Science.gov

Sample records for adaptive spatial sampling

  1. Adaptive spatial sampling of contaminated soil

    SciTech Connect

    Cox, L.A. Jr.

    1999-12-01

    Suppose that a residential neighborhood may have been contaminated by a nearby abandoned hazardous waste site. The suspected contamination consists of elevated soil concentrations o chemicals that are also found in the absence of site-related contamination. How should a risk manager decide which residential properties to sample and which ones to clean? This paper introduces an adaptive spatial sampling approach which uses initial observations to guide subsequent search. Unlike some recent model-based spatial data analysis methods, it does not require any specific statistical model for the spatial distribution of hazards, but instead constructs an increasingly accurate nonparametric approximation to it as sampling proceeds. Possible cost-effective sampling and cleanup decision rules are described by decision parameters such as the number of randomly selected locations used to initialize the process, the number of highest-concentration locations searched around, the number of samples taken at each location, a stopping rule, and a remediation action threshold. These decision parameters are optimized by simulating the performance of each decision rule. The simulation is performed using the data collected so far to impute multiple probably values of unknown soil concentration distributions during each simulation run.

  2. Bayesian approaches for adaptive spatial sampling : an example application.

    SciTech Connect

    Johnson, R. L.; LePoire, D.; Huttenga, A.; Quinn, J.

    2005-05-25

    BAASS (Bayesian Approaches for Adaptive Spatial Sampling) is a set of computational routines developed to support the design and deployment of spatial sampling programs for delineating contamination footprints, such as those that might result from the accidental or intentional environmental release of radionuclides. BAASS presumes the existence of real-time measurement technologies that provide information quickly enough to affect the progress of data collection. This technical memorandum describes the application of BAASS to a simple example, compares the performance of a BAASS-based program with that of a traditional gridded program, and explores the significance of several of the underlying assumptions required by BAASS. These assumptions include the range of spatial autocorrelation present, the value of prior information, the confidence level required for decision making, and ''inside-out'' versus ''outside-in'' sampling strategies. In the context of the example, adaptive sampling combined with prior information significantly reduced the number of samples required to delineate the contamination footprint.

  3. Sample-adaptive-prediction for HEVC SCC intra coding with ridge estimation from spatially neighboring samples

    NASA Astrophysics Data System (ADS)

    Kang, Je-Won; Ryu, Soo-Kyung

    2017-02-01

    In this paper a sample-adaptive prediction technique is proposed to yield efficient coding performance in an intracoding for screen content video coding. The sample-based prediction is to reduce spatial redundancies in neighboring samples. To this aim, the proposed technique uses a weighted linear combination of neighboring samples and applies the robust optimization technique, namely, ridge estimation to derive the weights in a decoder side. The ridge estimation uses L2 norm based regularization term, and, thus the solution is more robust to high variance samples such as in sharp edges and high color contrasts exhibited in screen content videos. It is demonstrated with the experimental results that the proposed technique provides an improved coding gain as compared to the HEVC screen content video coding reference software.

  4. A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

    USGS Publications Warehouse

    Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

    2013-01-01

    Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

  5. Adaptive Sampling Designs.

    ERIC Educational Resources Information Center

    Flournoy, Nancy

    Designs for sequential sampling procedures that adapt to cumulative information are discussed. A familiar illustration is the play-the-winner rule in which there are two treatments; after a random start, the same treatment is continued as long as each successive subject registers a success. When a failure occurs, the other treatment is used until…

  6. Adaptive sampling for noisy problems

    SciTech Connect

    Cantu-Paz, E

    2004-03-26

    The usual approach to deal with noise present in many real-world optimization problems is to take an arbitrary number of samples of the objective function and use the sample average as an estimate of the true objective value. The number of samples is typically chosen arbitrarily and remains constant for the entire optimization process. This paper studies an adaptive sampling technique that varies the number of samples based on the uncertainty of deciding between two individuals. Experiments demonstrate the effect of adaptive sampling on the final solution quality reached by a genetic algorithm and the computational cost required to find the solution. The results suggest that the adaptive technique can effectively eliminate the need to set the sample size a priori, but in many cases it requires high computational costs.

  7. Nonuniform spatially adaptive wavelet packets

    NASA Astrophysics Data System (ADS)

    Carre, Philippe; Fernandez-Maloigne, Christine

    2000-12-01

    In this paper, we propose a new decomposition scheme for spatially adaptive wavelet packets. Contrary to the double tree algorithm, our method is non-uniform and shift- invariant in the time and frequency domains, and is minimal for an information cost function. We prose some-restrictions to our algorithm to reduce the complexity and permitting us to provide some time-frequency partitions of the signal in agreement with its structure. This new 'totally' non-uniform transform, more adapted than Malvar, Packets or dyadic double-tree decomposition, allows the study of all possible time-frequency partitions with the only restriction that the blocks are rectangular. It permits one to obtain a satisfying Time-Frequency representation, and is applied for the study of EEG signals.

  8. Behavioral Regulation, Visual Spatial Maturity in Kindergarten, and the Relationship of School Adaptation in the First Grade for a Sample of Turkish Children.

    PubMed

    Özer, Serap

    2016-04-01

    Behavioral regulation has recently become an important variable in research looking at kindergarten and first-grade achievement of children in private and public schools. The purpose of this study was to examine a measure of behavioral regulation, the Head Toes Knees Shoulders Task, and to evaluate its relationship with visual spatial maturity at the end of kindergarten. Later, in first grade, teachers were asked to rate the children (N = 82) in terms of academic and behavioral adaptation. Behavioral regulation and visual spatial maturity were significantly different between the two school types, but ratings by the teachers in the first grade were affected by children's visual spatial maturity rather than by behavioral regulation. Socioeducational opportunities provided by the two types of schools may be more important to school adaptation than behavioral regulation.

  9. Adaptive Sampling in Hierarchical Simulation

    SciTech Connect

    Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R

    2007-07-09

    We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.

  10. Spatial adaptation on video display terminals

    SciTech Connect

    Greenhouse, D.S.; Bailey, I.L.; Howarth, P.A.; Berman, S.M.

    1989-01-01

    Spatial adaptation, in the form of a frequency-specific reduction in contrast sensitivity, can occur when the visual system is exposed to certain stimuli. We employed vertical sinusoidal test gratings to investigate adaptation to the horizontal structure of text presented on a standard video display terminal. The parameters of the contrast sensitivity test were selected on the basis of waveform analysis of spatial luminance scans of the text stimulus. We found that subjects exhibited a small, but significant, frequency-specific adaptation consistent with the spatial frequency spectrum of the stimulus. Theoretical and practical significance of this finding are discussed. 6 refs., 4 figs.

  11. Dynamics of Adaptation in Spatially Heterogeneous Metapopulations

    PubMed Central

    Papaïx, Julien; David, Olivier; Lannou, Christian; Monod, Hervé

    2013-01-01

    The selection pressure experienced by organisms often varies across the species range. It is hence crucial to characterise the link between environmental spatial heterogeneity and the adaptive dynamics of species or populations. We address this issue by studying the phenotypic evolution of a spatial metapopulation using an adaptive dynamics approach. The singular strategy is found to be the mean of the optimal phenotypes in each habitat with larger weights for habitats present in large and well connected patches. The presence of spatial clusters of habitats in the metapopulation is found to facilitate specialisation and to increase both the level of adaptation and the evolutionary speed of the population when dispersal is limited. By showing that spatial structures are crucial in determining the specialisation level and the evolutionary speed of a population, our results give insight into the influence of spatial heterogeneity on the niche breadth of species. PMID:23424618

  12. Adaptive down-sampling video coding

    NASA Astrophysics Data System (ADS)

    Wang, Ren-Jie; Chien, Ming-Chen; Chang, Pao-Chi

    2010-01-01

    Down-sampling coding, which sub-samples the image and encodes the smaller sized images, is one of the solutions to raise the image quality at insufficiently high rates. In this work, we propose an Adaptive Down-Sampling (ADS) coding for H.264/AVC. The overall system distortion can be analyzed as the sum of the down-sampling distortion and the coding distortion. The down-sampling distortion is mainly the loss of the high frequency components that is highly dependent of the spatial difference. The coding distortion can be derived from the classical Rate-Distortion theory. For a given rate and a video sequence, the optimum down-sampling resolution-ratio can be derived by utilizing the optimum theory toward minimizing the system distortion based on the models of the two distortions. This optimal resolution-ratio is used in both down-sampling and up-sampling processes in ADS coding scheme. As a result, the rate-distortion performance of ADS coding is always higher than the fixed ratio coding or H.264/AVC by 2 to 4 dB at low to medium rates.

  13. Adaptive sampling in convergent beams.

    PubMed

    Espinosa, Julián; Mas, David; Pérez, Jorge; Illueca, Carlos

    2008-09-01

    Numerical calculation of convergent Fresnel patterns through fast Fourier transform usually requires a large number of samples to fulfill the Nyquist sampling condition around the focus. From polynomial decomposition of the wavefront it is possible to determine which polynomial orders are the main contributors to the number of samples. This information can be used to properly modify the initial wavefront and relax the Nyquist condition thus giving a more efficient numerical algorithm.

  14. SPATIALLY-BALANCED SAMPLING OF NATURAL RESOURCES

    EPA Science Inventory

    The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. Generally, sample sites that are spatially-balanced, that is, more or less evenly dispersed over the extent of the resource, will ...

  15. Sampling design optimization for spatial functions

    USGS Publications Warehouse

    Olea, R.A.

    1984-01-01

    A new procedure is presented for minimizing the sampling requirements necessary to estimate a mappable spatial function at a specified level of accuracy. The technique is based on universal kriging, an estimation method within the theory of regionalized variables. Neither actual implementation of the sampling nor universal kriging estimations are necessary to make an optimal design. The average standard error and maximum standard error of estimation over the sampling domain are used as global indices of sampling efficiency. The procedure optimally selects those parameters controlling the magnitude of the indices, including the density and spatial pattern of the sample elements and the number of nearest sample elements used in the estimation. As an illustration, the network of observation wells used to monitor the water table in the Equus Beds of Kansas is analyzed and an improved sampling pattern suggested. This example demonstrates the practical utility of the procedure, which can be applied equally well to other spatial sampling problems, as the procedure is not limited by the nature of the spatial function. ?? 1984 Plenum Publishing Corporation.

  16. Spatial perception and adaptive sonar behavior.

    PubMed

    Aytekin, Murat; Mao, Beatrice; Moss, Cynthia F

    2010-12-01

    Bat echolocation is a dynamic behavior that allows for real-time adaptations in the timing and spectro-temporal design of sonar signals in response to a particular task and environment. To enable detailed, quantitative analyses of adaptive sonar behavior, echolocation call design was investigated in big brown bats, trained to rest on a stationary platform and track a tethered mealworm that approached from a starting distance of about 170 cm in the presence of a stationary sonar distracter. The distracter was presented at different angular offsets and distances from the bat. The results of this study show that the distance and the angular offset of the distracter influence sonar vocalization parameters of the big brown bat, Eptesicus fuscus. Specifically, the bat adjusted its call duration to the closer of two objects, distracter or insect target, and the magnitude of the adjustment depended on the angular offset of the distracter. In contrast, the bat consistently adjusted its call rate to the distance of the insect, even when this target was positioned behind the distracter. The results hold implications for understanding spatial information processing and perception by echolocation.

  17. Accurate Biomass Estimation via Bayesian Adaptive Sampling

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay

    2005-01-01

    The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

  18. Stepwise two-stage sample size adaptation.

    PubMed

    Wan, Hong; Ellenberg, Susan S; Anderson, Keaven M

    2015-01-15

    Several adaptive design methods have been proposed to reestimate sample size using the observed treatment effect after an initial stage of a clinical trial while preserving the overall type I error at the time of the final analysis. One unfortunate property of the algorithms used in some methods is that they can be inverted to reveal the exact treatment effect at the interim analysis. We propose using a step function with an inverted U-shape of observed treatment difference for sample size reestimation to lessen the information on treatment effect revealed. This will be referred to as stepwise two-stage sample size adaptation. This method applies calculation methods used for group sequential designs. We minimize expected sample size among a class of these designs and compare efficiency with the fully optimized two-stage design, optimal two-stage group sequential design, and designs based on promising conditional power. The trade-off between efficiency versus the improved blinding of the interim treatment effect will be discussed.

  19. Feature Adaptive Sampling for Scanning Electron Microscopy

    PubMed Central

    Dahmen, Tim; Engstler, Michael; Pauly, Christoph; Trampert, Patrick; de Jonge, Niels; Mücklich, Frank; Slusallek, Philipp

    2016-01-01

    A new method for the image acquisition in scanning electron microscopy (SEM) was introduced. The method used adaptively increased pixel-dwell times to improve the signal-to-noise ratio (SNR) in areas of high detail. In areas of low detail, the electron dose was reduced on a per pixel basis, and a-posteriori image processing techniques were applied to remove the resulting noise. The technique was realized by scanning the sample twice. The first, quick scan used small pixel-dwell times to generate a first, noisy image using a low electron dose. This image was analyzed automatically, and a software algorithm generated a sparse pattern of regions of the image that require additional sampling. A second scan generated a sparse image of only these regions, but using a highly increased electron dose. By applying a selective low-pass filter and combining both datasets, a single image was generated. The resulting image exhibited a factor of ≈3 better SNR than an image acquired with uniform sampling on a Cartesian grid and the same total acquisition time. This result implies that the required electron dose (or acquisition time) for the adaptive scanning method is a factor of ten lower than for uniform scanning. PMID:27150131

  20. Accurate Biomass Estimation via Bayesian Adaptive Sampling

    NASA Astrophysics Data System (ADS)

    Wheeler, K.; Knuth, K.; Castle, P.

    2005-12-01

    Typical estimates of standing wood derived from remote sensing sources take advantage of aggregate measurements of canopy heights (e.g. LIDAR) and canopy diameters (segmentation of IKONOS imagery) to obtain a wood volume estimate by assuming homogeneous species and a fixed function that returns volume. The validation of such techniques use manually measured diameter at breast height records (DBH). Our goal is to improve the accuracy and applicability of biomass estimation methods to heterogeneous forests and transitional areas. We are developing estimates with quantifiable uncertainty using a new form of estimation function, active sampling, and volumetric reconstruction image rendering for species specific mass truth. Initially we are developing a Bayesian adaptive sampling method for BRDF associated with the MISR Rahman model with respect to categorical biomes. This involves characterizing the probability distributions of the 3 free parameters of the Rahman model for the 6 categories of biomes used by MISR. Subsequently, these distributions can be used to determine the optimal sampling methodology to distinguish biomes during acquisition. We have a remotely controlled semi-autonomous helicopter that has stereo imaging, lidar, differential GPS, and spectrometers covering wavelengths from visible to NIR. We intend to automatically vary the way points of the flight path via the Bayesian adaptive sampling method. The second critical part of this work is in automating the validation of biomass estimates via using machine vision techniques. This involves taking 2-D pictures of trees of known species, and then via Bayesian techniques, reconstructing 3-D models of the trees to estimate the distribution moments associated with wood volume. Similar techniques have been developed by the medical imaging community. This then provides probability distributions conditional upon species. The final part of this work is in relating the BRDF actively sampled measurements to species

  1. Spatially adaptive regularized iterative high-resolution image reconstruction algorithm

    NASA Astrophysics Data System (ADS)

    Lim, Won Bae; Park, Min K.; Kang, Moon Gi

    2000-12-01

    High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The

  2. HASE - The Helsinki adaptive sample preparation line

    NASA Astrophysics Data System (ADS)

    Palonen, V.; Pesonen, A.; Herranen, T.; Tikkanen, P.; Oinonen, M.

    2013-01-01

    We have designed and built an adaptive sample preparation line with separate modules for combustion, molecular sieve handling, CO2 gas cleaning, CO2 storage, and graphitization. The line is also connected to an elemental analyzer. Operation of the vacuum equipment, a flow controller, pressure sensors, ovens, and graphitization reactors are automated with a reliable NI-cRIO real-time system. Stepped combustion can be performed in two ovens at temperatures up to 900 °C. Depending on the application, CuO or O2-flow combustion can be used. A flow controller is used to adjust the O2 flow and pressure during combustion. For environmental samples, a module for molecular sieve regeneration and sample desorption is attached to the line replacing the combustion module. In the storage module, CO2 samples can be stored behind a gas-tight diaphragm valve and either stored for later graphitization or taken for measurements with separate equipment (AMS gas ion source or a separate mass spectrometer). The graphitization module consists of four automated reactors, capable of graphitizing samples with masses from 3 mg down to 50 μg.

  3. Estimating abundance of mountain lions from unstructured spatial sampling

    USGS Publications Warehouse

    Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; Mckelvey, Kevin S.

    2012-01-01

    Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional mark–recapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capture–recapture data have produced methods estimating abundance and density of animals from spatially explicit capture–recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture–recapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908 km2) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100 km2 (95% Cl 2.3–5.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% Cl 3.1–11.0) under the full model (including effects of distance, sex, survey effort, and

  4. Cascaded Effects of Spatial Adaptation in the Early Visual System

    PubMed Central

    Dhruv, Neel T.; Carandini, Matteo

    2014-01-01

    Summary Virtually all stages of the visual system exhibit adaptation: neurons adjust their responses based on the recent stimulus history. While some of these adjustments occur at specific stages, others may be inherited from earlier stages. How do adaptation effects cascade along the visual system? We measured spatially selective adaptation at two successive stages in the mouse visual system: visual thalamus (LGN) and primary visual cortex (V1). This form of adaptation affected both stages but in drastically different ways: in LGN it only changed response gain, while in V1 it also shifted spatial tuning away from the adaptor. These effects, however, are reconciled by a simple model whereby V1 neurons summate LGN inputs with a fixed, unadaptable weighting profile. These results indicate that adaptation effects cascade through the visual system, that this cascading can shape selectivity, and that the rules of integration from one stage to the next are not themselves adaptable. PMID:24507190

  5. Cascaded effects of spatial adaptation in the early visual system.

    PubMed

    Dhruv, Neel T; Carandini, Matteo

    2014-02-05

    Virtually all stages of the visual system exhibit adaptation: neurons adjust their responses based on the recent stimulus history. While some of these adjustments occur at specific stages, others may be inherited from earlier stages. How do adaptation effects cascade along the visual system? We measured spatially selective adaptation at two successive stages in the mouse visual system: visual thalamus (LGN) and primary visual cortex (V1). This form of adaptation affected both stages but in drastically different ways: in LGN it only changed response gain, while in V1 it also shifted spatial tuning away from the adaptor. These effects, however, are reconciled by a simple model whereby V1 neurons summate LGN inputs with a fixed, unadaptable weighting profile. These results indicate that adaptation effects cascade through the visual system, that this cascading can shape selectivity, and that the rules of integration from one stage to the next are not themselves adaptable.

  6. Latent spatial models and sampling design for landscape genetics

    USGS Publications Warehouse

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  7. Spatially constrained adaptive rewiring in cortical networks creates spatially modular small world architectures.

    PubMed

    Jarman, Nicholas; Trengove, Chris; Steur, Erik; Tyukin, Ivan; van Leeuwen, Cees

    2014-12-01

    A modular small-world topology in functional and anatomical networks of the cortex is eminently suitable as an information processing architecture. This structure was shown in model studies to arise adaptively; it emerges through rewiring of network connections according to patterns of synchrony in ongoing oscillatory neural activity. However, in order to improve the applicability of such models to the cortex, spatial characteristics of cortical connectivity need to be respected, which were previously neglected. For this purpose we consider networks endowed with a metric by embedding them into a physical space. We provide an adaptive rewiring model with a spatial distance function and a corresponding spatially local rewiring bias. The spatially constrained adaptive rewiring principle is able to steer the evolving network topology to small world status, even more consistently so than without spatial constraints. Locally biased adaptive rewiring results in a spatial layout of the connectivity structure, in which topologically segregated modules correspond to spatially segregated regions, and these regions are linked by long-range connections. The principle of locally biased adaptive rewiring, thus, may explain both the topological connectivity structure and spatial distribution of connections between neuronal units in a large-scale cortical architecture.

  8. Weighted adaptive spatial filtering in digital holographic microscopy

    NASA Astrophysics Data System (ADS)

    Hong, Yuan; Shi, Tielin; Wang, Xiao; Zhang, Yichun; Chen, Kepeng; Liao, Guanglan

    2017-01-01

    Spatial filtering, a key point to realize real-time measurement, is used commonly in digital off-axis holography to extract desired terms. In this paper, we propose a weighted adaptive spatial filtering method by weighting the adaptive filtering window (obtained from image segmentation) based on signal to noise ratio. The advantages of this method are evaluated by simulations and further verified by recorded digital image plane holograms. The results demonstrate that our method is effective in suppressing noise and retaining the sharp edges in the reconstructed 3D profiles.

  9. A spatially and temporally adaptive solution of Richards’ equation

    NASA Astrophysics Data System (ADS)

    Miller, Cass T.; Abhishek, Chandra; Farthing, Matthew W.

    2006-04-01

    Efficient, robust simulation of groundwater flow in the unsaturated zone remains computationally expensive, especially for problems characterized by sharp fronts in both space and time. Standard approaches that employ uniform spatial and temporal discretizations for the numerical solution of these problems lead to inefficient and expensive simulations. In this work, we solve Richards' equation using adaptive methods in both space and time. Spatial adaption is based upon a coarse grid solve and a gradient error indicator using a fixed-order approximation. Temporal adaption is accomplished using variable order, variable step size approximations based upon the backward difference formulas up to fifth order. Since the advantages of similar adaptive methods in time are now established, we evaluate our method by comparison with a uniform spatial discretization that is adaptive in time for four different one-dimensional test problems. The numerical results demonstrate that the proposed method provides a robust and efficient alternative to standard approaches for simulating variably saturated flow in one spatial dimension.

  10. Radiotherapy Adapted to Spatial and Temporal Variability in Tumor Hypoxia

    SciTech Connect

    Sovik, Aste; Malinen, Eirik . E-mail: emalinen@fys.uio.no; Skogmo, Hege K.; Bentzen, Soren M.; Bruland, Oyvind S.; Olsen, Dag Rune

    2007-08-01

    Purpose: To explore the feasibility and clinical potential of adapting radiotherapy to temporal and spatial variations in tumor oxygenation. Methods and Materials: Repeated dynamic contrast enhanced magnetic resonance (DCEMR) images were taken of a canine sarcoma during the course of fractionated radiation therapy. The tumor contrast enhancement was assumed to represent the oxygen distribution. The IMRT plans were retrospectively adapted to the DCEMR images by employing tumor dose redistribution. Optimized nonuniform tumor dose distributions were calculated and compared with a uniform dose distribution delivering the same integral dose to the tumor. Clinical outcome was estimated from tumor control probability (TCP) and normal tissue complication probability (NTCP) modeling. Results: The biologically adapted treatment was found to give a substantial increase in TCP compared with conventional radiotherapy, even when only pretreatment images were used as basis for the treatment planning. The TCP was further increased by repeated replanning during the course of treatment, and replanning twice a week was found to give near optimal TCP. Random errors in patient positioning were found to give a small decrease in TCP, whereas systematic errors were found to reduce TCP substantially. NTCP for the adapted treatment was similar to or lower than for the conventional treatment, both for parallel and serial normal tissue structures. Conclusion: Biologically adapted radiotherapy is estimated to improve treatment outcome of tumors having spatial and temporal variations in radiosensitivity.

  11. Adaptive Metropolis Sampling with Product Distributions

    NASA Technical Reports Server (NTRS)

    Wolpert, David H.; Lee, Chiu Fan

    2005-01-01

    The Metropolis-Hastings (MH) algorithm is a way to sample a provided target distribution pi(z). It works by repeatedly sampling a separate proposal distribution T(x,x') to generate a random walk {x(t)}. We consider a modification of the MH algorithm in which T is dynamically updated during the walk. The update at time t uses the {x(t' less than t)} to estimate the product distribution that has the least Kullback-Leibler distance to pi. That estimate is the information-theoretically optimal mean-field approximation to pi. We demonstrate through computer experiments that our algorithm produces samples that are superior to those of the conventional MH algorithm.

  12. Regional spatially adaptive total variation super-resolution with spatial information filtering and clustering.

    PubMed

    Yuan, Qiangqiang; Zhang, Liangpei; Shen, Huanfeng

    2013-06-01

    Total variation is used as a popular and effective image prior model in the regularization-based image processing fields. However, as the total variation model favors a piecewise constant solution, the processing result under high noise intensity in the flat regions of the image is often poor, and some pseudoedges are produced. In this paper, we develop a regional spatially adaptive total variation model. Initially, the spatial information is extracted based on each pixel, and then two filtering processes are added to suppress the effect of pseudoedges. In addition, the spatial information weight is constructed and classified with k-means clustering, and the regularization strength in each region is controlled by the clustering center value. The experimental results, on both simulated and real datasets, show that the proposed approach can effectively reduce the pseudoedges of the total variation regularization in the flat regions, and maintain the partial smoothness of the high-resolution image. More importantly, compared with the traditional pixel-based spatial information adaptive approach, the proposed region-based spatial information adaptive total variation model can better avoid the effect of noise on the spatial information extraction, and maintains robustness with changes in the noise intensity in the super-resolution process.

  13. Sampling design for spatially distributed hydrogeologic and environmental processes

    USGS Publications Warehouse

    Christakos, G.; Olea, R.A.

    1992-01-01

    A methodology for the design of sampling networks over space is proposed. The methodology is based on spatial random field representations of nonhomogeneous natural processes, and on optimal spatial estimation techniques. One of the most important results of random field theory for physical sciences is its rationalization of correlations in spatial variability of natural processes. This correlation is extremely important both for interpreting spatially distributed observations and for predictive performance. The extent of site sampling and the types of data to be collected will depend on the relationship of subsurface variability to predictive uncertainty. While hypothesis formulation and initial identification of spatial variability characteristics are based on scientific understanding (such as knowledge of the physics of the underlying phenomena, geological interpretations, intuition and experience), the support offered by field data is statistically modelled. This model is not limited by the geometric nature of sampling and covers a wide range in subsurface uncertainties. A factorization scheme of the sampling error variance is derived, which possesses certain atttactive properties allowing significant savings in computations. By means of this scheme, a practical sampling design procedure providing suitable indices of the sampling error variance is established. These indices can be used by way of multiobjective decision criteria to obtain the best sampling strategy. Neither the actual implementation of the in-situ sampling nor the solution of the large spatial estimation systems of equations are necessary. The required values of the accuracy parameters involved in the network design are derived using reference charts (readily available for various combinations of data configurations and spatial variability parameters) and certain simple yet accurate analytical formulas. Insight is gained by applying the proposed sampling procedure to realistic examples related

  14. Sampling and kriging spatial means: efficiency and conditions.

    PubMed

    Wang, Jin-Feng; Li, Lian-Fa; Christakos, George

    2009-01-01

    Sampling and estimation of geographical attributes that vary across space (e.g., area temperature, urban pollution level, provincial cultivated land, regional population mortality and state agricultural production) are common yet important constituents of many real-world applications. Spatial attribute estimation and the associated accuracy depend on the available sampling design and statistical inference modelling. In the present work, our concern is areal attribute estimation, in which the spatial sampling and Kriging means are compared in terms of mean values, variances of mean values, comparative efficiencies and underlying conditions. Both the theoretical analysis and the empirical study show that the mean Kriging technique outperforms other commonly-used techniques. Estimation techniques that account for spatial correlation (dependence) are more efficient than those that do not, whereas the comparative efficiencies of the various methods change with surface features. The mean Kriging technique can be applied to other spatially distributed attributes, as well.

  15. Sampling and Kriging Spatial Means: Efficiency and Conditions

    PubMed Central

    Wang, Jin-Feng; Li, Lian-Fa; Christakos, George

    2009-01-01

    Sampling and estimation of geographical attributes that vary across space (e.g., area temperature, urban pollution level, provincial cultivated land, regional population mortality and state agricultural production) are common yet important constituents of many real-world applications. Spatial attribute estimation and the associated accuracy depend on the available sampling design and statistical inference modelling. In the present work, our concern is areal attribute estimation, in which the spatial sampling and Kriging means are compared in terms of mean values, variances of mean values, comparative efficiencies and underlying conditions. Both the theoretical analysis and the empirical study show that the mean Kriging technique outperforms other commonly-used techniques. Estimation techniques that account for spatial correlation (dependence) are more efficient than those that do not, whereas the comparative efficiencies of the various methods change with surface features. The mean Kriging technique can be applied to other spatially distributed attributes, as well. PMID:22346694

  16. Spatial Cognitive Performance During Adaptation to Conflicting Tilt-Translation Stimuli as a Sensorimotor Spaceflight Analog

    NASA Technical Reports Server (NTRS)

    Kayanickupuram, A. J.; Ramos, K. A.; Cordova, M. L.; Wood, S. J.

    2009-01-01

    The need to resolve new patterns of sensory feedback in altered gravitoinertial environments requires cognitive processes to develop appropriate reference frames for spatial orientation awareness. The purpose of this study was to examine deficits in spatial cognitive performance during adaptation to conflicting tilt-translation stimuli. Fourteen subjects were tilted within a lighted enclosure that simultaneously translated at one of 3 frequencies. Tilt and translation motion was synchronized to maintain the resultant gravitoinertial force aligned with the longitudinal body axis, resulting in a mismatch analogous to spaceflight in which the canals and vision signal tilt while the otoliths do not. Changes in performance on different spatial cognitive tasks were compared 1) without motion, 2) with tilt motion alone (pitch at 0.15, 0.3 and 0.6 Hz or roll at 0.3 Hz), and 3) with conflicting tilt-translation motion. The adaptation paradigm was continued for up to 30 min or until the onset of nausea. The order of the adaptation conditions were counter-balanced across 4 different test sessions. There was a significant effect of stimulus frequency on both motion sickness and spatial cognitive performance. Only 3 of 14 were able to complete the full 30 min protocol at 0.15 Hz, while 7 of 14 completed 0.3 Hz and 13 of 14 completed 0.6 Hz. There were no changes in simple visual-spatial cognitive tests, e.g., mental rotation or match-to-sample. There were significant deficits during 0.15 Hz adaptation in both accuracy and reaction time during a spatial reference task in which subjects are asked to identify a match of a 3D reoriented cube assemblage. Our results are consistent with antidotal reports of cognitive impairment that are common during sensorimotor adaptation with G-transitions. We conclude that these cognitive deficits stem from the ambiguity of spatial reference frames for central processing of inertial motion cues.

  17. Adaptive Importance Sampling for Control and Inference

    NASA Astrophysics Data System (ADS)

    Kappen, H. J.; Ruiz, H. C.

    2016-03-01

    Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.

  18. Adaptive conductance filtering for spatially varying noise in PET images

    NASA Astrophysics Data System (ADS)

    Padfield, Dirk R.; Manjeshwar, Ravindra

    2006-03-01

    PET images that have been reconstructed with unregularized algorithms are commonly smoothed with linear Gaussian filters to control noise. Since these filters are spatially invariant, they degrade feature contrast in the image, compromising lesion detectability. Edge-preserving smoothing filters can differentially preserve edges and features while smoothing noise. These filters assume spatially uniform noise models. However, the noise in PET images is spatially variant, approximately following a Poisson behavior. Therefore, different regions of a PET image need smoothing by different amounts. In this work, we introduce an adaptive filter, based on anisotropic diffusion, designed specifically to overcome this problem. In this algorithm, the diffusion is varied according to a local estimate of the noise using either the local median or the grayscale image opening to weight the conductance parameter. The algorithm is thus tailored to the task of smoothing PET images, or any image with Poisson-like noise characteristics, by adapting itself to varying noise while preserving significant features in the image. This filter was compared with Gaussian smoothing and a representative anisotropic diffusion method using three quantitative task-relevant metrics calculated on simulated PET images with lesions in the lung and liver. The contrast gain and noise ratio metrics were used to measure the ability to do accurate quantitation; the Channelized Hotelling Observer lesion detectability index was used to quantify lesion detectability. The adaptive filter improved the signal-to-noise ratio by more than 45% and lesion detectability by more than 55% over the Gaussian filter while producing "natural" looking images and consistent image quality across different anatomical regions.

  19. Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure

    USGS Publications Warehouse

    Salehi, M.; Smith, D.R.

    2005-01-01

    Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicability of adaptive cluster sampling. We propose a sampling design that is adaptive in the sense that the final sample depends on observed values, but it avoids the use of neighborhoods and the sampling of edge units. Unbiased estimators of population total and its variance are derived using Murthy's estimator. The modified two-stage sampling design is easy to implement and can be applied to a wider range of populations than adaptive cluster sampling. We evaluate the proposed sampling design by simulating sampling of two real biological populations and an artificial population for which the variable of interest took the value either 0 or 1 (e.g., indicating presence and absence of a rare event). We show that the proposed sampling design is more efficient than conventional sampling in nearly all cases. The approach used to derive estimators (Murthy's estimator) opens the door for unbiased estimators to be found for similar sequential sampling designs. ?? 2005 American Statistical Association and the International Biometric Society.

  20. VARIANCE ESTIMATION FOR SPATIALLY BALANCED SAMPLES OF ENVIRONMENTAL RESOURCES

    EPA Science Inventory

    The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. We review a unified strategy for designing probability samples of discrete, finite resource populations, such as lakes within som...

  1. On the Effect of Preferential Sampling in Spatial Prediction

    EPA Science Inventory

    The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...

  2. Spatial downscaling of precipitation using adaptable random forests

    NASA Astrophysics Data System (ADS)

    He, Xiaogang; Chaney, Nathaniel W.; Schleiss, Marc; Sheffield, Justin

    2016-10-01

    This paper introduces Prec-DWARF (Precipitation Downscaling With Adaptable Random Forests), a novel machine-learning based method for statistical downscaling of precipitation. Prec-DWARF sets up a nonlinear relationship between precipitation at fine resolution and covariates at coarse/fine resolution, based on the advanced binary tree method known as Random Forests (RF). In addition to a single RF, we also consider a more advanced implementation based on two independent RFs which yield better results for extreme precipitation. Hourly gauge-radar precipitation data at 0.125° from NLDAS-2 are used to conduct synthetic experiments with different spatial resolutions (0.25°, 0.5°, and 1°). Quantitative evaluation of these experiments demonstrates that Prec-DWARF consistently outperforms the baseline (i.e., bilinear interpolation in this case) and can reasonably reproduce the spatial and temporal patterns, occurrence and distribution of observed precipitation fields. However, Prec-DWARF with a single RF significantly underestimates precipitation extremes and often cannot correctly recover the fine-scale spatial structure, especially for the 1° experiments. Prec-DWARF with a double RF exhibits improvement in the simulation of extreme precipitation as well as its spatial and temporal structures, but variogram analyses show that the spatial and temporal variability of the downscaled fields are still strongly underestimated. Covariate importance analysis shows that the most important predictors for the downscaling are the coarse-scale precipitation values over adjacent grid cells as well as the distance to the closest dry grid cell (i.e., the dry drift). The encouraging results demonstrate the potential of Prec-DWARF and machine-learning based techniques in general for the statistical downscaling of precipitation.

  3. Spatial structure enhanced cooperation in dissatisfied adaptive snowdrift game

    NASA Astrophysics Data System (ADS)

    Zhang, Wen; Xu, Chen; Hui, Pak Ming

    2013-05-01

    The dissatisfied adaptive snowdrift game (DASG) describes the adaptive actions driven by the level of dissatisfaction when two connected agents interact. We study the DASG in static networks both numerically and analytically. In a random network of uniform degree k, the system evolves into a homogeneous state consisting only of cooperators when the cost-to-benefit ratio r < r 0 and a mixed phase with the coexistence of cooperators and defectors when r > r 0, where r 0 is a threshold. For an infinite population, the large k limit corresponding to the well-mixed case is solved analytically. A theory is developed based on the pair approximation. It gives the frequency of cooperation f c and the densities of different pairs that are in good agreement with simulation results. The results revealed that f c is enhanced in networked populations with a finite k, when compared with the well-mixed case. The reasons that the theory works well for the present model are traced back to the weak spatial correlation implied by the random network and the fact that the adaptive actions in DASG are driven only by the strategy pairs. The results shed light on the class of models that the pair approximation is applicable.

  4. Spatial Compression Impairs Prism Adaptation in Healthy Individuals

    PubMed Central

    Scriven, Rachel J.; Newport, Roger

    2013-01-01

    Neglect patients typically present with gross inattention to one side of space following damage to the contralateral hemisphere. While prism-adaptation (PA) is effective in ameliorating some neglect behaviors, the mechanisms involved and their relationship to neglect remain unclear. Recent studies have shown that conscious strategic control (SC) processes in PA may be impaired in neglect patients, who are also reported to show extraordinarily long aftereffects compared to healthy participants. Determining the underlying cause of these effects may be the key to understanding therapeutic benefits. Alternative accounts suggest that reduced SC might result from a failure to detect prism-induced reaching errors properly either because (a) the size of the error is underestimated in compressed visual space or (b) pathologically increased error-detection thresholds reduce the requirement for error correction. The purpose of this study was to model these two alternatives in healthy participants and to examine whether SC and subsequent aftereffects were abnormal compared to standard PA. Each participant completed three PA procedures within a MIRAGE mediated reality environment with direction errors recorded before, during and after adaptation. During PA, visual feedback of the reach could be compressed, perturbed by noise, or represented veridically. Compressed visual space significantly reduced SC and aftereffects compared to control and noise conditions. These results support recent observations in neglect patients, suggesting that a distortion of spatial representation may successfully model neglect and explain neglect performance while adapting to prisms. PMID:23675332

  5. Adaptive Sampling for High Throughput Data Using Similarity Measures

    SciTech Connect

    Bulaevskaya, V.; Sales, A. P.

    2015-05-06

    The need for adaptive sampling arises in the context of high throughput data because the rates of data arrival are many orders of magnitude larger than the rates at which they can be analyzed. A very fast decision must therefore be made regarding the value of each incoming observation and its inclusion in the analysis. In this report we discuss one approach to adaptive sampling, based on the new data point’s similarity to the other data points being considered for inclusion. We present preliminary results for one real and one synthetic data set.

  6. Improved spatial resolution in PET scanners using sampling techniques

    PubMed Central

    Surti, Suleman; Scheuermann, Ryan; Werner, Matthew E.; Karp, Joel S.

