliana has evolved high connectivity in terms of transcriptional regulation among cellular functions involved in response and adaptation to changing environments, while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this eukaryote. PMID:19754933

Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-10-01

An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection-diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

Optimal structure of metaplasticity for adaptive learning

PubMed Central

2017-01-01

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

GEMINI-9 - EARTH SKY - ATDA

NASA Image and Video Library

1966-06-06

S66-37943 (3 June 1966) --- The Augmented Target Docking Adapter is photographed against the background of the blackness of space from the Gemini-9 spacecraft during one of their three rendezvous in space. The ATDA and Gemini-9 spacecraft are 71.5 feet apart. Failure of the docking adapter protective cover to fully separate on the ATDA prevented the docking of the two spacecraft. The ATDA was described by the Gemini-9 crew as an ?Angry Alligator.? Photo credit: NASA

Real-time contaminant detection and classification in a drinking water pipe using conventional water quality sensors: techniques and experimental results.

PubMed

Jeffrey Yang, Y; Haught, Roy C; Goodrich, James A

2009-06-01

Accurate detection and identification of natural or intentional contamination events in a drinking water pipe is critical to drinking water supply security and health risk management. To use conventional water quality sensors for the purpose, we have explored a real-time event adaptive detection, identification and warning (READiw) methodology and examined it using pilot-scale pipe flow experiments of 11 chemical and biological contaminants each at three concentration levels. The tested contaminants include pesticide and herbicides (aldicarb, glyphosate and dicamba), alkaloids (nicotine and colchicine), E. coli in terrific broth, biological growth media (nutrient broth, terrific broth, tryptic soy broth), and inorganic chemical compounds (mercuric chloride and potassium ferricyanide). First, through adaptive transformation of the sensor outputs, contaminant signals were enhanced and background noise was reduced in time-series plots leading to detection and identification of all simulated contamination events. The improved sensor detection threshold was 0.1% of the background for pH and oxidation-reduction potential (ORP), 0.9% for free chlorine, 1.6% for total chlorine, and 0.9% for chloride. Second, the relative changes calculated from adaptively transformed residual chlorine measurements were quantitatively related to contaminant-chlorine reactivity in drinking water. We have shown that based on these kinetic and chemical differences, the tested contaminants were distinguishable in forensic discrimination diagrams made of adaptively transformed sensor measurements.

Nondestructive testing of delaminated interfaces between two materials using electromagnetic interrogation

NASA Astrophysics Data System (ADS)

Cakoni, Fioralba; de Teresa, Irene; Monk, Peter

2018-06-01

We consider the problem of detecting whether two materials that should be in contact have separated or delaminated using electromagnetic radiation. The interface damage is modeled as a thin opening between two materials of different electromagnetic properties. To derive a reconstruction algorithm that focuses on testing for the delamination at the interface between the two materials, we use the approximate asymptotic model for the forward problem derived in de Teresa (2017 PhD Thesis University of Delaware). In this model, the differential equations in the small opening are replaced by approximate transmission conditions for the electromagnetic fields across the interface. We also assume that the undamaged or background state is known and it is desired to find where the delamination has opened. We adapt the linear sampling method to this configuration in order to locate the damaged part of the interface from a knowledge of the scattered field and the undamaged configuration, but without needing to know the electromagnetic properties of the opening. Numerical examples are presented to validate our algorithm.

Publishing biomedical journals on the World-Wide Web using an open architecture model.

PubMed Central

Shareck, E. P.; Greenes, R. A.

1996-01-01

BACKGROUND: In many respects, biomedical publications are ideally suited for distribution via the World-Wide Web, but economic concerns have prevented the rapid adoption of an on-line publishing model. PURPOSE: We report on our experiences with assisting biomedical journals in developing an online presence, issues that were encountered, and methods used to address these issues. Our approach is based on an open architecture that fosters adaptation and interconnection of biomedical resources. METHODS: We have worked with the New England Journal of Medicine (NEJM), as well as five other publishers. A set of tools and protocols was employed to develop a scalable and customizable solution for publishing journals on-line. RESULTS: In March, 1996, the New England Journal of Medicine published its first World-Wide Web issue. Explorations with other publishers have helped to generalize the model. CONCLUSIONS: Economic and technical issues play a major role in developing World-Wide Web publishing solutions. PMID:8947685

Camouflage effects of various colour-marking morphs against different microhabitat backgrounds in a polymorphic pygmy grasshopper Tetrix japonica.

PubMed

Tsurui, Kaori; Honma, Atsushi; Nishida, Takayoshi

2010-07-06

Colour-marking polymorphism is widely distributed among cryptic species. To account for the adaptive significance of such polymorphisms, several hypotheses have been proposed to date. Although these hypotheses argue over the degree of camouflage effects of marking morphs (and the interactions between morphs and their microhabitat backgrounds), as far as we know, most empirical evidence has been provided under unnatural conditions (i.e., using artificial prey). Tetrix japonica, a pygmy grasshopper, is highly polymorphic in colour-markings and occurs in both sand and grass microhabitats. Even within a microhabitat, T. japonica is highly polymorphic. Using humans as dummy predators and printed photographs in which various morphs of grasshoppers were placed against different backgrounds, we addressed three questions to test the neutral, background heterogeneity, and differential crypsis hypotheses in four marking-type morphs: 1) do the morphs differ in the degree of crypsis in each microhabitat, 2) are different morphs most cryptic in specific backgrounds of the microhabitats, and 3) does the morph frequency reflect the degree of crypsis? The degree of camouflage differed among the four morphs; therefore, the neutral hypothesis was rejected. Furthermore, the order of camouflage advantage among morphs differed depending on the two types of backgrounds (sand and grass), although the grass background consistently provided greater camouflage effects. Thus, based on our results, we could not reject the background heterogeneity hypothesis. Under field conditions, the more cryptic morphs comprised a minority of the population. Overall, our results demonstrate that the different morphs were not equivalent in the degree of crypsis, but the degree of camouflage of the morphs was not consistent with the morph frequency. These findings suggest that trade-offs exist between the camouflage benefit of body colouration and other fitness components, providing a better understanding of the adaptive significance of colour-markings and presumably supporting the differential crypsis hypothesis.

Adaptive Management as an Effective Strategy: Interdisciplinary Perceptions for Natural Resources Management

NASA Astrophysics Data System (ADS)

Dreiss, Lindsay M.; Hessenauer, Jan-Michael; Nathan, Lucas R.; O'Connor, Kelly M.; Liberati, Marjorie R.; Kloster, Danielle P.; Barclay, Janet R.; Vokoun, Jason C.; Morzillo, Anita T.

2017-02-01

Adaptive management is a well-established approach to managing natural resources, but there is little evidence demonstrating effectiveness of adaptive management over traditional management techniques. Peer-reviewed literature attempts to draw conclusions about adaptive management effectiveness using social perceptions, but those studies are largely restricted to employees of US federal organizations. To gain a more comprehensive insight into perceived adaptive management effectiveness, this study aimed to broaden the suite of disciplines, professional affiliations, and geographic backgrounds represented by both practitioners and scholars. A questionnaire contained a series of questions concerning factors that lead to or inhibit effective management, followed by another set of questions focused on adaptive management. Using a continuum representing strategies of both adaptive management and traditional management, respondents selected those strategies that they perceived as being effective. Overall, characteristics (i.e., strategies, stakeholders, and barriers) identified by respondents as contributing to effective management closely aligned with adaptive management. Responses were correlated to the type of adaptive management experience rather than an individual's discipline, occupational, or regional affiliation. In particular, perceptions of characteristics contributing to adaptive management effectiveness varied between respondents who identified as adaptive management scholars (i.e., no implementation experience) and adaptive management practitioners. Together, these results supported two concepts that make adaptive management effective: practitioners emphasized adaptive management's value as a long-term approach and scholars noted the importance of stakeholder involvement. Even so, more communication between practitioners and scholars regarding adaptive management effectiveness could promote interdisciplinary learning and problem solving for improved resources management.

Adaptive Management as an Effective Strategy: Interdisciplinary Perceptions for Natural Resources Management.