    2009-01-01

    Increased focus towards improved detector spatial resolution in PET has led to the use of smaller crystals in some form of light sharing detector design. In this work we evaluate two sampling techniques that can be applied during calibrations for pixelated detector designs in order to improve the reconstructed spatial resolution. The inter-crystal positioning technique utilizes sub-sampling in the crystal flood map to better sample the Compton scatter events in the detector. The Compton scatter rejection technique, on the other hand, rejects those events that are located further from individual crystal centers in the flood map. We performed Monte Carlo simulations followed by measurements on two whole-body scanners for point source data. The simulations and measurements were performed for scanners using scintillators with Zeff ranging from 46.9 to 63 for LaBr3 and LYSO, respectively. Our results show that near the center of the scanner, inter-crystal positioning technique leads to a gain of about 0.5-mm in reconstructed spatial resolution (FWHM) for both scanner designs. In a small animal LYSO scanner the resolution improves from 1.9-mm to 1.6-mm with the inter-crystal technique. The Compton scatter rejection technique shows higher gains in spatial resolution but at the cost of reduction in scanner sensitivity. The inter-crystal positioning technique represents a modest acquisition software modification for an improvement in spatial resolution, but at a cost of potentially longer data correction and reconstruction times. The Compton scatter rejection technique, while also requiring a modest acquisition software change with no increased data correction and reconstruction times, will be useful in applications where the scanner sensitivity is very high and larger improvements in spatial resolution are desirable. PMID:19779586

  7. spsann - optimization of sample patterns using spatial simulated annealing

    NASA Astrophysics Data System (ADS)

    Samuel-Rosa, Alessandro; Heuvelink, Gerard; Vasques, Gustavo; Anjos, Lúcia

    2015-04-01

    There are many algorithms and computer programs to optimize sample patterns, some private and others publicly available. A few have only been presented in scientific articles and text books. This dispersion and somewhat poor availability is holds back to their wider adoption and further development. We introduce spsann, a new R-package for the optimization of sample patterns using spatial simulated annealing. R is the most popular environment for data processing and analysis. Spatial simulated annealing is a well known method with widespread use to solve optimization problems in the soil and geo-sciences. This is mainly due to its robustness against local optima and easiness of implementation. spsann offers many optimizing criteria for sampling for variogram estimation (number of points or point-pairs per lag distance class - PPL), trend estimation (association/correlation and marginal distribution of the covariates - ACDC), and spatial interpolation (mean squared shortest distance - MSSD). spsann also includes the mean or maximum universal kriging variance (MUKV) as an optimizing criterion, which is used when the model of spatial variation is known. PPL, ACDC and MSSD were combined (PAN) for sampling when we are ignorant about the model of spatial variation. spsann solves this multi-objective optimization problem scaling the objective function values using their maximum absolute value or the mean value computed over 1000 random samples. Scaled values are aggregated using the weighted sum method. A graphical display allows to follow how the sample pattern is being perturbed during the optimization, as well as the evolution of its energy state. It is possible to start perturbing many points and exponentially reduce the number of perturbed points. The maximum perturbation distance reduces linearly with the number of iterations. The acceptance probability also reduces exponentially with the number of iterations. R is memory hungry and spatial simulated annealing is a

  8. An Integrative Hierarchical Stepwise Sampling Strategy For Spatial Sampling And Its Application In Digital Soil Mapping

    NASA Astrophysics Data System (ADS)

    Yang, L.; Zhu, A.; Qi, F.; Qin, C.; Li, B.; Pei, T.

    2011-12-01

    Sampling design plays an important role in spatial modeling. Existing methods often require large amount of samples to achieve desired mapping accuracy but imply considerable cost. When there are not enough resources for collecting a large set of samples at once, stepwise sampling approach is often the only option for collecting the needed large sample set, especially in the case of field surveying over large areas. This paper proposes an integrative hierarchical stepwise sampling strategy which makes the samples collected at different stages an integrative one. The strategy is based on samples' representativeness of the geographic feature at different scales. The basic idea is to sample at locations that are representative of large-scale spatial patterns first and then add samples that represent more local patterns in a stepwise fashion. Based on the relationships between geographic feature and its environmental covariates, the proposed sampling method approximates a hierarchy of spatial variations of the geographic feature under concern by delineating natural aggregates (clusters) of its relevant environmental covariates at different scales. The natural occurrence of such aggregates is modeled using a fuzzy c-means clustering method. We iterate through different numbers of clusters from only a few to many more to be able to reveal clusters at different spatial scales. At a particular iteration, locations that bear high similarity to the cluster prototypes are identified. If a location is consistently identified at multiple iterations it is then considered to be more representative of the general or large-scale spatial patterns. Locations that are identified less during the iterations are representative of local patterns. The integrative stepwise sampling design then gives higher sampling priority to the locations that are more representative of the large scale patterns than local ones. We applied this sampling design in a digital soil mapping case study

  9. Adaptive spatially dependent weighting scheme for tomosynthesis reconstruction

    NASA Astrophysics Data System (ADS)

    Levakhina, Yulia; Duschka, Robert; Vogt, Florian; Barkhausen, JOErg; Buzug, Thorsten M.

    2012-03-01

    Digital Tomosynthesis (DT) is an x-ray limited-angle imaging technique. An accurate image reconstruction in tomosynthesis is a challenging task due to the violation of the tomographic sufficiency conditions. A classical "shift-and-add" algorithm (or simple backprojection) suffers from blurring artifacts, produced by structures located above and below the plane of interest. The artifact problem becomes even more prominent in the presence of materials and tissues with a high x-ray attenuation, such as bones, microcalcifications or metal. The focus of the current work is on reduction of ghosting artifacts produced by bones in the musculoskeletal tomosynthesis. A novel dissimilarity concept and a modified backprojection with an adaptive spatially dependent weighting scheme (ωBP) are proposed. Simulated data of software phantom, a structured hardware phantom and a human hand raw-data acquired with a Siemens Mammomat Inspiration tomosynthesis system were reconstructed using conventional backprojection algorithm and the new ωBP-algorithm. The comparison of the results to the non-weighted case demonstrates the potential of the proposed weighted backprojection to reduce the blurring artifacts in musculoskeletal DT. The proposed weighting scheme is not limited to the tomosynthesis limitedangle geometry. It can also be adapted for Computed Tomography (CT) and included in iterative reconstruction algorithms (e.g. SART).

  10. Efficiency enhancement of RELAP/PANBOX using adaptive spatial kinetics

    SciTech Connect

    Jackson, C.J.; Cacuci, D.G.; Finnemann, H.B.

    1996-12-31

    The coupled RELAP/PANBOX code system was developed to analyze more accurately those pressurized water reactor (PWR) plant transients in which the core neutron flux distribution changes significantly in time. Examples of such transients are those initiated by steam-line breaks and rapid boron dilution events. On the other hand, instances may occur during long thermal-hydraulic transients when the neutron flux shape varies slowly in time. During such slow transients, a one-dimensional (1-D) model in the axial direction or a point-kinetics model, rather than a three-dimensional (3-D) one, would suffice to calculate the power distribution. To switch between 3-D, 1-D, and/or point-kinetics models, it is very advantageous to generate the respective 1-D and/or point-kinetics parameters automatically and internally within the code. In this paper, the authors describe the features of an adaptive spatial kinetics algorithm that performs the switching process between 3-D and 1-D and/or point-kinetics models according to the physical phenomena underlying the specific plant transient under investigation. The adaptive algorithm has been implemented as a module of the core simulation package PANBOX and therefore does not disturb the subroutines that couple PANBOX to RELAP.

  11. Fast unsupervised Bayesian image segmentation with adaptive spatial regularisation.

    PubMed

    Pereyra, Marcelo; McLaughlin, Stephen

    2017-03-15

    This paper presents a new Bayesian estimation technique for hidden Potts-Markov random fields with unknown regularisation parameters, with application to fast unsupervised K-class image segmentation. The technique is derived by first removing the regularisation parameter from the Bayesian model by marginalisation, followed by a small-variance-asymptotic (SVA) analysis in which the spatial regularisation and the integer-constrained terms of the Potts model are decoupled. The evaluation of this SVA Bayesian estimator is then relaxed into a problem that can be computed efficiently by iteratively solving a convex total-variation denoising problem and a least-squares clustering (K-means) problem, both of which can be solved straightforwardly, even in high-dimensions, and with parallel computing techniques. This leads to a fast fully unsupervised Bayesian image segmentation methodology in which the strength of the spatial regularisation is adapted automatically to the observed image during the inference procedure, and that can be easily applied in large 2D and 3D scenarios or in applications requiring low computing times. Experimental results on synthetic and real images, as well as extensive comparisons with state-ofthe- art algorithms, confirm that the proposed methodology offer extremely fast convergence and produces accurate segmentation results, with the important additional advantage of self-adjusting regularisation parameters.

  12. Spatial sampling errors for a satellite-borne scanning radiometer

    NASA Technical Reports Server (NTRS)

    Manalo, Natividad D.; Smith, G. L.

    1991-01-01

    The Clouds and Earth's Radiant Energy System (CERES) scanning radiometer is planned as the Earth radiation budget instrument for the Earth Observation System, to be flown in the late 1990's. In order to minimize the spatial sampling errors of the measurements, it is necessary to select design parameters for the instrument such that the resulting point spread function will minimize spatial sampling errors. These errors are described as aliasing and blurring errors. Aliasing errors are due to presence in the measurements of spatial frequencies beyond the Nyquist frequency, and blurring errors are due to attenuation of frequencies below the Nyquist frequency. The design parameters include pixel shape and dimensions, sampling rate, scan period, and time constants of the measurements. For a satellite-borne scanning radiometer, the pixel footprint grows quickly at large nadir angles. The aliasing errors thus decrease with increasing scan angle, but the blurring errors grow quickly. The best design minimizes the sum of these two errors over a range of scan angles. Results of a parameter study are presented, showing effects of data rates, pixel dimensions, spacecraft altitude, and distance from the spacecraft track.

  13. The effects of spatial sampling choices on MR temperature measurements.

    PubMed

    Todd, Nick; Vyas, Urvi; de Bever, Josh; Payne, Allison; Parker, Dennis L

    2011-02-01

    The purpose of this article is to quantify the effects that spatial sampling parameters have on the accuracy of magnetic resonance temperature measurements during high intensity focused ultrasound treatments. Spatial resolution and position of the sampling grid were considered using experimental and simulated data for two different types of high intensity focused ultrasound heating trajectories (a single point and a 4-mm circle) with maximum measured temperature and thermal dose volume as the metrics. It is demonstrated that measurement accuracy is related to the curvature of the temperature distribution, where regions with larger spatial second derivatives require higher resolution. The location of the sampling grid relative temperature distribution has a significant effect on the measured values. When imaging at 1.0 × 1.0 × 3.0 mm(3) resolution, the measured values for maximum temperature and volume dosed to 240 cumulative equivalent minutes (CEM) or greater varied by 17% and 33%, respectively, for the single-point heating case, and by 5% and 18%, respectively, for the 4-mm circle heating case. Accurate measurement of the maximum temperature required imaging at 1.0 × 1.0 × 3.0 mm(3) resolution for the single-point heating case and 2.0 × 2.0 × 5.0 mm(3) resolution for the 4-mm circle heating case.

  14. Adaptive data assimilation including the effect of spatial variations in observation error

    NASA Astrophysics Data System (ADS)

    Frehlich, Rod

    2006-04-01

    An optimal adaptive data assimilation algorithm is derived using the maximum likelihood method based on a conditional Gaussian probability density function for the first-guess and direct observations of the state variables but including local estimates of the observation and first-guess error statistics. An interpolation of the first-guess field to the observation coordinates is not required under the assumption of locally homogeneous statistics for the random atmosphere. However, the definition of observation error requires a definition of model 'truth' which is defined as a spatial average of the continuous random atmospheric variables. Then the total observation error consists of two independent components: an instrument error and an observation sampling error defined by the spatial average of the observation and the statistics of the local turbulence. Estimates of the observation sampling error statistics are determined from an ensemble of background or first-guess fields or from the analysis of the raw data from instrumented aircraft, Doppler lidars, or radar profilers. The spatial variations of the sampling error are referenced to the local turbulence conditions at each analysis coordinate and therefore each observation can have a different observation error for each nearby analysis coordinate. The extension of the adaptive assimilation concept to include the spatial variations in observation error for statistical interpolation, 3D-Var, 4D-Var, extended Kalman filtering, and ensemble Kalman filtering is also presented for the traditional meaning of observation error, i.e. each observation is assigned a single error. The conditional analysis error is derived for a single observation at the analysis coordinate and multiple observations around the analysis point. Example calculations of the conditional analysis error are presented for a few simple set of observation and measurement geometries to demonstrate the impact of the spatially variable observation errors

  15. Node Based Adaptive Sampling and Advanced AUV Capabilities

    DTIC Science & Technology

    2001-09-30

    is to develop and refine node based adaptive sampling and hovering technology using FAU Morpheus vehicle as a test platform. The former one is a...included two days of testing with a “dummy” vehicle followed by two days of testing with the real Morpheus . The initial tests were done with the dummy...vehicle because the Morpheus was unavailable for docking experiments at the time. These tests were conducted in order to get a better sense of

  16. Node Based Adaptive Sampling and Advanced AUV Capabilities

    DTIC Science & Technology

    2002-09-30

    is to develop and refine node based adaptive sampling and hovering technology using FAU Morpheus vehicle as a test platform. The former one is a...dummy” vehicle followed by two days of testing with the real Morpheus . The initial tests were done with the dummy vehicle because the Morpheus was... Morpheus when it became available. The dummy vehicle was constructed from empty Morpheus modules with weight placed inside each at a calculated

  17. Adaptive Sampling Algorithms for Probabilistic Risk Assessment of Nuclear Simulations

    SciTech Connect

    Diego Mandelli; Dan Maljovec; Bei Wang; Valerio Pascucci; Peer-Timo Bremer

    2013-09-01

    Nuclear simulations are often computationally expensive, time-consuming, and high-dimensional with respect to the number of input parameters. Thus exploring the space of all possible simulation outcomes is infeasible using finite computing resources. During simulation-based probabilistic risk analysis, it is important to discover the relationship between a potentially large number of input parameters and the output of a simulation using as few simulation trials as possible. This is a typical context for performing adaptive sampling where a few observations are obtained from the simulation, a surrogate model is built to represent the simulation space, and new samples are selected based on the model constructed. The surrogate model is then updated based on the simulation results of the sampled points. In this way, we attempt to gain the most information possible with a small number of carefully selected sampled points, limiting the number of expensive trials needed to understand features of the simulation space. We analyze the specific use case of identifying the limit surface, i.e., the boundaries in the simulation space between system failure and system success. In this study, we explore several techniques for adaptively sampling the parameter space in order to reconstruct the limit surface. We focus on several adaptive sampling schemes. First, we seek to learn a global model of the entire simulation space using prediction models or neighborhood graphs and extract the limit surface as an iso-surface of the global model. Second, we estimate the limit surface by sampling in the neighborhood of the current estimate based on topological segmentations obtained locally. Our techniques draw inspirations from topological structure known as the Morse-Smale complex. We highlight the advantages and disadvantages of using a global prediction model versus local topological view of the simulation space, comparing several different strategies for adaptive sampling in both

  18. A random spatial sampling method in a rural developing nation

    PubMed Central

    2014-01-01

    Background Nonrandom sampling of populations in developing nations has limitations and can inaccurately estimate health phenomena, especially among hard-to-reach populations such as rural residents. However, random sampling of rural populations in developing nations can be challenged by incomplete enumeration of the base population. Methods We describe a stratified random sampling method using geographical information system (GIS) software and global positioning system (GPS) technology for application in a health survey in a rural region of Guatemala, as well as a qualitative study of the enumeration process. Results This method offers an alternative sampling technique that could reduce opportunities for bias in household selection compared to cluster methods. However, its use is subject to issues surrounding survey preparation, technological limitations and in-the-field household selection. Application of this method in remote areas will raise challenges surrounding the boundary delineation process, use and translation of satellite imagery between GIS and GPS, and household selection at each survey point in varying field conditions. This method favors household selection in denser urban areas and in new residential developments. Conclusions Random spatial sampling methodology can be used to survey a random sample of population in a remote region of a developing nation. Although this method should be further validated and compared with more established methods to determine its utility in social survey applications, it shows promise for use in developing nations with resource-challenged environments where detailed geographic and human census data are less available. PMID:24716473

  19. Local Adaptation in European Firs Assessed through Extensive Sampling across Altitudinal Gradients in Southern Europe

    PubMed Central

    Postolache, Dragos; Lascoux, Martin; Drouzas, Andreas D.; Källman, Thomas; Leonarduzzi, Cristina; Liepelt, Sascha; Piotti, Andrea; Popescu, Flaviu; Roschanski, Anna M.; Zhelev, Peter; Fady, Bruno; Vendramin, Giovanni Giuseppe

    2016-01-01

    Background Local adaptation is a key driver of phenotypic and genetic divergence at loci responsible for adaptive traits variations in forest tree populations. Its experimental assessment requires rigorous sampling strategies such as those involving population pairs replicated across broad spatial scales. Methods A hierarchical Bayesian model of selection (HBM) that explicitly considers both the replication of the environmental contrast and the hierarchical genetic structure among replicated study sites is introduced. Its power was assessed through simulations and compared to classical ‘within-site’ approaches (FDIST, BAYESCAN) and a simplified, within-site, version of the model introduced here (SBM). Results HBM demonstrates that hierarchical approaches are very powerful to detect replicated patterns of adaptive divergence with low false-discovery (FDR) and false-non-discovery (FNR) rates compared to the analysis of different sites separately through within-site approaches. The hypothesis of local adaptation to altitude was further addressed by analyzing replicated Abies alba population pairs (low and high elevations) across the species’ southern distribution range, where the effects of climatic selection are expected to be the strongest. For comparison, a single population pair from the closely related species A. cephalonica was also analyzed. The hierarchical model did not detect any pattern of adaptive divergence to altitude replicated in the different study sites. Instead, idiosyncratic patterns of local adaptation among sites were detected by within-site approaches. Conclusion Hierarchical approaches may miss idiosyncratic patterns of adaptation among sites, and we strongly recommend the use of both hierarchical (multi-site) and classical (within-site) approaches when addressing the question of adaptation across broad spatial scales. PMID:27392065

  20. Contrast enhancement in microscopy of human thyroid tumors by means of acousto-optic adaptive spatial filtering

    NASA Astrophysics Data System (ADS)

    Yushkov, Konstantin B.; Molchanov, Vladimir Y.; Belousov, Pavel V.; Abrosimov, Aleksander Y.

    2016-01-01

    We report a method for edge enhancement in the images of transparent samples using analog image processing in coherent light. The experimental technique is based on adaptive spatial filtering with an acousto-optic tunable filter in a telecentric optical system. We demonstrate processing of microscopic images of unstained and stained histological sections of human thyroid tumor with improved contrast.

  1. Adaptive spatial filtering for off-axis digital holographic microscopy based on region recognition approach with iterative thresholding

    NASA Astrophysics Data System (ADS)

    He, Xuefei; Nguyen, Chuong Vinh; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R.; Rug, Melanie; Maier, Alexander G.; Lee, Woei Ming

    2016-12-01

    Here we propose a region-recognition approach with iterative thresholding, which is adaptively tailored to extract the appropriate region or shape of spatial frequency. In order to justify the method, we tested it with different samples and imaging conditions (different objectives). We demonstrate that our method provides a useful method for rapid imaging of cellular dynamics in microfluidic and cell cultures.

  2. Spatially adaptive block-based super-resolution.

    PubMed

    Su, Heng; Tang, Liang; Wu, Ying; Tretter, Daniel; Zhou, Jie

    2012-03-01

    Super-resolution technology provides an effective way to increase image resolution by incorporating additional information from successive input images or training samples. Various super-resolution algorithms have been proposed based on different assumptions, and their relative performances can differ in regions of different characteristics within a single image. Based on this observation, an adaptive algorithm is proposed in this paper to integrate a higher level image classification task and a lower level super-resolution process, in which we incorporate reconstruction-based super-resolution algorithms, single-image enhancement, and image/video classification into a single comprehensive framework. The target high-resolution image plane is divided into adaptive-sized blocks, and different suitable super-resolution algorithms are automatically selected for the blocks. Then, a deblocking process is applied to reduce block edge artifacts. A new benchmark is also utilized to measure the performance of super-resolution algorithms. Experimental results with real-life videos indicate encouraging improvements with our method.

  3. Adaptive Sampling of Time Series During Remote Exploration

    NASA Technical Reports Server (NTRS)

    Thompson, David R.

    2012-01-01

    This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models

  4. Distributed database kriging for adaptive sampling (D²KAS)

    DOE PAGES

    Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; ...

    2015-03-18

    We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our predictionmore » scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.« less

  5. Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data.

    PubMed

    Liu, Zitao; Hauskrecht, Milos

    2016-02-01

    Building accurate predictive models of clinical multivariate time series is crucial for understanding of the patient condition, the dynamics of a disease, and clinical decision making. A challenging aspect of this process is that the model should be flexible and adaptive to reflect well patient-specific temporal behaviors and this also in the case when the available patient-specific data are sparse and short span. To address this problem we propose and develop an adaptive two-stage forecasting approach for modeling multivariate, irregularly sampled clinical time series of varying lengths. The proposed model (1) learns the population trend from a collection of time series for past patients; (2) captures individual-specific short-term multivariate variability; and (3) adapts by automatically adjusting its predictions based on new observations. The proposed forecasting model is evaluated on a real-world clinical time series dataset. The results demonstrate the benefits of our approach on the prediction tasks for multivariate, irregularly sampled clinical time series, and show that it can outperform both the population based and patient-specific time series prediction models in terms of prediction accuracy.

  6. Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2016-01-01

    Building accurate predictive models of clinical multivariate time series is crucial for understanding of the patient condition, the dynamics of a disease, and clinical decision making. A challenging aspect of this process is that the model should be flexible and adaptive to reflect well patient-specific temporal behaviors and this also in the case when the available patient-specific data are sparse and short span. To address this problem we propose and develop an adaptive two-stage forecasting approach for modeling multivariate, irregularly sampled clinical time series of varying lengths. The proposed model (1) learns the population trend from a collection of time series for past patients; (2) captures individual-specific short-term multivariate variability; and (3) adapts by automatically adjusting its predictions based on new observations. The proposed forecasting model is evaluated on a real-world clinical time series dataset. The results demonstrate the benefits of our approach on the prediction tasks for multivariate, irregularly sampled clinical time series, and show that it can outperform both the population based and patient-specific time series prediction models in terms of prediction accuracy. PMID:27525189

  7. Distributed Database Kriging for Adaptive Sampling (D2 KAS)

    NASA Astrophysics Data System (ADS)

    Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; Rouet-Leduc, Bertrand; McPherson, Allen L.; Germann, Timothy C.; Junghans, Christoph

    2015-07-01

    We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our prediction scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5-25, while retaining high accuracy for various choices of the algorithm parameters.

  8. Distributed database kriging for adaptive sampling (D²KAS)

    SciTech Connect

    Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; Rouet-Leduc, Bertrand; McPherson, Allen L.; Germann, Timothy C.; Junghans, Christoph

    2015-03-18

    We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our prediction scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.

  9. Adaptive sampling for learning gaussian processes using mobile sensor networks.

    PubMed

    Xu, Yunfei; Choi, Jongeun

    2011-01-01

    This paper presents a novel class of self-organizing sensing agents that adaptively learn an anisotropic, spatio-temporal gaussian process using noisy measurements and move in order to improve the quality of the estimated covariance function. This approach is based on a class of anisotropic covariance functions of gaussian processes introduced to model a broad range of spatio-temporal physical phenomena. The covariance function is assumed to be unknown a priori. Hence, it is estimated by the maximum a posteriori probability (MAP) estimator. The prediction of the field of interest is then obtained based on the MAP estimate of the covariance function. An optimal sampling strategy is proposed to minimize the information-theoretic cost function of the Fisher Information Matrix. Simulation results demonstrate the effectiveness and the adaptability of the proposed scheme.

  10. Improving Wang-Landau sampling with adaptive windows.

    PubMed

    Cunha-Netto, A G; Caparica, A A; Tsai, Shan-Ho; Dickman, Ronald; Landau, D P

    2008-11-01

    Wang-Landau sampling (WLS) of large systems requires dividing the energy range into "windows" and joining the results of simulations in each window. The resulting density of states (and associated thermodynamic functions) is shown to suffer from boundary effects in simulations of lattice polymers and the five-state Potts model. Here, we implement WLS using adaptive windows. Instead of defining fixed energy windows (or windows in the energy-magnetization plane for the Potts model), the boundary positions depend on the set of energy values on which the histogram is flat at a given stage of the simulation. Shifting the windows each time the modification factor f is reduced, we eliminate border effects that arise in simulations using fixed windows. Adaptive windows extend significantly the range of system sizes that may be studied reliably using WLS.

  11. Improving Wang-Landau sampling with adaptive windows

    NASA Astrophysics Data System (ADS)

    Cunha-Netto, A. G.; Caparica, A. A.; Tsai, Shan-Ho; Dickman, Ronald; Landau, D. P.

    2008-11-01

    Wang-Landau sampling (WLS) of large systems requires dividing the energy range into “windows” and joining the results of simulations in each window. The resulting density of states (and associated thermodynamic functions) is shown to suffer from boundary effects in simulations of lattice polymers and the five-state Potts model. Here, we implement WLS using adaptive windows. Instead of defining fixed energy windows (or windows in the energy-magnetization plane for the Potts model), the boundary positions depend on the set of energy values on which the histogram is flat at a given stage of the simulation. Shifting the windows each time the modification factor f is reduced, we eliminate border effects that arise in simulations using fixed windows. Adaptive windows extend significantly the range of system sizes that may be studied reliably using WLS.

  12. Adaptive Sampling for Learning Gaussian Processes Using Mobile Sensor Networks

    PubMed Central

    Xu, Yunfei; Choi, Jongeun

    2011-01-01

    This paper presents a novel class of self-organizing sensing agents that adaptively learn an anisotropic, spatio-temporal Gaussian process using noisy measurements and move in order to improve the quality of the estimated covariance function. This approach is based on a class of anisotropic covariance functions of Gaussian processes introduced to model a broad range of spatio-temporal physical phenomena. The covariance function is assumed to be unknown a priori. Hence, it is estimated by the maximum a posteriori probability (MAP) estimator. The prediction of the field of interest is then obtained based on the MAP estimate of the covariance function. An optimal sampling strategy is proposed to minimize the information-theoretic cost function of the Fisher Information Matrix. Simulation results demonstrate the effectiveness and the adaptability of the proposed scheme. PMID:22163785

  13. Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

    PubMed

    Liu, Dong; Wang, Shengsheng; Huang, Dezhi; Deng, Gang; Zeng, Fantao; Chen, Huiling

    2016-05-01

    Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches.

  14. Flicker adaptation or superimposition raises the apparent spatial frequency of coarse test gratings.

    PubMed

    Kaneko, Sae; Giaschi, Deborah; Anstis, Stuart

    2015-03-01

    Independent channels respond to both the spatial and temporal characteristics of visual stimuli. Gratings <3 cycles per degree (cpd) are sensed by transient channels that prefer intermittent stimulation, while gratings >3 cpd are sensed by sustained channels that prefer steady stimulation. From this we predict that adaptation to a spatially uniform flickering field will selectively adapt the transient channels and raise the apparent spatial frequency of coarse sinusoidal gratings. Observers adapted to a spatially uniform field whose upper or lower half was steady and whose other half was flickering. They then adjusted the spatial frequency of a stationary test (matching) grating on the previously unmodulated half field until it matched the apparent spatial frequency of a grating falling on the previously flickering half field. The adapting field flickered at 8 Hz and the spatial frequency of the gratings was varied in octave steps from 0.25 to 16 cpd. As predicted, adapting to flicker raised the apparent spatial frequency of the test gratings. The aftereffect reached a peak of 11% between 0.5 and 1 cpd and disappeared above 4 cpd. We also observed that superimposed 10 Hz luminance flicker raised the apparent spatial frequency of 0.5 cpd test gratings. The effect was not seen with slower flicker or finer test gratings. Altogether, our study suggests that apparent spatial frequency is determined by the balance between transient and sustained channels and that an imbalance between the channels caused by flicker can alter spatial frequency perception.

  15. The Lyman alpha reference sample. VII. Spatially resolved Hα kinematics

    NASA Astrophysics Data System (ADS)

    Herenz, Edmund Christian; Gruyters, Pieter; Orlitova, Ivana; Hayes, Matthew; Östlin, Göran; Cannon, John M.; Roth, Martin M.; Bik, Arjan; Pardy, Stephen; Otí-Floranes, Héctor; Mas-Hesse, J. Miguel; Adamo, Angela; Atek, Hakim; Duval, Florent; Guaita, Lucia; Kunth, Daniel; Laursen, Peter; Melinder, Jens; Puschnig, Johannes; Rivera-Thorsen, Thøger E.; Schaerer, Daniel; Verhamme, Anne

    2016-03-01

    We present integral field spectroscopic observations with the Potsdam Multi-Aperture Spectrophotometer of all 14 galaxies in the z ~ 0.1 Lyman Alpha Reference Sample (LARS). We produce 2D line-of-sight velocity maps and velocity dispersion maps from the Balmer α (Hα) emission in our data cubes. These maps trace the spectral and spatial properties of the LARS galaxies' intrinsic Lyα radiation field. We show our kinematic maps that are spatially registered onto the Hubble Space Telescope Hα and Lyman α (Lyα) images. We can conjecture a causal connection between spatially resolved Hα kinematics and Lyα photometry for individual galaxies, however, no general trend can be established for the whole sample. Furthermore, we compute the intrinsic velocity dispersion σ0, the shearing velocity vshear, and the vshear/σ0 ratio from our kinematic maps. In general LARS galaxies are characterised by high intrinsic velocity dispersions (54 km s-1 median) and low shearing velocities (65 km s-1 median). The vshear/σ0 values range from 0.5 to 3.2 with an average of 1.5. It is noteworthy that five galaxies of the sample are dispersion-dominated systems with vshear/σ0< 1, and are thus kinematically similar to turbulent star-forming galaxies seen at high redshift. When linking our kinematical statistics to the global LARS Lyα properties, we find that dispersion-dominated systems show higher Lyα equivalent widths and higher Lyα escape fractions than systems with vshear/σ0> 1. Our result indicates that turbulence in actively star-forming systems is causally connected to interstellar medium conditions that favour an escape of Lyα radiation. Based on observations collected at the Centro Astronómico Hispano Alemán (CAHA) at Calar Alto, operated jointly by the Max-Planck Institut für Astronomie and the Instituto de Astrofísica de Andalucía (CSIC).The reduced data cubes (FITS files) are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130

  16. Effect of imperfect detectability on adaptive and conventional sampling: Simulated sampling of freshwater mussels in the upper Mississippi River

    USGS Publications Warehouse

    Smith, D.R.; Gray, B.R.; Newton, T.J.; Nichols, D.

    2010-01-01

    Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.

  17. Effect of imperfect detectability on adaptive and conventional sampling: simulated sampling of freshwater mussels in the upper Mississippi River.

    PubMed

    Smith, David R; Gray, Brian R; Newton, Teresa J; Nichols, Doug

    2010-11-01

    Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.

  18. Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

    NASA Technical Reports Server (NTRS)

    Grace, Joseph M.; Verseux, Cyprien; Gentry, Diana; Moffet, Amy; Thayabaran, Ramanen; Wong, Nathan; Rothschild, Lynn

    2013-01-01

    The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the

  19. Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

    NASA Astrophysics Data System (ADS)

    Grace, J. M.; Verseux, C.; Gentry, D.; Moffet, A.; Thayabaran, R.; Wong, N.; Rothschild, L.

    2013-12-01

    The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates[Wielgoss et al., 2013]. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques[Wassmann et al., 2010]. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols[Alcántara-Díaz et al., 2004; Goldman and Travisano, 2011]. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of

  20. Robust online tracking via adaptive samples selection with saliency detection

    NASA Astrophysics Data System (ADS)

    Yan, Jia; Chen, Xi; Zhu, QiuPing

    2013-12-01

    Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

  1. Divide sampling-based hybrid temporal-spatial prediction coding for H.264/AVC

    NASA Astrophysics Data System (ADS)

    Li, Hongwei; Song, Rui; Wu, Chengke; Zhang, Jie

    2011-11-01

    A divide sampling-based hybrid temporal-spatial prediction coding algorithm is designed to further improve the coding performance of the conventional H.264/AVC coding. In the proposed algorithm, a frame is first divided into four equal-sized subframes, and the first subframe is coded using the rate distortion optimization model with inter- or intraprediction adaptively. Then, the optimal prediction method of the macroblock in other subframes is selected flexibly and reasonably from intraprediction, the fast interprediction, and the spatial interpolation prediction. The simulation results show that compared with the conventional H.264/AVC coding, the average bit rate is reduced by 6.15% under the same peak signal-to-noise ratio (PSNR), the average PSNR is increased by 0.22 dB under the same bit rate, and the average coding time is saved by 12.40% in the proposed algorithm.

  2. Spatial analysis of NDVI readings with difference sampling density

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Advanced remote sensing technologies provide research an innovative way of collecting spatial data for use in precision agriculture. Sensor information and spatial analysis together allow for a complete understanding of the spatial complexity of a field and its crop. The objective of the study was...

  3. Structured estimation - Sample size reduction for adaptive pattern classification

    NASA Technical Reports Server (NTRS)

    Morgera, S.; Cooper, D. B.

    1977-01-01

    The Gaussian two-category classification problem with known category mean value vectors and identical but unknown category covariance matrices is considered. The weight vector depends on the unknown common covariance matrix, so the procedure is to estimate the covariance matrix in order to obtain an estimate of the optimum weight vector. The measure of performance for the adapted classifier is the output signal-to-interference noise ratio (SIR). A simple approximation for the expected SIR is gained by using the general sample covariance matrix estimator; this performance is both signal and true covariance matrix independent. An approximation is also found for the expected SIR obtained by using a Toeplitz form covariance matrix estimator; this performance is found to be dependent on both the signal and the true covariance matrix.

  4. Image classification with densely sampled image windows and generalized adaptive multiple kernel learning.

    PubMed

    Yan, Shengye; Xu, Xinxing; Xu, Dong; Lin, Stephen; Li, Xuelong

    2015-03-01

    We present a framework for image classification that extends beyond the window sampling of fixed spatial pyramids and is supported by a new learning algorithm. Based on the observation that fixed spatial pyramids sample a rather limited subset of the possible image windows, we propose a method that accounts for a comprehensive set of windows densely sampled over location, size, and aspect ratio. A concise high-level image feature is derived to effectively deal with this large set of windows, and this higher level of abstraction offers both efficient handling of the dense samples and reduced sensitivity to misalignment. In addition to dense window sampling, we introduce generalized adaptive l(p)-norm multiple kernel learning (GA-MKL) to learn a robust classifier based on multiple base kernels constructed from the new image features and multiple sets of prelearned classifiers from other classes. With GA-MKL, multiple levels of image features are effectively fused, and information is shared among different classifiers. Extensive evaluation on benchmark datasets for object recognition (Caltech256 and Caltech101) and scene recognition (15Scenes) demonstrate that the proposed method outperforms the state-of-the-art under a broad range of settings.

  5. A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile.

    PubMed

    Inostroza, Luis; Palme, Massimo; de la Barrera, Francisco

    2016-01-01

    Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

  6. Spatial frequency-specific contrast adaptation originates in the primary visual cortex.

    PubMed

    Duong, Thang; Freeman, Ralph D

    2007-07-01

    Adaptation to a high-contrast grating stimulus causes reduced sensitivity to subsequent presentation of a visual stimulus with similar spatial characteristics. This behavioral finding has been attributed by neurophysiological studies to processes within the visual cortex. However, some evidence indicates that contrast adaptation phenomena are also found in early visual pathways. Adaptation effects have been reported in retina and lateral geniculation nucleus (LGN). It is possible that these early pathways could be the physiological origin of the cortical adaptation effect. To study this, we recorded from single neurons in the cat's LGN. We find that contrast adaptation in the LGN, unlike that in the visual cortex, is not spatial frequency specific, i.e., adaptation effects apply to a broad range of spatial frequencies. In addition, aside from the amplitude attenuation, the shape of spatial frequency tuning curves of LGN cells is not affected by contrast adaptation. Again, these findings are unlike those found for cells in the visual cortex. Together, these results demonstrate that pattern specific contrast adaptation is a cortical process.

  7. Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

    NASA Technical Reports Server (NTRS)

    Wang, Ray (Inventor)

    2009-01-01

    A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

  8. Development of Climate Change Adaptation Platform using Spatial Information

    NASA Astrophysics Data System (ADS)

    Lee, J.; Oh, K. Y.; Lee, M. J.; Han, W. J.

    2014-12-01

    Climate change adaptation has attracted growing attention with the recent extreme weather conditions that affect people around the world. More and more countries, including the Republic of Korea, have begun to hatch adaptation plan to resolve these matters of great concern. They all, meanwhile, have mentioned that it should come first to integrate climate information in all analysed areas. That's because climate information is not independently made through one source; that is to say, the climate information is connected one another in a complicated way. That is the reason why we have to promote integrated climate change adaptation platform before setting up climate change adaptation plan. Therefore, the large-scaled project has been actively launched and worked on. To date, we researched 620 literatures and interviewed 51 government organizations. Based on the results of the researches and interviews, we obtained 2,725 impacts about vulnerability assessment information such as Monitoring and Forecasting, Health, Disaster, Agriculture, Forest, Water Management, Ecosystem, Ocean/Fisheries, Industry/Energy. Among 2,725 impacts, 995 impacts are made into a database until now. This database is made up 3 sub categories like Climate-Exposure, Sensitivity, Adaptive capacity, presented by IPCC. Based on the constructed database, vulnerability assessments were carried out in order to evaluate climate change capacity of local governments all over the country. These assessments were conducted by using web-based vulnerability assessment tool which was newly developed through this project. These results have shown that, metropolitan areas like Seoul, Pusan, Inchon, and so on have high risks more than twice than rural areas. Acknowledgements: The authors appreciate the support that this study has received from "Development of integrated model for climate change impact and vulnerability assessment and strengthening the framework for model implementation ", an initiative of the

  9. COST-EFFECTIVE SAMPLING FOR SPATIALLY DISTRIBUTED PHENOMENA

    EPA Science Inventory

    Various measures of sampling plan cost and loss are developed and analyzed as they relate to a variety of multidisciplinary sampling techniques. The sampling choices examined include methods from design-based sampling, model-based sampling, and geostatistics. Graphs and tables ar...

  10. Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

    USGS Publications Warehouse

    Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

    2011-01-01

    Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

  11. Research on test of product based on spatial sampling criteria and variable step sampling mechanism

    NASA Astrophysics Data System (ADS)

    Li, Ruihong; Han, Yueping

    2014-09-01

    This paper presents an effective approach for online testing the assembly structures inside products using multiple views technique and X-ray digital radiography system based on spatial sampling criteria and variable step sampling mechanism. Although there are some objects inside one product to be tested, there must be a maximal rotary step for an object within which the least structural size to be tested is predictable. In offline learning process, Rotating the object by the step and imaging it and so on until a complete cycle is completed, an image sequence is obtained that includes the full structural information for recognition. The maximal rotary step is restricted by the least structural size and the inherent resolution of the imaging system. During online inspection process, the program firstly finds the optimum solutions to all different target parts in the standard sequence, i.e., finds their exact angles in one cycle. Aiming at the issue of most sizes of other targets in product are larger than that of the least structure, the paper adopts variable step-size sampling mechanism to rotate the product specific angles with different steps according to different objects inside the product and match. Experimental results show that the variable step-size method can greatly save time compared with the traditional fixed-step inspection method while the recognition accuracy is guaranteed.

  12. Preflight Adaptation Training for Spatial Orientation and Space Motion Sickness

    NASA Technical Reports Server (NTRS)

    Harm, Deborah L.; Parker, Donald E.

    1994-01-01

    Two part-task preflight adaptation trainers (PATs) are being developed at the NASA Johnson Space Center to preadapt astronauts to novel sensory stimulus conditions similar to those present in microgravity to facilitate adaptation to microgravity and readaptation to Earth. This activity is a major component of a general effort to develop countermeasures aimed at minimizing sensory and sensorimotor disturbances and Space Motion Sickness (SMS) associated with adaptation to microgravity and readaptation to Earth. Design principles for the development of the two trainers are discussed, along with a detailed description of both devices. In addition, a summary of four ground-based investigations using one of the trainers to determine the extent to which various novel sensory stimulus conditions produce changes in compensatory eye movement responses, postural equilibrium, motion sickness symptoms, and electrogastric responses are presented. Finally, a brief description of the general concept of dual-adopted states that underly the development of the PATs, and ongoing and future operational and basic research activities are presented.

  13. High-resolution in-depth imaging of optically cleared thick samples using an adaptive SPIM

    PubMed Central

    Masson, Aurore; Escande, Paul; Frongia, Céline; Clouvel, Grégory; Ducommun, Bernard; Lorenzo, Corinne

    2015-01-01

    Today, Light Sheet Fluorescence Microscopy (LSFM) makes it possible to image fluorescent samples through depths of several hundreds of microns. However, LSFM also suffers from scattering, absorption and optical aberrations. Spatial variations in the refractive index inside the samples cause major changes to the light path resulting in loss of signal and contrast in the deepest regions, thus impairing in-depth imaging capability. These effects are particularly marked when inhomogeneous, complex biological samples are under study. Recently, chemical treatments have been developed to render a sample transparent by homogenizing its refractive index (RI), consequently enabling a reduction of scattering phenomena and a simplification of optical aberration patterns. One drawback of these methods is that the resulting RI of cleared samples does not match the working RI medium generally used for LSFM lenses. This RI mismatch leads to the presence of low-order aberrations and therefore to a significant degradation of image quality. In this paper, we introduce an original optical-chemical combined method based on an adaptive SPIM and a water-based clearing protocol enabling compensation for aberrations arising from RI mismatches induced by optical clearing methods and acquisition of high-resolution in-depth images of optically cleared complex thick samples such as Multi-Cellular Tumour Spheroids. PMID:26576666

  14. High-resolution in-depth imaging of optically cleared thick samples using an adaptive SPIM

    NASA Astrophysics Data System (ADS)

    Masson, Aurore; Escande, Paul; Frongia, Céline; Clouvel, Grégory; Ducommun, Bernard; Lorenzo, Corinne

    2015-11-01

    Today, Light Sheet Fluorescence Microscopy (LSFM) makes it possible to image fluorescent samples through depths of several hundreds of microns. However, LSFM also suffers from scattering, absorption and optical aberrations. Spatial variations in the refractive index inside the samples cause major changes to the light path resulting in loss of signal and contrast in the deepest regions, thus impairing in-depth imaging capability. These effects are particularly marked when inhomogeneous, complex biological samples are under study. Recently, chemical treatments have been developed to render a sample transparent by homogenizing its refractive index (RI), consequently enabling a reduction of scattering phenomena and a simplification of optical aberration patterns. One drawback of these methods is that the resulting RI of cleared samples does not match the working RI medium generally used for LSFM lenses. This RI mismatch leads to the presence of low-order aberrations and therefore to a significant degradation of image quality. In this paper, we introduce an original optical-chemical combined method based on an adaptive SPIM and a water-based clearing protocol enabling compensation for aberrations arising from RI mismatches induced by optical clearing methods and acquisition of high-resolution in-depth images of optically cleared complex thick samples such as Multi-Cellular Tumour Spheroids.

  15. Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

    USGS Publications Warehouse

    Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

    2011-01-01

    designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

  16. Presence of Motor-Intentional Aiming Deficit Predicts Functional Improvement of Spatial Neglect with Prism Adaptation

    PubMed Central

    Goedert, Kelly M.; Chen, Peii; Boston, Raymond C.; Foundas, Anne L.; Barrett, A. M.

    2013-01-01

    Spatial neglect is a debilitating disorder for which there is no agreed upon course of rehabilitation. The lack of consensus on treatment may result from systematic differences in the syndromes’ characteristics, with spatial cognitive deficits potentially affecting perceptual-attentional Where or motor-intentional Aiming spatial processing. Heterogeneity of response to treatment might be explained by different treatment impact on these dissociated deficits: prism adaptation, for example, might reduce Aiming deficits without affecting Where spatial deficits. Here, we tested the hypothesis that classifying patients by their profile of Where-vs-Aiming spatial deficit would predict response to prism adaptation, and specifically that patients with Aiming bias would have better recovery than those with isolated Where bias. We classified the spatial errors of 24 sub-acute right-stroke survivors with left spatial neglect as: 1) isolated Where bias, 2) isolated Aiming bias or 3) both. Participants then completed two weeks of prism adaptation treatment. They also completed the Behavioral Inattention Test (BIT) and Catherine Bergego Scale (CBS) tests of neglect recovery weekly for six weeks. As hypothesized, participants with only Aiming deficits improved on the CBS, whereas, those with only Where deficits did not improve. Participants with both deficits demonstrated intermediate improvement. These results support behavioral classification of spatial neglect patients as a potential valuable tool for assigning targeted, effective early rehabilitation. PMID:24376064

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

    PubMed

    Fox, Jeremy W; Harder, Lawrence D

    2015-01-01

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

  18. Sparse sampling: Spatial design for monitoring stream networks

    EPA Science Inventory

    Spatial designs for monitoring stream networks, especially ephemeral systems, are typically non-standard, ‘sparse’ and can be very complex, reflecting the complexity of the ecosystem being monitored, the scale of the population, and the competing multiple monitoring objectives. ...

  19. An R package for spatial coverage sampling and random sampling from compact geographical strata by k-means

    NASA Astrophysics Data System (ADS)

    Walvoort, D. J. J.; Brus, D. J.; de Gruijter, J. J.

    2010-10-01

    Both for mapping and for estimating spatial means of an environmental variable, the accuracy of the result will usually be increased by dispersing the sample locations so that they cover the study area as uniformly as possible. We developed a new R package for designing spatial coverage samples for mapping, and for random sampling from compact geographical strata for estimating spatial means. The mean squared shortest distance (MSSD) was chosen as objective function, which can be minimized by k-means clustering. Two k-means algorithms are described, one for unequal area and one for equal area partitioning. The R package is illustrated with three examples: (1) subsampling of square and circular sampling plots commonly used in surveys of soil, vegetation, forest, etc.; (2) sampling of agricultural fields for soil testing; and (3) infill sampling of climate stations for mainland Australia and Tasmania. The algorithms give satisfactory results within reasonable computing time.

  20. Optimal sampling design for estimating spatial distribution and abundance of a freshwater mussel population

    USGS Publications Warehouse

    Pooler, P.S.; Smith, D.R.

    2005-01-01

    We compared the ability of simple random sampling (SRS) and a variety of systematic sampling (SYS) designs to estimate abundance, quantify spatial clustering, and predict spatial distribution of freshwater mussels. Sampling simulations were conducted using data obtained from a census of freshwater mussels in a 40 X 33 m section of the Cacapon River near Capon Bridge, West Virginia, and from a simulated spatially random population generated to have the same abundance as the real population. Sampling units that were 0.25 m 2 gave more accurate and precise abundance estimates and generally better spatial predictions than 1-m2 sampling units. Systematic sampling with ???2 random starts was more efficient than SRS. Estimates of abundance based on SYS were more accurate when the distance between sampling units across the stream was less than or equal to the distance between sampling units along the stream. Three measures for quantifying spatial clustering were examined: Hopkins Statistic, the Clumping Index, and Morisita's Index. Morisita's Index was the most reliable, and the Hopkins Statistic was prone to false rejection of complete spatial randomness. SYS designs with units spaced equally across and up stream provided the most accurate predictions when estimating the spatial distribution by kriging. Our research indicates that SYS designs with sampling units equally spaced both across and along the stream would be appropriate for sampling freshwater mussels even if no information about the true underlying spatial distribution of the population were available to guide the design choice. ?? 2005 by The North American Benthological Society.

  1. Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi

    PubMed Central

    Chipeta, Michael G.; McCann, Robert S.; Phiri, Kamija S.; van Vugt, Michèle; Takken, Willem; Diggle, Peter; Terlouw, Anja D.

    2017-01-01

    Introduction In the context of malaria elimination, interventions will need to target high burden areas to further reduce transmission. Current tools to monitor and report disease burden lack the capacity to continuously detect fine-scale spatial and temporal variations of disease distribution exhibited by malaria. These tools use random sampling techniques that are inefficient for capturing underlying heterogeneity while health facility data in resource-limited settings are inaccurate. Continuous community surveys of malaria burden provide real-time results of local spatio-temporal variation. Adaptive geostatistical design (AGD) improves prediction of outcome of interest compared to current random sampling techniques. We present findings of continuous malaria prevalence surveys using an adaptive sampling design. Methods We conducted repeated cross sectional surveys guided by an adaptive sampling design to monitor the prevalence of malaria parasitaemia and anaemia in children below five years old in the communities living around Majete Wildlife Reserve in Chikwawa district, Southern Malawi. AGD sampling uses previously collected data to sample new locations of high prediction variance or, where prediction exceeds a set threshold. We fitted a geostatistical model to predict malaria prevalence in the area. Findings We conducted five rounds of sampling, and tested 876 children aged 6–59 months from 1377 households over a 12-month period. Malaria prevalence prediction maps showed spatial heterogeneity and presence of hotspots—where predicted malaria prevalence was above 30%; predictors of malaria included age, socio-economic status and ownership of insecticide-treated mosquito nets. Conclusions Continuous malaria prevalence surveys using adaptive sampling increased malaria prevalence prediction accuracy. Results from the surveys were readily available after data collection. The tool can assist local managers to target malaria control interventions in areas with the

  2. A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile

    PubMed Central

    Palme, Massimo; de la Barrera, Francisco

    2016-01-01

    Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making. PMID:27606592

  3. Experiments with central-limit properties of spatial samples from locally covariant random fields

    USGS Publications Warehouse

    Barringer, T.H.; Smith, T.E.

    1992-01-01

    When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

  4. Stabilizing Spatially-Structured Populations through Adaptive Limiter Control

    PubMed Central

    Sah, Pratha; Dey, Sutirth

    2014-01-01

    Stabilizing the dynamics of complex, non-linear systems is a major concern across several scientific disciplines including ecology and conservation biology. Unfortunately, most methods proposed to reduce the fluctuations in chaotic systems are not applicable to real, biological populations. This is because such methods typically require detailed knowledge of system specific parameters and the ability to manipulate them in real time; conditions often not met by most real populations. Moreover, real populations are often noisy and extinction-prone, which can sometimes render such methods ineffective. Here, we investigate a control strategy, which works by perturbing the population size, and is robust to reasonable amounts of noise and extinction probability. This strategy, called the Adaptive Limiter Control (ALC), has been previously shown to increase constancy and persistence of laboratory populations and metapopulations of Drosophila melanogaster. Here, we present a detailed numerical investigation of the effects of ALC on the fluctuations and persistence of metapopulations. We show that at high migration rates, application of ALC does not require a priori information about the population growth rates. We also show that ALC can stabilize metapopulations even when applied to as low as one-tenth of the total number of subpopulations. Moreover, ALC is effective even when the subpopulations have high extinction rates: conditions under which another control algorithm had previously failed to attain stability. Importantly, ALC not only reduces the fluctuation in metapopulation sizes, but also the global extinction probability. Finally, the method is robust to moderate levels of noise in the dynamics and the carrying capacity of the environment. These results, coupled with our earlier empirical findings, establish ALC to be a strong candidate for stabilizing real biological metapopulations. PMID:25153073

  5. Reversible wavelet filter banks with side informationless spatially adaptive low-pass filters

    NASA Astrophysics Data System (ADS)

    Abhayaratne, Charith

    2011-07-01

    Wavelet transforms that have an adaptive low-pass filter are useful in applications that require the signal singularities, sharp transitions, and image edges to be left intact in the low-pass signal. In scalable image coding, the spatial resolution scalability is achieved by reconstructing the low-pass signal subband, which corresponds to the desired resolution level, and discarding other high-frequency wavelet subbands. In such applications, it is vital to have low-pass subbands that are not affected by smoothing artifacts associated with low-pass filtering. We present the mathematical framework for achieving 1-D wavelet transforms that have a spatially adaptive low-pass filter (SALP) using the prediction-first lifting scheme. The adaptivity decisions are computed using the wavelet coefficients, and no bookkeeping is required for the perfect reconstruction. Then, 2-D wavelet transforms that have a spatially adaptive low-pass filter are designed by extending the 1-D SALP framework. Because the 2-D polyphase decompositions are used in this case, the 2-D adaptivity decisions are made nonseparable as opposed to the separable 2-D realization using 1-D transforms. We present examples using the 2-D 5/3 wavelet transform and their lossless image coding and scalable decoding performances in terms of quality and resolution scalability. The proposed 2-D-SALP scheme results in better performance compared to the existing adaptive update lifting schemes.

  6. Principle and application of high density spatial sampling in seismic migration

    NASA Astrophysics Data System (ADS)

    Li, Zi-Shun

    2012-06-01

    To avoid spatial aliasing problems in broad band high resolution seismic sections, I present a high density migration processing solution. I first analyze the spatial aliasing definition for stack and migration seismic sections and point out the differences between the two. We recognize that migration sections more often show spatial aliasing than stacked sections. Second, from wave propagation theory, I know that migration output is a new spatial sampling process and seismic prestack time migration can provide the high density sampling to prevent spatial aliasing on high resolution migration sections. Using a 2D seismic forward modeling analysis, I have found that seismic spatial aliasing noise can be eliminated by high density spatial sampling in prestack migration. In a 3D seismic data study for Daqing Oilfield in the Songliao Basin, I have also found that seismic sections obtained by high-density spatial sampling (10 × 10 m) in prestack migration have less spatial aliasing noise than those obtained by conventional low density spatial sampling (20 × 40 m) in prestack migration.

  7. Spatial-light-modulator-based adaptive optical system for the use of multiple phase retrieval methods.

    PubMed

    Lingel, Christian; Haist, Tobias; Osten, Wolfgang

    2016-12-20

    We propose an adaptive optical setup using a spatial light modulator (SLM), which is suitable to perform different phase retrieval methods with varying optical features and without mechanical movement. By this approach, it is possible to test many different phase retrieval methods and their parameters (optical and algorithmic) using one stable setup and without hardware adaption. We show exemplary results for the well-known transport of intensity equation (TIE) method and a new iterative adaptive phase retrieval method, where the object phase is canceled by an inverse phase written into part of the SLM. The measurement results are compared to white light interferometric measurements.

  8. An adaptive two-stage sequential design for sampling rare and clustered populations

    USGS Publications Warehouse

    Brown, J.A.; Salehi, M.M.; Moradi, M.; Bell, G.; Smith, D.R.

    2008-01-01

    How to design an efficient large-area survey continues to be an interesting question for ecologists. In sampling large areas, as is common in environmental studies, adaptive sampling can be efficient because it ensures survey effort is targeted to subareas of high interest. In two-stage sampling, higher density primary sample units are usually of more interest than lower density primary units when populations are rare and clustered. Two-stage sequential sampling has been suggested as a method for allocating second stage sample effort among primary units. Here, we suggest a modification: adaptive two-stage sequential sampling. In this method, the adaptive part of the allocation process means the design is more flexible in how much extra effort can be directed to higher-abundance primary units. We discuss how best to design an adaptive two-stage sequential sample. ?? 2008 The Society of Population Ecology and Springer.

  9. A Framework for Spatial Assessment of Local Level Vulnerability and Adaptive Capacity to Extreme Heat

    NASA Astrophysics Data System (ADS)

    Wilhelmi, O.; Hayden, M.; Harlan, S.; Ruddell, D.; Komatsu, K.; England, B.; Uejio, C.

    2008-12-01

    Changing climate is predicted to increase the intensity and impacts of heat waves prompting the need to develop preparedness and adaptation strategies that reduce societal vulnerability. Central to understanding societal vulnerability, is adaptive capacity, the potential of a system or population to modify its features/behaviors so as to better cope with existing and anticipated stresses and fluctuations. Adaptive capacity influences adaptation, the actual adjustments made to cope with the impacts from current and future hazardous heat events. Understanding societal risks, vulnerabilities and adaptive capacity to extreme heat events and climate change requires an interdisciplinary approach that includes information about weather and climate, the natural and built environment, social processes and characteristics, interactions with the stakeholders, and an assessment of community vulnerability. This project presents a framework for an interdisciplinary approach and a case study that explore linkages between quantitative and qualitative data for a more comprehensive understanding of local level vulnerability and adaptive capacity to extreme heat events in Phoenix, Arizona. In this talk, we will present a methodological framework for conducting collaborative research on societal vulnerability and adaptive capacity on a local level that includes integration of household surveys into a quantitative spatial assessment of societal vulnerability. We highlight a collaborative partnership among researchers, community leaders and public health officials. Linkages between assessment of local adaptive capacity and development of regional climate change adaptation strategies will be discussed.

  10. Adaptive Spatial Filtering with Principal Component Analysis for Biomedical Photoacoustic Imaging

    NASA Astrophysics Data System (ADS)

    Nagaoka, Ryo; Yamazaki, Rena; Saijo, Yoshifumi

    Photoacoustic (PA) signal is very sensitive to noise generated by peripheral equipment such as power supply, stepping motor or semiconductor laser. Band-pass filter is not effective because the frequency bandwidth of the PA signal also covers the noise frequency. The objective of the present study is to reduce the noise by using an adaptive spatial filter with principal component analysis (PCA).

  11. Adaptive Fraunhofer diffraction particle sizing instrument using a spatial light modulator.

    PubMed

    Hirleman, E D; Dellenback, P A

    1989-11-15

    Integration of a magnetooptic spatial light modulator into a Fraunhofer diffraction particle sizing instrument is proposed and demonstrated theoretically and experimentally. The concept gives the instrument the ability to reconfigure a detector array on-line and thereby adapt to the measurement context.

  12. Time-and-Spatially Adapting Simulations for Efficient Dynamic Stall Predictions

    DTIC Science & Technology

    2015-09-01

    SIMULATIONS FOR EFFICIENTDYNAMIC STALL PREDICTIONS The ability to accurately and efficiently predict the occurrence and severity of dynamic stall...The ability to accurately and efficiently predict the occurrence and severity of dynamic stall remains a major roadblock in the design and analysis...SPATIALLY ADAPTING SIMULATIONS FOR EFFICIENT DYNAMIC STALL PREDICTIONS Marilyn J. Smith Professor Georgia Tech Rohit Jain Aerospace Engineer US Army

  13. Multisensory adaptation of spatial-to-motor transformations in children with developmental coordination disorder.

    PubMed

    King, Bradley R; Kagerer, Florian A; Harring, Jeffrey R; Contreras-Vidal, Jose L; Clark, Jane E

    2011-07-01

    Recent research has demonstrated that adaptation to a visuomotor distortion systematically influenced movements to auditory targets in adults and typically developing (TD) children, suggesting that the adaptation of spatial-to-motor transformations for reaching movements is multisensory (i.e., generalizable across sensory modalities). The multisensory characteristics of these transformations in children with developmental coordination disorder (DCD) have not been examined. Given that previous research has demonstrated that children with DCD have deficits in sensorimotor integration, these children may also have impairments in the formation of multisensory spatial-to-motor transformations for target-directed arm movements. To investigate this hypothesis, children with and without DCD executed discrete arm movements to visual and acoustic targets prior to and following exposure to an abrupt visual feedback rotation. Results demonstrated that the magnitudes of the visual aftereffects were equivalent in the TD children and the children with DCD, indicating that both groups of children adapted similarly to the visuomotor perturbation. Moreover, the influence of visuomotor adaptation on auditory-motor performance was similar in the two groups of children. This suggests that the multisensory processes underlying adaptation of spatial-to-motor transformations are similar in children with DCD and TD children.

  14. Spatially intensive sampling by electrofishing for assessing longitudinal discontinuities in fish distribution in a headwater stream

    USGS Publications Warehouse

    Le Pichon, Céline; Tales, Évelyne; Belliard, Jérôme; Torgersen, Christian E.

    2017-01-01

    Spatially intensive sampling by electrofishing is proposed as a method for quantifying spatial variation in fish assemblages at multiple scales along extensive stream sections in headwater catchments. We used this method to sample fish species at 10-m2 points spaced every 20 m throughout 5 km of a headwater stream in France. The spatially intensive sampling design provided information at a spatial resolution and extent that enabled exploration of spatial heterogeneity in fish assemblage structure and aquatic habitat at multiple scales with empirical variograms and wavelet analysis. These analyses were effective for detecting scales of periodicity, trends, and discontinuities in the distribution of species in relation to tributary junctions and obstacles to fish movement. This approach to sampling riverine fishes may be useful in fisheries research and management for evaluating stream fish responses to natural and altered habitats and for identifying sites for potential restoration.

  15. Adaptive single replica multiple state transition interface sampling

    NASA Astrophysics Data System (ADS)

    Du, Wei-Na; Bolhuis, Peter G.

    2013-07-01

    The multiple state transition path sampling method allows sampling of rare transitions between many metastable states, but has the drawback that switching between qualitatively different pathways is difficult. Combination with replica exchange transition interface sampling can in principle alleviate this problem, but requires a large number of simultaneous replicas. Here we remove these drawbacks by introducing a single replica sampling algorithm that samples only one interface at a time, while efficiently walking through the entire path space using a Wang-Landau approach or, alternatively, a fixed bias. We illustrate the method on several model systems: a particle diffusing in a simple 2D potential, isomerization in a small Lennard Jones cluster, and isomerization of the alanine dipeptide in explicit water.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  17. POF-Darts: Geometric adaptive sampling for probability of failure

    SciTech Connect

    Ebeida, Mohamed S.; Mitchell, Scott A.; Swiler, Laura P.; Romero, Vicente J.; Rushdi, Ahmad A.

    2016-06-18

    We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink, improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.

  18. POF-Darts: Geometric adaptive sampling for probability of failure

    DOE PAGES

    Ebeida, Mohamed S.; Mitchell, Scott A.; Swiler, Laura P.; ...

    2016-06-18

    We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink,more » improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.« less

  19. Ensembles of adaptive spatial filters increase BCI performance: an online evaluation

    NASA Astrophysics Data System (ADS)

    Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin

    2016-08-01

    Objective: In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain-computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Approach: Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. Main results: The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. Significance: CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI

  20. Spatial variation in soil biota mediates plant adaptation to a foliar pathogen.

    PubMed

    Mursinoff, Sini; Tack, Ayco J M

    2017-01-02

    Theory suggests that below-ground spatial heterogeneity may mediate host-parasite evolutionary dynamics and patterns of local adaptation, but this has rarely been tested in natural systems. Here, we test experimentally for the impact of spatial variation in the abiotic and biotic soil environment on the evolutionary outcome of the interaction between the host plant Plantago lanceolata and its specialist foliar pathogen Podosphaera plantaginis. Plants showed no adaptation to the local soil environment in the absence of natural enemies. However, quantitative, but not qualitative, plant resistance against local pathogens was higher when plants were grown in their local field soil than when they were grown in nonlocal field soil. This pattern was robust when extending the spatial scale beyond a single region, but disappeared with soil sterilization, indicating that soil biota mediated plant adaptation. We conclude that below-ground biotic heterogeneity mediates above-ground patterns of plant adaptation, resulting in increased plant resistance when plants are grown in their local soil environment. From an applied perspective, our findings emphasize the importance of using locally selected seeds in restoration ecology and low-input agriculture.

  1. Spatially adaptive bases in wavelet-based coding of semi-regular meshes

    NASA Astrophysics Data System (ADS)

    Denis, Leon; Florea, Ruxandra; Munteanu, Adrian; Schelkens, Peter

    2010-05-01

    In this paper we present a wavelet-based coding approach for semi-regular meshes, which spatially adapts the employed wavelet basis in the wavelet transformation of the mesh. The spatially-adaptive nature of the transform requires additional information to be stored in the bit-stream in order to allow the reconstruction of the transformed mesh at the decoder side. In order to limit this overhead, the mesh is first segmented into regions of approximately equal size. For each spatial region, a predictor is selected in a rate-distortion optimal manner by using a Lagrangian rate-distortion optimization technique. When compared against the classical wavelet transform employing the butterfly subdivision filter, experiments reveal that the proposed spatially-adaptive wavelet transform significantly decreases the energy of the wavelet coefficients for all subbands. Preliminary results show also that employing the proposed transform for the lowest-resolution subband systematically yields improved compression performance at low-to-medium bit-rates. For the Venus and Rabbit test models the compression improvements add up to 1.47 dB and 0.95 dB, respectively.

  2. Noise-adaptive nonlinear diffusion filtering of MR images with spatially varying noise levels.

    PubMed

    Samsonov, Alexei A; Johnson, Chris R

    2004-10-01

    Anisotropic diffusion filtering is widely used for MR image enhancement. However, the anisotropic filter is nonoptimal for MR images with spatially varying noise levels, such as images reconstructed from sensitivity-encoded data and intensity inhomogeneity-corrected images. In this work, a new method for filtering MR images with spatially varying noise levels is presented. In the new method, a priori information regarding the image noise level spatial distribution is utilized for the local adjustment of the anisotropic diffusion filter. Our new method was validated and compared with the standard filter on simulated and real MRI data. The noise-adaptive method was demonstrated to outperform the standard anisotropic diffusion filter in both image error reduction and image signal-to-noise ratio (SNR) improvement. The method was also applied to inhomogeneity-corrected and sensitivity encoding (SENSE) images. The new filter was shown to improve segmentation of MR brain images with spatially varying noise levels.

  3. The effects of adapted tango on spatial cognition and disease severity in Parkinson's disease.

    PubMed

    McKee, Kathleen E; Hackney, Madeleine E

    2013-01-01

    The authors determined effects of community-based adapted tango on spatial cognition and disease severity in Parkinson's disease (PD) while controlling for the effects of social interaction. Thirty-three individuals with mild-to-moderate PD (stage I-III) were assigned to twenty 90-min tango (n = 24) or education (n = 9) lessons over 12 weeks. Disease severity, spatial cognition, balance, and fall incidence were evaluated pre-, post-, and 10-12 weeks postintervention. The authors evaluated differences using t tests and analyses of variance. Twenty-three tango and 8 education participants finished. Tango participants improved on disease severity (p = .008), and spatial cognition (p = .021) compared with education participants. Tango participants also improved in balance (p = .038), and executive function (p = .012). Gains were maintained 10-12 weeks postintervention. Multimodal exercise with structured syllabi may improve disease severity and spatial cognition in PD.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. Adaptive Web Sampling - ArcPad Applet Manual

    DTIC Science & Technology

    2011-09-01

    10 3.1.1 Create and GPS-enable the GIS sampling design geodatabase ............................... 10...38 Appendix D: Geodatabase Design .......................................................................................................... 40...hence, it requires ESRI ArcGIS. It functions as a navigational GPS data collection and decision support tool to guide a user through the process of

  6. Motor adaptation and generalization of reaching movements using motor primitives based on spatial coordinates

    PubMed Central

    Sejnowski, Terrence J.

    2014-01-01

    The brain processes sensory and motor information in a wide range of coordinate systems, ranging from retinal coordinates in vision to body-centered coordinates in areas that control musculature. Here we focus on the coordinate system used in the motor cortex to guide actions and examine physiological and psychophysical evidence for an allocentric reference frame based on spatial coordinates. When the equations of motion governing reaching dynamics are expressed as spatial vectors, each term is a vector cross product between a limb-segment position and a velocity or acceleration. We extend this computational framework to motor adaptation, in which the cross-product terms form adaptive bases for canceling imposed perturbations. Coefficients of the velocity- and acceleration-dependent cross products are assumed to undergo plastic changes to compensate the force-field or visuomotor perturbations. Consistent with experimental findings, each of the cross products had a distinct reference frame, which predicted how an acquired remapping generalized to untrained location in the workspace. In response to force field or visual rotation, mainly the coefficients of the velocity- or acceleration-dependent cross products adapted, leading to transfer in an intrinsic or extrinsic reference frame, respectively. The model further predicted that remapping of visuomotor rotation should under- or overgeneralize in a distal or proximal workspace. The cross-product bases can explain the distinct patterns of generalization in visuomotor and force-field adaptation in a unified way, showing that kinematic and dynamic motor adaptation need not arise through separate neural substrates. PMID:25429111

  7. Motor adaptation and generalization of reaching movements using motor primitives based on spatial coordinates.

    PubMed

    Tanaka, Hirokazu; Sejnowski, Terrence J

    2015-02-15

    The brain processes sensory and motor information in a wide range of coordinate systems, ranging from retinal coordinates in vision to body-centered coordinates in areas that control musculature. Here we focus on the coordinate system used in the motor cortex to guide actions and examine physiological and psychophysical evidence for an allocentric reference frame based on spatial coordinates. When the equations of motion governing reaching dynamics are expressed as spatial vectors, each term is a vector cross product between a limb-segment position and a velocity or acceleration. We extend this computational framework to motor adaptation, in which the cross-product terms form adaptive bases for canceling imposed perturbations. Coefficients of the velocity- and acceleration-dependent cross products are assumed to undergo plastic changes to compensate the force-field or visuomotor perturbations. Consistent with experimental findings, each of the cross products had a distinct reference frame, which predicted how an acquired remapping generalized to untrained location in the workspace. In response to force field or visual rotation, mainly the coefficients of the velocity- or acceleration-dependent cross products adapted, leading to transfer in an intrinsic or extrinsic reference frame, respectively. The model further predicted that remapping of visuomotor rotation should under- or overgeneralize in a distal or proximal workspace. The cross-product bases can explain the distinct patterns of generalization in visuomotor and force-field adaptation in a unified way, showing that kinematic and dynamic motor adaptation need not arise through separate neural substrates.

  8. Validation of Sensor-Directed Spatial Simulated Annealing Soil Sampling Strategy.

    PubMed

    Scudiero, Elia; Lesch, Scott M; Corwin, Dennis L

    2016-07-01

    Soil spatial variability has a profound influence on most agronomic and environmental processes at field and landscape scales, including site-specific management, vadose zone hydrology and transport, and soil quality. Mobile sensors are a practical means of mapping spatial variability because their measurements serve as a proxy for many soil properties, provided a sensor-soil calibration is conducted. A viable means of calibrating sensor measurements over soil properties is through linear regression modeling of sensor and target property data. In the present study, two sensor-directed, model-based, sampling scheme delineation methods were compared to validate recent applications of soil apparent electrical conductivity (EC)-directed spatial simulated annealing against the more established EC-directed response surface sampling design (RSSD) approach. A 6.8-ha study area near San Jacinto, CA, was surveyed for EC, and 30 soil sampling locations per sampling strategy were selected. Spatial simulated annealing and RSSD were compared for sensor calibration to a target soil property (i.e., salinity) and for evenness of spatial coverage of the study area, which is beneficial for mapping nontarget soil properties (i.e., those not correlated with EC). The results indicate that the linear modeling EC-salinity calibrations obtained from the two sampling schemes provided salinity maps characterized by similar errors. The maps of nontarget soil properties show similar errors across sampling strategies. The Spatial Simulated Annealing methodology is, therefore, validated, and its use in agronomic and environmental soil science applications is justified.

  9. Device for high spatial resolution chemical analysis of a sample and method of high spatial resolution chemical analysis

    DOEpatents

    Van Berkel, Gary J.

    2015-10-06

    A system and method for analyzing a chemical composition of a specimen are described. The system can include at least one pin; a sampling device configured to contact a liquid with a specimen on the at least one pin to form a testing solution; and a stepper mechanism configured to move the at least one pin and the sampling device relative to one another. The system can also include an analytical instrument for determining a chemical composition of the specimen from the testing solution. In particular, the systems and methods described herein enable chemical analysis of specimens, such as tissue, to be evaluated in a manner that the spatial-resolution is limited by the size of the pins used to obtain tissue samples, not the size of the sampling device used to solubilize the samples coupled to the pins.

  10. Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.; Thompson, David R.; Hsiang, Kian

    2013-01-01

    This work was designed to find a way to optimally (or near optimally) sample spatiotemporal phenomena based on limited sensing capability, and to create a model that can be run to estimate uncertainties, as well as to estimate covariances. The goal was to maximize (or minimize) some function of the overall uncertainty. The uncertainties and covariances were modeled presuming a parametric distribution, and then the model was used to approximate the overall information gain, and consequently, the objective function from each potential sense. These candidate sensings were then crosschecked against operation costs and feasibility. Consequently, an operations plan was derived that combined both operational constraints/costs and sensing gain. Probabilistic modeling was used to perform an approximate inversion of the model, which enabled calculation of sensing gains, and subsequent combination with operational costs. This incorporation of operations models to assess cost and feasibility for specific classes of vehicles is unique.

  11. Lost in space: multisensory conflict yields adaptation in spatial representations across frames of reference.

    PubMed

    Lohmann, Johannes; Butz, Martin V

    2017-03-27

    According to embodied cognition, bodily interactions with our environment shape the perception and representation of our body and the surrounding space, that is, peripersonal space. To investigate the adaptive nature of these spatial representations, we introduced a multisensory conflict between vision and proprioception in an immersive virtual reality. During individual bimanual interaction trials, we gradually shifted the visual hand representation. As a result, participants unknowingly shifted their actual hands to compensate for the visual shift. We then measured the adaptation to the invoked multisensory conflict by means of a self-localization and an external localization task. While effects of the conflict were observed in both tasks, the effects systematically interacted with the type of localization task and the available visual information while performing the localization task (i.e., the visibility of the virtual hands). The results imply that the localization of one's own hands is based on a multisensory integration process, which is modulated by the saliency of the currently most relevant sensory modality and the involved frame of reference. Moreover, the results suggest that our brain strives for consistency between its body and spatial estimates, thereby adapting multiple, related frames of reference, and the spatial estimates within, due to a sensory conflict in one of them.

  12. An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure.

    PubMed

    Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül

    2015-01-01

    In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.

  13. Detecting spatial structures in throughfall data: the effect of extent, sample size, sampling design, and variogram estimation method

    NASA Astrophysics Data System (ADS)

    Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

    2016-04-01

    In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least

  14. Efficient estimation of abundance for patchily distributed populations via two-phase, adaptive sampling.

    USGS Publications Warehouse

    Conroy, M.J.; Runge, J.P.; Barker, R.J.; Schofield, M.R.; Fonnesbeck, C.J.

    2008-01-01

    Many organisms are patchily distributed, with some patches occupied at high density, others at lower densities, and others not occupied. Estimation of overall abundance can be difficult and is inefficient via intensive approaches such as capture-mark-recapture (CMR) or distance sampling. We propose a two-phase sampling scheme and model in a Bayesian framework to estimate abundance for patchily distributed populations. In the first phase, occupancy is estimated by binomial detection samples taken on all selected sites, where selection may be of all sites available, or a random sample of sites. Detection can be by visual surveys, detection of sign, physical captures, or other approach. At the second phase, if a detection threshold is achieved, CMR or other intensive sampling is conducted via standard procedures (grids or webs) to estimate abundance. Detection and CMR data are then used in a joint likelihood to model probability of detection in the occupancy sample via an abundance-detection model. CMR modeling is used to estimate abundance for the abundance-detection relationship, which in turn is used to predict abundance at the remaining sites, where only detection data are collected. We present a full Bayesian modeling treatment of this problem, in which posterior inference on abundance and other parameters (detection, capture probability) is obtained under a variety of assumptions about spatial and individual sources of heterogeneity. We apply the approach to abundance estimation for two species of voles (Microtus spp.) in Montana, USA. We also use a simulation study to evaluate the frequentist properties of our procedure given known patterns in abundance and detection among sites as well as design criteria. For most population characteristics and designs considered, bias and mean-square error (MSE) were low, and coverage of true parameter values by Bayesian credibility intervals was near nominal. Our two-phase, adaptive approach allows efficient estimation of

  15. A class-adaptive spatially variant mixture model for image segmentation.

    PubMed

    Nikou, Christophoros; Galatsanos, Nikolaos P; Likas, Aristidis C

    2007-04-01

    We propose a new approach for image segmentation based on a hierarchical and spatially variant mixture model. According to this model, the pixel labels are random variables and a smoothness prior is imposed on them. The main novelty of this work is a new family of smoothness priors for the label probabilities in spatially variant mixture models. These Gauss-Markov random field-based priors allow all their parameters to be estimated in closed form via the maximum a posteriori (MAP) estimation using the expectation-maximization methodology. Thus, it is possible to introduce priors with multiple parameters that adapt to different aspects of the data. Numerical experiments are presented where the proposed MAP algorithms were tested in various image segmentation scenarios. These experiments demonstrate that the proposed segmentation scheme compares favorably to both standard and previous spatially constrained mixture model-based segmentation.

  16. Spatial variation in soil properties among North American ecosystems and guidelines for sampling designs.

    PubMed

    Loescher, Henry; Ayres, Edward; Duffy, Paul; Luo, Hongyan; Brunke, Max

    2014-01-01

    Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our

  17. Spatial Variation in Soil Properties among North American Ecosystems and Guidelines for Sampling Designs

    PubMed Central

    Loescher, Henry; Ayres, Edward; Duffy, Paul; Luo, Hongyan; Brunke, Max

    2014-01-01

    Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our

  18. Reducing Spatial Heterogeneity of MALDI Samples with Marangoni Flows During Sample Preparation.

    PubMed

    Lai, Yin-Hung; Cai, Yi-Hong; Lee, Hsun; Ou, Yu-Meng; Hsiao, Chih-Hao; Tsao, Chien-Wei; Chang, Huan-Tsung; Wang, Yi-Sheng

    2016-08-01

    This work demonstrates a method to prepare homogeneous distributions of analytes to improve data reproducibility in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). Natural-air drying processes normally result in unwanted heterogeneous spatial distributions of analytes in MALDI crystals and make quantitative analysis difficult. This study demonstrates that inducing Marangoni flows within drying droplets can significantly reduce the heterogeneity problem. The Marangoni flows are accelerated by changing substrate temperatures to create temperature gradients across droplets. Such hydrodynamic flows are analyzed semi-empirically. Using imaging mass spectrometry, changes of heterogeneity of molecules with the change of substrate temperature during drying processes are demonstrated. The observed heterogeneities of the biomolecules reduce as predicted Marangoni velocities increase. In comparison to conventional methods, drying droplets on a 5 °C substrate while keeping the surroundings at ambient conditions typically reduces the heterogeneity of biomolecular ions by 65%-80%. The observation suggests that decreasing substrate temperature during droplet drying processes is a simple and effective means to reduce analyte heterogeneity for quantitative applications. Graphical Abstract ᅟ.