PubMed

Dreiss, Lindsay M; Hessenauer, Jan-Michael; Nathan, Lucas R; O'Connor, Kelly M; Liberati, Marjorie R; Kloster, Danielle P; Barclay, Janet R; Vokoun, Jason C; Morzillo, Anita T

2017-02-01

Adaptive management is a well-established approach to managing natural resources, but there is little evidence demonstrating effectiveness of adaptive management over traditional management techniques. Peer-reviewed literature attempts to draw conclusions about adaptive management effectiveness using social perceptions, but those studies are largely restricted to employees of US federal organizations. To gain a more comprehensive insight into perceived adaptive management effectiveness, this study aimed to broaden the suite of disciplines, professional affiliations, and geographic backgrounds represented by both practitioners and scholars. A questionnaire contained a series of questions concerning factors that lead to or inhibit effective management, followed by another set of questions focused on adaptive management. Using a continuum representing strategies of both adaptive management and traditional management, respondents selected those strategies that they perceived as being effective. Overall, characteristics (i.e., strategies, stakeholders, and barriers) identified by respondents as contributing to effective management closely aligned with adaptive management. Responses were correlated to the type of adaptive management experience rather than an individual's discipline, occupational, or regional affiliation. In particular, perceptions of characteristics contributing to adaptive management effectiveness varied between respondents who identified as adaptive management scholars (i.e., no implementation experience) and adaptive management practitioners. Together, these results supported two concepts that make adaptive management effective: practitioners emphasized adaptive management's value as a long-term approach and scholars noted the importance of stakeholder involvement. Even so, more communication between practitioners and scholars regarding adaptive management effectiveness could promote interdisciplinary learning and problem solving for improved resources management.

Land-use Scene Classification in High-Resolution Remote Sensing Images by Multiscale Deeply Described Correlatons

NASA Astrophysics Data System (ADS)

Qi, K.; Qingfeng, G.

2017-12-01

With the popular use of High-Resolution Satellite (HRS) images, more and more research efforts have been placed on land-use scene classification. However, it makes the task difficult with HRS images for the complex background and multiple land-cover classes or objects. This article presents a multiscale deeply described correlaton model for land-use scene classification. Specifically, the convolutional neural network is introduced to learn and characterize the local features at different scales. Then, learnt multiscale deep features are explored to generate visual words. The spatial arrangement of visual words is achieved through the introduction of adaptive vector quantized correlograms at different scales. Experiments on two publicly available land-use scene datasets demonstrate that the proposed model is compact and yet discriminative for efficient representation of land-use scene images, and achieves competitive classification results with the state-of-art methods.

Drift wave turbulence simulations in LAPD

NASA Astrophysics Data System (ADS)

Popovich, P.; Umansky, M.; Carter, T. A.; Auerbach, D. W.; Friedman, B.; Schaffner, D.; Vincena, S.

2009-11-01

We present numerical simulations of turbulence in LAPD plasmas using the 3D electromagnetic code BOUT (BOUndary Turbulence). BOUT solves a system of fluid moment equations in a general toroidal equlibrium geometry near the plasma boundary. The underlying assumptions for the validity of the fluid model are well satisfied for drift waves in LAPD plasmas (typical plasma parameters ne˜1x10^12cm-3, Te˜10eV, and B ˜1kG), which makes BOUT a perfect tool for simulating LAPD. We have adapted BOUT for the cylindrical geometry of LAPD and have extended the model to include the background flows required for simulations of recent bias-driven rotation experiments. We have successfully verified the code for several linear instabilities, including resistive drift waves, Kelvin-Helmholtz and rotation-driven interchange. We will discuss first non-linear simulations and quasi-stationary solutions with self-consistent plasma flows and saturated density profiles.

The Quantized Geometry of Visual Space: The Coherent Computation of Depth, Form, and Lightness. Revised Version.

DTIC Science & Technology

1982-08-01

of sensitivity with background luminance, and the finitE capacity of visual short term memory are discussed in terms of a small set of ...binocular rivalry, reflectance rivalry, Fechner’s paradox, decrease of threshold contrast with increased number of cycles in a grating pattern, hysteresis...adaptation level tuning, Weber law modulation, shift of sensitivity with background luminance, and the finite capacity of visual

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.