  19. Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

    SciTech Connect

    McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; Huynh, Timmy N.; Bhaduri, Budhendra L.

    2015-02-03

    Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

  20. Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

    DOE PAGES

    McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...

    2015-02-03

    Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

  1. Locally adaptive, spatially explicit projection of US population for 2030 and 2050

    PubMed Central

    McKee, Jacob J.; Rose, Amy N.; Bright, Edward A.; Huynh, Timmy; Bhaduri, Budhendra L.

    2015-01-01

    Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census’s projection methodology, with the US Census’s official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations. PMID:25605882

  2. Common spatial pattern patches - an optimized filter ensemble for adaptive brain-computer interfaces.

    PubMed

    Sannelli, Claudia; Vidaurre, Carmen; Muller, Klaus-Robert; Blankertz, Benjamin

    2010-01-01

    Laplacian filters are commonly used in Brain Computer Interfacing (BCI). When only data from few channels are available, or when, like at the beginning of an experiment, no previous data from the same user is available complex features cannot be used. In this case band power features calculated from Laplacian filtered channels represents an easy, robust and general feature to control a BCI, since its calculation does not involve any class information. For the same reason, the performance obtained with Laplacian features is poor in comparison to subject-specific optimized spatial filters, such as Common Spatial Patterns (CSP) analysis, which, on the other hand, can be used just in a later phase of the experiment, since they require a considerable amount of training data in order to enroll a stable and good performance. This drawback is particularly evident in case of poor performing BCI users, whose data is highly non-stationary and contains little class relevant information. Therefore, Laplacian filtering is preferred to CSP, e.g., in the initial period of co-adaptive calibration, a novel BCI paradigm designed to alleviate the problem of BCI illiteracy. In fact, in the co-adaptive calibration design the experiment starts with a subject-independent classifier and simple features are needed in order to obtain a fast adaptation of the classifier to the newly acquired user's data. Here, the use of an ensemble of local CSP patches (CSPP) is proposed, which can be considered as a compromise between Laplacians and CSP: CSPP needs less data and channels than CSP, while being superior to Laplacian filtering. This property is shown to be particularly useful for the co-adaptive calibration design and is demonstrated on off-line data from a previous co-adaptive BCI study.

  3. Adapting geostatistics to analyze spatial and temporal trends in weed populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Spatially adaptive stochastic numerical methods for intrinsic fluctuations in reaction-diffusion systems

    SciTech Connect

    Atzberger, Paul J.

    2010-05-01

    Stochastic partial differential equations are introduced for the continuum concentration fields of reaction-diffusion systems. The stochastic partial differential equations account for fluctuations arising from the finite number of molecules which diffusively migrate and react. Spatially adaptive stochastic numerical methods are developed for approximation of the stochastic partial differential equations. The methods allow for adaptive meshes with multiple levels of resolution, Neumann and Dirichlet boundary conditions, and domains having geometries with curved boundaries. A key issue addressed by the methods is the formulation of consistent discretizations for the stochastic driving fields at coarse-refined interfaces of the mesh and at boundaries. Methods are also introduced for the efficient generation of the required stochastic driving fields on such meshes. As a demonstration of the methods, investigations are made of the role of fluctuations in a biological model for microorganism direction sensing based on concentration gradients. Also investigated, a mechanism for spatial pattern formation induced by fluctuations. The discretization approaches introduced for SPDEs have the potential to be widely applicable in the development of numerical methods for the study of spatially extended stochastic systems.

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

    PubMed Central

    Patané, Ivan; Farnè, Alessandro; Frassinetti, Francesca

    2016-01-01

    A large literature has documented interactions between space and time suggesting that the two experiential domains may share a common format in a generalized magnitude system (ATOM theory). To further explore this hypothesis, here we measured the extent to which time and space are sensitive to the same sensorimotor plasticity processes, as induced by classical prismatic adaptation procedures (PA). We also exanimated whether spatial-attention shifts on time and space processing, produced through PA, extend to stimuli presented beyond the immediate near space. Results indicated that PA affected both temporal and spatial representations not only in the near space (i.e., the region within which the adaptation occurred), but also in the far space. In addition, both rightward and leftward PA directions caused opposite and symmetrical modulations on time processing, whereas only leftward PA biased space processing rightward. We discuss these findings within the ATOM framework and models that account for PA effects on space and time processing. We propose that the differential and asymmetrical effects following PA may suggest that temporal and spatial representations are not perfectly aligned. PMID:26981286

  6. Effects of Calibration Sample Size and Item Bank Size on Ability Estimation in Computerized Adaptive Testing

    ERIC Educational Resources Information Center

    Sahin, Alper; Weiss, David J.

    2015-01-01

    This study aimed to investigate the effects of calibration sample size and item bank size on examinee ability estimation in computerized adaptive testing (CAT). For this purpose, a 500-item bank pre-calibrated using the three-parameter logistic model with 10,000 examinees was simulated. Calibration samples of varying sizes (150, 250, 350, 500,…

  7. Quantitative analysis of spatial sampling error in the infant and adult electroencephalogram.

    PubMed

    Grieve, Philip G; Emerson, Ronald G; Isler, Joseph R; Stark, Raymond I

    2004-04-01

    The purpose of this report was to determine the required number of electrodes to record the infant and adult electroencephalogram (EEG) with a specified amount of spatial sampling error. We first developed mathematical theory that governs the spatial sampling of EEG data distributed on a spherical approximation to the scalp. We then used a concentric sphere model of current flow in the head to simulate realistic EEG data. Quantitative spatial sampling error was calculated for the simulated EEG, with additive measurement noise, for 64, 128, and 256 electrodes equally spaced over the surface of the sphere corresponding to the coverage of the human scalp by commercially available "geodesic" electrode arrays. We found the sampling error for the infant to be larger than that for the adult. For example, a sampling error of less than 10% for the adult was obtained with a 64-electrode array but a 256-electrode array was needed for the infant to achieve the same level of error. With the addition of measurement noise, with power 10 times less than that of the EEG, the sampling error increased to 25% for both the infant and adult, for these numbers of electrodes. These results show that accurate measurement of the spatial properties of the infant EEG requires more electrodes than for the adult.

  8. Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research.

    PubMed

    Zhang, Shaocun; Cao, Xiaocang; Huang, He

    2017-01-01

    Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research.

  9. Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research

    PubMed Central

    Zhang, Shaocun; Cao, Xiaocang; Huang, He

    2017-01-01

    Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research. PMID:28286741

  10. Spatial frequency sampling look-up table method for computer-generated hologram

    NASA Astrophysics Data System (ADS)

    Zhao, Kai; Huang, Yingqing; Jiang, Xiaoyu; Yan, Xingpeng

    2016-04-01

    A spatial frequency sampling look-up table method is proposed to generate a hologram. The three-dimensional (3-D) scene is sampled as several intensity images by computer rendering. Each object point on the rendered images has a defined spatial frequency. The basis terms for calculating fringe patterns are precomputed and stored in a table to improve the calculation speed. Both numerical simulations and optical experiments are performed. The results show that the proposed approach can easily realize color reconstructions of a 3-D scene with a low computation cost. The occlusion effects and depth information are all provided accurately.

  11. Spatial over-sampling and its influence on spatial resolution for photoacoustic tomography with finite sized detectors

    NASA Astrophysics Data System (ADS)

    Burgholzer, P.; Roitner, H.; Berer, T.; Grün, H.; Nuster, R.; Paltauf, G.; Haltmeier, M.

    2014-03-01

    Detector arrays enable parallel detection for faster photoacoustic imaging than by moving a single detector, but the detector spacing for arrays cannot be smaller than the size of an array element. Spatial over-sampling is scanning with a step-size smaller than the size of the detector element and is possible only for a moving single detector. For a detector with finite sized surface the measured acoustic signal is a spatial average of the pressure field over the detector surface. If the reconstruction is performed assuming point-like detection over-sampling brings no advantage as e.g. for spherical or cylindrical detection surfaces the blurring caused by a finite detector size is proportional to the distance from the rotation center and is equal to the detector size at the detection surface. Iterative reconstruction algorithms or inverting directly the imaging matrix can take the finite size of real detectors directly into account, but the numerical effort is significantly higher compared to direct algorithms assuming point-like detection. Another reconstruction with less numerical effort is to use a direct algorithm assuming point-like detectors and run a deconvolution algorithm for deblurring afterwards. For such reconstruction methods spatial over-sampling makes sense because it reduces the blurring significantly. The effect of step size on the reconstructed image is systematically examined using simulated and experimental data. Experimental data are obtained on a plastisol cylinder with thin holes filled with an absorbing liquid. Data acquisition is done by utilization of a piezoelectric detector (PVDF stripe) which is rotated around the plastisol cylinder.

  12. A spatial explicit strategy reduces error but interferes with sensorimotor adaptation

    PubMed Central

    Benson, Bryan L.; Anguera, Joaquin A.

    2011-01-01

    Although sensorimotor adaptation is typically thought of as an implicit form of learning, it has been shown that participants who gain explicit awareness of the nature of the perturbation during adaptation exhibit more learning than those who do not. With rare exceptions, however, explicit awareness is typically polled at the end of the study. Here, we provided participants with either an explicit spatial strategy or no instructions before learning. Early in learning, explicit instructions greatly reduced movement errors but also resulted in increased trial-to-trial variability and longer reaction times. Late in adaptation, performance was indistinguishable between the explicit and implicit groups, but the mechanisms underlying performance improvements remained fundamentally different, as revealed by catch trials. The progression of implicit recalibration in the explicit group was modulated by the use of an explicit strategy: these participants showed a lower level of recalibration as well as decreased aftereffects. This phenomenon may be due to the reduced magnitude of errors made to the target during adaptation or inhibition of implicit learning mechanisms by explicit processing. PMID:21451054

  13. Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra.

    PubMed

    Cannistraci, Carlo Vittorio; Abbas, Ahmed; Gao, Xin

    2015-01-26

    Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet's performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.

  14. Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

    PubMed Central

    Cannistraci, Carlo Vittorio; Abbas, Ahmed; Gao, Xin

    2015-01-01

    Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet's performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis. PMID:25619991

  15. Estimating the abundance of clustered animal population by using adaptive cluster sampling and negative binomial distribution

    NASA Astrophysics Data System (ADS)

    Bo, Yizhou; Shifa, Naima

    2013-09-01

    An estimator for finding the abundance of a rare, clustered and mobile population has been introduced. This model is based on adaptive cluster sampling (ACS) to identify the location of the population and negative binomial distribution to estimate the total in each site. To identify the location of the population we consider both sampling with replacement (WR) and sampling without replacement (WOR). Some mathematical properties of the model are also developed.

  16. Spatially adaptive probabilistic computation of a sub-kilometre resolution lightning climatology for New Zealand

    NASA Astrophysics Data System (ADS)

    Etherington, Thomas R.; Perry, George L. W.

    2017-01-01

    Lightning is a key component of the Earth's atmosphere and climate systems, and there is a potential positive feedback between a warming climate and increased lightning activity. In the biosphere, lightning is important as the main natural ignition source for wildfires and because of its contribution to the nitrogen cycle. Therefore, it is important to develop lightning climatologies to characterise and monitor lightning activity. While traditional methods for constructing lightning climatologies are suitable for examining lightning's influence on atmospheric processes, they are less well suited for examining questions about biosphere-lightning interactions. For example, examining the interaction between lightning and wildfires requires linking atmospheric processes to finer scale terrestrial processes and patterns. Most wildfires ignited by lightning are less than one hectare in size, and so require lightning climatologies at a comparable spatial resolution. However, such high resolution lightning climatologies cannot be derived using the traditional cell-count methodology. Here we present a novel geocomputational approach for analysing lightning data at high spatial resolutions. Our approach is based on probabilistic computational methods and is capable of producing a sub-kilometre lightning climatology that honours the spatial accuracy of the strike locations and is adaptive to underlying spatial patterns. We demonstrate our methods by applying them to the mid-latitude oceanic landmass of New Zealand, an area with geographic conditions that are under-represented in existing lightning climatologies. Our resulting lightning climatology has unparalleled spatial resolution, and the spatial and temporal patterns we observe in it are consistent with other continental and tropical lightning climatologies. To encourage further use and development of our probabilistic approach, we provide Python scripts that demonstrate the method alongside our resulting New Zealand

  17. SMI adaptive antenna arrays for weak interfering signals. [Sample Matrix Inversion

    NASA Technical Reports Server (NTRS)

    Gupta, Inder J.

    1986-01-01

    The performance of adaptive antenna arrays in the presence of weak interfering signals (below thermal noise) is studied. It is shown that a conventional adaptive antenna array sample matrix inversion (SMI) algorithm is unable to suppress such interfering signals. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is redefined such that the effect of thermal noise on the weights of adaptive arrays is reduced. Thus, the weights are dictated by relatively weak signals. It is shown that the modified algorithm provides the desired interference protection.

  18. Spatial recruitment bias in respondent-driven sampling: Implications for HIV prevalence estimation in urban heterosexuals.

    PubMed

    Jenness, Samuel M; Neaigus, Alan; Wendel, Travis; Gelpi-Acosta, Camila; Hagan, Holly

    2014-12-01

    Respondent-driven sampling (RDS) is a study design used to investigate populations for which a probabilistic sampling frame cannot be efficiently generated. Biases in parameter estimates may result from systematic non-random recruitment within social networks by geography. We investigate the spatial distribution of RDS recruits relative to an inferred social network among heterosexual adults in New York City in 2010. Mean distances between recruitment dyads are compared to those of network dyads to quantify bias. Spatial regression models are then used to assess the impact of spatial structure on risk and prevalence outcomes. In our primary distance metric, network dyads were an average of 1.34 (95 % CI 0.82–1.86) miles farther dispersed than recruitment dyads, suggesting spatial bias. However, there was no evidence that demographic associations with HIV risk or prevalence were spatially confounded. Therefore, while the spatial structure of recruitment may be biased in heterogeneous urban settings, the impact of this bias on estimates of outcome measures appears minimal.

  19. Spatial differences in an integral membrane proteome detected in laser capture microdissected samples.

    PubMed

    Wang, Zhen; Han, Jun; Schey, Kevin L

    2008-07-01

    The combination of laser capture microdissection and mass spectrometry represents a powerful technology for studying spatially resolved proteomes. Moreover, the compositions of integral membrane proteomes have rarely been studied in a spatially resolved manner. In this study, ocular lens tissue was carefully dissected by laser capture microdissection and conditions for membrane protein enrichment, trypsin digestion, and mass spectrometry analysis were optimized. Proteomic analysis allowed the identification of 170 proteins, 136 of which were identified with more than one peptide match. Spatial differences in protein expression were observed between cortical and nuclear samples. In addition, the spatial distribution of post-translational modifications to lens membrane proteins, such as the lens major intrinsic protein AQP0, were investigated and regional differences were measured for AQP0 C-terminal phosphorylation and truncation.

  20. Four-dimensional tracking of spatially incoherent illuminated samples using self-interference digital holography

    NASA Astrophysics Data System (ADS)

    Man, Tianlong; Wan, Yuhong; Wu, Fan; Wang, Dayong

    2015-11-01

    We present a new method for the four-dimensional tracking of a spatially incoherent illuminated object. Self-interference digital holography is utilized for recording the hologram of the spatially incoherent illuminated object. Three-dimensional spatial coordinates encoded in the hologram are extracted by holographic reconstruction procedure and tracking algorithms, while the time information is reserved by the single-shot configuration. Applications of the holographic tracking methods are expanded to the incoherent imaging areas. Speckles and potential damage to the samples of the coherent illuminated tracking methods are overcome. Results on the quantitative tracking of three-dimensional spatial position over time are reported. In practical, living zebra fish larva is used to demonstrate one of the applications of the method.

  1. Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater

    PubMed Central

    Shabbir, Javid; M. AbdEl-Salam, Nasser; Hussain, Tajammal

    2016-01-01

    Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used to predict the sodium concentrations. Spatial simulated annealing is used to generate optimized sampling designs. Different estimation methods (i.e., maximum likelihood, restricted maximum likelihood, ordinary least squares, and weighted least squares) are used to estimate the parameters of the variogram model (i.e, exponential, Gaussian, spherical and cubic). It is concluded that Bayesian universal kriging fits better than universal kriging. It is also observed that the universal kriging predictor provides minimum mean universal kriging variance for both adding and deleting locations during sampling design. PMID:27683016

  2. Integrating population dynamics models and distance sampling data: a spatial hierarchical state-space approach.

    PubMed

    Nadeem, Khurram; Moore, Jeffrey E; Zhang, Ying; Chipman, Hugh

    2016-07-01

    Stochastic versions of Gompertz, Ricker, and various other dynamics models play a fundamental role in quantifying strength of density dependence and studying long-term dynamics of wildlife populations. These models are frequently estimated using time series of abundance estimates that are inevitably subject to observation error and missing data. This issue can be addressed with a state-space modeling framework that jointly estimates the observed data model and the underlying stochastic population dynamics (SPD) model. In cases where abundance data are from multiple locations with a smaller spatial resolution (e.g., from mark-recapture and distance sampling studies), models are conventionally fitted to spatially pooled estimates of yearly abundances. Here, we demonstrate that a spatial version of SPD models can be directly estimated from short time series of spatially referenced distance sampling data in a unified hierarchical state-space modeling framework that also allows for spatial variance (covariance) in population growth. We also show that a full range of likelihood based inference, including estimability diagnostics and model selection, is feasible in this class of models using a data cloning algorithm. We further show through simulation experiments that the hierarchical state-space framework introduced herein efficiently captures the underlying dynamical parameters and spatial abundance distribution. We apply our methodology by analyzing a time series of line-transect distance sampling data for fin whales (Balaenoptera physalus) off the U.S. west coast. Although there were only seven surveys conducted during the study time frame, 1991-2014, our analysis detected presence of strong density regulation and provided reliable estimates of fin whale densities. In summary, we show that the integrative framework developed herein allows ecologists to better infer key population characteristics such as presence of density regulation and spatial variability in a

  3. Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

    PubMed

    Broekhuis, Femke; Gopalaswamy, Arjun M

    2016-01-01

    Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

  4. Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

    PubMed Central

    Broekhuis, Femke; Gopalaswamy, Arjun M.

    2016-01-01

    Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

  5. Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

    NASA Astrophysics Data System (ADS)

    Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

    2016-09-01

    In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous

  6. Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

    NASA Technical Reports Server (NTRS)

    Rao, R. G. S.; Ulaby, F. T.

    1977-01-01

    The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

  7. SPATIALLY-BALANCED SAMPLING OF NATURAL RESOURCES IN THE PRESENCE OF FRAME IMPERFECTIONS

    EPA Science Inventory

    The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. Generally, samples that are more or less evenly dispersed over the extent of the resource will be more efficient than simple rando...

  8. Demography-based adaptive network model reproduces the spatial organization of human linguistic groups.

    PubMed

    Capitán, José A; Manrubia, Susanna

    2015-12-01

    The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

  9. Adaptive and bounded investment returns promote cooperation in spatial public goods games.

    PubMed

    Chen, Xiaojie; Liu, Yongkui; Zhou, Yonghui; Wang, Long; Perc, Matjaž

    2012-01-01

    The public goods game is one of the most famous models for studying the evolution of cooperation in sizable groups. The multiplication factor in this game can characterize the investment return from the public good, which may be variable depending on the interactive environment in realistic situations. Instead of using the same universal value, here we consider that the multiplication factor in each group is updated based on the differences between the local and global interactive environments in the spatial public goods game, but meanwhile limited to within a certain range. We find that the adaptive and bounded investment returns can significantly promote cooperation. In particular, full cooperation can be achieved for high feedback strength when appropriate limitation is set for the investment return. Also, we show that the fraction of cooperators in the whole population can become larger if the lower and upper limits of the multiplication factor are increased. Furthermore, in comparison to the traditionally spatial public goods game where the multiplication factor in each group is identical and fixed, we find that cooperation can be better promoted if the multiplication factor is constrained to adjust between one and the group size in our model. Our results highlight the importance of the locally adaptive and bounded investment returns for the emergence and dominance of cooperative behavior in structured populations.

  10. The role of motor learning in spatial adaptation near a tool.

    PubMed

    Brown, Liana E; Doole, Robert; Malfait, Nicole

    2011-01-01

    Some visual-tactile (bimodal) cells have visual receptive fields (vRFs) that overlap and extend moderately beyond the skin of the hand. Neurophysiological evidence suggests, however, that a vRF will grow to encompass a hand-held tool following active tool use but not after passive holding. Why does active tool use, and not passive holding, lead to spatial adaptation near a tool? We asked whether spatial adaptation could be the result of motor or visual experience with the tool, and we distinguished between these alternatives by isolating motor from visual experience with the tool. Participants learned to use a novel, weighted tool. The active training group received both motor and visual experience with the tool, the passive training group received visual experience with the tool, but no motor experience, and finally, a no-training control group received neither visual nor motor experience using the tool. After training, we used a cueing paradigm to measure how quickly participants detected targets, varying whether the tool was placed near or far from the target display. Only the active training group detected targets more quickly when the tool was placed near, rather than far, from the target display. This effect of tool location was not present for either the passive-training or control groups. These results suggest that motor learning influences how visual space around the tool is represented.

  11. Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

    NASA Astrophysics Data System (ADS)

    Capitán, José A.; Manrubia, Susanna

    2015-12-01

    The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

  12. Implementation of time-efficient adaptive sampling function design for improved undersampled MRI reconstruction

    NASA Astrophysics Data System (ADS)

    Choi, Jinhyeok; Kim, Hyeonjin

    2016-12-01

    To improve the efficacy of undersampled MRI, a method of designing adaptive sampling functions is proposed that is simple to implement on an MR scanner and yet effectively improves the performance of the sampling functions. An approximation of the energy distribution of an image (E-map) is estimated from highly undersampled k-space data acquired in a prescan and efficiently recycled in the main scan. An adaptive probability density function (PDF) is generated by combining the E-map with a modeled PDF. A set of candidate sampling functions are then prepared from the adaptive PDF, among which the one with maximum energy is selected as the final sampling function. To validate its computational efficiency, the proposed method was implemented on an MR scanner, and its robust performance in Fourier-transform (FT) MRI and compressed sensing (CS) MRI was tested by simulations and in a cherry tomato. The proposed method consistently outperforms the conventional modeled PDF approach for undersampling ratios of 0.2 or higher in both FT-MRI and CS-MRI. To fully benefit from undersampled MRI, it is preferable that the design of adaptive sampling functions be performed online immediately before the main scan. In this way, the proposed method may further improve the efficacy of the undersampled MRI.

  13. Spatial and temporal variation of an ice-adapted predator's feeding ecology in a changing Arctic marine ecosystem.

    PubMed

    Yurkowski, David J; Ferguson, Steven H; Semeniuk, Christina A D; Brown, Tanya M; Muir, Derek C G; Fisk, Aaron T

    2016-03-01

    Spatial and temporal variation can confound interpretations of relationships within and between species in terms of diet composition, niche size, and trophic position (TP). The cause of dietary variation within species is commonly an ontogenetic niche shift, which is a key dynamic influencing community structure. We quantified spatial and temporal variations in ringed seal (Pusa hispida) diet, niche size, and TP during ontogeny across the Arctic-a rapidly changing ecosystem. Stable carbon and nitrogen isotope analysis was performed on 558 liver and 630 muscle samples from ringed seals and on likely prey species from five locations ranging from the High to the Low Arctic. A modest ontogenetic diet shift occurred, with adult ringed seals consuming more forage fish (approximately 80 versus 60 %) and having a higher TP than subadults, which generally decreased with latitude. However, the degree of shift varied spatially, with adults in the High Arctic presenting a more restricted niche size and consuming more Arctic cod (Boreogadus saida) than subadults (87 versus 44 %) and adults at the lowest latitude (29 %). The TPs of adult and subadult ringed seals generally decreased with latitude (4.7-3.3), which was mainly driven by greater complexity in trophic structure within the zooplankton communities. Adult isotopic niche size increased over time, likely due to the recent circumpolar increases in subarctic forage fish distribution and abundance. Given the spatial and temporal variability in ringed seal foraging ecology, ringed seals exhibit dietary plasticity as a species, suggesting adaptability in terms of their diet to climate change.

  14. Adaptive Sampling-Based Information Collection for Wireless Body Area Networks.

    PubMed

    Xu, Xiaobin; Zhao, Fang; Wang, Wendong; Tian, Hui

    2016-08-31

    To collect important health information, WBAN applications typically sense data at a high frequency. However, limited by the quality of wireless link, the uploading of sensed data has an upper frequency. To reduce upload frequency, most of the existing WBAN data collection approaches collect data with a tolerable error. These approaches can guarantee precision of the collected data, but they are not able to ensure that the upload frequency is within the upper frequency. Some traditional sampling based approaches can control upload frequency directly, however, they usually have a high loss of information. Since the core task of WBAN applications is to collect health information, this paper aims to collect optimized information under the limitation of upload frequency. The importance of sensed data is defined according to information theory for the first time. Information-aware adaptive sampling is proposed to collect uniformly distributed data. Then we propose Adaptive Sampling-based Information Collection (ASIC) which consists of two algorithms. An adaptive sampling probability algorithm is proposed to compute sampling probabilities of different sensed values. A multiple uniform sampling algorithm provides uniform samplings for values in different intervals. Experiments based on a real dataset show that the proposed approach has higher performance in terms of data coverage and information quantity. The parameter analysis shows the optimized parameter settings and the discussion shows the underlying reason of high performance in the proposed approach.

  15. Adaptive Sampling-Based Information Collection for Wireless Body Area Networks

    PubMed Central

    Xu, Xiaobin; Zhao, Fang; Wang, Wendong; Tian, Hui

    2016-01-01

    To collect important health information, WBAN applications typically sense data at a high frequency. However, limited by the quality of wireless link, the uploading of sensed data has an upper frequency. To reduce upload frequency, most of the existing WBAN data collection approaches collect data with a tolerable error. These approaches can guarantee precision of the collected data, but they are not able to ensure that the upload frequency is within the upper frequency. Some traditional sampling based approaches can control upload frequency directly, however, they usually have a high loss of information. Since the core task of WBAN applications is to collect health information, this paper aims to collect optimized information under the limitation of upload frequency. The importance of sensed data is defined according to information theory for the first time. Information-aware adaptive sampling is proposed to collect uniformly distributed data. Then we propose Adaptive Sampling-based Information Collection (ASIC) which consists of two algorithms. An adaptive sampling probability algorithm is proposed to compute sampling probabilities of different sensed values. A multiple uniform sampling algorithm provides uniform samplings for values in different intervals. Experiments based on a real dataset show that the proposed approach has higher performance in terms of data coverage and information quantity. The parameter analysis shows the optimized parameter settings and the discussion shows the underlying reason of high performance in the proposed approach. PMID:27589758

  16. Temporally adaptive sampling: a case study in rare species survey design with marbled salamanders (Ambystoma opacum).

    PubMed

    Charney, Noah D; Kubel, Jacob E; Eiseman, Charles S

    2015-01-01

    Improving detection rates for elusive species with clumped distributions is often accomplished through adaptive sampling designs. This approach can be extended to include species with temporally variable detection probabilities. By concentrating survey effort in years when the focal species are most abundant or visible, overall detection rates can be improved. This requires either long-term monitoring at a few locations where the species are known to occur or models capable of predicting population trends using climatic and demographic data. For marbled salamanders (Ambystoma opacum) in Massachusetts, we demonstrate that annual variation in detection probability of larvae is regionally correlated. In our data, the difference in survey success between years was far more important than the difference among the three survey methods we employed: diurnal surveys, nocturnal surveys, and dipnet surveys. Based on these data, we simulate future surveys to locate unknown populations under a temporally adaptive sampling framework. In the simulations, when pond dynamics are correlated over the focal region, the temporally adaptive design improved mean survey success by as much as 26% over a non-adaptive sampling design. Employing a temporally adaptive strategy costs very little, is simple, and has the potential to substantially improve the efficient use of scarce conservation funds.

  17. Temporally Adaptive Sampling: A Case Study in Rare Species Survey Design with Marbled Salamanders (Ambystoma opacum)

    PubMed Central

    Charney, Noah D.; Kubel, Jacob E.; Eiseman, Charles S.

    2015-01-01

    Improving detection rates for elusive species with clumped distributions is often accomplished through adaptive sampling designs. This approach can be extended to include species with temporally variable detection probabilities. By concentrating survey effort in years when the focal species are most abundant or visible, overall detection rates can be improved. This requires either long-term monitoring at a few locations where the species are known to occur or models capable of predicting population trends using climatic and demographic data. For marbled salamanders (Ambystoma opacum) in Massachusetts, we demonstrate that annual variation in detection probability of larvae is regionally correlated. In our data, the difference in survey success between years was far more important than the difference among the three survey methods we employed: diurnal surveys, nocturnal surveys, and dipnet surveys. Based on these data, we simulate future surveys to locate unknown populations under a temporally adaptive sampling framework. In the simulations, when pond dynamics are correlated over the focal region, the temporally adaptive design improved mean survey success by as much as 26% over a non-adaptive sampling design. Employing a temporally adaptive strategy costs very little, is simple, and has the potential to substantially improve the efficient use of scarce conservation funds. PMID:25799224

  18. Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.

    PubMed

    Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong

    2015-04-01

    Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.

  19. Image slicing with a twist: spatial and spectral Nyquist sampling without anamorphic optics

    NASA Astrophysics Data System (ADS)

    Tecza, Matthias

    2014-07-01

    Integral field spectrographs have become mainstream instruments at modern telescopes because of their efficient way of collecting data-cubes. Image slicer based integral field spectrographs achieve the highest fill-factor on the detector, but due to the need to Nyquist-sample the spectra, their spatial sampling on the sky is rectangular. Using anamorphic pre-optics before the image slicer overcomes this effect further maximising the fill-factor, but introduces optical aberrations, throughput losses, and additional alignment and calibration requirements, compromising overall instrument performance. In this paper I present a concept for an image-slicer that achieves both spatial and spectral Nyquist-sampling without anamorphic pre-optics. Rotating each slitlet by 45° with respect to the dispersion direction, and arranging them into a saw-tooth pseudo-slit, leads to a lozenge shaped sampling element on the sky, however, the centres of the lozenges lie on a regular and square grid, satisfying the Nyquist sampling criterion in both spatial directions.

  20. Efficient sampling for spatial uncertainty qualification in multibody system dynamics applications.

    SciTech Connect

    Schmitt, K.; Anitescu, M.; Negrut, D.; Mathematics and Computer Science; Univ. of Wisconsin

    2009-01-01

    We present two methods for efficiently sampling the response (trajectory space) of multibody systems operating under spatial uncertainty, when the latter is assumed to be representable with Gaussian processes. In this case, the dynamics (time evolution) of the multibody systems depends on spatially indexed uncertain parameters that span infinite-dimensional spaces. This places a heavy computational burden on existing methodologies, an issue addressed herein with two new conditional sampling approaches. When a single instance of the uncertainty is needed in the entire domain, we use a fast Fourier transform technique. When the initial conditions are fixed and the path distribution of the dynamical system is relatively narrow, we use an incremental sampling approach that is fast and has a small memory footprint. Both methods produce the same distributions as the widely used Cholesky-based approaches. We illustrate this convergence at a smaller computational effort and memory cost for a simple non-linear vehicle model.

  1. Generalized total variation-based MRI Rician denoising model with spatially adaptive regularization parameters.

    PubMed

    Liu, Ryan Wen; Shi, Lin; Huang, Wenhua; Xu, Jing; Yu, Simon Chun Ho; Wang, Defeng

    2014-07-01

    Magnetic resonance imaging (MRI) is an outstanding medical imaging modality but the quality often suffers from noise pollution during image acquisition and transmission. The purpose of this study is to enhance image quality using feature-preserving denoising method. In current literature, most existing MRI denoising methods did not simultaneously take the global image prior and local image features into account. The denoising method proposed in this paper is implemented based on an assumption of spatially varying Rician noise map. A two-step wavelet-domain estimation method is developed to extract the noise map. Following a Bayesian modeling approach, a generalized total variation-based MRI denoising model is proposed based on global hyper-Laplacian prior and Rician noise assumption. The proposed model has the properties of backward diffusion in local normal directions and forward diffusion in local tangent directions. To further improve the denoising performance, a local variance estimator-based method is introduced to calculate the spatially adaptive regularization parameters related to local image features and spatially varying noise map. The main benefit of the proposed method is that it takes full advantage of the global MR image prior and local image features. Numerous experiments have been conducted on both synthetic and real MR data sets to compare our proposed model with some state-of-the-art denoising methods. The experimental results have demonstrated the superior performance of our proposed model in terms of quantitative and qualitative image quality evaluations.

  2. [A spatial adaptive algorithm for endmember extraction on multispectral remote sensing image].

    PubMed

    Zhu, Chang-Ming; Luo, Jian-Cheng; Shen, Zhan-Feng; Li, Jun-Li; Hu, Xiao-Dong

    2011-10-01

    Due to the problem that the convex cone analysis (CCA) method can only extract limited endmember in multispectral imagery, this paper proposed a new endmember extraction method by spatial adaptive spectral feature analysis in multispectral remote sensing image based on spatial clustering and imagery slice. Firstly, in order to remove spatial and spectral redundancies, the principal component analysis (PCA) algorithm was used for lowering the dimensions of the multispectral data. Secondly, iterative self-organizing data analysis technology algorithm (ISODATA) was used for image cluster through the similarity of the pixel spectral. And then, through clustering post process and litter clusters combination, we divided the whole image data into several blocks (tiles). Lastly, according to the complexity of image blocks' landscape and the feature of the scatter diagrams analysis, the authors can determine the number of endmembers. Then using hourglass algorithm extracts endmembers. Through the endmember extraction experiment on TM multispectral imagery, the experiment result showed that the method can extract endmember spectra form multispectral imagery effectively. What's more, the method resolved the problem of the amount of endmember limitation and improved accuracy of the endmember extraction. The method has provided a new way for multispectral image endmember extraction.

  3. Relativistic Flows Using Spatial And Temporal Adaptive Structured Mesh Refinement. I. Hydrodynamics

    SciTech Connect

    Wang, Peng; Abel, Tom; Zhang, Weiqun; /KIPAC, Menlo Park

    2007-04-02

    Astrophysical relativistic flow problems require high resolution three-dimensional numerical simulations. In this paper, we describe a new parallel three-dimensional code for simulations of special relativistic hydrodynamics (SRHD) using both spatially and temporally structured adaptive mesh refinement (AMR). We used method of lines to discrete SRHD equations spatially and used a total variation diminishing (TVD) Runge-Kutta scheme for time integration. For spatial reconstruction, we have implemented piecewise linear method (PLM), piecewise parabolic method (PPM), third order convex essentially non-oscillatory (CENO) and third and fifth order weighted essentially non-oscillatory (WENO) schemes. Flux is computed using either direct flux reconstruction or approximate Riemann solvers including HLL, modified Marquina flux, local Lax-Friedrichs flux formulas and HLLC. The AMR part of the code is built on top of the cosmological Eulerian AMR code enzo, which uses the Berger-Colella AMR algorithm and is parallel with dynamical load balancing using the widely available Message Passing Interface library. We discuss the coupling of the AMR framework with the relativistic solvers and show its performance on eleven test problems.

  4. Adaptive sampling rate control for networked systems based on statistical characteristics of packet disordering.

    PubMed

    Li, Jin-Na; Er, Meng-Joo; Tan, Yen-Kheng; Yu, Hai-Bin; Zeng, Peng

    2015-09-01

    This paper investigates an adaptive sampling rate control scheme for networked control systems (NCSs) subject to packet disordering. The main objectives of the proposed scheme are (a) to avoid heavy packet disordering existing in communication networks and (b) to stabilize NCSs with packet disordering, transmission delay and packet loss. First, a novel sampling rate control algorithm based on statistical characteristics of disordering entropy is proposed; secondly, an augmented closed-loop NCS that consists of a plant, a sampler and a state-feedback controller is transformed into an uncertain and stochastic system, which facilitates the controller design. Then, a sufficient condition for stochastic stability in terms of Linear Matrix Inequalities (LMIs) is given. Moreover, an adaptive tracking controller is designed such that the sampling period tracks a desired sampling period, which represents a significant contribution. Finally, experimental results are given to illustrate the effectiveness and advantages of the proposed scheme.

  5. Career Adapt-Abilities Scale in a French-Speaking Swiss Sample: Psychometric Properties and Relationships to Personality and Work Engagement

    ERIC Educational Resources Information Center

    Rossier, Jerome; Zecca, Gregory; Stauffer, Sarah D.; Maggiori, Christian; Dauwalder, Jean-Pierre

    2012-01-01

    The aim of this study was to analyze the psychometric properties of the Career Adapt-Abilities Scale (CAAS) in a French-speaking Swiss sample and its relationship with personality dimensions and work engagement. The heterogeneous sample of 391 participants (M[subscript age] = 39.59, SD = 12.30) completed the CAAS-International and a short version…

  6. Competition and time-dependent behavior in spatial iterated prisoner’s dilemma incorporating adaptive zero-determinant strategies

    NASA Astrophysics Data System (ADS)

    Li, Yong; Xu, Chen; Liu, Jie; Hui, Pak Ming

    2016-10-01

    We propose and study the competitiveness of a class of adaptive zero-determinant strategies (ZDSs) in a population with spatial structure against four classic strategies in iterated prisoner’s dilemma. Besides strategy updating via a probabilistic mechanism by imitating the strategy of a better performing opponent, players using the ZDSs can also adapt their strategies to take advantage of their local competing environment with another probability. The adapted ZDSs could be extortionate-like to avoid being continually cheated by defectors or to take advantage of unconditional cooperators. The adapted ZDSs could also be a compliance strategy so as to cooperate with the conditionally cooperative players. This flexibility makes adaptive ZDSs more competitive than nonadaptive ZDSs. Results show that adaptive ZDSs can either dominate over other strategies or at least coexist with them when the ZDSs are allowed to adapt more readily than to imitate other strategies. The effectiveness of the adaptive ZDSs relies on how fast they can adapt to the competing environment before they are replaced by other strategies. The adaptive ZDSs generally work well as they could adapt gradually and make use of other strategies for suppressing their enemies. When adaptation happens more readily than imitation for the ZDSs, they outperform other strategies over a wide range of cost-to-benefit ratios.