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

PubMed

Zhang, Yaping; Hu, Kaiqiang; Beumer, Jan H; Bakkenist, Christopher J; D'Argenio, David Z

2017-04-01

We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model prediction plots, tabulates model parameter estimates, and allows automatic statistical comparison of parameters between different groups. The RAD-ADAPT interface is written using the statistical software R and the underlying computations are accomplished by the ADAPT software system for pharmacokinetic/pharmacodynamic systems analysis. The use of RAD-ADAPT is demonstrated using an example that examines the impact of pharmacologic ATM and ATR kinase inhibition on human lung cancer cell line A549 after ionizing radiation. Copyright © 2017 Elsevier B.V. All rights reserved.

Cardiovascular Adaptations Induced by Resistance Training in Animal Models.

PubMed

Melo, S F S; da Silva Júnior, N D; Barauna, V G; Oliveira, E M

2018-01-01

In the last 10 years the number of studies showing the benefits of resistance training (RT) to the cardiovascular system, have grown. In comparison to aerobic training, RT-induced favorable adaptations to the cardiovascular system have been ignored for many years, thus the mechanisms of the RT-induced cardiovascular adaptations are still uncovered. The lack of animal models with comparable protocols to the RT performed by humans hampers the knowledge. We have used squat-exercise model, which is widely used by many others laboratories. However, to a lesser extent, other models are also employed to investigate the cardiovascular adaptations. In the subsequent sections we will review the information regarding cardiac morphological adaptations, signaling pathway of the cardiac cell, cardiac function and the vascular adaptation induced by RT using this animal model developed by Tamaki et al. in 1992. Furthermore, we also describe cardiovascular findings observed using other animal models of RT.

When and How to Take Antibiotics

MedlinePlus

... Work Contact Us ABOUT THE ISSUE What is Antibiotic Resistance? General Background Science of Resistance Glossary References POLICY ... for Adaptation Genetics and Drug Resistance Reservoirs of Antibiotic Resistance Project (ROAR) INTERNATIONAL CHAPTERS APUA Chapter Network Africa ...

The Application of COMSOL Multiphysics Package on the Modelling of Complex 3-D Lithospheric Electrical Resistivity Structures - A Case Study from the Proterozoic Orogenic belt within the North China Craton

NASA Astrophysics Data System (ADS)

Guo, L.; Yin, Y.; Deng, M.; Guo, L.; Yan, J.

2017-12-01

At present, most magnetotelluric (MT) forward modelling and inversion codes are based on finite difference method. But its structured mesh gridding cannot be well adapted for the conditions with arbitrary topography or complex tectonic structures. By contrast, the finite element method is more accurate in calculating complex and irregular 3-D region and has lower requirement of function smoothness. However, the complexity of mesh gridding and limitation of computer capacity has been affecting its application. COMSOL Multiphysics is a cross-platform finite element analysis, solver and multiphysics full-coupling simulation software. It achieves highly accurate numerical simulations with high computational performance and outstanding multi-field bi-directional coupling analysis capability. In addition, its AC/DC and RF module can be used to easily calculate the electromagnetic responses of complex geological structures. Using the adaptive unstructured grid, the calculation is much faster. In order to improve the discretization technique of computing area, we use the combination of Matlab and COMSOL Multiphysics to establish a general procedure for calculating the MT responses for arbitrary resistivity models. The calculated responses include the surface electric and magnetic field components, impedance components, magnetic transfer functions and phase tensors. Then, the reliability of this procedure is certificated by 1-D, 2-D and 3-D and anisotropic forward modeling tests. Finally, we establish the 3-D lithospheric resistivity model for the Proterozoic Wutai-Hengshan Mts. within the North China Craton by fitting the real MT data collected there. The reliability of the model is also verified by induced vectors and phase tensors. Our model shows more details and better resolution, compared with the previously published 3-D model based on the finite difference method. In conclusion, COMSOL Multiphysics package is suitable for modeling the 3-D lithospheric resistivity structures under complex tectonic deformation backgrounds, which could be a good complement to the existing finite-difference inversion algorithms.