  7. Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs.

    PubMed

    Rigamonti, Ivo E; Brambilla, Carla; Colleoni, Emanuele; Jermini, Mauro; Trivellone, Valeria; Baumgärtner, Johann

    2016-04-01

    The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.

  8. Spatial scales of variation in lichens: implications for sampling design in biomonitoring surveys.

    PubMed

    Giordani, Paolo; Brunialti, Giorgio; Frati, Luisa; Incerti, Guido; Ianesch, Luca; Vallone, Emanuele; Bacaro, Giovanni; Maccherini, Simona

    2013-02-01

    The variability of biological data is a main constraint affecting the quality and reliability of lichen biomonitoring surveys for estimation of the effects of atmospheric pollution. Although most epiphytic lichen bioindication surveys focus on between-site differences at the landscape level, associated with the large scale effects of atmospheric pollution, current protocols are based on multilevel sampling, thus adding further sources of variation and affecting the error budget. We test the hypothesis that assemblages of lichen communities vary at each spatial scale examined, in order to determine what scales should be included in future monitoring studies. We compared four sites in Italy, along gradients of atmospheric pollution and climate, to test the partitioning of the variance components of lichen diversity across spatial scales (from trunks to landscapes). Despite environmental heterogeneity, we observed comparable spatial variance. However, residuals often overcame between-plot variability, leading to biased estimation of atmospheric pollution effects.

  9. Spatially varying relationships between land-cover change and driving factors at multiple sampling scales.

    PubMed

    Du, Shihong; Wang, Qiao; Guo, Luo

    2014-05-01

    Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human-environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at different sampling scales in the Tibetan Autonomous Prefecture of Qinghai Province, P.R. China. Regular sampling methods are used first to generate eight sets of data points at different scales, and then the values for land-cover changes and the factors are extracted for these data points. Geographically weighted regression (GWR) model is applied to analyze the relationships between land-cover changes and the factors at different sampling scales. The results indicate that the influences of the factors (e.g. the signs, significances, and values of coefficients) change greatly over different sampling scales; similarly, for different types of land-cover changes, the contributions of the factors also vary. Generally, roads, rivers, and lakes contribute greatly to land-cover changes, while villages, temples, and elevations contribute less. A possible reason is that the densities of roads, rivers, and lakes is much greater than those of villages and temples, and the populations in temples and villages are too small to have much effect on land-cover changes. The results demonstrate that the sampling scales have an important influence on the relationships between land-cover change and the factors.

  10. ECa-Directed Soil Sampling for Characterizing Spatial Variability: Monitoring Management- Induced Change

    NASA Astrophysics Data System (ADS)

    Corwin, D. L.

    2006-05-01

    Characterizing spatial variability is an important consideration of any landscape-scale soil-related problem. Geospatial measurements of apparent soil electrical conductivity (ECa) are useful for characterizing spatial variability by directing soil sampling. The objective of this presentation is to discuss equipment, protocols, sampling designs, and a case study of an ECa survey to characterize spatial variability. Specifically, a preliminary spatio-temporal study of management-induced changes to soil quality will be demonstrated for a drainage water reuse study site. The spatio-temporal study used electromagnetic induction ECa data and a response surface sampling design to select 40 sites that reflected the spatial variability of soil properties (i.e., salinity, Na levels, Mo, and B) impacting the intended agricultural use of a saline-sodic field in California's San Joaquin Valley. Soil samples were collected in August 1999 and April 2002. Data from 1999 indicate the presence of high salinity, which increased with depth, high sodium adsorption ratio (SAR), which also increased with depth, and moderate to high B and Mo, which showed no specific trends with depth. The application of drainage water for 32 months resulted in leaching of B from the top 0.3 of soil, leaching of salinity from the top 0.6 m of soil, and leaching of Na and Mo from the top 1.2 m of soil. The leaching fraction over the time period from 1999-2002 was estimated to be 0.10. The level of salinity in the reused drainage water (i.e., 3-5 dS/m) allowed infiltration and leaching to occur even though high sodium and high expanding-lattice clay levels posed potential water flow problems. The leaching of salinity, Na, Mo, and B has resulted in increased forage yield and improved quality of those yields. Preliminary spatio-temporal analyses indicate at least short-term feasibility of drainage water reuse from the perspective of soil quality when the goal is forage production for grazing livestock. The

  11. Dynamically optimized Wang-Landau sampling with adaptive trial moves and modification factors.

    PubMed

    Koh, Yang Wei; Lee, Hwee Kuan; Okabe, Yutaka

    2013-11-01

    The density of states of continuous models is known to span many orders of magnitudes at different energies due to the small volume of phase space near the ground state. Consequently, the traditional Wang-Landau sampling which uses the same trial move for all energies faces difficulties sampling the low-entropic states. We developed an adaptive variant of the Wang-Landau algorithm that very effectively samples the density of states of continuous models across the entire energy range. By extending the acceptance ratio method of Bouzida, Kumar, and Swendsen such that the step size of the trial move and acceptance rate are adapted in an energy-dependent fashion, the random walker efficiently adapts its sampling according to the local phase space structure. The Wang-Landau modification factor is also made energy dependent in accordance with the step size, enhancing the accumulation of the density of states. Numerical simulations show that our proposed method performs much better than the traditional Wang-Landau sampling.

  12. An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

    SciTech Connect

    Li, Weixuan; Lin, Guang

    2015-08-01

    Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes' rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle these challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.

  13. An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

    SciTech Connect

    Li, Weixuan; Lin, Guang

    2015-03-21

    Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes’ rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle these challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.

  14. An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

    DOE PAGES

    Li, Weixuan; Lin, Guang

    2015-03-21

    Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes’ rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle thesemore » challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.« less

  15. Spatial distribution of single-nucleotide polymorphisms related to fungicide resistance and implications for sampling.

    PubMed

    Van der Heyden, H; Dutilleul, P; Brodeur, L; Carisse, O

    2014-06-01

    Spatial distribution of single-nucleotide polymorphisms (SNPs) related to fungicide resistance was studied for Botrytis cinerea populations in vineyards and for B. squamosa populations in onion fields. Heterogeneity in this distribution was characterized by performing geostatistical analyses based on semivariograms and through the fitting of discrete probability distributions. Two SNPs known to be responsible for boscalid resistance (H272R and H272Y), both located on the B subunit of the succinate dehydrogenase gene, and one SNP known to be responsible for dicarboximide resistance (I365S) were chosen for B. cinerea in grape. For B. squamosa in onion, one SNP responsible for dicarboximide resistance (I365S homologous) was chosen. One onion field was sampled in 2009 and another one was sampled in 2010 for B. squamosa, and two vineyards were sampled in 2011 for B. cinerea, for a total of four sampled sites. Cluster sampling was carried on a 10-by-10 grid, each of the 100 nodes being the center of a 10-by-10-m quadrat. In each quadrat, 10 samples were collected and analyzed by restriction fragment length polymorphism polymerase chain reaction (PCR) or allele specific PCR. Mean SNP incidence varied from 16 to 68%, with an overall mean incidence of 43%. In the geostatistical analyses, omnidirectional variograms showed spatial autocorrelation characterized by ranges of 21 to 1 m. Various levels of anisotropy were detected, however, with variograms computed in four directions (at 0°, 45°, 90°, and 135° from the within-row direction used as reference), indicating that spatial autocorrelation was prevalent or characterized by a longer range in one direction. For all eight data sets, the β-binomial distribution was found to fit the data better than the binomial distribution. This indicates local aggregation of fungicide resistance among sampling units, as supported by estimates of the parameter θ of the β-binomial distribution of 0.09 to 0.23 (overall median value = 0

  16. Understanding the effects of administrative boundary in sampling spatially embedded networks

    NASA Astrophysics Data System (ADS)

    Chi, Guanghua; Liu, Yu; Shi, Li; Gao, Yong

    2017-01-01

    When analyzing spatially embedded networks, networks consisting of nodes and connections within an administrative boundary are commonly analyzed directly without considering possible errors or biases due to lost connections to nodes outside the network. However, connections exist not only within administrative boundaries but also to nodes outside of the boundaries. This study empirically analyzed the geographical boundary problem using a mobile communication network constructed based on mobile phone data collected in Heilongjiang province, China. We find that although many connections outside of the administrative boundary are lost, sampled networks based on administrative boundaries perform relatively well in terms of degree and clustering coefficient. We find that the mechanisms behind the reliability of these sampled networks include the effects of distance decay and cohesion strength in administrative regions on spatially embedded networks.

  17. Standard Deviation and Intra Prediction Mode Based Adaptive Spatial Error Concealment (SEC) in H.264/AVC

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Wang, Lei; Ikenaga, Takeshi; Goto, Satoshi

    Transmission of compressed video over error prone channels may result in packet losses or errors, which can significantly degrade the image quality. Therefore an error concealment scheme is applied at the video receiver side to mask the damaged video. Considering there are 3 types of MBs (Macro Blocks) in natural video frame, i. e., Textural MB, Edged MB, and Smooth MB, this paper proposes an adaptive spatial error concealment which can choose 3 different methods for these 3 different MBs. For criteria of choosing appropriate method, 2 factors are taken into consideration. Firstly, standard deviation of our proposed edge statistical model is exploited. Secondly, some new features of latest video compression standard H.264/AVC, i. e., intra prediction mode is also considered for criterion formulation. Compared with previous works, which are only based on deterministic measurement, proposed method achieves the best image recovery. Subjective and objective image quality evaluations in experiments confirmed this.

  18. Adaptive electron beam shaping using a photoemission gun and spatial light modulator

    NASA Astrophysics Data System (ADS)

    Maxson, Jared; Lee, Hyeri; Bartnik, Adam C.; Kiefer, Jacob; Bazarov, Ivan

    2015-02-01

    The need for precisely defined beam shapes in photoelectron sources has been well established. In this paper, we use a spatial light modulator and simple shaping algorithm to create arbitrary, detailed transverse laser shapes with high fidelity. We transmit this shaped laser to the photocathode of a high voltage dc gun. Using beam currents where space charge is negligible, and using an imaging solenoid and fluorescent viewscreen, we show that the resultant beam shape preserves these detailed features with similar fidelity. Next, instead of transmitting a shaped laser profile, we use an active feedback on the unshaped electron beam image to create equally accurate and detailed shapes. We demonstrate that this electron beam feedback has the added advantage of correcting for electron optical aberrations, yielding shapes without skew. The method may serve to provide precisely defined electron beams for low current target experiments, space-charge dominated beam commissioning, as well as for online adaptive correction of photocathode quantum efficiency degradation.

  19. Analysis of spatial lamellar distribution from adaptive-optics second harmonic generation corneal images.

    PubMed

    Bueno, Juan M; Palacios, Raquel; Chessey, Mary K; Ginis, Harilaos

    2013-07-01

    The spatial organization of stromal collagen of ex-vivo corneas has been quantified in adaptive-optics second harmonic generation (SHG) images by means of an optimized Fourier transform (FT) based analysis. At a particular depth location, adjacent lamellae often present similar orientations and run parallel to the corneal surface. However this pattern might be combined with interweaved collagen bundles leading to crosshatched structures with different orientations. The procedure here reported provides us with both principal and crosshatched angles. This is also able to automatically distinguish a random distribution from a cross-shaped one, since it uses the ratio of the axes lengths of the best-fitted ellipse of the FT data as an auxiliary parameter. The technique has successfully been applied to SHG images of healthy corneas (both stroma and Bowman's layer) of different species and to corneas undergoing cross-linking treatment.

  20. Region and edge-adaptive sampling and boundary completion for segmentation

    SciTech Connect

    Dillard, Scott E; Prasad, Lakshman; Grazzini, Jacopo A

    2010-01-01

    Edge detection produces a set of points that are likely to lie on discontinuities between objects within an image. We consider faces of the Gabriel graph of these points, a sub-graph of the Delaunay triangulation. Features are extracted by merging these faces using size, shape and color cues. We measure regional properties of faces using a novel shape-dependant sampling method that overcomes undesirable sampling bias of the Delaunay triangles. Instead, sampling is biased so as to smooth regional statistics within the detected object boundaries, and this smoothing adapts to local geometric features of the shape such as curvature, thickness and straightness.

  1. Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

    SciTech Connect

    Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora; Kitzmiller, Joseph A.; Huang, Eric L.; Zink, Erika M.; Sontag, Ryan L.; Orton, Daniel J.; Moore, Ronald J.; Carson, James P.; Smith, Richard D.; Whitsett, Jeffrey A.; Corley, Richard A.; Ambalavanan, Namasivayam; Ansong, Charles

    2016-12-22

    Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow that with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and

  2. Tunable WDM sampling pulse streams using a spatial phase modulator in a biased pulse shaper.

    PubMed

    Sinefeld, David; Shayovitz, Dror; Golani, Ori; Marom, Dan M

    2014-02-01

    We generate transform-limited WDM optical sampling pulse bursts by filtering ultrashort pulses from a mode-locked laser. A phase spatial light modulator (SLM) is used in a biased pulse shaper to circumvent the need to modulate with 2π phase wraps, which are known to limit the phase response. The arrangement compresses and retimes user-selectable bandwidths from the optical short pulse source with precise control of pulse bandwidth, pulse stream rates, and duty cycle.

  3. Minimum detection limit and spatial resolution of thin-sample field-emission electron probe microanalysis.

    PubMed

    Kubo, Yugo; Hamada, Kotaro; Urano, Akira

    2013-12-01

    The minimum detection limit and spatial resolution for a thinned semiconductor sample were determined by electron probe microanalysis (EPMA) using a Schottky field emission (FE) electron gun and wavelength dispersive X-ray spectrometry. Comparison of the FE-EPMA results with those obtained using energy dispersive X-ray spectrometry in conjunction with scanning transmission electron microscopy, confirmed that FE-EPMA is largely superior in terms of detection sensitivity. Thin-sample FE-EPMA is demonstrated as a very effective method for high resolution, high sensitivity analysis in a laboratory environment because a high probe current and high signal-to-noise ratio can be achieved.

  4. Spatial inventory integrating raster databases and point sample data. [Geographic Information System for timber inventory

    NASA Technical Reports Server (NTRS)

    Strahler, A. H.; Woodcock, C. E.; Logan, T. L.

    1983-01-01

    A timber inventory of the Eldorado National Forest, located in east-central California, provides an example of the use of a Geographic Information System (GIS) to stratify large areas of land for sampling and the collection of statistical data. The raster-based GIS format of the VICAR/IBIS software system allows simple and rapid tabulation of areas, and facilitates the selection of random locations for ground sampling. Algorithms that simplify the complex spatial pattern of raster-based information, and convert raster format data to strings of coordinate vectors, provide a link to conventional vector-based geographic information systems.

  5. Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

    PubMed

    Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

    2014-07-01

    Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate.

  6. Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization.

    PubMed

    Petrovskaya, Natalia; Petrovskii, Sergei

    2017-02-01

    Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error-i.e. the difference between the true value of the population size and its estimated value-can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe 'ghost synchronization' when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient.

  7. Spatial and temporal variation in indicator microbe sampling is influential in beach management decisions.

    PubMed

    Enns, Amber A; Vogel, Laura J; Abdelzaher, Amir M; Solo-Gabriele, Helena M; Plano, Lisa R W; Gidley, Maribeth L; Phillips, Matthew C; Klaus, James S; Piggot, Alan M; Feng, Zhixuan; Reniers, Ad J H M; Haus, Brian K; Elmir, Samir M; Zhang, Yifan; Jimenez, Nasly H; Abdel-Mottaleb, Noha; Schoor, Michael E; Brown, Alexis; Khan, Sumbul Q; Dameron, Adrienne S; Salazar, Norma C; Fleming, Lora E

    2012-05-01

    Fecal indicator microbes, such as enterococci, are often used to assess potential health risks caused by pathogens at recreational beaches. Microbe levels often vary based on collection time and sampling location. The primary goal of this study was to assess how spatial and temporal variations in sample collection, which are driven by environmental parameters, impact enterococci measurements and beach management decisions. A secondary goal was to assess whether enterococci levels can be predictive of the presence of Staphylococcus aureus, a skin pathogen. Over a ten-day period, hydrometeorologic data, hydrodynamic data, bather densities, enterococci levels, and S. aureus levels including methicillin-resistant S. aureus (MRSA) were measured in both water and sand. Samples were collected hourly for both water and sediment at knee-depth, and every 6 h for water at waist-depth, supratidal sand, intertidal sand, and waterline sand. Results showed that solar radiation, tides, and rainfall events were major environmental factors that impacted enterococci levels. S. aureus levels were associated with bathing load, but did not correlate with enterococci levels or any other measured parameters. The results imply that frequencies of advisories depend heavily upon sample collection policies due to spatial and temporal variation of enterococci levels in response to environmental parameters. Thus, sampling at different times of the day and at different depths can significantly impact beach management decisions. Additionally, the lack of correlation between S. aureus and enterococci suggests that use of fecal indicators may not accurately assess risk for some pathogens.

  8. Spatial and Temporal Variation in Indicator Microbe Sampling is Influential in Beach Management Decisions

    PubMed Central

    Enns, Amber A.; Vogel, Laura J.; Abdelzaher, Amir M.; Gabriele, Helena M. Solo; Plano, Lisa R.W.; Gidley, Maribeth L.; Phillips, Matthew C.; Klaus, James S.; Piggot, Alan M.; Feng, Zhixuan; Reniers, Adrianus J.H.M.; Haus, Brian K.; Elmir, Samir M.; Zhang, Yifan; Jimenez, Nasly H.; Mottaleb, Noha Abdel; Schoor, Michael E.; Brown, Alexis; Khan, Sumbul Q.; Dameron, Adrienne S.; Salazar, Norma C.; Fleming, Lora E.

    2012-01-01

    Fecal indicator microbes such as enterococci are often used to assess potential health risks caused by pathogens at recreational beaches. Microbe levels often vary based on collection time and sampling location. The primary goal of this study was to assess how spatial and temporal variations in sample collection which are driven by environmental parameters impact enterococci measurements and beach management decisions. A secondary goal was to assess whether enterococci levels can be predictive of the presence of Staphylococcus aureus a skin pathogen. Over a ten day period hydrometeorologic data hydrodynamic data bather densities enterococci levels and S. aureus levels including methicillin-resistant S. aureus (MRSA) were measured in both water and sand. Samples were collected hourly for both water and sediment at knee-depth and every 6 hours for water at waist-depth supratidal sand intertidal sand and waterline sand. Results showed that solar radiation tides and rainfall events were major environmental factors that impacted enterococci levels. S. aureus levels were associated with bathing load but did not correlate with enterococci levels or any other measured parameters. The results imply that frequencies of advisories depend heavily upon sample collection policies due to spatial and temporal variation of enterococci levels in response to environmental parameters. Thus sampling at different times of the day and at different depths can significantly impact beach management decisions. Additionally the lack of correlation between S. aureus and enterococci suggests that use of fecal indicators may not accurately assess risk for some pathogens. PMID:22365370

  9. Effect of different sampling schemes on the spatial placement of conservation reserves in Utah, USA

    USGS Publications Warehouse

    Bassett, S.D.; Edwards, T.C.

    2003-01-01

    We evaluated the effect of three different sampling schemes used to organize spatially explicit biological information had on the spatial placement of conservation reserves in Utah, USA. The three sampling schemes consisted of a hexagon representation developed by the EPA/EMAP program (statistical basis), watershed boundaries (ecological), and the current county boundaries of Utah (socio-political). Four decision criteria were used to estimate effects, including amount of area, length of edge, lowest number of contiguous reserves, and greatest number of terrestrial vertebrate species covered. A fifth evaluation criterion was the effect each sampling scheme had on the ability of the modeled conservation reserves to cover the six major ecoregions found in Utah. Of the three sampling schemes, county boundaries covered the greatest number of species, but also created the longest length of edge and greatest number of reserves. Watersheds maximized species coverage using the least amount of area. Hexagons and watersheds provide the least amount of edge and fewest number of reserves. Although there were differences in area, edge and number of reserves among the sampling schemes, all three schemes covered all the major ecoregions in Utah and their inclusive biodiversity. ?? 2003 Elsevier Science Ltd. All rights reserved.

  10. Spatial aggregation across ephemeral resource patches in insect communities: an adaptive response to natural enemies?

    PubMed

    Rohlfs, Marko; Hoffmeister, Thomas S

    2004-08-01

    Although an increase in competition is a common cost associated with intraspecific crowding, spatial aggregation across food-limited resource patches is a widespread phenomenon in many insect communities. Because intraspecific aggregation of competing insect larvae across, e.show $132#g. fruits, dung, mushrooms etc., is an important means by which many species can coexist (aggregation model of species coexistence), there is a strong need to explore the mechanisms that contribute to the maintenance of this kind of spatial resource exploitation. In the present study, by using Drosophila-parasitoid interactions as a model system, we tested the hypothesis whether intraspecific aggregation reflects an adaptive response to natural enemies. Most of the studies that have hitherto been carried out on Drosophila-parasitoid interactions used an almost two-dimensional artificial host environment, where host larvae could not escape from parasitoid attacks, and have demonstrated positive density-dependent parasitism risk. To test whether these studies captured the essence of such interactions, we used natural breeding substrates (decaying fruits). In a first step, we analysed the parasitism risk of Drosophila larvae on a three-dimensional substrate in natural fly communities in the field, and found that the risk of parasitism decreased with increasing host larval density (inverse density dependence). In a second step, we analysed the parasitism risk of Drosophila subobscura larvae on three breeding substrate types exposed to the larval parasitoids Asobara tabida and Leptopilina heterotoma. We found direct density-dependent parasitism on decaying sloes, inverse density dependence on plums, and a hump-shaped relationship between fly larval density and parasitism risk on crab apples. On crab apples and plums, fly larvae benefited from a density-dependent refuge against the parasitoids. While the proportion of larvae feeding within the fruit tissues increased with larval density

  11. High spectral and spatial resolution spectroscopy of YSOs with a silicon grism and adaptive optics

    NASA Astrophysics Data System (ADS)

    Ge, J.; Lloyd, J. P.; Gavel, D.; Macintosh, B.; Max, C. E.; Ciarlo, D.; Kuzmenko, P.; Graham, J. R.

    2000-12-01

    We have obtained complete K band spectra of a total of 6 T Tauri and Ae/Be stars and their close companions at a spectral resolution of R ≈ 5000 using a silicon grism at the Lick 3m telescope. These results represent our first scientific observations conducted by the high resolution silicon grisms. Coupled with the LLNL adaptive optics system, a spatial resolution of 0.2 arcsec was achieved to allow observations of the companions with separations between 0.3-1.3 arcsec. The complete wavelength coverage was achieved by placing 16 cross-dispersed echelle orders on a 256x256 HgCdTe array with the silicon grism operating on high diffraction orders and a low dispersing CaF2 grism as a cross-disperser. High spectral resolution observations allow us to characterize each of the companions. Analysis of the spectra of these YSOs will be reported. The observations also allow us to measure the optical performance of the second generation of silicon grisms made with the techniques developed in early 2000. The new silicon grism has a peak efficiency of 45% and scattered light of ~ 8% in the K band. New techniques have been developed at Penn State to further reduce scattered light in the K band (Bernecker et al. this meeting) and are being applied in fabricating the third generation of silicon grisms for scientific observations. Fabrication of the silicon grisms and work on the Lick adaptive optics system was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract W-7405-ENG-48. Graham and Lloyd were also supported by the Center for Adaptive Optics under the STC Program of the National Science Foundation, Agreement No. AST-9876783

  12. Spatial distribution of grape root borer (Lepidoptera: Sesiidae) infestations in Virginia vineyards and implications for sampling.

    PubMed

    Rijal, J P; Brewster, C C; Bergh, J C

    2014-06-01

    Grape root borer, Vitacea polistiformis (Harris) (Lepidoptera: Sesiidae) is a potentially destructive pest of grape vines, Vitis spp. in the eastern United States. After feeding on grape roots for ≍2 yr in Virginia, larvae pupate beneath the soil surface around the vine base. Adults emerge during July and August, leaving empty pupal exuviae on or protruding from the soil. Weekly collections of pupal exuviae from an ≍1-m-diameter weed-free zone around the base of a grid of sample vines in Virginia vineyards were conducted in July and August, 2008-2012, and their distribution was characterized using both nonspatial (dispersion) and spatial techniques. Taylor's power law showed a significant aggregation of pupal exuviae, based on data from 19 vineyard blocks. Combined use of geostatistical and Spatial Analysis by Distance IndicEs methods indicated evidence of an aggregated pupal exuviae distribution pattern in seven of the nine blocks used for those analyses. Grape root borer pupal exuviae exhibited spatial dependency within a mean distance of 8.8 m, based on the range values of best-fitted variograms. Interpolated and clustering index-based infestation distribution maps were developed to show the spatial pattern of the insect within the vineyard blocks. The temporal distribution of pupal exuviae showed that the majority of moths emerged during the 3-wk period spanning the third week of July and the first week of August. The spatial distribution of grape root borer pupal exuviae was used in combination with temporal moth emergence patterns to develop a quantitative and efficient sampling scheme to assess infestations.

  13. Self-adaptive sampling rate data acquisition in JET's correlation reflectometer

    SciTech Connect

    Arcas, G. de; Lopez, J. M.; Ruiz, M.; Barrera, E.; Vega, J.; Fonseca, A.

    2008-10-15

    Data acquisition systems with self-adaptive sampling rate capabilities have been proposed as a solution to reduce the shear amount of data collected in every discharge of present fusion devices. This paper discusses the design of such a system for its use in the KG8B correlation reflectometer at JET. The system, which is based on the ITMS platform, continuously adapts the sample rate during the acquisition depending on the signal bandwidth. Data are acquired continuously at the expected maximum sample rate and transferred to a memory buffer in the host processor. Thereafter the rest of the process is based on software. Data are read from the memory buffer in blocks and for each block an intelligent decimation algorithm is applied. The decimation algorithm determines the signal bandwidth for each block in order to choose the optimum sample rate for that block, and from there the decimation factor to be used. Memory buffers are used to adapt the throughput of the three main software modules (data acquisition, processing, and storage) following a typical producer-consumer architecture. The system optimizes the amount of data collected while maintaining the same information. Design issues are discussed and results of performance evaluation are presented.

  14. Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

    PubMed Central

    Chu, Hone-Jay; Lin, Yu-Pin; Huang, Yu-Long; Wang, Yung-Chieh

    2009-01-01

    The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS), sequential Gaussian simulation (SGS) and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI) images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE). Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management. PMID:22399972

  15. Characterization of spatial distribution of Tetranychus urticae in peppermint in California and implication for improving sampling plan.

    PubMed

    Rijal, Jhalendra P; Wilson, Rob; Godfrey, Larry D

    2016-02-01

    Twospotted spider mite, Tetranychus urticae Koch, is an important pest of peppermint in California, USA. Spider mite feeding on peppermint leaves causes physiological changes in the plant, which coupling with the favorable environmental condition can lead to increased mite infestations. Significant yield loss can occur in absence of pest monitoring and timely management. Understating the within-field spatial distribution of T. urticae is critical for the development of reliable sampling plan. The study reported here aims to characterize the spatial distribution of mite infestation in four commercial peppermint fields in northern California using spatial techniques, variogram and Spatial Analysis by Distance IndicEs (SADIE). Variogram analysis revealed that there was a strong evidence for spatially dependent (aggregated) mite population in 13 of 17 sampling dates and the physical distance of the aggregation reached maximum to 7 m in peppermint fields. Using SADIE, 11 of 17 sampling dates showed aggregated distribution pattern of mite infestation. Combining results from variogram and SADIE analysis, the spatial aggregation of T. urticae was evident in all four fields for all 17 sampling dates evaluated. Comparing spatial association using SADIE, ca. 62% of the total sampling pairs showed a positive association of mite spatial distribution patterns between two consecutive sampling dates, which indicates a strong spatial and temporal stability of mite infestation in peppermint fields. These results are discussed in relation to behavior of spider mite distribution within field, and its implications for improving sampling guidelines that are essential for effective pest monitoring and management.

  16. Spatial Variation of Soil Lead in an Urban Community Garden: Implications for Risk-Based Sampling.

    PubMed

    Bugdalski, Lauren; Lemke, Lawrence D; McElmurry, Shawn P

    2014-01-01

    Soil lead pollution is a recalcitrant problem in urban areas resulting from a combination of historical residential, industrial, and transportation practices. The emergence of urban gardening movements in postindustrial cities necessitates accurate assessment of soil lead levels to ensure safe gardening. In this study, we examined small-scale spatial variability of soil lead within a 15 × 30 m urban garden plot established on two adjacent residential lots located in Detroit, Michigan, USA. Eighty samples collected using a variably spaced sampling grid were analyzed for total, fine fraction (less than 250 μm), and bioaccessible soil lead. Measured concentrations varied at sampling scales of 1-10 m and a hot spot exceeding 400 ppm total soil lead was identified in the northwest portion of the site. An interpolated map of total lead was treated as an exhaustive data set, and random sampling was simulated to generate Monte Carlo distributions and evaluate alternative sampling strategies intended to estimate the average soil lead concentration or detect hot spots. Increasing the number of individual samples decreases the probability of overlooking the hot spot (type II error). However, the practice of compositing and averaging samples decreased the probability of overestimating the mean concentration (type I error) at the expense of increasing the chance for type II error. The results reported here suggest a need to reconsider U.S. Environmental Protection Agency sampling objectives and consequent guidelines for reclaimed city lots where soil lead distributions are expected to be nonuniform.

  17. Determination of conformational free energies of peptides by multidimensional adaptive umbrella sampling

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Gu, Yan; Liu, Haiyan

    2006-09-01

    We improve the multidimensional adaptive umbrella sampling method for the computation of conformational free energies of biomolecules. The conformational transition between the α-helical and β-hairpin conformational states of an alanine decapeptide is used as an example. Convergence properties of the weighted-histogram-analysis-based adaptive umbrella sampling can be improved by using multiple replicas in each adaptive iteration and by using adaptive updating of the bounds of the umbrella potential. Using positional root-mean-square deviations from structures of the α-helical and β-hairpin reference states as reaction coordinates, we obtained well-converged free energy surfaces of both the in-vacuum and in-solution decapeptide systems. From the free energy surfaces well-converged relative free energies between the two conformational states can be derived. Advantages and disadvantages of different methods for obtaining conformational free energies as well as implications of our results in studying conformational transitions of proteins and in improving force field are discussed.

  18. Using continuous in-situ measurements to adaptively trigger urban storm water samples

    NASA Astrophysics Data System (ADS)

    Wong, B. P.; Kerkez, B.

    2015-12-01

    Until cost-effective in-situ sensors are available for biological parameters, nutrients and metals, automated samplers will continue to be the primary source of reliable water quality measurements. Given limited samples bottles, however, autosamplers often obscure insights on nutrient sources and biogeochemical processes which would otherwise be captured using a continuous sampling approach. To that end, we evaluate the efficacy a novel method to measure first-flush nutrient dynamics in flashy, urban watersheds. Our approach reduces the number of samples required to capture water quality dynamics by leveraging an internet-connected sensor node, which is equipped with a suite of continuous in-situ sensors and an automated sampler. To capture both the initial baseflow as well as storm concentrations, a cloud-hosted adaptive algorithm analyzes the high-resolution sensor data along with local weather forecasts to optimize a sampling schedule. The method was tested in a highly developed urban catchment in Ann Arbor, Michigan and collected samples of nitrate, phosphorus, and suspended solids throughout several storm events. Results indicate that the watershed does not exhibit first flush dynamics, a behavior that would have been obscured when using a non-adaptive sampling approach.

  19. Reducing Uncertainty In Ecosystem Structure Inventories From Spaceborne Lidar Using Alternate Spatial Sampling Approaches

    NASA Astrophysics Data System (ADS)

    Lefsky, M. A.; Ramond, T.; Weimer, C. S.

    2010-12-01

    Current and proposed spaceborne lidar sensors sample the land surface using observations along transects in which consecutive observations in the along-track dimension are either contiguous (e.g. VCL, DESDynI, Livex) or spaced (ICESat). These sampling patterns are inefficient because multiple observations are made of a spatially autocorrelated phenomenon (i.e. vegetation patches) while large areas of the landscape are left un-sampled. This results in higher uncertainty in estimates of average ecosystem structure than would be obtained using either random sampling or sampling in regular grids. We compared three sampling scenarios for spaceborne lidar: five transects spaced every 850 m across-track with contiguous 25m footprints along-track, the same number of footprints distributed randomly, and a hybrid approach that retains the central transect of contiguous 25m footprints and distributes the remainder of the footprints into a grid with 178 m spacing. We used simulated ground tracks at four latitudes for a realistic spaceborne lidar mission and calculated the amount of time required to achieve 150 m spacing between transects and the number of near-coincident observations for each scenario. We used four lidar height datasets collected using the Laser Vegetation Imaging Sensor (La Selva, Costa Rica, Sierra Nevada, California, Duke Forest, North Carolina and Harvard Forest, Massachusetts) to calculate the standard error of estimates of landscape height for each scenario. We found that a hybrid sampling approach reduced the amount of time required to reach a transect spacing of 150 m by a factor of three at all four latitudes, and that the number of near-coincident observations was greater by a factor of five at the equator and at least equal throughout the range of latitudes sampled. The standard error of landscape height was between 2 and 2.5 times smaller using either hybrid or random sampling than using transect sampling. As the pulses generated by a spaceborne

  20. Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations

    USGS Publications Warehouse

    Dorazio, R.M.; Jelks, H.L.; Jordan, F.

    2005-01-01

     A statistical modeling framework is described for estimating the abundances of spatially distinct subpopulations of animals surveyed using removal sampling. To illustrate this framework, hierarchical models are developed using the Poisson and negative-binomial distributions to model variation in abundance among subpopulations and using the beta distribution to model variation in capture probabilities. These models are fitted to the removal counts observed in a survey of a federally endangered fish species. The resulting estimates of abundance have similar or better precision than those computed using the conventional approach of analyzing the removal counts of each subpopulation separately. Extension of the hierarchical models to include spatial covariates of abundance is straightforward and may be used to identify important features of an animal's habitat or to predict the abundance of animals at unsampled locations.

  1. Adaptation and Validation of the Sexual Assertiveness Scale (SAS) in a Sample of Male Drug Users.

    PubMed

    Vallejo-Medina, Pablo; Sierra, Juan Carlos

    2015-04-21

    The aim of the present study was to adapt and validate the Sexual Assertiveness Scale (SAS) in a sample of male drug users. A sample of 326 male drug users and 322 non-clinical males was selected by cluster sampling and convenience sampling, respectively. Results showed that the scale had good psychometric properties and adequate internal consistency reliability (Initiation = .66, Refusal = .74 and STD-P = .79). An evaluation of the invariance showed strong factor equivalence between both samples. A high and moderate effect of Differential Item Functioning was only found in items 1 and 14 (∆R 2 Nagelkerke = .076 and .037, respectively). We strongly recommend not using item 1 if the goal is to compare the scores of both groups, otherwise the comparison will be biased. Correlations obtained between the CSFQ-14 and the safe sex ratio and the SAS subscales were significant (CI = 95%) and indicated good concurrent validity. Scores of male drug users were similar to those of non-clinical males. Therefore, the adaptation of the SAS to drug users provides enough guarantees for reliable and valid use in both clinical practice and research, although care should be taken with item 1.

  2. Will a perfect model agree with perfect observations? The impact of spatial sampling

    NASA Astrophysics Data System (ADS)

    Schutgens, Nick A. J.; Gryspeerdt, Edward; Weigum, Natalie; Tsyro, Svetlana; Goto, Daisuke; Schulz, Michael; Stier, Philip

    2016-05-01

    The spatial resolution of global climate models with interactive aerosol and the observations used to evaluate them is very different. Current models use grid spacings of ˜ 200 km, while satellite observations of aerosol use so-called pixels of ˜ 10 km. Ground site or airborne observations relate to even smaller spatial scales. We study the errors incurred due to different resolutions by aggregating high-resolution simulations (10 km grid spacing) over either the large areas of global model grid boxes ("perfect" model data) or small areas corresponding to the pixels of satellite measurements or the field of view of ground sites ("perfect" observations). Our analysis suggests that instantaneous root-mean-square (RMS) differences of perfect observations from perfect global models can easily amount to 30-160 %, for a range of observables like AOT (aerosol optical thickness), extinction, black carbon mass concentrations, PM2.5, number densities and CCN (cloud condensation nuclei). These differences, due entirely to different spatial sampling of models and observations, are often larger than measurement errors in real observations. Temporal averaging over a month of data reduces these differences more strongly for some observables (e.g. a threefold reduction for AOT), than for others (e.g. a twofold reduction for surface black carbon concentrations), but significant RMS differences remain (10-75 %). Note that this study ignores the issue of temporal sampling of real observations, which is likely to affect our present monthly error estimates. We examine several other strategies (e.g. spatial aggregation of observations, interpolation of model data) for reducing these differences and show their effectiveness. Finally, we examine consequences for the use of flight campaign data in global model evaluation and show that significant biases may be introduced depending on the flight strategy used.

  3. Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

    PubMed

    Piastra, Marco

    2013-05-01

    Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise.

  4. Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations

    PubMed Central

    Wang, Junxiao; Wang, Xiaorui; Zhou, Shenglu; Wu, Shaohua; Zhu, Yan; Lu, Chunfeng

    2016-01-01

    With China’s rapid economic development, the reduction in arable land has emerged as one of the most prominent problems in the nation. The long-term dynamic monitoring of arable land quality is important for protecting arable land resources. An efficient practice is to select optimal sample points while obtaining accurate predictions. To this end, the selection of effective points from a dense set of soil sample points is an urgent problem. In this study, data were collected from Donghai County, Jiangsu Province, China. The number and layout of soil sample points are optimized by considering the spatial variations in soil properties and by using an improved simulated annealing (SA) algorithm. The conclusions are as follows: (1) Optimization results in the retention of more sample points in the moderate- and high-variation partitions of the study area; (2) The number of optimal sample points obtained with the improved SA algorithm is markedly reduced, while the accuracy of the predicted soil properties is improved by approximately 5% compared with the raw data; (3) With regard to the monitoring of arable land quality, a dense distribution of sample points is needed to monitor the granularity. PMID:27706051

  5. Damage identification in beams using speckle shearography and an optimal spatial sampling

    NASA Astrophysics Data System (ADS)

    Mininni, M.; Gabriele, S.; Lopes, H.; Araújo dos Santos, J. V.