Electronic Quality of Life Assessment Using Computer-Adaptive Testing

PubMed Central

2016-01-01

Background Quality of life (QoL) questionnaires are desirable for clinical practice but can be time-consuming to administer and interpret, making their widespread adoption difficult. Objective Our aim was to assess the performance of the World Health Organization Quality of Life (WHOQOL)-100 questionnaire as four item banks to facilitate adaptive testing using simulated computer adaptive tests (CATs) for physical, psychological, social, and environmental QoL. Methods We used data from the UK WHOQOL-100 questionnaire (N=320) to calibrate item banks using item response theory, which included psychometric assessments of differential item functioning, local dependency, unidimensionality, and reliability. We simulated CATs to assess the number of items administered before prespecified levels of reliability was met. Results The item banks (40 items) all displayed good model fit (P>.01) and were unidimensional (fewer than 5% of t tests significant), reliable (Person Separation Index>.70), and free from differential item functioning (no significant analysis of variance interaction) or local dependency (residual correlations < +.20). When matched for reliability, the item banks were between 45% and 75% shorter than paper-based WHOQOL measures. Across the four domains, a high standard of reliability (alpha>.90) could be gained with a median of 9 items. Conclusions Using CAT, simulated assessments were as reliable as paper-based forms of the WHOQOL with a fraction of the number of items. These properties suggest that these item banks are suitable for computerized adaptive assessment. These item banks have the potential for international development using existing alternative language versions of the WHOQOL items. PMID:27694100

Cultural Adaptation and Psychometric Properties of the Persian Version of the Circumstances, Motivation, and Readiness Scale

PubMed Central

Norozi, Ensiyeh; Miri, Mohammad Reza; Soltani, Raheleh; Eslami, Ahmad Ali; Harivandi, Ali Reza; Dastjerdi, Reza

2016-01-01

Background Treatment motivation has always been an important issue in substance abuse treatment. In recent decades, several instruments have been developed to measure this concept. Objectives In this study, cultural adaptation and psychometric properties of the Persian version of the circumstances, motivation and readiness scale (CMR) are illustrated in a sample of Iranian addicts. Materials and Methods The translation process followed Beaton et al.’s (2000) guideline for the cross-cultural adaptation of self-administered questionnaires, including the steps of translation, synthesis, back translation, expert committee review, and pre-testing. The final version of the Persian CMR was assessed for internal consistency and construct validity (n = 203). Results There was one eliminated item in the cross-cultural adaptation process. Also, four items that had low correlation with the total score were excluded from the questionnaire during the initial analysis. Using the remaining items, Principle axis factoring with Promax rotation was performed and three factors, circumstance, motivation, and readiness, were identified. The secondary order three factor model provided a good statistical and conceptual fit for the data. Internal consistency met the criterion for a reliable measure (Cronbach’s alpha = 0.840). The α range for these identified factors was 0.597 to 0.837. Conclusions Although the CMR was originally designed for use in TC treatment, this study suggests that it is also applicable, with some modifications, in short-term residential camps. Also, it is concluded that the Persian translation of the CMR can be applied for studies among Persian addicts. PMID:27622165

Principles underlying the design of "The Number Race", an adaptive computer game for remediation of dyscalculia

PubMed Central

Wilson, Anna J; Dehaene, Stanislas; Pinel, Philippe; Revkin, Susannah K; Cohen, Laurent; Cohen, David

2006-01-01

Background Adaptive game software has been successful in remediation of dyslexia. Here we describe the cognitive and algorithmic principles underlying the development of similar software for dyscalculia. Our software is based on current understanding of the cerebral representation of number and the hypotheses that dyscalculia is due to a "core deficit" in number sense or in the link between number sense and symbolic number representations. Methods "The Number Race" software trains children on an entertaining numerical comparison task, by presenting problems adapted to the performance level of the individual child. We report full mathematical specifications of the algorithm used, which relies on an internal model of the child's knowledge in a multidimensional "learning space" consisting of three difficulty dimensions: numerical distance, response deadline, and conceptual complexity (from non-symbolic numerosity processing to increasingly complex symbolic operations). Results The performance of the software was evaluated both by mathematical simulations and by five weeks of use by nine children with mathematical learning difficulties. The results indicate that the software adapts well to varying levels of initial knowledge and learning speeds. Feedback from children, parents and teachers was positive. A companion article [1] describes the evolution of number sense and arithmetic scores before and after training. Conclusion The software, open-source and freely available online, is designed for learning disabled children aged 5–8, and may also be useful for general instruction of normal preschool children. The learning algorithm reported is highly general, and may be applied in other domains. PMID:16734905

Rapid response to changing environments during biological invasions: DNA methylation perspectives.