    2016-10-01

    Over the years, the derivatives of modal displacement and rotation fields have been used to localize damage in beams. Usually, the derivatives are computed by applying finite differences. The finite differences propagate and amplify the errors that exist in real measurements, and thus, it is necessary to minimize this problem in order to get reliable damage localizations. A way to decrease the propagation and amplification of the errors is to select an optimal spatial sampling. This paper presents a technique where an optimal spatial sampling of modal rotation fields is computed and used to obtain the modal curvatures. Experimental measurements of modal rotation fields of a beam with single and multiple damages are obtained with shearography, which is an optical technique allowing the measurement of full-fields. These measurements are used to test the validity of the optimal sampling technique for the improvement of damage localization in real structures. An investigation on the ability of a model updating technique to quantify the damage is also reported. The model updating technique is defined by the variations of measured natural frequencies and measured modal rotations and aims at calibrating the values of the second moment of area in the damaged areas, which were previously localized.

  6. HydroCrowd: Citizen-empowered snapshot sampling to assess the spatial distribution of stream

    NASA Astrophysics Data System (ADS)

    Kraft, Philipp; Breuer, Lutz; Bach, Martin; Aubert, Alice H.; Frede, Hans-Georg

    2016-04-01

    Large parts of groundwater bodies in Central Europe shows elevated nitrate concentrations. While groundwater samplings characterize the water quality for a longer period, surface water resources, in particular streams, may be subject of fast concentration fluctuations and measurements distributed in time cannot by compared. Thus, sampling should be done in a short time frame (snapshot sampling). To describe the nitrogen status of streams in Germany, we organized a crowdsourcing experiment in the form of a snapshot sampling at a distinct day. We selected a national holiday in fall 2013 (Oct, 3rd) to ensure that a) volunteers have time to take a sample, b) stream water is unlikely to be influenced by recent agricultural fertilizer application, and c) low flow conditions are likely. We distributed 570 cleaned sample flasks to volunteers and got 280 filled flasks back with coordinates and other meta data about the sampled stream. The volunteers were asked to visit any stream outside of settlements and fill the flask with water from that stream. The samples were analyzed in our lab for concentration of nitrate, ammonium and dissolved organic nitrogen (DON), results are presented as a map on the web site http://www.uni-giessen.de/hydrocrowd. The measured results are related to catchment features such as population density, soil properties, and land use derived from national geodata sources. The statistical analyses revealed a significant correlation between nitrate and fraction of arable land (0.46), as well as soil humus content (0.37), but a weak correlation with population density (0.12). DON correlations were weak but significant with humus content (0.14) and arable land (0.13). The mean contribution of DON to total dissolved nitrogen was 22%. Crowdsourcing turned out to be a useful method to assess the spatial distribution of stream solutes, as considerable amounts of samples were collected with comparatively little effort at a single day.

  7. Application of mobile sampling to investigate spatial variation in fine particle composition

    NASA Astrophysics Data System (ADS)

    Li, Hugh Z.; Dallmann, Timothy R.; Gu, Peishi; Presto, Albert A.

    2016-10-01

    Long-term exposure to particulate matter (PM) is a major contributor to air pollution related deaths. Evidence indicates that metals play an important role in harming human health due to their redox potential. We conducted a mobile sampling campaign in 2013 summer and winter in Pittsburgh, PA to characterize spatial variation in PM2.5 mass and composition. Thirty-six sites were chosen based on three stratification variables: traffic density, proximity to point sources, and elevation. We collected filters in three time sessions (morning, afternoon, and overnight) in each season. X-ray fluorescence (XRF) was used to analyze concentrations of 26 elements: Na, Mg, Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Zr, Cd, Sb, and Pb. Trace elements had a broad range of concentrations from 0 to 300 ng/m3. Comparison of data from mobile sampling filters with stationary monitors suggested that the mobile sampling strategy did not lead to a biased dataset. We developed Land Use Regression (LUR) models to describe spatial variation of PM2.5, Si, S, Cl, K, Ca, Ti, Cr, Fe, Cu, and Zn. Using ArcGIS-10.3 (ESRI, Redlands, CA), we extracted different independent variables related to traffic influence, land-use type, and facility emissions based on the National Emission Inventory (NEI). To validate LUR models, we used regression diagnostics such as leave-one-out cross validation (LOOCV), mean studentized prediction residual (MSPR), and root mean square of studentized residuals (RMS). The number of predictors in final LUR models ranged from 1 to 6. Models had an average R2 of 0.57 (SD = 0.16). Traffic related variables explained the most variability with an average R2 contribution of 0.20 (SD = 0.20). Overall, these results demonstrated significant intra-urban spatial variability of fine particle composition.

  8. Adaptive sampling strategy support for the unlined chromic acid pit, chemical waste landfill, Sandia National Laboratories, Albuquerque, New Mexico

    SciTech Connect

    Johnson, R.L.

    1993-11-01

    Adaptive sampling programs offer substantial savings in time and money when assessing hazardous waste sites. Key to some of these savings is the ability to adapt a sampling program to the real-time data generated by an adaptive sampling program. This paper presents a two-prong approach to supporting adaptive sampling programs: a specialized object-oriented database/geographical information system (SitePlanner{trademark} ) for data fusion, management, and display and combined Bayesian/geostatistical methods (PLUME) for contamination-extent estimation and sample location selection. This approach is applied in a retrospective study of a subsurface chromium plume at Sandia National Laboratories` chemical waste landfill. Retrospective analyses suggest the potential for characterization cost savings on the order of 60% through a reduction in the number of sampling programs, total number of soil boreholes, and number of samples analyzed from each borehole.

  9. An attentional-adaptation account of spatial negative priming: evidence from event-related potentials.

    PubMed

    Liu, Xiaonan L; Walsh, Matthew M; Reder, Lynne M

    2014-03-01

    Negative priming (NP) refers to a slower response to a target stimulus if it has been previously ignored. To examine theoretical accounts of spatial NP, we recorded behavioral measures and event-related potentials (ERPs) in a target localization task. A target and distractor briefly appeared, and the participant pressed a key corresponding to the target's location. The probability of the distractor appearing in each of four locations varied, whereas the target appeared with equal probabilities in all locations. We found that response times (RTs) were fastest when the prime distractor appeared in its most probable (frequent) location and when the prime target appeared in the location that never contained a distractor. Moreover, NP effects varied as a function of location: They were smallest when targets followed distractors in the frequent distractor location-a finding not predicted by episodic-retrieval or suppression accounts of NP. The ERP results showed that the P2, an ERP component associated with attentional orientation, was smaller in prime displays when the distractor appeared in its frequent location. Moreover, no differences were apparent between negative-prime and control trials in the N2, which is associated with suppression processes, nor in the P3, which is associated with episodic retrieval processes. These results indicate that the spatial NP effect is caused by both short- and long-term adaptation in preferences based on the history of inspecting unsuccessful locations. This article is dedicated to the memory of Edward E. Smith, and we indicate how this study was inspired by his research career.

  10. Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

    PubMed Central

    Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

    2016-01-01

    The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

  11. Test Sample for the Spatially Resolved Quantification of Illicit Drugs on Fingerprints Using Imaging Mass Spectrometry.

    PubMed

    Muramoto, Shin; Forbes, Thomas P; van Asten, Arian C; Gillen, Greg

    2015-01-01

    A novel test sample for the spatially resolved quantification of illicit drugs on the surface of a fingerprint using time-of-flight secondary ion mass spectrometry (ToF-SIMS) and desorption electrospray ionization mass spectrometry (DESI-MS) was demonstrated. Calibration curves relating the signal intensity to the amount of drug deposited on the surface were generated from inkjet-printed arrays of cocaine, methamphetamine, and heroin with a deposited-mass ranging nominally from 10 pg to 50 ng per spot. These curves were used to construct concentration maps that visualized the spatial distribution of the drugs on top of a fingerprint, as well as being able to quantify the amount of drugs in a given area within the map. For the drugs on the fingerprint on silicon, ToF-SIMS showed great success, as it was able to generate concentration maps of all three drugs. On the fingerprint on paper, only the concentration map of cocaine could be constructed using ToF-SIMS and DESI-MS, as the signals of methamphetamine and heroin were completely suppressed by matrix and substrate effects. Spatially resolved quantification of illicit drugs using imaging mass spectrometry is possible, but the choice of substrates could significantly affect the results.

  12. Signatures of local adaptation in lowland and highland teosintes from whole-genome sequencing of pooled samples.

    PubMed

    Fustier, M-A; Brandenburg, J-T; Boitard, S; Lapeyronnie, J; Eguiarte, L E; Vigouroux, Y; Manicacci, D; Tenaillon, M I

    2017-03-03

    Spatially varying selection triggers differential adaptation of local populations. Here, we mined the determinants of local adaptation at the genomewide scale in the two closest maize wild relatives, the teosintes Zea mays ssp parviglumis and ssp. mexicana. We sequenced 120 individuals from six populations: two lowland, two intermediate and two highland populations sampled along two altitudinal gradients. We detected 8 479 581 single nucleotide polymorphisms (SNPs) covered in the six populations with an average sequencing depth per site per population ranging from 17.0× to 32.2×. Population diversity varied from 0.10 to 0.15, and linkage disequilibrium decayed very rapidly. We combined two differentiation-based methods, and correlation of allele frequencies with environmental variables to detect outlier SNPs. Outlier SNPs displayed significant clustering. From clusters, we identified 47 candidate regions. We further modified a haplotype-based method to incorporate genotype uncertainties in haplotype calling, and applied it to candidate regions. We retrieved evidence for selection at the haplotype level in 53% of our candidate regions, and in 70% of the cases the same haplotype was selected in the two lowland or the two highland populations. We recovered a candidate region located within a previously characterized inversion on chromosome 1. We found evidence of a soft sweep at a locus involved in leaf macrohair variation. Finally, our results revealed frequent colocalization between our candidate regions and loci involved in the variation of traits associated with plant-soil interactions such as root morphology, aluminium and low phosphorus tolerance. Soil therefore appears to be a major driver of local adaptation in teosintes.

  13. A cautionary note on substituting spatial subunits for repeated temporal sampling in studies of site occupancy

    USGS Publications Warehouse

    Kendall, William L.; White, Gary C.

    2009-01-01

    1. Assessing the probability that a given site is occupied by a species of interest is important to resource managers, as well as metapopulation or landscape ecologists. Managers require accurate estimates of the state of the system, in order to make informed decisions. Models that yield estimates of occupancy, while accounting for imperfect detection, have proven useful by removing a potentially important source of bias. To account for detection probability, multiple independent searches per site for the species are required, under the assumption that the species is available for detection during each search of an occupied site. 2. We demonstrate that when multiple samples per site are defined by searching different locations within a site, absence of the species from a subset of these spatial subunits induces estimation bias when locations are exhaustively assessed or sampled without replacement. 3. We further demonstrate that this bias can be removed by choosing sampling locations with replacement, or if the species is highly mobile over a short period of time. 4. Resampling an existing data set does not mitigate bias due to exhaustive assessment of locations or sampling without replacement. 5. Synthesis and applications. Selecting sampling locations for presence/absence surveys with replacement is practical in most cases. Such an adjustment to field methods will prevent one source of bias, and therefore produce more robust statistical inferences about species occupancy. This will in turn permit managers to make resource decisions based on better knowledge of the state of the system.

  14. The Portuguese adaptation of the Gudjonsson Suggestibility Scale (GSS1) in a sample of inmates.

    PubMed

    Pires, Rute; Silva, Danilo R; Ferreira, Ana Sousa

    2014-01-01

    This paper comprises two studies which address the validity of the Portuguese adaptation of the Gudjonsson Suggestibility Scale, GSS1. In study 1, the means and standard deviations for the suggestibility results of a sample of Portuguese inmates (N=40, Mage=37.5 years, SD=8.1) were compared to those of a sample of Icelandic inmates (Gudjonsson, 1997; Gudjonsson & Sigurdsson, 1996). Portuguese inmates' results were in line with the original results. In study 2, the means and standard deviations for the suggestibility results of the sample of Portuguese inmates were compared to those of a general Portuguese population sample (N=57, Mage=36.1 years, SD=12.7). The forensic sample obtained significantly higher scores in suggestibility measures than the general population sample. ANOVA confirmed that the increased suggestibility in the inmates sample was due to the limited memory capacity of this latter group. Given that the results of both studies 1 and 2 are in keeping with the author's original results (Gudjonsson, 1997), this may be regarded as a confirmation of the validity of the Portuguese GSS1.

  15. Spatially-Optimized Sequential Sampling Plan for Cabbage Aphids Brevicoryne brassicae L. (Hemiptera: Aphididae) in Canola Fields.

    PubMed

    Severtson, Dustin; Flower, Ken; Nansen, Christian

    2016-08-01

    The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact.

  16. Adaptive millimeter-wave synthetic aperture imaging for compressive sampling of sparse scenes.

    PubMed

    Mrozack, Alex; Heimbeck, Martin; Marks, Daniel L; Richard, Jonathan; Everitt, Henry O; Brady, David J

    2014-06-02

    We apply adaptive sensing techniques to the problem of locating sparse metallic scatterers using high-resolution, frequency modulated continuous wave W-band RADAR. Using a single detector, a frequency stepped source, and a lateral translation stage, inverse synthetic aperture RADAR reconstruction techniques are used to search for one or two wire scatterers within a specified range, while an adaptive algorithm determined successive sampling locations. The two-dimensional location of each scatterer is thereby identified with sub-wavelength accuracy in as few as 1/4 the number of lateral steps required for a simple raster scan. The implications of applying this approach to more complex scattering geometries are explored in light of the various assumptions made.

  17. Radiative heat transfer between metallic gratings using Fourier modal method with adaptive spatial resolution

    NASA Astrophysics Data System (ADS)

    Messina, Riccardo; Noto, Antonio; Guizal, Brahim; Antezza, Mauro

    2017-03-01

    We calculate the radiative heat transfer between two identical metallic one-dimensional lamellar gratings. To this aim we present and exploit a modification to the widely used Fourier modal method, known as adaptive spatial resolution, based on a stretch of the coordinate associated with the periodicity of the grating. We first show that this technique dramatically improves the rate of convergence when calculating the heat flux, allowing us to explore smaller separations. We then present a study of heat flux as a function of the grating height, highlighting a remarkable amplification of the exchanged energy, ascribed to the appearance of spoof-plasmon modes, whose behavior is also spectrally investigated. Differently from previous works, our method allows us to explore a range of grating heights extending over several orders of magnitude. By comparing our results to recent studies we find a consistent quantitative disagreement with some previously obtained results going up to 50%. In some cases, this disagreement is explained in terms of an incorrect connection between the reflection operators of the two gratings.

  18. Evolution of cooperation in the spatial public goods game with adaptive reputation assortment

    NASA Astrophysics Data System (ADS)

    Chen, Mei-huan; Wang, Li; Sun, Shi-wen; Wang, Juan; Xia, Cheng-yi

    2016-01-01

    We present a new spatial public goods game model, which takes the individual reputation and behavior diversity into account at the same time, to investigate the evolution of cooperation. Initially, each player x will be endowed with an integer Rx between 1 and Rmax to characterize his reputation value, which will be adaptively varied according to the strategy action at each time step. Then, the agents play the game and the system proceeds in accordance with a Fermi-like rule, in which a multiplicative factor (wy) to denote the individual difference to perform the strategy transfer will be placed before the traditional Fermi probability. For influential participants, wy is set to be 1.0, but be a smaller value w (0 < w < 1) for non-influential ones. Large quantities of simulations demonstrate that the cooperation behavior will be obviously influenced by the reputation threshold (RC), and the greater the threshold, the higher the fraction of cooperators. The origin of promotion of cooperation will be attributed to the fact that the larger reputation threshold renders the higher heterogeneity in the fraction of two types of players and strategy spreading capability. Our work is conducive to a better understanding of the emergence of cooperation within many real-world systems.

  19. Fine-granularity and spatially-adaptive regularization for projection-based image deblurring.

    PubMed

    Li, Xin

    2011-04-01

    This paper studies two classes of regularization strategies to achieve an improved tradeoff between image recovery and noise suppression in projection-based image deblurring. The first is based on a simple fact that r-times Landweber iteration leads to a fixed level of regularization, which allows us to achieve fine-granularity control of projection-based iterative deblurring by varying the value r. The regularization behavior is explained by using the theory of Lagrangian multiplier for variational schemes. The second class of regularization strategy is based on the observation that various regularized filters can be viewed as nonexpansive mappings in the metric space. A deeper understanding about different regularization filters can be gained by probing into their asymptotic behavior--the fixed point of nonexpansive mappings. By making an analogy to the states of matter in statistical physics, we can observe that different image structures (smooth regions, regular edges and textures) correspond to different fixed points of nonexpansive mappings when the temperature(regularization) parameter varies. Such an analogy motivates us to propose a deterministic annealing based approach toward spatial adaptation in projection-based image deblurring. Significant performance improvements over the current state-of-the-art schemes have been observed in our experiments, which substantiates the effectiveness of the proposed regularization strategies.

  20. Adaptive engineering of coherent soft-x-rays by temporal and spatial laser-pulse shaping

    NASA Astrophysics Data System (ADS)

    Pfeifer, Thomas

    2005-03-01

    We demonstrate qualitative amplitude shaping of the coherent soft x-ray spectrum produced in the process of high-harmonic generation. This is accomplished by applying adaptive femtosecond pulse shaping methods. We performed the basic operations of complete spectral control by 1) selective generation of extended parts of the high-harmonic spectra, 2) tunable single harmonic generation and 3) creation of spectral holes (suppression of harmonics) in the plateau region of the spectrum. Our ability to qualitatively ``engineer'' the coherent spectral properties by application of temporal and spatial laser-pulse-shaping methods has immediate consequences for the developing field of attosecond x-ray science. Control over the spectrum is directly related to the control over the attosecond pulse shape as we will show by comparing experiment with simulation. In addition, even more important is the prospect to extend the field of coherent control into the soft x-ray range. In the future, the proposed technique will allow us to directly manipulate electronic motion on its natural attosecond time scale.

  1. Improving spatial adaptivity of nonlocal means in low-dosed CT imaging using pointwise fractal dimension.

    PubMed

    Zheng, Xiuqing; Liao, Zhiwu; Hu, Shaoxiang; Li, Ming; Zhou, Jiliu

    2013-01-01

    NLMs is a state-of-art image denoising method; however, it sometimes oversmoothes anatomical features in low-dose CT (LDCT) imaging. In this paper, we propose a simple way to improve the spatial adaptivity (SA) of NLMs using pointwise fractal dimension (PWFD). Unlike existing fractal image dimensions that are computed on the whole images or blocks of images, the new PWFD, named pointwise box-counting dimension (PWBCD), is computed for each image pixel. PWBCD uses a fixed size local window centered at the considered image pixel to fit the different local structures of images. Then based on PWBCD, a new method that uses PWBCD to improve SA of NLMs directly is proposed. That is, PWBCD is combined with the weight of the difference between local comparison windows for NLMs. Smoothing results for test images and real sinograms show that PWBCD-NLMs with well-chosen parameters can preserve anatomical features better while suppressing the noises efficiently. In addition, PWBCD-NLMs also has better performance both in visual quality and peak signal to noise ratio (PSNR) than NLMs in LDCT imaging.

  2. Adaptive Bessel-autocorrelation of ultrashort pulses with phase-only spatial light modulators

    NASA Astrophysics Data System (ADS)

    Huferath-von Luepke, Silke; Bock, Martin; Grunwald, Ruediger

    2009-06-01

    Recently, we proposed a new approach of a noncollinear correlation technique for ultrashort-pulsed coherent optical signals which was referred to as Bessel-autocorrelator (BAC). The BAC-principle combines the advantages of Bessellike nondiffracting beams like stable propagation, angular robustness and self-reconstruction with the principle of temporal autocorrelation. In comparison to other phase-sensitive measuring techniques, autocorrelation is most straightforward and time-effective because of non-iterative data processing. The analysis of nonlinearly converted fringe patterns of pulsed Bessel-like beams reveals their temporal signature from details of fringe envelopes. By splitting the beams with axicon arrays into multiple sub-beams, transversal resolution is approximated. Here we report on adaptive implementations of BACs with improved phase resolution realized by phase-only liquid-crystal-on-silicon spatial light modulators (LCoS-SLMs). Programming microaxicon phase functions in gray value maps enables for a flexible variation of phase and geometry. Experiments on the diagnostics of few-cycle pulses emitted by a mode-locked Ti:sapphire laser oscillator at wavelengths around 800 nm with 2D-BAC and angular tuned BAC were performed. All-optical phase shift BAC and fringe free BAC approaches are discussed.

  3. Influence of wave-front sampling in adaptive optics retinal imaging

    PubMed Central

    Laslandes, Marie; Salas, Matthias; Hitzenberger, Christoph K.; Pircher, Michael

    2017-01-01

    A wide range of sampling densities of the wave-front has been used in retinal adaptive optics (AO) instruments, compared to the number of corrector elements. We developed a model in order to characterize the link between number of actuators, number of wave-front sampling points and AO correction performance. Based on available data from aberration measurements in the human eye, 1000 wave-fronts were generated for the simulations. The AO correction performance in the presence of these representative aberrations was simulated for different deformable mirror and Shack Hartmann wave-front sensor combinations. Predictions of the model were experimentally tested through in vivo measurements in 10 eyes including retinal imaging with an AO scanning laser ophthalmoscope. According to our study, a ratio between wavefront sampling points and actuator elements of 2 is sufficient to achieve high resolution in vivo images of photoreceptors. PMID:28271004

  4. Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales.

    PubMed

    Metcalfe, H; Milne, A E; Webster, R; Lark, R M; Murdoch, A J; Storkey, J

    2016-02-01

    Weeds tend to aggregate in patches within fields, and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at various scales, the strength of the relations between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We developed a general method that uses novel within-field nested sampling and residual maximum-likelihood (reml) estimation to explore scale-dependent relations between weeds and soil properties. We validated the method using a case study of Alopecurus myosuroides in winter wheat. Using reml, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales, we optimised the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.

  5. Patchiness of Ciliate Communities Sampled at Varying Spatial Scales along the New England Shelf

    PubMed Central

    McManus, George B.; Katz, Laura A.

    2016-01-01

    Although protists (microbial eukaryotes) provide an important link between bacteria and Metazoa in food webs, we do not yet have a clear understanding of the spatial scales on which protist diversity varies. Here, we use a combination of DNA fingerprinting (denaturant gradient gel electrophoresis or DGGE) and high-throughput sequencing (HTS) to assess the ciliate community in the class Spirotrichea at varying scales of 1–3 km sampled in three locations separated by at least 25 km—offshore, midshelf and inshore—along the New England shelf. Analyses of both abundant community (DGGE) and the total community (HTS) members reveal that: 1) ciliate communities are patchily distributed inshore (i.e. the middle station of a transect is distinct from its two neighboring stations), whereas communities are more homogeneous among samples within the midshelf and offshore stations; 2) a ciliate closely related to Pelagostrobilidium paraepacrum ‘blooms’ inshore and; 3) environmental factors may differentially impact the distributions of individual ciliates (i.e. OTUs) rather than the community as a whole as OTUs tend to show distinct biogeographies (e.g. some OTUs are restricted to the offshore locations, some to the surface, etc.). Together, these data show the complexity underlying the spatial distributions of marine protists, and suggest that biogeography may be a property of ciliate species rather than communities. PMID:27936137

  6. Seasonal phenology, spatial distribution, and sampling plan for the invasive mealybug Phenacoccus peruvianus (Hemiptera: Pseudococcidae).

    PubMed

    Beltrá, A; Garcia-Marí, F; Soto, A

    2013-06-01

    Phlenacoccus peruvianus Granara de Willink (Hemiptera: Pseudococcidae) is an invasive mealybug of Neotropical origin. In recent years it has invaded the Mediterranean Basin causing significant damages in bougainvillea and other ornamental plants. This article examines its phenology, location on the plant and spatial distribution, and presents a sampling plan to determine P. peruvianus population density for the management of this mealybug in southern Europe. Six urban green spaces with bougainvillea plants were periodically surveyed between March 2008 and September 2010 in eastern Spain, sampling bracts, leaves, and twigs. Our results show that P. peruvianus abundance was high in spring and summer, declining to almost undetectable levels in autumn and winter. The mealybugs showed a preference for settling on bracts and there were no significant migrations between plant organs. P. peruvianus showed a highly aggregated distribution on bracts, leaves, and twigs. We recommend abinomial sampling of 200 leaves and an action threshold of 55% infested leaves for integrated pest management purposes on urban landscapes and enumerative sampling for ornamental nursery management and additional biological studies.

  7. Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

    SciTech Connect

    Nie Xiaobo; Liang Jian; Yan Di

    2012-12-15

    Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h

  8. Low-power metabolic equivalents estimation algorithm using adaptive acceleration sampling.

    PubMed

    Tsukahara, Mio; Nakanishi, Motofumi; Izumi, Shintaro; Nakai, Yozaburo; Kawaguchi, Hiroshi; Yoshimoto, Masahiko; Tsukahara, Mio; Nakanishi, Motofumi; Izumi, Shintaro; Nakai, Yozaburo; Kawaguchi, Hiroshi; Yoshimoto, Masahiko; Izumi, Shintaro; Nakai, Yozaburo; Kawaguchi, Hiroshi; Yoshimoto, Masahiko; Tsukahara, Mio; Nakanishi, Motofumi

    2016-08-01

    This paper describes a proposed low-power metabolic equivalent estimation algorithm that can calculate the value of metabolic equivalents (METs) from triaxial acceleration at an adaptively changeable sampling rate. This algorithm uses four rates of 32, 16, 8 and 4 Hz. The mode of switching them is decided from synthetic acceleration. Applying this proposed algorithm to acceleration measured for 1 day, we achieved the low root mean squared error (RMSE) of calculated METs, with current consumption that was 41.5 % of the value at 32 Hz, and 75.4 % of the value at 16 Hz.

  9. CSD Fans and Disjointed CSD Bundles: Recovery of The Spatial Sample Locations from CSD Ensembles

    NASA Astrophysics Data System (ADS)

    Marsh, B. D.; Zieg, M. J.

    2001-05-01

    Volcanic rock captures magmatic time through eruption and quenching, but its spatial connection to the parent magma has been scrambled. It is an aliquot of magma from an unknown position within the magmatic body, and its relation to other coeval and comagmatic samples is also unknown. P-T determinations, although invaluable are not precise enough to arrange successive samples with any real certainty within the magmatic regime. This is a severe limitation in using lavas to infer magma chamber processes. We have developed a technique that allows the relative spatial order of comagmatic samples in the magmatic environment to be recovered. The method rests on a recent advance in CSD analysis. We have been able to show that CSD slope (S) and intercept (I) are linked through a universal relation (Zieg and Marsh, 2001, sub. J. Pet.). The CSDs of all igneous rocks fall on this I-S curve. Moreover, it can also be shown that CSD slope is inversely related to mean crystal size (S=1/Lm) and also that mean crystal size is the product of mean growth rate (G) and solidification time (Dt). That is, Lm = GDt. (The exact form of this growth law is completely arbitrary.). Because the rate of solidification front (SF) advance decreases as it propagates inward, local solidification time increases and so does mean crystal size, but nucleation rate must, in accordance with the universal I-S relation, decrease. The CSD slope thus must decrease systematically inward in the body, and a series of spatially contiguous CSDs thus form a fan. (This solves the mystery of CSD pivot points and of the often noticed correlation between CSD slope and intercept (Marsh et al., 1995 EOS).) A series of fanning CSDs for the Sudbury norite melt sheet match exactly the CSD fan calculated from the I - S relation. CSD slope decreases inward from the margins of the body as Lm increases due to increasing solidification time. Given a set of blind samples from a pluton, the order of the CSDs in a fan determines

  10. Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling

    SciTech Connect

    Vrugt, Jasper A; Hyman, James M; Robinson, Bruce A; Higdon, Dave; Ter Braak, Cajo J F; Diks, Cees G H

    2008-01-01

    Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.

  11. 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.

  12. A Surrogate-based Adaptive Sampling Approach for History Matching and Uncertainty Quantification

    SciTech Connect

    Li, Weixuan; Zhang, Dongxiao; Lin, Guang

    2015-02-25

    A critical procedure in reservoir simulations is history matching (or data assimilation in a broader sense), which calibrates model parameters such that the simulation results are consistent with field measurements, and hence improves the credibility of the predictions given by the simulations. Often there exist non-unique combinations of parameter values that all yield the simulation results matching the measurements. For such ill-posed history matching problems, Bayesian theorem provides a theoretical foundation to represent different solutions and to quantify the uncertainty with the posterior PDF. Lacking an analytical solution in most situations, the posterior PDF may be characterized with a sample of realizations, each representing a possible scenario. A novel sampling algorithm is presented here for the Bayesian solutions to history matching problems. We aim to deal with two commonly encountered issues: 1) as a result of the nonlinear input-output relationship in a reservoir model, the posterior distribution could be in a complex form, such as multimodal, which violates the Gaussian assumption required by most of the commonly used data assimilation approaches; 2) a typical sampling method requires intensive model evaluations and hence may cause unaffordable computational cost. In the developed algorithm, we use a Gaussian mixture model as the proposal distribution in the sampling process, which is simple but also flexible to approximate non-Gaussian distributions and is particularly efficient when the posterior is multimodal. Also, a Gaussian process is utilized as a surrogate model to speed up the sampling process. Furthermore, an iterative scheme of adaptive surrogate refinement and re-sampling ensures sampling accuracy while keeping the computational cost at a minimum level. The developed approach is demonstrated with an illustrative example and shows its capability in handling the above-mentioned issues. Multimodal posterior of the history matching

  13. Adaptive pulse width control and sampling for low power pulse oximetry.

    PubMed

    Gubbi, Sagar Venkatesh; Amrutur, Bharadwaj

    2015-04-01

    Remote sensing of physiological parameters could be a cost effective approach to improving health care, and low-power sensors are essential for remote sensing because these sensors are often energy constrained. This paper presents a power optimized photoplethysmographic sensor interface to sense arterial oxygen saturation, a technique to dynamically trade off SNR for power during sensor operation, and a simple algorithm to choose when to acquire samples in photoplethysmography. A prototype of the proposed pulse oximeter built using commercial-off-the-shelf (COTS) components is tested on 10 adults. The dynamic adaptation techniques described reduce power consumption considerably compared to our reference implementation, and our approach is competitive to state-of-the-art implementations. The techniques presented in this paper may be applied to low-power sensor interface designs where acquiring samples is expensive in terms of power as epitomized by pulse oximetry.

  14. Adaptive Optics with a Liquid-Crystal-on-Silicon Spatial Light Modulator and Its Behavior in Retinal Imaging

    NASA Astrophysics Data System (ADS)

    Shirai, Tomohiro; Takeno, Kohei; Arimoto, Hidenobu; Furukawa, Hiromitsu

    2009-07-01

    An adaptive optics system with a brand-new device of a liquid-crystal-on-silicon (LCOS) spatial light modulator (SLM) and its behavior in in vivo imaging of the human retina are described. We confirmed by experiments that closed-loop correction of ocular aberrations of the subject's eye was successfully achieved at the rate of 16.7 Hz in our system to obtain a clear retinal image in real time. The result suggests that an LCOS SLM is one of the promising candidates for a wavefront corrector in a prospective commercial ophthalmic instrument with adaptive optics.

  15. Passive sampling to capture the spatial variability of coarse particles by composition in Cleveland, OH

    NASA Astrophysics Data System (ADS)

    Sawvel, Eric J.; Willis, Robert; West, Roger R.; Casuccio, Gary S.; Norris, Gary; Kumar, Naresh; Hammond, Davyda; Peters, Thomas M.

    2015-03-01

    Passive samplers deployed at 25 sites for three, week-long intervals were used to characterize spatial variability in the mass and composition of coarse particulate matter (PM10-2.5) in Cleveland, OH in summer 2008. The size and composition of individual particles determined using computer-controlled scanning electron microscopy with energy-dispersive X-ray spectroscopy (CCSEM-EDS) was then used to estimate PM10-2.5 concentrations (μg m-3) and its components in 13 particle classes. The highest PM10-2.5 mean mass concentrations were observed at three central industrial sites (35 μg m-3, 43 μg m-3, and 48 μg m-3), whereas substantially lower mean concentrations were observed to the west and east of this area at suburban background sites (13 μg m-3 and 15 μg m-3). PM10-2.5 mass and components associated with steel and cement production (Fe-oxide and Ca-rich) exhibited substantial heterogeneity with elevated concentrations observed in the river valley, stretching from Lake Erie south through the central industrial area and in the case of Fe-oxide to a suburban valley site. Other components (e.g., Si/Al-rich typical of crustal material) were considerably less heterogeneous. This work shows that some species of coarse particles are considerably more spatially heterogeneous than others in an urban area with a strong industrial core. It also demonstrates that passive sampling coupled with analysis by CCSEM-EDS is a useful tool to assess the spatial variability of particulate pollutants by composition.

  16. Retrieval of Brain Tumors by Adaptive Spatial Pooling and Fisher Vector Representation

    PubMed Central

    Huang, Meiyan; Huang, Wei; Jiang, Jun; Zhou, Yujia; Yang, Ru; Zhao, Jie; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

    2016-01-01

    Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on developing a CBIR system for retrieving brain tumors in T1-weighted contrast-enhanced MRI images. Specifically, when the user roughly outlines the tumor region of a query image, brain tumor images in the database of the same pathological type are expected to be returned. We propose a novel feature extraction framework to improve the retrieval performance. The proposed framework consists of three steps. First, we augment the tumor region and use the augmented tumor region as the region of interest to incorporate informative contextual information. Second, the augmented tumor region is split into subregions by an adaptive spatial division method based on intensity orders; within each subregion, we extract raw image patches as local features. Third, we apply the Fisher kernel framework to aggregate the local features of each subregion into a respective single vector representation and concatenate these per-subregion vector representations to obtain an image-level signature. After feature extraction, a closed-form metric learning algorithm is applied to measure the similarity between the query image and database images. Extensive experiments are conducted on a large dataset of 3604 images with three types of brain tumors, namely, meningiomas, gliomas, and pituitary tumors. The mean average precision can reach 94.68%. Experimental results demonstrate the power of the proposed algorithm against some related state-of-the-art methods on the same dataset. PMID:27273091

  17. Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition

    NASA Astrophysics Data System (ADS)

    Parrish, Robert M.; Sherrill, C. David

    2014-07-01

    We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work through the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in

  18. Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition

    SciTech Connect

    Parrish, Robert M.; Sherrill, C. David

    2014-07-28

    We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work through the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in

  19. Spatially adaptive radiation-hydrodynamical simulations of galaxy formation during cosmological reionization

    NASA Astrophysics Data System (ADS)

    Pawlik, Andreas H.; Schaye, Joop; Dalla Vecchia, Claudio

    2015-08-01

    We present a suite of cosmological radiation-hydrodynamical simulations of the assembly of galaxies driving the reionization of the intergalactic medium (IGM) at z ≳ 6. The simulations account for the hydrodynamical feedback from photoionization heating and the explosion of massive stars as supernovae (SNe). Our reference simulation, which was carried out in a box of size 25 h-1 comovingMpc using 2 × 5123 particles, produces a reasonable reionization history and matches the observed UV luminosity function of galaxies. Simulations with different box sizes and resolutions are used to investigate numerical convergence, and simulations in which either SNe or photoionization heating or both are turned off, are used to investigate the role of feedback from star formation. Ionizing radiation is treated using accurate radiative transfer at the high spatially adaptive resolution at which the hydrodynamics is carried out. SN feedback strongly reduces the star formation rates (SFRs) over nearly the full mass range of simulated galaxies and is required to yield SFRs in agreement with observations. Photoheating helps to suppress star formation in low-mass galaxies, but its impact on the cosmic SFR is small. Because the effect of photoheating is masked by the strong SN feedback, it does not imprint a signature on the UV galaxy luminosity function, although we note that our resolution is insufficient to model star-forming minihaloes cooling through molecular hydrogen transitions. Photoheating does provide a strong positive feedback on reionization because it smooths density fluctuations in the IGM, which lowers the IGM recombination rate substantially. Our simulations demonstrate a tight non-linear coupling of galaxy formation and reionization, motivating the need for the accurate and simultaneous inclusion of photoheating and SN feedback in models of the early Universe.

  20. Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition.

    PubMed

    Parrish, Robert M; Sherrill, C David

    2014-07-28

    We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work through the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in

  1. Sample entropy-based adaptive wavelet de-noising approach for meteorologic and hydrologic time series

    NASA Astrophysics Data System (ADS)

    Wang, Dong; Singh, Vijay P.; Shang, Xiaosan; Ding, Hao; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Wang, Shicheng; Wang, Zhenlong

    2014-07-01

    De-noising meteorologic and hydrologic time series is important to improve the accuracy and reliability of extraction, analysis, simulation, and forecasting. A hybrid approach, combining sample entropy and wavelet de-noising method, is developed to separate noise from original series and is named as AWDA-SE (adaptive wavelet de-noising approach using sample entropy). The AWDA-SE approach adaptively determines the threshold for wavelet analysis. Two kinds of meteorologic and hydrologic data sets, synthetic data set and 3 representative field measured data sets (one is the annual rainfall data of Jinan station and the other two are annual streamflow series from two typical stations in China, Yingluoxia station on the Heihe River, which is little affected by human activities, and Lijin station on the Yellow River, which is greatly affected by human activities), are used to illustrate the approach. The AWDA-SE approach is compared with three conventional de-noising methods, including fixed-form threshold algorithm, Stein unbiased risk estimation algorithm, and minimax algorithm. Results show that the AWDA-SE approach separates effectively the signal and noise of the data sets and is found to be better than the conventional methods. Measures of assessment standards show that the developed approach can be employed to investigate noisy and short time series and can also be applied to other areas.

  2. Adaptive sampling dual terahertz comb spectroscopy using dual free-running femtosecond lasers

    PubMed Central

    Yasui, Takeshi; Ichikawa, Ryuji; Hsieh, Yi-Da; Hayashi, Kenta; Cahyadi, Harsono; Hindle, Francis; Sakaguchi, Yoshiyuki; Iwata, Tetsuo; Mizutani, Yasuhiro; Yamamoto, Hirotsugu; Minoshima, Kaoru; Inaba, Hajime

    2015-01-01

    Terahertz (THz) dual comb spectroscopy (DCS) is a promising method for high-accuracy, high-resolution, broadband THz spectroscopy because the mode-resolved THz comb spectrum includes both broadband THz radiation and narrow-line CW-THz radiation characteristics. In addition, all frequency modes of a THz comb can be phase-locked to a microwave frequency standard, providing excellent traceability. However, the need for stabilization of dual femtosecond lasers has often hindered its wide use. To overcome this limitation, here we have demonstrated adaptive-sampling THz-DCS, allowing the use of free-running femtosecond lasers. To correct the fluctuation of the time and frequency scales caused by the laser timing jitter, an adaptive sampling clock is generated by dual THz-comb-referenced spectrum analysers and is used for a timing clock signal in a data acquisition board. The results not only indicated the successful implementation of THz-DCS with free-running lasers but also showed that this configuration outperforms standard THz-DCS with stabilized lasers due to the slight jitter remained in the stabilized lasers. PMID:26035687

  3. Motion-adapted pulse sequences for oriented sample (OS) solid-state NMR of biopolymers.

    PubMed

    Lu, George J; Opella, Stanley J

    2013-08-28

    One of the main applications of solid-state NMR is to study the structure and dynamics of biopolymers, such as membrane proteins, under physiological conditions where the polypeptides undergo global motions as they do in biological membranes. The effects of NMR radiofrequency irradiations on nuclear spins are strongly influenced by these motions. For example, we previously showed that the MSHOT-Pi4 pulse sequence yields spectra with resonance line widths about half of those observed using the conventional pulse sequence when applied to membrane proteins undergoing rapid uniaxial rotational diffusion in phospholipid bilayers. In contrast, the line widths were not changed in microcrystalline samples where the molecules did not undergo global motions. Here, we demonstrate experimentally and describe analytically how some Hamiltonian terms are susceptible to sample motions, and it is their removal through the critical π/2 Z-rotational symmetry that confers the "motion adapted" property to the MSHOT-Pi4 pulse sequence. This leads to the design of separated local field pulse sequence "Motion-adapted SAMPI4" and is generalized to an approach for the design of decoupling sequences whose performance is superior in the presence of molecular motions. It works by cancelling the spin interaction by explicitly averaging the reduced Wigner matrix to zero, rather than utilizing the 2π nutation to average spin interactions. This approach is applicable to both stationary and magic angle spinning solid-state NMR experiments.

  4. An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors.

    PubMed

    Srbinovski, Bruno; Magno, Michele; Edwards-Murphy, Fiona; Pakrashi, Vikram; Popovici, Emanuel

    2016-03-28

    Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA.

  5. A rotating hot-wire technique for spatial sampling of disturbed and manipulated duct flows

    NASA Technical Reports Server (NTRS)

    Wark, C. E.; Nagib, H. M.; Jennings, M. J.

    1990-01-01

    A duct flow spatial sampling technique, in which an X-wire probe is rotated about the center of a cylindrical test section at a radius equal to one-half that of the test section in order to furnish nearly instantaneous multipoint measurements of the streamwise and azimuthal components, is presently evaluated in view of the control of flow disturbances downstream of various open inlet contractions. The effectiveness of a particular contraction in controlling ingested flow disturbances was ascertained by artificially introducing disturbances upstream of the contractions; control effectiveness if found to be strongly dependent on inlet contraction, with consequences for the reduction of passing-blade frequency noise during gas turbine engine ground testing.

  6. A sampling approach to estimate the log determinant used in spatial likelihood problems

    NASA Astrophysics Data System (ADS)

    Pace, R. Kelley; Lesage, James P.

    2009-09-01

    Likelihood-based methods for modeling multivariate Gaussian spatial data have desirable statistical characteristics, but the practicality of these methods for massive georeferenced data sets is often questioned. A sampling algorithm is proposed that exploits a relationship involving log-pivots arising from matrix decompositions used to compute the log determinant term that appears in the model likelihood. We demonstrate that the method can be used to successfully estimate log-determinants for large numbers of observations. Specifically, we produce an log-determinant estimate for a 3,954,400 by 3,954,400 matrix in less than two minutes on a desktop computer. The proposed method involves computations that are independent, making it amenable to out-of-core computation as well as to coarse-grained parallel or distributed processing. The proposed technique yields an estimated log-determinant and associated confidence interval.

  7. The adaptive value of habitat preferences from a multi-scale spatial perspective: insights from marsh-nesting avian species

    PubMed Central

    Brambilla, Mattia

    2017-01-01

    Background Habitat selection and its adaptive outcomes are crucial features for animal life-history strategies. Nevertheless, congruence between habitat preferences and breeding success has been rarely demonstrated, which may result from the single-scale evaluation of animal choices. As habitat selection is a complex multi-scale process in many groups of animal species, investigating adaptiveness of habitat selection in a multi-scale framework is crucial. In this study, we explore whether habitat preferences acting at different spatial scales enhance the fitness of bird species, and check the appropriateness of single vs. multi-scale models. We expected that variables found to be more important for habitat selection at individual scale(s), would coherently play a major role in affecting nest survival at the same scale(s). Methods We considered habitat preferences of two Rallidae species, little crake (Zapornia parva) and water rail (Rallus aquaticus), at three spatial scales (landscape, territory, and nest-site) and related them to nest survival. Single-scale versus multi-scale models (GLS and glmmPQL) were compared to check which model better described adaptiveness of habitat preferences. Consistency between the effect of variables on habitat selection and on nest survival was checked to investigate their adaptive value. Results In both species, multi-scale models for nest survival were more supported than single-scale ones. In little crake, the multi-scale model indicated vegetation density and water depth at the territory scale, as well as vegetation height at nest-site scale, as the most important variables. The first two variables were among the most important for nest survival and habitat selection, and the coherent effects suggested the adaptive value of habitat preferences. In water rail, the multi-scale model of nest survival showed vegetation density at territory scale and extent of emergent vegetation within landscape scale as the most important ones

  8. Spatial analysis of Mount St. Helens tephra leachate compositions: implications for future sampling strategies.

    PubMed

    Ayris, P M; Delmelle, P; Pereira, B; Maters, E C; Damby, D E; Durant, A J; Dingwell, D B

    Tephra particles in physically and chemically evolving volcanic plumes and clouds carry soluble sulphate and halide salts to the Earth's surface, ultimately depositing volcanogenic compounds into terrestrial or aquatic environments. Upon leaching of tephra in water, these salts dissolve rapidly. Previous studies have investigated the spatial and temporal variability of tephra leachate compositions during an eruption in order to gain insight into the mechanisms of gas-tephra interaction which emplace those salts. However, the leachate datasets analysed are typically small and may poorly represent the natural variability and complexity of tephra deposits. Here, we have conducted a retrospective analysis of published leachate analyses from the 18 May 1980 eruption of Mount St. Helens, Washington, analysing the spatial structure of the concentrations and relative abundances of soluble Ca, Cl, Na and S across the deposits. We have identified two spatial features: (1) concentrated tephra leachate compositions in blast deposits to the north of the volcano and (2) low S/Cl and Na/Cl ratios around the Washington-Idaho border. By reference to the bulk chemistry and granulometry of the deposit and to current knowledge of gas-tephra interactions, we suggest that the proximal enrichments are the product of pre-eruptive gas uptake during cryptodome emplacement. We speculate that the low S/Cl and Na/Cl ratios reflect a combination of compositional dependences on high-temperature SO2 uptake and preferential HCl uptake by hydrometeor-tephra aggregates, manifested in terrestrial deposits by tephra sedimentation and fallout patterns. However, despite our interrogation of the most exhaustive tephra leachate dataset available, it has become clear in this effort that more detailed insights into gas-tephra interaction mechanisms are prevented by the prevalent poor temporal and spatial representativeness of the collated data and the limited characterisation of the tephra deposits. Future

  9. Spatial analysis of Mount St. Helens tephra leachate compositions: implications for future sampling strategies

    NASA Astrophysics Data System (ADS)

    Ayris, P. M.; Delmelle, P.; Pereira, B.; Maters, E. C.; Damby, D. E.; Durant, A. J.; Dingwell, D. B.

    2015-07-01

    Tephra particles in physically and chemically evolving volcanic plumes and clouds carry soluble sulphate and halide salts to the Earth's surface, ultimately depositing volcanogenic compounds into terrestrial or aquatic environments. Upon leaching of tephra in water, these salts dissolve rapidly. Previous studies have investigated the spatial and temporal variability of tephra leachate compositions during an eruption in order to gain insight into the mechanisms of gas-tephra interaction which emplace those salts. However, the leachate datasets analysed are typically small and may poorly represent the natural variability and complexity of tephra deposits. Here, we have conducted a retrospective analysis of published leachate analyses from the 18 May 1980 eruption of Mount St. Helens, Washington, analysing the spatial structure of the concentrations and relative abundances of soluble Ca, Cl, Na and S across the deposits. We have identified two spatial features: (1) concentrated tephra leachate compositions in blast deposits to the north of the volcano and (2) low S/Cl and Na/Cl ratios around the Washington-Idaho border. By reference to the bulk chemistry and granulometry of the deposit and to current knowledge of gas-tephra interactions, we suggest that the proximal enrichments are the product of pre-eruptive gas uptake during cryptodome emplacement. We speculate that the low S/Cl and Na/Cl ratios reflect a combination of compositional dependences on high-temperature SO2 uptake and preferential HCl uptake by hydrometeor-tephra aggregates, manifested in terrestrial deposits by tephra sedimentation and fallout patterns. However, despite our interrogation of the most exhaustive tephra leachate dataset available, it has become clear in this effort that more detailed insights into gas-tephra interaction mechanisms are prevented by the prevalent poor temporal and spatial representativeness of the collated data and the limited characterisation of the tephra deposits. Future

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

    PubMed Central

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

    2013-01-01

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

  11. Adaption of G-TAG Software for Validating Touch and Go Asteroid Sample Return Design Methodology

    NASA Technical Reports Server (NTRS)

    Blackmore, Lars James C.; Acikmese, Behcet; Mandic, Milan

    2012-01-01

    A software tool is used to demonstrate the feasibility of Touch and Go (TAG) sampling for Asteroid Sample Return missions. TAG is a concept whereby a spacecraft is in contact with the surface of a small body, such as a comet or asteroid, for a few seconds or less before ascending to a safe location away from the small body. Previous work at JPL developed the G-TAG simulation tool, which provides a software environment for fast, multi-body simulations of the TAG event. G-TAG is described in Multibody Simulation Software Testbed for Small-Body Exploration and Sampling, (NPO-47196) NASA Tech Briefs, Vol. 35, No. 11 (November 2011), p.54. This current innovation adapts this tool to a mission that intends to return a sample from the surface of an asteroid. In order to demonstrate the feasibility of the TAG concept, the new software tool was used to generate extensive simulations that demonstrate the designed spacecraft meets key requirements. These requirements state that contact force and duration must be sufficient to ensure that enough material from the surface is collected in the brushwheel sampler (BWS), and that the spacecraft must survive the contact and must be able to recover and ascend to a safe position, and maintain velocity and orientation after the contact.

  12. Temporal and spatial trends of chemical composition of wet deposition samples collected in Austria

    NASA Astrophysics Data System (ADS)

    Schreiner, Elisabeth; Kasper-Giebl, Anne; Lohninger, Hans

    2016-04-01

    deposition loads of these ions are influenced by the seasonality of precipitation amount, the deposition data shows some seasonality for some ions and stations as well. Spatial distributions changed over the observation period. Differences obtained within the more recent years tend to be smaller compared to results reported for the 1980s and 1990s. Sampling and analysis of rain water samples was financed by the respective authorities in Tyrol, Salzburg, Styria, Carinthia and Lower Austria.

  13. Adaptive free energy sampling in multidimensional collective variable space using boxed molecular dynamics.

    PubMed

    O'Connor, Mike; Paci, Emanuele; McIntosh-Smith, Simon; Glowacki, David R

    2016-12-22

    The past decade has seen the development of a new class of rare event methods in which molecular configuration space is divided into a set of boundaries/interfaces, and then short trajectories are run between boundaries. For all these methods, an important concern is how to generate boundaries. In this paper, we outline an algorithm for adaptively generating boundaries along a free energy surface in multi-dimensional collective variable (CV) space, building on the boxed molecular dynamics (BXD) rare event algorithm. BXD is a simple technique for accelerating the simulation of rare events and free energy sampling which has proven useful for calculating kinetics and free energy profiles in reactive and non-reactive molecular dynamics (MD) simulations across a range of systems, in both NVT and NVE ensembles. Two key developments outlined in this paper make it possible to automate BXD, and to adaptively map free energy and kinetics in complex systems. First, we have generalized BXD to multidimensional CV space. Using strategies from rigid-body dynamics, we have derived a simple and general velocity-reflection procedure that conserves energy for arbitrary collective variable definitions in multiple dimensions, and show that it is straightforward to apply BXD to sampling in multidimensional CV space so long as the Cartesian gradients ∇CV are available. Second, we have modified BXD to undertake on-the-fly statistical analysis during a trajectory, harnessing the information content latent in the dynamics to automatically determine boundary locations. Such automation not only makes BXD considerably easier to use; it also guarantees optimal boundaries, speeding up convergence. We have tested the multidimensional adaptive BXD procedure by calculating the potential of mean force for a chemical reaction recently investigated using both experimental and computational approaches - i.e., F + CD3CN → DF + D2CN in both the gas phase and a strongly coupled explicit CD3CN solvent

  14. Vector Doppler: spatial sampling analysis and presentation techniques for real-time systems

    NASA Astrophysics Data System (ADS)

    Capineri, Lorenzo; Scabia, Marco; Masotti, Leonardo F.

    2001-05-01

    The aim of the vector Doppler (VD) technique is the quantitative reconstruction of a velocity field independently of the ultrasonic probe axis to flow angle. In particular vector Doppler is interesting for studying vascular pathologies related to complex blood flow conditions. Clinical applications require a real-time operating mode and the capability to perform Doppler measurements over a defined volume. The combination of these two characteristics produces a real-time vector velocity map. In previous works the authors investigated the theory of pulsed wave (PW) vector Doppler and developed an experimental system capable of producing off-line 3D vector velocity maps. Afterwards, for producing dynamic velocity vector maps, we realized a new 2D vector Doppler system based on a modified commercial echograph. The measurement and presentation of a vector velocity field requires a correct spatial sampling that must satisfy the Shannon criterion. In this work we tackled this problem, establishing a relationship between sampling steps and scanning system characteristics. Another problem posed by the vector Doppler technique is the data representation in real-time that should be easy to interpret for the physician. With this in mine we attempted a multimedia solution that uses both interpolated images and sound to represent the information of the measured vector velocity map. These presentation techniques were experimented for real-time scanning on flow phantoms and preliminary measurements in vivo on a human carotid artery.

  15. Improving neutron multiplicity counting for the spatial dependence of multiplication: Results for spherical plutonium samples

    NASA Astrophysics Data System (ADS)

    Göttsche, Malte; Kirchner, Gerald

    2015-10-01

    The fissile mass deduced from a neutron multiplicity counting measurement of high mass dense items is underestimated if the spatial dependence of the multiplication is not taken into account. It is shown that an appropriate physics-based correction successfully removes the bias. It depends on four correction coefficients which can only be exactly determined if the sample geometry and composition are known. In some cases, for example in warhead authentication, available information on the sample will be very limited. MCNPX-PoliMi simulations have been performed to obtain the correction coefficients for a range of spherical plutonium metal geometries, with and without polyethylene reflection placed around the spheres. For hollow spheres, the analysis shows that the correction coefficients can be approximated with high accuracy as a function of the sphere's thickness depending only slightly on the radius. If the thickness remains unknown, less accurate estimates of the correction coefficients can be obtained from the neutron multiplication. The influence of isotopic composition is limited. The correction coefficients become somewhat smaller when reflection is present.

  16. Differentially Private Histogram Publication For Dynamic Datasets: An Adaptive Sampling Approach.

    PubMed

    Li, Haoran; Jiang, Xiaoqian; Xiong, Li; Liu, Jinfei

    2015-10-01

    Differential privacy has recently become a de facto standard for private statistical data release. Many algorithms have been proposed to generate differentially private histograms or synthetic data. However, most of them focus on "one-time" release of a static dataset and do not adequately address the increasing need of releasing series of dynamic datasets in real time. A straightforward application of existing histogram methods on each snapshot of such dynamic datasets will incur high accumulated error due to the composibility of differential privacy and correlations or overlapping users between the snapshots. In this paper, we address the problem of releasing series of dynamic datasets in real time with differential privacy, using a novel adaptive distance-based sampling approach. Our first method, DSFT, uses a fixed distance threshold and releases a differentially private histogram only when the current snapshot is sufficiently different from the previous one, i.e., with a distance greater than a predefined threshold. Our second method, DSAT, further improves DSFT and uses a dynamic threshold adaptively adjusted by a feedback control mechanism to capture the data dynamics. Extensive experiments on real and synthetic datasets demonstrate that our approach achieves better utility than baseline methods and existing state-of-the-art methods.

  17. Differentially Private Histogram Publication For Dynamic Datasets: An Adaptive Sampling Approach

    PubMed Central

    Li, Haoran; Jiang, Xiaoqian; Xiong, Li; Liu, Jinfei

    2016-01-01

    Differential privacy has recently become a de facto standard for private statistical data release. Many algorithms have been proposed to generate differentially private histograms or synthetic data. However, most of them focus on “one-time” release of a static dataset and do not adequately address the increasing need of releasing series of dynamic datasets in real time. A straightforward application of existing histogram methods on each snapshot of such dynamic datasets will incur high accumulated error due to the composibility of differential privacy and correlations or overlapping users between the snapshots. In this paper, we address the problem of releasing series of dynamic datasets in real time with differential privacy, using a novel adaptive distance-based sampling approach. Our first method, DSFT, uses a fixed distance threshold and releases a differentially private histogram only when the current snapshot is sufficiently different from the previous one, i.e., with a distance greater than a predefined threshold. Our second method, DSAT, further improves DSFT and uses a dynamic threshold adaptively adjusted by a feedback control mechanism to capture the data dynamics. Extensive experiments on real and synthetic datasets demonstrate that our approach achieves better utility than baseline methods and existing state-of-the-art methods. PMID:26973795

  18. A Bayesian adaptive blinded sample size adjustment method for risk differences.

    PubMed

    Hartley, Andrew Montgomery

    2015-01-01

    Adaptive sample size adjustment (SSA) for clinical trials consists of examining early subsets of on trial data to adjust estimates of sample size requirements. Blinded SSA is often preferred over unblinded SSA because it obviates many logistical complications of the latter and generally introduces less bias. On the other hand, current blinded SSA methods for binary data offer little to no new information about the treatment effect, ignore uncertainties associated with the population treatment proportions, and/or depend on enhanced randomization schemes that risk partial unblinding. I propose an innovative blinded SSA method for use when the primary analysis is a non-inferiority or superiority test regarding a risk difference. The method incorporates evidence about the treatment effect via the likelihood function of a mixture distribution. I compare the new method with an established one and with the fixed sample size study design, in terms of maximization of an expected utility function. The new method maximizes the expected utility better than do the comparators, under a range of assumptions. I illustrate the use of the proposed method with an example that incorporates a Bayesian hierarchical model. Lastly, I suggest topics for future study regarding the proposed methods.

  19. A framework for inference about carnivore density from unstructured spatial sampling of scat using detector dogs

    USGS Publications Warehouse

    Thompson, Craig M.; Royle, J. Andrew; Garner, James D.

    2012-01-01

    Wildlife management often hinges upon an accurate assessment of population density. Although undeniably useful, many of the traditional approaches to density estimation such as visual counts, livetrapping, or mark–recapture suffer from a suite of methodological and analytical weaknesses. Rare, secretive, or highly mobile species exacerbate these problems through the reality of small sample sizes and movement on and off study sites. In response to these difficulties, there is growing interest in the use of non-invasive survey techniques, which provide the opportunity to collect larger samples with minimal increases in effort, as well as the application of analytical frameworks that are not reliant on large sample size arguments. One promising survey technique, the use of scat detecting dogs, offers a greatly enhanced probability of detection while at the same time generating new difficulties with respect to non-standard survey routes, variable search intensity, and the lack of a fixed survey point for characterizing non-detection. In order to account for these issues, we modified an existing spatially explicit, capture–recapture model for camera trap data to account for variable search intensity and the lack of fixed, georeferenced trap locations. We applied this modified model to a fisher (Martes pennanti) dataset from the Sierra National Forest, California, and compared the results (12.3 fishers/100 km2) to more traditional density estimates. We then evaluated model performance using simulations at 3 levels of population density. Simulation results indicated that estimates based on the posterior mode were relatively unbiased. We believe that this approach provides a flexible analytical framework for reconciling the inconsistencies between detector dog survey data and density estimation procedures.

  20. Recruiting hard-to-reach United States population sub-groups via adaptations of snowball sampling strategy

    PubMed Central

    Sadler, Georgia Robins; Lee, Hau-Chen; Seung-Hwan Lim, Rod; Fullerton, Judith

    2011-01-01

    Nurse researchers and educators often engage in outreach to narrowly defined populations. This article offers examples of how variations on the snowball sampling recruitment strategy can be applied in the creation of culturally appropriate, community-based information dissemination efforts related to recruitment to health education programs and research studies. Examples from the primary author’s program of research are provided to demonstrate how adaptations of snowball sampling can be effectively used in the recruitment of members of traditionally underserved or vulnerable populations. The adaptation of snowball sampling techniques, as described in this article, helped the authors to gain access to each of the more vulnerable population groups of interest. The use of culturally sensitive recruitment strategies is both appropriate and effective in enlisting the involvement of members of vulnerable populations. Adaptations of snowball sampling strategies should be considered when recruiting participants for education programs or subjects for research studies when recruitment of a population based sample is not essential. PMID:20727089

  1. Accelerating the Convergence of Replica Exchange Simulations Using Gibbs Sampling and Adaptive Temperature Sets

    DOE PAGES

    Vogel, Thomas; Perez, Danny

    2015-08-28

    We recently introduced a novel replica-exchange scheme in which an individual replica can sample from states encountered by other replicas at any previous time by way of a global configuration database, enabling the fast propagation of relevant states through the whole ensemble of replicas. This mechanism depends on the knowledge of global thermodynamic functions which are measured during the simulation and not coupled to the heat bath temperatures driving the individual simulations. Therefore, this setup also allows for a continuous adaptation of the temperature set. In this paper, we will review the new scheme and demonstrate its capability. The methodmore » is particularly useful for the fast and reliable estimation of the microcanonical temperature T (U) or, equivalently, of the density of states g(U) over a wide range of energies.« less

  2. Accelerating the Convergence of Replica Exchange Simulations Using Gibbs Sampling and Adaptive Temperature Sets

    SciTech Connect

    Vogel, Thomas; Perez, Danny

    2015-08-28

    We recently introduced a novel replica-exchange scheme in which an individual replica can sample from states encountered by other replicas at any previous time by way of a global configuration database, enabling the fast propagation of relevant states through the whole ensemble of replicas. This mechanism depends on the knowledge of global thermodynamic functions which are measured during the simulation and not coupled to the heat bath temperatures driving the individual simulations. Therefore, this setup also allows for a continuous adaptation of the temperature set. In this paper, we will review the new scheme and demonstrate its capability. The method is particularly useful for the fast and reliable estimation of the microcanonical temperature T (U) or, equivalently, of the density of states g(U) over a wide range of energies.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  4. An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

    PubMed Central

    Srbinovski, Bruno; Magno, Michele; Edwards-Murphy, Fiona; Pakrashi, Vikram; Popovici, Emanuel

    2016-01-01

    Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA. PMID:27043559

  5. Adaptive sampling of CT data for myocardial blood flow estimation from dose-reduced dynamic CT

    NASA Astrophysics Data System (ADS)

    Modgil, Dimple; Bindschadler, Michael D.; Alessio, Adam M.; La Rivière, Patrick J.

    2015-03-01

    Quantification of myocardial blood flow (MBF) can aid in the diagnosis and treatment of coronary artery disease (CAD). However, there are no widely accepted clinical methods for estimating MBF. Dynamic CT holds the promise of providing a quick and easy method to measure MBF quantitatively, however the need for repeated scans has raised concerns about the potential for high radiation dose. In our previous work, we explored techniques to reduce the patient dose by either uniformly reducing the tube current or by uniformly reducing the number of temporal frames in the dynamic CT sequence. These dose reduction techniques result in very noisy data, which can give rise to large errors in MBF estimation. In this work, we seek to investigate whether nonuniformly varying the tube current or sampling intervals can yield more accurate MBF estimates. Specifically, we try to minimize the dose and obtain the most accurate MBF estimate through addressing the following questions: when in the time attenuation curve (TAC) should the CT data be collected and at what tube current(s). We hypothesize that increasing the sampling rate and/or tube current during the time frames when the myocardial CT number is most sensitive to the flow rate, while reducing them elsewhere, can achieve better estimation accuracy for the same dose. We perform simulations of contrast agent kinetics and CT acquisitions to evaluate the relative MBF estimation performance of several clinically viable adaptive acquisition methods. We found that adaptive temporal and tube current sequences can be performed that impart an effective dose of about 5 mSv and allow for reductions in MBF estimation RMSE on the order of 11% compared to uniform acquisition sequences with comparable or higher radiation doses.

  6. Spatial perception changes associated with space flight: implications for adaptation to altered inertial environments.

    PubMed

    Parker, Donald E

    2003-01-01

    Preparation for extended travel by astronauts within the Solar System, including a possible manned mission to Mars, requires more complete understanding of adaptation to altered inertial environments. Improved understanding is needed to support development and evaluation of interventions to facilitate adaptations during transitions between those environments. Travel to another planet escalates the adaptive challenge because astronauts will experience prolonged exposure to microgravity before encountering a novel gravitational environment. This challenge would have to be met without ground support at the landing site. Evaluation of current adaptive status as well as intervention efficacy can be performed using perceptual, eye movement and postural measures. Due to discrepancies of adaptation magnitude and time-course among these measures, complete understanding of adaptation processes, as well as intervention evaluation, requires examination of all three. Previous research and theory that provide models for comprehending adaptation to altered inertial environments are briefly examined. Reports from astronauts of selected pre- in- and postflight self-motion illusions are described. The currently controversial tilt-translation reinterpretation hypothesis is reviewed and possible resolutions to the controversy are proposed. Finally, based on apparent gaps in our current knowledge, further research is proposed to achieve a more complete understanding of adaptation as well as to develop effective counter-measures.

  7. Focussing over the edge: adaptive subsurface laser fabrication up to the sample face.

    PubMed

    Salter, P S; Booth, M J

    2012-08-27

    Direct laser writing is widely used for fabrication of subsurface, three dimensional structures in transparent media. However, the accessible volume is limited by distortion of the focussed beam at the sample edge. We determine the aberrated focal intensity distribution for light focused close to the edge of the substrate. Aberrations are modelled by dividing the pupil into two regions, each corresponding to light passing through the top and side facets. Aberration correction is demonstrated experimentally using a liquid crystal spatial light modulator for femtosecond microfabrication in fused silica. This technique allows controlled subsurface fabrication right up to the edge of the substrate. This can benefit a wide range of applications using direct laser writing, including the manufacture of waveguides and photonic crystals.

  8. Spatial Characterization of Polycyclic Aromatic Hydrocarbons in 2008 TC3 Samples

    NASA Astrophysics Data System (ADS)

    Sabbah, Hassan; Morrow, A.; Zare, R. N.; Jenniskens, P.

    2009-09-01

    Hassan Sabbah1, Amy L. Morrow1, Richard N. Zare1 and Petrus Jenniskens2 1Stanford University, Stanford, California 94305, 2 SETI Institute, Carl Sagan Center, 515 North Whisman Road, Mountain View, California 94043, USA. In October 2006 a small asteroid (2-3 meters) was observed in outer space. On October 7, 2008, it entered the Earth's atmosphere creating a fireball over Northern Sudan. Some 280 meteorites were collected by the University of Khartoum. In order to explore the existence of organic materials, specifically polycyclic aromatic hydrocarbons (PAHs), we applied two-step laser desorption laser ionization mass spectrometry (L2MS) to some selected fragments. This technique consists of desorbing with a pulsed infrared laser beam the solid materials into a gaseous phase with no fragmentation followed by resonance enhanced multiphoton ionization to analyze the PAH content. L2MS was already applied to an array of extraterrestrial objects including interplanetary dust particles IDPs, carbonaceous chondrites and comet coma particles. Moreover, spatial resolution of PAHs in 2008 TC3 samples was achieved to explore the heterogeneity within individual fragments. The results of these studies and their contribution to understanding the formation of this asteroid will be discussed.

  9. APPLICATIONS OF LASERS AND OTHER TOPICS IN LASER PHYSICS AND TECHNOLOGY: Adaptive compensation of atmospheric phase distortions using the spatial spectrum of images

    NASA Astrophysics Data System (ADS)

    Anufriev, A. V.; Zimin, Yu A.; Tolmachev, Alexei I.

    1987-10-01

    A theoretical investigation is reported of an algorithm for adaptive compensation of atmospheric phase distortions using the spatial spectrum of images. This algorithm can be used to reconstruct images of incoherently illuminated objects of arbitrary shape.

  10. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  11. Parallel phase-shifting digital holography with adaptive function using phase-mode spatial light modulator.

    PubMed

    Lin, Miao; Nitta, Kouichi; Matoba, Osamu; Awatsuji, Yasuhiro

    2012-05-10

    Parallel phase-shifting digital holography using a phase-mode spatial light modulator (SLM) is proposed. The phase-mode SLM implements spatial distribution of phase retardation required in the parallel phase-shifting digital holography. This SLM can also compensate dynamically the phase distortion caused by optical elements such as beam splitters, lenses, and air fluctuation. Experimental demonstration using a static object is presented.

  12. A technique for evaluating the influence of spatial sampling on the determination of global mean total columnar ozone

    NASA Technical Reports Server (NTRS)

    Tolson, R. H.

    1981-01-01

    A technique is described for providing a means of evaluating the influence of spatial sampling on the determination of global mean total columnar ozone. A finite number of coefficients in the expansion are determined, and the truncated part of the expansion is shown to contribute an error to the estimate, which depends strongly on the spatial sampling and is relatively insensitive to data noise. First and second order statistics are derived for each term in a spherical harmonic expansion which represents the ozone field, and the statistics are used to estimate systematic and random errors in the estimates of total ozone.

  13. Validation of sensor-directed spatial simulated annealing soil sampling strategy

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil spatial variability has a profound influence on most agronomical and environmental processes at field- and landscape-scales, including: site-specific management, vadose zone hydrology and transport, and soil quality, to mention a few. Mobile sensors are a practical means of mapping spatial vari...

  14. Investigating the tradeoffs between spatial resolution and diffusion sampling for brain mapping with diffusion tractography: time well spent?

    PubMed

    Calabrese, Evan; Badea, Alexandra; Coe, Christopher L; Lubach, Gabriele R; Styner, Martin A; Johnson, G Allan

    2014-11-01

    Interest in mapping white matter pathways in the brain has peaked with the recognition that altered brain connectivity may contribute to a variety of neurologic and psychiatric diseases. Diffusion tractography has emerged as a popular method for postmortem brain mapping initiatives, including the ex-vivo component of the human connectome project, yet it remains unclear to what extent computer-generated tracks fully reflect the actual underlying anatomy. Of particular concern is the fact that diffusion tractography results vary widely depending on the choice of acquisition protocol. The two major acquisition variables that consume scan time, spatial resolution, and diffusion sampling, can each have profound effects on the resulting tractography. In this analysis, we determined the effects of the temporal tradeoff between spatial resolution and diffusion sampling on tractography in the ex-vivo rhesus macaque brain, a close primate model for the human brain. We used the wealth of autoradiography-based connectivity data available for the rhesus macaque brain to assess the anatomic accuracy of six time-matched diffusion acquisition protocols with varying balance between spatial and diffusion sampling. We show that tractography results vary greatly, even when the subject and the total acquisition time are held constant. Further, we found that focusing on either spatial resolution or diffusion sampling at the expense of the other is counterproductive. A balanced consideration of both sampling domains produces the most anatomically accurate and consistent results.

  15. A sampling method for improving the representation of spatially varying precipitation and soil moisture using the Simple Biosphere Model

    NASA Astrophysics Data System (ADS)

    Medina, Isaac D.; Denning, A. Scott; Baker, Ian T.; Ramirez, Jorge A.; Randall, David A.

    2014-03-01

    spatially varying precipitation for current grid length scales used in General Circulation Models (GCMs) is a continuing challenge. Furthermore, to fully capture the hydrologic effects of nonuniform precipitation, a representation of soil moisture heterogeneity and distribution of spatially varying precipitation must exist within the same framework. For this study, the explicit and sampling methods of Sellers et al. (2007) are tested off-line using the Simple Biosphere Model (SiB3) in an arid, semiarid, and wet site, and are numerically compared to the bulk method, which is currently used in GCMs. To carry out the numerical experiments, an arbitrary grid area was defined by (1) a single instance of SiB3 (bulk method), (2) 100 instances of SiB3 (explicit method), and (3) less than 100 instances of SiB3 (sampling method). Precipitation was randomly distributed over fractions of the grid area for the explicit and sampling methods, while the standard SiB3 exponential distribution relating precipitation intensity to the grid area wet fraction was used in the bulk method. Comparing the sampling and bulk method to the explicit method indicates that 10 instances of SiB3 in the sampling method better captures the spatial variability in soil moisture and grid area flux calculations produced by the explicit method, and deals realistically with spatially varying precipitation at little additional computational cost to the bulk method.

  16. Spatial, Hysteretic, and Adaptive Host-Guest Chemistry in a Metal-Organic Framework with Open Watson-Crick Sites.

    PubMed

    Cai, Hong; Li, Mian; Lin, Xiao-Rong; Chen, Wei; Chen, Guang-Hui; Huang, Xiao-Chun; Li, Dan

    2015-09-01

    Biological and artificial molecules and assemblies capable of supramolecular recognition, especially those with nucleobase pairing, usually rely on autonomous or collective binding to function. Advanced site-specific recognition takes advantage of cooperative spatial effects, as in local folding in protein-DNA binding. Herein, we report a new nucleobase-tagged metal-organic framework (MOF), namely ZnBTCA (BTC=benzene-1,3,5-tricarboxyl, A=adenine), in which the exposed Watson-Crick faces of adenine residues are immobilized periodically on the interior crystalline surface. Systematic control experiments demonstrated the cooperation of the open Watson-Crick sites and spatial effects within the nanopores, and thermodynamic and kinetic studies revealed a hysteretic host-guest interaction attributed to mild chemisorption. We further exploited this behavior for adenine-thymine binding within the constrained pores, and a globally adaptive response of the MOF host was observed.

  17. French Adaptation of the Narcissistic Personality Inventory in a Belgian French-Speaking Sample.

    PubMed

    Braun, Stéphanie; Kempenaers, Chantal; Linkowski, Paul; Loas, Gwenolé

    2016-01-01

    The Narcissistic Personality Inventory (NPI) is the most widely used self-report scale to assess the construct of narcissism, especially in its grandiosity expression. Over the years, several factor models have been proposed in order to improve the understanding of the multidimensional aspect of this construct. The available data are heterogeneous, suggesting one to at least seven factors. In this study, we propose a French adaptation of the NPI submitted to a sample of Belgian French-speaking students (n = 942). We performed a principal component analysis on a tetrachoric correlation matrix to explore its factor structure. Unlike previous studies, our study shows that a first factor explains the largest part of the variance. Internal consistency is excellent and we reproduced the sex differences reported when using the original scale. Correlations with social desirability are taken into account in the interpretation of our results. Altogether, the results of this study support a unidimensional structure for the NPI using the total score as a self-report measure of the Narcissistic Personality Disorder in its grandiose form. Future studies including confirmatory factor analysis and gender invariance measurement are also discussed.

  18. French Adaptation of the Narcissistic Personality Inventory in a Belgian French-Speaking Sample

    PubMed Central

    Braun, Stéphanie; Kempenaers, Chantal; Linkowski, Paul; Loas, Gwenolé

    2016-01-01

    The Narcissistic Personality Inventory (NPI) is the most widely used self-report scale to assess the construct of narcissism, especially in its grandiosity expression. Over the years, several factor models have been proposed in order to improve the understanding of the multidimensional aspect of this construct. The available data are heterogeneous, suggesting one to at least seven factors. In this study, we propose a French adaptation of the NPI submitted to a sample of Belgian French-speaking students (n = 942). We performed a principal component analysis on a tetrachoric correlation matrix to explore its factor structure. Unlike previous studies, our study shows that a first factor explains the largest part of the variance. Internal consistency is excellent and we reproduced the sex differences reported when using the original scale. Correlations with social desirability are taken into account in the interpretation of our results. Altogether, the results of this study support a unidimensional structure for the NPI using the total score as a self-report measure of the Narcissistic Personality Disorder in its grandiose form. Future studies including confirmatory factor analysis and gender invariance measurement are also discussed. PMID:28066299

  19. Adaptive illumination through spatial modulation of light intensity and image inversion

    NASA Astrophysics Data System (ADS)

    Castellini, P.; Cecchini, S.; Stroppa, L.; Paone, N.

    2013-05-01

    The paper introduces the concept of spatial modulation of light intensity in the context of vision-based quality control, with the aim to improve image quality, measurable by indices such as image contrast and Tenengrad, so as to enhance the level of confidence of the diagnosis performed by image processing. The proposed technique is based on the projection of spatially modulated light intensity distribution by a digital light projector that allows an arbitrary light distribution to be projected on the target. The projected spatial distribution of light is determined by implementing an algorithm based on image inversion: the image acquired by the camera under uniform illumination is inverted and it is then used to modulate the light spatial distribution for projection. The process is repeated iteratively with the purpose to enhance image quality until convergence. The technique proves particularly valuable to avoid saturation from reflecting surfaces, which are often found in industrial practice. The procedure is tested and validated both by a numerical model and by an experimental validation, referring to a significant problem for the washing machine manufacturing industry. The use of image quality estimators confirms the effectiveness of the method.

  20. Spatially distinct response of rice yield to autonomous adaptation under the CMIP5 multi-model projections

    NASA Astrophysics Data System (ADS)

    Shin, Yonghee; Lee, Eun-Jeong; Im, Eun-Soon; Jung, Il-Won

    2017-02-01

    Rice ( Oryza sativa L.) is a very important staple crop, as it feeds more than half of the world's population. Numerous studies have focused on the negative impacts of climate change on rice production. However, there is little debate on which region of the world is more vulnerable to climate change and how adaptation to this change can mitigate the negative impacts on rice production. We investigated the impacts of climate change on rice yield, based on simulations combining a global crop model, M-GAZE, and Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model projections. Our focus was the impact of mitigating emission forcings (representative concentration pathway RCP 4.5 vs. RCP 8.5) and autonomous adaptation (i.e., changing crop variety and planting date) on rice yield. In general, our results showed that climate change due to anthropogenic warming leads to a significant reduction in rice yield. However, autonomous adaptation provides the potential to reduce the negative impact of global warming on rice yields in a spatially distinct manner. The adaptation was less beneficial for countries located at a low latitude (e.g., Cambodia, Thailand, Brazil) compared to mid-latitude countries (e.g., USA, China, Pakistan), as regional climates at the lower latitudes are already near the upper temperature thresholds for acceptable rice growth. These findings suggest that the socioeconomic effects from rice production in lowlatitude countries can be highly vulnerable to anthropogenic global warming. Therefore, these countries need to be accountable to develop transformative adaptation strategies, such as adopting (or developing) heat-tolerant varieties, and/or improve irrigation systems and fertilizer use efficiency.