PubMed

Huang, Xuena; Li, Shiguo; Ni, Ping; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

2017-12-01

Dissecting complex interactions between species and their environments has long been a research hot spot in the fields of ecology and evolutionary biology. The well-recognized Darwinian evolution has well-explained long-term adaptation scenarios; however, "rapid" processes of biological responses to environmental changes remain largely unexplored, particularly molecular mechanisms such as DNA methylation that have recently been proposed to play crucial roles in rapid environmental adaptation. Invasive species, which have capacities to successfully survive rapidly changing environments during biological invasions, provide great opportunities to study molecular mechanisms of rapid environmental adaptation. Here, we used the methylation-sensitive amplified polymorphism (MSAP) technique in an invasive model ascidian, Ciona savignyi, to investigate how species interact with rapidly changing environments at the whole-genome level. We detected quite rapid DNA methylation response: significant changes of DNA methylation frequency and epigenetic differentiation between treatment and control groups occurred only after 1 hr of high-temperature exposure or after 3 hr of low-salinity challenge. In addition, we detected time-dependent hemimethylation changes and increased intragroup epigenetic divergence induced by environmental stresses. Interestingly, we found evidence of DNA methylation resilience, as most stress-induced DNA methylation variation maintained shortly (~48 hr) and quickly returned back to the control levels. Our findings clearly showed that invasive species could rapidly respond to acute environmental changes through DNA methylation modifications, and rapid environmental changes left significant epigenetic signatures at the whole-genome level. All these results provide fundamental background to deeply investigate the contribution of DNA methylation mechanisms to rapid contemporary environmental adaptation. © 2017 John Wiley & Sons Ltd.

Stochastic, Adaptive Sampling of Information by Microvilli in Fly Photoreceptors

PubMed Central

Song, Zhuoyi; Postma, Marten; Billings, Stephen A.; Coca, Daniel; Hardie, Roger C.; Juusola, Mikko

2012-01-01

Summary Background In fly photoreceptors, light is focused onto a photosensitive waveguide, the rhabdomere, consisting of tens of thousands of microvilli. Each microvillus is capable of generating elementary responses, quantum bumps, in response to single photons using a stochastically operating phototransduction cascade. Whereas much is known about the cascade reactions, less is known about how the concerted action of the microvilli population encodes light changes into neural information and how the ultrastructure and biochemical machinery of photoreceptors of flies and other insects evolved in relation to the information sampling and processing they perform. Results We generated biophysically realistic fly photoreceptor models, which accurately simulate the encoding of visual information. By comparing stochastic simulations with single cell recordings from Drosophila photoreceptors, we show how adaptive sampling by 30,000 microvilli captures the temporal structure of natural contrast changes. Following each bump, individual microvilli are rendered briefly (∼100–200 ms) refractory, thereby reducing quantum efficiency with increasing intensity. The refractory period opposes saturation, dynamically and stochastically adjusting availability of microvilli (bump production rate: sample rate), whereas intracellular calcium and voltage adapt bump amplitude and waveform (sample size). These adapting sampling principles result in robust encoding of natural light changes, which both approximates perceptual contrast constancy and enhances novel events under different light conditions, and predict information processing across a range of species with different visual ecologies. Conclusions These results clarify why fly photoreceptors are structured the way they are and function as they do, linking sensory information to sensory evolution and revealing benefits of stochasticity for neural information processing. PMID:22704990

A new multiscale air quality transport model (Fluidity, 4.1.9) using fully unstructured anisotropic adaptive mesh technology

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-06-01

A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.