  1. Spatial co-adaptation of cortical control columns in a micro-ECoG brain-computer interface

    NASA Astrophysics Data System (ADS)

    Rouse, A. G.; Williams, J. J.; Wheeler, J. J.; Moran, D. W.

    2016-10-01

    Objective. Electrocorticography (ECoG) has been used for a range of applications including electrophysiological mapping, epilepsy monitoring, and more recently as a recording modality for brain-computer interfaces (BCIs). Studies that examine ECoG electrodes designed and implanted chronically solely for BCI applications remain limited. The present study explored how two key factors influence chronic, closed-loop ECoG BCI: (i) the effect of inter-electrode distance on BCI performance and (ii) the differences in neural adaptation and performance when fixed versus adaptive BCI decoding weights are used. Approach. The amplitudes of epidural micro-ECoG signals between 75 and 105 Hz with 300 μm diameter electrodes were used for one-dimensional and two-dimensional BCI tasks. The effect of inter-electrode distance on BCI control was tested between 3 and 15 mm. Additionally, the performance and cortical modulation differences between constant, fixed decoding using a small subset of channels versus adaptive decoding weights using the entire array were explored. Main results. Successful BCI control was possible with two electrodes separated by 9 and 15 mm. Performance decreased and the signals became more correlated when the electrodes were only 3 mm apart. BCI performance in a 2D BCI task improved significantly when using adaptive decoding weights (80%-90%) compared to using constant, fixed weights (50%-60%). Additionally, modulation increased for channels previously unavailable for BCI control under the fixed decoding scheme upon switching to the adaptive, all-channel scheme. Significance. Our results clearly show that neural activity under a BCI recording electrode (which we define as a ‘cortical control column’) readily adapts to generate an appropriate control signal. These results show that the practical minimal spatial resolution of these control columns with micro-ECoG BCI is likely on the order of 3 mm. Additionally, they show that the combination and

  2. An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures

    PubMed Central

    Zandi, Kasra; Butler, Gregory; Kharma, Nawwaf

    2016-01-01

    Computational design of RNA sequences that fold into targeted secondary structures has many applications in biomedicine, nanotechnology and synthetic biology. An RNA molecule is made of different types of secondary structure elements and an important RNA element named pseudoknot plays a key role in stabilizing the functional form of the molecule. However, due to the computational complexities associated with characterizing pseudoknotted RNA structures, most of the existing RNA sequence designer algorithms generally ignore this important structural element and therefore limit their applications. In this paper we present a new algorithm to design RNA sequences for pseudoknotted secondary structures. We use NUPACK as the folding algorithm to compute the equilibrium characteristics of the pseudoknotted RNAs, and describe a new adaptive defect weighted sampling algorithm named Enzymer to design low ensemble defect RNA sequences for targeted secondary structures including pseudoknots. We used a biological data set of 201 pseudoknotted structures from the Pseudobase library to benchmark the performance of our algorithm. We compared the quality characteristics of the RNA sequences we designed by Enzymer with the results obtained from the state of the art MODENA and antaRNA. Our results show our method succeeds more frequently than MODENA and antaRNA do, and generates sequences that have lower ensemble defect, lower probability defect and higher thermostability. Finally by using Enzymer and by constraining the design to a naturally occurring and highly conserved Hammerhead motif, we designed 8 sequences for a pseudoknotted cis-acting Hammerhead ribozyme. Enzymer is available for download at https://bitbucket.org/casraz/enzymer. PMID:27499762

  3. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  4. The Parent Version of the Preschool Social Skills Rating System: Psychometric Analysis and Adaptation with a German Preschool Sample

    ERIC Educational Resources Information Center

    Hess, Markus; Scheithauer, Herbert; Kleiber, Dieter; Wille, Nora; Erhart, Michael; Ravens-Sieberer, Ulrike

    2014-01-01

    The Social Skills Rating System (SSRS) developed by Gresham and Elliott (1990) is a multirater, norm-referenced instrument measuring social skills and adaptive behavior in preschool children. The aims of the present study were (a) to test the factorial structure of the Parent Form of the SSRS for the first time with a German preschool sample (391…

  5. Some Features of the Sampling Distribution of the Ability Estimate in Computerized Adaptive Testing According to Two Stopping Rules.

    ERIC Educational Resources Information Center

    Blais, Jean-Guy; Raiche, Gilles

    This paper examines some characteristics of the statistics associated with the sampling distribution of the proficiency level estimate when the Rasch model is used. These characteristics allow the judgment of the meaning to be given to the proficiency level estimate obtained in adaptive testing, and as a consequence, they can illustrate the…

  6. Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus).

    PubMed

    Marsden, Clare D; Woodroffe, Rosie; Mills, Michael G L; McNutt, J Weldon; Creel, Scott; Groom, Rosemary; Emmanuel, Masenga; Cleaveland, Sarah; Kat, Pieter; Rasmussen, Gregory S A; Ginsberg, Joshua; Lines, Robin; André, Jean-Marc; Begg, Colleen; Wayne, Robert K; Mable, Barbara K

    2012-03-01

    Deciphering patterns of genetic variation within a species is essential for understanding population structure, local adaptation and differences in diversity between populations. Whilst neutrally evolving genetic markers can be used to elucidate demographic processes and genetic structure, they are not subject to selection and therefore are not informative about patterns of adaptive variation. As such, assessments of pertinent adaptive loci, such as the immunity genes of the major histocompatibility complex (MHC), are increasingly being incorporated into genetic studies. In this study, we combined neutral (microsatellite, mtDNA) and adaptive (MHC class II DLA-DRB1 locus) markers to elucidate the factors influencing patterns of genetic variation in the African wild dog (Lycaon pictus); an endangered canid that has suffered extensive declines in distribution and abundance. Our genetic analyses found all extant wild dog populations to be relatively small (N(e)  < 30). Furthermore, through coalescent modelling, we detected a genetic signature of a recent and substantial demographic decline, which correlates with human expansion, but contrasts with findings in some other African mammals. We found strong structuring of wild dog populations, indicating the negative influence of extensive habitat fragmentation and loss of gene flow between habitat patches. Across populations, we found that the spatial and temporal structure of microsatellite diversity and MHC diversity were correlated and strongly influenced by demographic stability and population size, indicating the effects of genetic drift in these small populations. Despite this correlation, we detected signatures of selection at the MHC, implying that selection has not been completely overwhelmed by genetic drift.

  7. Simulating spatial adaption of groundwater pumping on seawater intrusion in coastal regions

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Ladwig, Robert; Schütze, Niels; Walther, Marc

    2016-04-01

    Coastal aquifer systems are used intensively to meet the growing demands for water in those regions. They are especially at risk for the intrusion of seawater due to aquifer overpumping, limited groundwater replenishment and unsustainable groundwater management which in turn also impacts the social and economical development of coastal regions. One example is the Al-Batinah coastal plain in northern Oman where irrigated agriculture is practiced by lots of small scaled farms in different distances from the sea, each of them pumping their water from coastal aquifer. Due to continuous overpumping and progressing saltwater intrusion farms near the coast had to close since water for irrigation got too saline. For investigating appropriate management options numerical density dependent groundwater modelling is required which should also portray the adaption of groundwater abstraction schemes on the water quality. For addressing this challenge a moving inner boundary condition is implemented in the numerical density dependent groundwater model which adjusts the locations for groundwater abstraction according to the position of the seawater intrusion front controlled by thresholds of relative chloride concentration. The adaption process is repeated for each management cycle within transient model simulations and allows for considering feedbacks with the consumers e.g. the agriculture by moving agricultural farms more inland or towards the sea if more fertile soils at the coast could be recovered. For finding optimal water management strategies efficiently, the behaviour of the numerical groundwater model for different extraction and replenishment scenarios is approximated by an artificial neural network using a novel approach for state space surrogate model development. Afterwards the derived surrogate is coupled with an agriculture module within a simulation based water management optimisation framework to achieve optimal cropping pattern and water abstraction schemes

  8. Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

    DTIC Science & Technology

    2002-09-30

    integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to develop hyperspectral remote sensing techniques in optically complex nearshore coastal waters.

  9. Passive Sampling to Capture the Spatial Variability of Coarse Particles by Composition in Cleveland, OH

    EPA Science Inventory

    Passive samplers deployed at 25 sites for three week-long intervals were used to characterize spatial variability in the mass and composition of coarse particulate matter (PM10-2.5) in Cleveland, OH in summer 2008. The size and composition of individual particles deter...

  10. Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

    NASA Technical Reports Server (NTRS)

    Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong

    2016-01-01

    With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for

  11. Spatial pattern of nucleotide polymorphism indicates molecular adaptation in the bryophyte Sphagnum fimbriatum.

    PubMed

    Szövényi, P; Hock, Zs; Korpelainen, H; Shaw, A Jonathan

    2009-10-01

    In organisms with haploid-dominant life cycles, natural selection is expected to be especially effective because genetic variation is exposed directly to selection. However, in spore-producing plants with high dispersal abilities, among-population migration may counteract local adaptation by continuously redistributing genetic variability. In this study, we tested for adaptation at the molecular level by comparing nucleotide polymorphism in two genes (GapC and Rpb2) in 10 European populations of the peatmoss species, Sphagnum fimbriatum with variability at nine microsatellite loci assumed to be selectively neutral. In line with previous results, the GapC and Rpb2 genes showed strikingly different patterns of nucleotide polymorphism. Neutrality tests and comparison of population differentiation based on the GapC and Rpb2 genes with neutrally evolving microsatellites using coalescent simulations supported non-neutral evolution in GapC, but neutral evolution in the Rpb2 gene. These observations and the positions of the replacement mutations in the GAPDH enzyme (coded by GapC) indicate a significant impact of replacement mutations on enzyme function. Furthermore, the geographic distribution of alternate GapC alleles and/or linked genomic regions suggests that they have had differential success in the recolonization of Europe following the Last Glacial Maximum.

  12. Adaptation of G-TAG Software for Validating Touch-and-Go Comet Surface Sampling Design Methodology

    NASA Technical Reports Server (NTRS)

    Mandic, Milan; Acikmese, Behcet; Blackmore, Lars

    2011-01-01

    The G-TAG software tool was developed under the R&TD on Integrated Autonomous Guidance, Navigation, and Control for Comet Sample Return, and represents a novel, multi-body dynamics simulation software tool for studying TAG sampling. The G-TAG multi-body simulation tool provides a simulation environment in which a Touch-and-Go (TAG) sampling event can be extensively tested. TAG sampling requires the spacecraft to descend to the surface, contact the surface with a sampling collection device, and then to ascend to a safe altitude. The TAG event lasts only a few seconds but is mission-critical with potentially high risk. Consequently, there is a need for the TAG event to be well characterized and studied by simulation and analysis in order for the proposal teams to converge on a reliable spacecraft design. This adaptation of the G-TAG tool was developed to support the Comet Odyssey proposal effort, and is specifically focused to address comet sample return missions. In this application, the spacecraft descends to and samples from the surface of a comet. Performance of the spacecraft during TAG is assessed based on survivability and sample collection performance. For the adaptation of the G-TAG simulation tool to comet scenarios, models are developed that accurately describe the properties of the spacecraft, approach trajectories, and descent velocities, as well as the models of the external forces and torques acting on the spacecraft. The adapted models of the spacecraft, descent profiles, and external sampling forces/torques were more sophisticated and customized for comets than those available in the basic G-TAG simulation tool. Scenarios implemented include the study of variations in requirements, spacecraft design (size, locations, etc. of the spacecraft components), and the environment (surface properties, slope, disturbances, etc.). The simulations, along with their visual representations using G-View, contributed to the Comet Odyssey New Frontiers proposal

  13. Adaptation and psychometric properties of the student career construction inventory for a Portuguese sample: formative and reflective constructs.

    PubMed

    Rocha, Magda; Guimarães, Maria Isabel

    2012-12-01

    The adaptation of the student career construction inventory was carried out with a Portuguese sample of 356 first-year economics, management, psychology, nursing, nutrition sciences, bio-engineering, and biosciences students (244 women, 112 men; M age = 19.4, SD = 4.4) in the Catholic University of Portugal, Porto. Confirmatory factorial analysis supported the prior structure of the reflective models, with acceptable fit indexes. Internal consistency coefficients for the scales were poor to acceptable (.51 to .89). The formative nature of career adaptability was supported in a complex model identified by structural relations for which the fit indexes were weak but acceptable for a preliminary study.

  14. Temporal and spatial instability in neutral and adaptive (MHC) genetic variation in marginal salmon populations

    PubMed Central

    Ciborowski, Kate; Jordan, William C; Garcia de Leaniz, Carlos; Consuegra, Sofia

    2017-01-01

    The role of marginal populations for the long-term maintenance of species’ genetic diversity and evolutionary potential is particularly timely in view of the range shifts caused by climate change. The Centre-Periphery hypothesis predicts that marginal populations should bear reduced genetic diversity and have low evolutionary potential. We analysed temporal stability at neutral microsatellite and adaptive MHC genetic variation over five decades in four marginal Atlantic salmon populations located at the southern limit of the species’ distribution with a complicated demographic history, which includes stocking with foreign and native salmon for at least 2 decades. We found a temporal increase in neutral genetic variation, as well as temporal instability in population structuring, highlighting the importance of temporal analyses in studies that examine the genetic diversity of peripheral populations at the margins of the species’ range, particularly in face of climate change. PMID:28186200

  15. Urban Infrastructure Monitoring with a Spatially Adaptive Multi-Looking InSAR Technique

    NASA Astrophysics Data System (ADS)

    Sharma, Jayanti; Eppler, Jayson; Busler, Jennifer

    2015-05-01

    Surface displacements for urban infrastructure monitoring are derived using Interferometric Synthetic Aperture Radar (InSAR). The analysis uses a novel InSAR method, Homogenous Distributed Scatterer (HDS)-InSAR, that exploits both persistent point and coherent distributed scatterers using adaptive multi-looking of statistically homogenous pixel neighbourhoods. An unwrapped phase model incorporating meteorological data enables separation of temperature-correlated displacement from potentially hazardous long-term trends. Results are presented over the Canadian cities of Regina, Winnipeg and Montreal using RADARSAT-2 and TerraSAR-X data. The new combination of HDS-InSAR and the extended phase model permits large areas of infrastructure to be remotely monitored on a regular basis and enables a more targeted monitoring process to help identify infrastructure at greatest risk for damage.

  16. Use of spatially distributed time-integrated sediment sampling networks and distributed fine sediment modelling to inform catchment management.

    PubMed

    Perks, M T; Warburton, J; Bracken, L J; Reaney, S M; Emery, S B; Hirst, S

    2017-02-06

    Under the EU Water Framework Directive, suspended sediment is omitted from environmental quality standards and compliance targets. This omission is partly explained by difficulties in assessing the complex dose-response of ecological communities. But equally, it is hindered by a lack of spatially distributed estimates of suspended sediment variability across catchments. In this paper, we demonstrate the inability of traditional, discrete sampling campaigns for assessing exposure to fine sediment. Sampling frequencies based on Environmental Quality Standard protocols, whilst reflecting typical manual sampling constraints, are unable to determine the magnitude of sediment exposure with an acceptable level of precision. Deviations from actual concentrations range between -35 and +20% based on the interquartile range of simulations. As an alternative, we assess the value of low-cost, suspended sediment sampling networks for quantifying suspended sediment transfer (SST). In this study of the 362 km(2) upland Esk catchment we observe that spatial patterns of sediment flux are consistent over the two year monitoring period across a network of 17 monitoring sites. This enables the key contributing sub-catchments of Butter Beck (SST: 1141 t km(2) yr(-1)) and Glaisdale Beck (SST: 841 t km(2) yr(-1)) to be identified. The time-integrated samplers offer a feasible alternative to traditional infrequent and discrete sampling approaches for assessing spatio-temporal changes in contamination. In conjunction with a spatially distributed diffuse pollution model (SCIMAP), time-integrated sediment sampling is an effective means of identifying critical sediment source areas in the catchment, which can better inform sediment management strategies for pollution prevention and control.

  17. Spatial Distribution and Minimum Sample Size for Overwintering Larvae of the Rice Stem Borer Chilo suppressalis (Walker) in Paddy Fields.

    PubMed

    Arbab, A

    2014-10-01

    The rice stem borer, Chilo suppressalis (Walker), feeds almost exclusively in paddy fields in most regions of the world. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling procedures, and adopting precise agricultural techniques. Field experiments were conducted during 2011 and 2012 to estimate the spatial distribution pattern of the overwintering larvae. Data were analyzed using five distribution indices and two regression models (Taylor and Iwao). All of the indices and Taylor's model indicated random spatial distribution pattern of the rice stem borer overwintering larvae. Iwao's patchiness regression was inappropriate for our data as shown by the non-homogeneity of variance, whereas Taylor's power law fitted the data well. The coefficients of Taylor's power law for a combined 2 years of data were a = -0.1118, b = 0.9202 ± 0.02, and r (2) = 96.81. Taylor's power law parameters were used to compute minimum sample size needed to estimate populations at three fixed precision levels, 5, 10, and 25% at 0.05 probabilities. Results based on this equation parameters suggesting that minimum sample sizes needed for a precision level of 0.25 were 74 and 20 rice stubble for rice stem borer larvae when the average larvae is near 0.10 and 0.20 larvae per rice stubble, respectively.

  18. Amoeboid migration mode adaption in quasi-3D spatial density gradients of varying lattice geometry

    NASA Astrophysics Data System (ADS)

    Gorelashvili, Mari; Emmert, Martin; Hodeck, Kai F.; Heinrich, Doris

    2014-07-01

    Cell migration processes are controlled by sensitive interaction with external cues such as topographic structures of the cell’s environment. Here, we present systematically controlled assays to investigate the specific effects of spatial density and local geometry of topographic structure on amoeboid migration of Dictyostelium discoideum cells. This is realized by well-controlled fabrication of quasi-3D pillar fields exhibiting a systematic variation of inter-pillar distance and pillar lattice geometry. By time-resolved local mean-squared displacement analysis of amoeboid migration, we can extract motility parameters in order to elucidate the details of amoeboid migration mechanisms and consolidate them in a two-state contact-controlled motility model, distinguishing directed and random phases. Specifically, we find that directed pillar-to-pillar runs are found preferably in high pillar density regions, and cells in directed motion states sense pillars as attractive topographic stimuli. In contrast, cell motion in random probing states is inhibited by high pillar density, where pillars act as obstacles for cell motion. In a gradient spatial density, these mechanisms lead to topographic guidance of cells, with a general trend towards a regime of inter-pillar spacing close to the cell diameter. In locally anisotropic pillar environments, cell migration is often found to be damped due to competing attraction by different pillars in close proximity and due to lack of other potential stimuli in the vicinity of the cell. Further, we demonstrate topographic cell guidance reflecting the lattice geometry of the quasi-3D environment by distinct preferences in migration direction. Our findings allow to specifically control amoeboid cell migration by purely topographic effects and thus, to induce active cell guidance. These tools hold prospects for medical applications like improved wound treatment, or invasion assays for immune cells.

  19. A stochastic optimisation method to estimate the spatial distribution of a pathogen from a sample.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sampling is of central importance in plant pathology. It facilitates our understanding of how epidemics develop in space and time and can also be used to inform disease management decisions. Making inferences from a sample is necessary because we rarely have the resources to conduct a complete censu...

  20. Anti-aliasing Wiener filtering for wave-front reconstruction in the spatial-frequency domain for high-order astronomical adaptive-optics systems.

    PubMed

    Correia, Carlos M; Teixeira, Joel

    2014-12-01

    Computationally efficient wave-front reconstruction techniques for astronomical adaptive-optics (AO) systems have seen great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered much attention, especially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl ratio) and further develop formulae for the anti-aliasing (AA) Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e., discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise, and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of forward models for the Shack-Hartmann wave-front sensor (using sparse and nonsparse representations) and compute point-spread-function raw intensities. We find that for a 32×32 single-conjugated AOs system the aliasing propagation coefficient is roughly 60% of the least-squares filters, whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in the H band. For current and next-generation high-contrast imagers, despite better aliasing mitigation, AA Wiener filtering cannot be used as a standalone method and must therefore be used in combination with optical spatial filters deployed before image formation actually takes place.

  1. Sample preparation and biomass determination of SRF model mixture using cryogenic milling and the adapted balance method

    SciTech Connect

    Schnöller, Johannes Aschenbrenner, Philipp; Hahn, Manuel; Fellner, Johann; Rechberger, Helmut

    2014-11-15

    Highlights: • An alternative sample comminution procedure for SRF is tested. • Proof of principle is shown on a SRF model mixture. • The biogenic content of the SRF is analyzed with the adapted balance method. • The novel method combines combustion analysis and a data reconciliation algorithm. • Factors for the variance of the analysis results are statistically quantified. - Abstract: The biogenic fraction of a simple solid recovered fuel (SRF) mixture (80 wt% printer paper/20 wt% high density polyethylene) is analyzed with the in-house developed adapted balance method (aBM). This fairly new approach is a combination of combustion elemental analysis (CHNS) and a data reconciliation algorithm based on successive linearisation for evaluation of the analysis results. This method shows a great potential as an alternative way to determine the biomass content in SRF. However, the employed analytical technique (CHNS elemental analysis) restricts the probed sample mass to low amounts in the range of a few hundred milligrams. This requires sample comminution to small grain sizes (<200 μm) to generate representative SRF specimen. This is not easily accomplished for certain material mixtures (e.g. SRF with rubber content) by conventional means of sample size reduction. This paper presents a proof of principle investigation of the sample preparation and analysis of an SRF model mixture with the use of cryogenic impact milling (final sample comminution) and the adapted balance method (determination of biomass content). The so derived sample preparation methodology (cutting mills and cryogenic impact milling) shows a better performance in accuracy and precision for the determination of the biomass content than one solely based on cutting mills. The results for the determination of the biogenic fraction are within 1–5% of the data obtained by the reference methods, selective dissolution method (SDM) and {sup 14}C-method ({sup 14}C-M)

  2. Quantifying microplastic pollution on sandy beaches: the conundrum of large sample variability and spatial heterogeneity.

    PubMed

    Fisner, Mara; Majer, Alessandra P; Balthazar-Silva, Danilo; Gorman, Daniel; Turra, Alexander

    2017-04-11

    Despite the environmental risks posed by microplastic pollution, there are presently few standardized protocols for monitoring these materials within marine and coastal habitats. We provide a robust comparison of methods for sampling microplastics on sandy beaches using pellets as a model and attempt to define a framework for reliable standing stock estimation. We performed multiple comparisons to determine: (1) the optimal size of sampling equipment, (2) the depth to which samples should be obtained, (3) the optimal sample resolution for cross-shore transects, and (4) the number of transects required to yield reproducible along-shore estimates across the entire sections of a beach. Results affirmed that the use of a manual auger with a 20-cm diameter yielded the best compromise between reproducibility (i.e., standard deviation) and sampling/processing time. Secondly, we suggest that sediments should be profiled to a depth of at least 1 m to fully assess the depth distribution of pellets. Thirdly, although sample resolution did not have major consequence for overall density estimates, using 7-m intervals provides an optimal balance between precision (SD) and effort (total sampling time). Finally, and perhaps most importantly, comparing the minimum detectable difference yielded by different numbers of transects along a given section of beach suggests that estimating absolute particle density is probably unviable for most systems and that monitoring might be better accomplished through hierarchical or time series sampling efforts. Overall, while our study provides practical information that can improve sampling efforts, the heterogeneous nature of microplastic pollution poses a major conundrum to reproducible monitoring and management of this significant and growing problem.

  3. Spatial distribution of nymphs of Scaphoideus titanus (Homoptera: Cicadellidae) in grapes, and evaluation of sequential sampling plans.

    PubMed

    Lessio, Federico; Alma, Alberto

    2006-04-01

    The spatial distribution of the nymphs of Scaphoideus titanus Ball (Homoptera Cicadellidae), the vector of grapevine flavescence dorée (Candidatus Phytoplasma vitis, 16Sr-V), was studied by applying Taylor's power law. Studies were conducted from 2002 to 2005, in organic and conventional vineyards of Piedmont, northern Italy. Minimum sample size and fixed precision level stop lines were calculated to develop appropriate sampling plans. Model validation was performed, using independent field data, by means of Resampling Validation of Sample Plans (RVSP) resampling software. The nymphal distribution, analyzed via Taylor's power law, was aggregated, with b = 1.49. A sample of 32 plants was adequate at low pest densities with a precision level of D0 = 0.30; but for a more accurate estimate (D0 = 0.10), the required sample size needs to be 292 plants. Green's fixed precision level stop lines seem to be more suitable for field sampling: RVSP simulations of this sampling plan showed precision levels very close to the desired levels. However, at a prefixed precision level of 0.10, sampling would become too time-consuming, whereas a precision level of 0.25 is easily achievable. How these results could influence the correct application of the compulsory control of S. titanus and Flavescence dorée in Italy is discussed.

  4. Psychometric Properties of the Schedule for Nonadaptive and Adaptive Personality in a PTSD Sample

    ERIC Educational Resources Information Center

    Wolf, Erika J.; Harrington, Kelly M.; Miller, Mark W.

    2011-01-01

    This study evaluated the psychometric characteristics of the Schedule for Nonadaptive and Adaptive Personality (SNAP; Clark, 1996) in 280 individuals who screened positive for posttraumatic stress disorder (PTSD). The SNAP validity, trait, temperament, and personality disorder (PD) scales were compared with scales on the Brief Form of the…

  5. Adaption of egg and larvae sampling techniques for lake sturgeon and broadcast spawning fishes in a deep river

    USGS Publications Warehouse

    Roseman, Edward F.; Kennedy, Gregory W.; Craig, Jaquelyn; Boase, James; Soper, Karen

    2011-01-01

    In this report we describe how we adapted two techniques for sampling lake sturgeon (Acipenser fulvescens) and other fish early life history stages to meet our research needs in the Detroit River, a deep, flowing Great Lakes connecting channel. First, we developed a buoy-less method for sampling fish eggs and spawning activity using egg mats deployed on the river bottom. The buoy-less method allowed us to fish gear in areas frequented by boaters and recreational anglers, thus eliminating surface obstructions that interfered with recreational and boating activities. The buoy-less method also reduced gear loss due to drift when masses of floating aquatic vegetation would accumulate on buoys and lines, increasing the drag on the gear and pulling it downstream. Second, we adapted a D-frame drift net system formerly employed in shallow streams to assess larval lake sturgeon dispersal for use in the deeper (>8 m) Detroit River using an anchor and buoy system.

  6. Design of a sample chamber for spatial emissivity measurements using thermal imaging

    NASA Astrophysics Data System (ADS)

    Clarke, F. J. J.; Boyd, N. A.; Leonard, J. K.

    1988-01-01

    Optical and electronic modifications have been made to a TICM II thermal imager to allow its use in near-focus radiometric measurements. A GEMS image processing system has customized enhancements to the existing GEMMA software permitting pixel-by-pixel restoration and radiometric calibration of images with user-defined algorithms. To allow emissivity measurements to be made at near-ambient temperatures, a nonreflecting cryogenic sample chamber is necessary to remove the reflected component of sample radiance. The design and construction of such a sample chamber are discussed in detail in relation to the NPL facility nearing completion for measuring the emissivity of nonuniform materials or objects. Particular features are the avoidance of vacuum systems for purging or insulation, and the geometrical and thermal design to give easy of handling and a long operating period from a single filling with liquid nitrogen.

  7. Optical limiting using spatial self-phase modulation in hot atomic sample

    NASA Astrophysics Data System (ADS)

    Zhang, Qian; Cheng, Xuemei; Zhang, Ying; Yin, Xunli; Jiang, Man; Chen, Haowei; Bai, Jintao

    2017-02-01

    In this work, we characterized the performance of optical limiting by self-phase modulation (SPM) in hot atomic vapor cell. The results indicated that the performance of the optical limiter is closely related to the position of the sample cell, which is determined by the Rayleigh lenght of beam. The lowest limiting threshold and clamp output were obtained at the sample position at -10 mm from the coordinate origin (the beam waist). The phenomenon was explained well by the theory of SPM and z-scan, which are caused by both Kerr effect and the thermal optical nonlinear effect. This useful information obtained in the meaning of this work is determining the optimal position of the sample cell in the optical limiter and other applications of SPM.

  8. Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of In situ Optical Properties

    DTIC Science & Technology

    2003-09-30

    We are developing an integrated rapid environmental assessment capability that will be used to feed an ocean nowcast/forecast system. The goal is to develop a capacity for predicting the dynamics in inherent optical properties in coastal waters. This is being accomplished by developing an integrated observation system that is being coupled to a data assimilative hydrodynamic bio-optical ecosystem model. The system was used adaptively to calibrate hyperspectral remote sensing sensors in optically complex nearshore coastal waters.

  9. Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain

    PubMed Central

    2014-01-01

    Background Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. Methods We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. Results During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Conclusions Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling. PMID:24735818

  10. Use of Spatial Sampling and Microbial Source-Tracking Tools for Understanding Fecal Contamination at Two Lake Erie Beaches

    USGS Publications Warehouse

    Francy, Donna S.; Bertke, Erin E.; Finnegan, Dennis P.; Kephart, Christopher M.; Sheets, Rodney A.; Rhoades, John; Stumpe, Lester

    2006-01-01

    Source-tracking tools were used to identify potential sources of fecal contamination at two Lake Erie bathing beaches: an urban beach (Edgewater in Cleveland, Ohio) and a beach in a small city (Lakeshore in Ashtabula, Ohio). These tools included identifying spatial patterns of Escherichia coli (E. coli) concentrations in each area, determining weather patterns that caused elevated E. coli, and applying microbial source tracking (MST) techniques to specific sites. Three MST methods were used during this study: multiple antibiotic resistance (MAR) indexing of E. coli isolates and the presence of human-specific genetic markers within two types of bacteria, the genus Bacteroides and the species Enterococcus faecium. At Edgewater, sampling for E. coli was done during 2003-05 at bathing-area sites, at nearshore lake sites, and in shallow ground water in foreshore and backshore areas. Spatial sampling at nearshore lake sites showed that fecal contamination was most likely of local origin; E. coli concentrations near the mouths of rivers and outfalls remote to the beach were elevated (greater than 235 colony-forming units per 100 milliliters (CFU/100 mL)) but decreased along transport pathways to the beach. In addition, E. coli concentrations were generally highest in bathing-area samples collected at 1- and 2-foot water depths, midrange at 3-foot depths, and lowest in nearshore lake samples typically collected 150 feet from the shoreline. Elevated E. coli concentrations at bathing-area sites were generally associated with increased wave heights and rainfall, but not always. E. coli concentrations were often elevated in shallow ground-water samples, especially in samples collected less than 10 feet from the edge of water (near foreshore area). The interaction of shallow ground water and waves may be a mechanism of E. coli storage and accumulation in foreshore sands. Infiltration of bird feces through sand with surface water from rainfall and high waves may be concentrating

  11. Spatial variation in osteon population density at the human femoral midshaft: histomorphometric adaptations to habitual load environment.

    PubMed

    Gocha, Timothy P; Agnew, Amanda M

    2016-05-01

    Intracortical remodeling, and the osteons it produces, is one aspect of the bone microstructure that is influenced by and, in turn, can influence its mechanical properties. Previous research examining the spatial distribution of intracortical remodeling density across the femoral midshaft has been limited to either considering only small regions of the cortex or, when looking at the entirety of the cortex, considering only a single individual. This study examined the spatial distribution of all remodeling events (intact osteons, fragmentary osteons, and resorptive bays) across the entirety of the femoral midshaft in a sample of 30 modern cadaveric donors. The sample consisted of 15 males and 15 females, aged 21-97 years at time of death. Using geographic information systems software, the femoral cortex was subdivided radially into thirds and circumferentially into octants, and the spatial location of all remodeling events was marked. Density maps and calculation of osteon population density in cortical regions of interest revealed that remodeling density is typically highest in the periosteal third of the bone, particularly in the lateral and anterolateral regions of the cortex. Due to modeling drift, this area of the midshaft femur has some of the youngest primary tissue, which consequently reveals that the lateral and anterolateral regions of the femoral midshaft have higher remodeling rates than elsewhere in the cortex. This is likely the result of tension/shear forces and/or greater strain magnitudes acting upon the anterolateral femur, which results in a greater amount of microdamage in need of repair than is seen in the medial and posterior regions of the femoral midshaft, which are more subject to compressive forces and/or lesser strain magnitudes.

  12. Spatial and temporal influences on bacterial profiling of forensic soil samples.

    PubMed

    Meyers, Melissa S; Foran, David R

    2008-05-01

    Bacterial content may be helpful in differentiating forensic soil samples; however, the effectiveness of bacterial profiling depends on several factors, including uniqueness among different habitat types, the level of heterogeneity within a habitat, and changes in bacterial communities over time. To examine these, soils from five diverse habitats were tested over a 1 year period using terminal restriction fragment length polymorphism (TRFLP) analysis. Soil samples were collected at central locations monthly, and 10 feet in cardinal directions quarterly. Similarity indices were found to be least related among habitats, while the greatest bacterial similarities existed among collection locations within a habitat. Temporally, however, bacterial content varied considerably, and there was substantial overlap in similarity indices among habitats during different parts of the year. Taken together, the results indicate that while bacterial DNA profiling may be useful for forensic soil analysis, certain variables, particularly time, must be considered.

  13. Characterization of the spatial variability of soil available zinc at various sampling densities using grouped soil type information.

    PubMed

    Song, Xiao-Dong; Zhang, Gan-Lin; Liu, Feng; Li, De-Cheng; Zhao, Yu-Guo

    2016-11-01

    The influence of anthropogenic activities and natural processes involved high uncertainties to the spatial variation modeling of soil available zinc (AZn) in plain river network regions. Four datasets with different sampling densities were split over the Qiaocheng district of Bozhou City, China. The difference of AZn concentrations regarding soil types was analyzed by the principal component analysis (PCA). Since the stationarity was not indicated and effective ranges of four datasets were larger than the sampling extent (about 400 m), two investigation tools, namely F3 test and stationarity index (SI), were employed to test the local non-stationarity. Geographically weighted regression (GWR) technique was performed to describe the spatial heterogeneity of AZn concentrations under the non-stationarity assumption. GWR based on grouped soil type information (GWRG for short) was proposed so as to benefit the local modeling of soil AZn within each soil-landscape unit. For reference, the multiple linear regression (MLR) model, a global regression technique, was also employed and incorporated the same predictors as in the GWR models. Validation results based on 100 times realization demonstrated that GWRG outperformed MLR and can produce similar or better accuracy than the GWR approach. Nevertheless, GWRG can generate better soil maps than GWR for limit soil data. Two-sample t test of produced soil maps also confirmed significantly different means. Variogram analysis of the model residuals exhibited weak spatial correlation, rejecting the use of hybrid kriging techniques. As a heuristically statistical method, the GWRG was beneficial in this study and potentially for other soil properties.

  14. Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

    USGS Publications Warehouse

    Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

    2012-01-01

    The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

  15. Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

    USGS Publications Warehouse

    Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

    2012-01-01

    The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

  16. The spatial and temporal patterns of odors sampled by lobsters and crabs in a turbulent plume.

    PubMed

    Reidenbach, Matthew A; Koehl, M A R

    2011-09-15

    Odors are dispersed across aquatic habitats by turbulent water flow as filamentous, intermittent plumes. Many crustaceans sniff (take discrete samples of ambient water and the odors it carries) by flicking their olfactory antennules. We used planar laser-induced fluorescence to investigate how flicking antennules of different morphologies (long antennules of spiny lobsters, Panulirus argus; short antennules of blue crabs, Callinectes sapidus) sample fluctuating odor signals at different positions in a turbulent odor plume in a flume to determine whether the patterns of concentrations captured can provide information about an animal's position relative to the odor source. Lobster antennules intercept odors during a greater percentage of flicks and encounter higher peak concentrations than do crab antennules, but because crabs flick at higher frequency, the duration of odor-free gaps between encountered odor pulses is similar. For flicking antennules there were longer time gaps between odor encounters as the downstream distance to the odor source decreases, but shorter gaps along the plume centerline than near the edge. In contrast to the case for antennule flicking, almost all odor-free gaps were <500 ms at all positions in the plume if concentration was measured continuously at the same height as the antennules. Variance in concentration is lower and mean concentration is greater near the substratum, where leg chemosensors continuously sample the plume, than in the water where antennules sniff. Concentrations sampled by legs increase as an animal nears an odor source, but decrease for antennules. Both legs and antennules encounter higher concentrations near the centerline than at the edge of the plume.

  17. A Preview of the OCO-2 Spatial and Temporal Sampling Strategy

    NASA Technical Reports Server (NTRS)

    Crisp, David

    2013-01-01

    For routine science observations, the OC0-2 spacecraft bus points the instrument bore sight either at the local nadir (85 < 85deg) or at the glint spot (85 < 81 deg) and collects -106 soundings/day over the sunlit hemisphere. center dot Nadir observations: expected to yield more spatially-homogeneous optical paths in partially cloudy regions and over topographically rough land regions center dot Glint observations are expected to yield (much) higher SNR over dark ocean or ice covered surfaces. center dot For both glint and nadir observations, the spacecraft performs a yaw maneuver to orient the long axis of the spectrometer slits perpendicular to the principle plane center dot The nominal plan is to alternate between glint and nadir observations on alternate 16-day ground repeat cycles, but this strategy may be modified to maximize coverage Target observations: For calibration and validation, the spacecraft bus can also point the instrument bore sight at a stationary surface target center dot Collects up to 12,000 soundings at observing zenith angles from +75deg GEO CL-

  18. Overcoming the Curse of Dimension: Methods Based on Sparse Representation and Adaptive Sampling

    DTIC Science & Technology

    2011-02-28

    carried out mainly by him, together with our joint post-doc Haijun Yu. Please refer to his report for the progress made in this direction. 3 Exploring...multiscale modeling using sparse representation”, Comm. Comp. Phys., 4(5), pp. 1025–1033 (2008). [3] X. Zhou and W. Ren and W. E, “Adaptive minimum...action method for the study of rare events”, J. Chem. Phys., 128, 10, 2008. [4] X. Wan, X. Zhou and W. E, “Noise-induced transitions in the Kuramoto-Sivashinsky equation”, preprint, submitted. 4

  19. Comparison of different spatial sampling methods for validation of GEOV1 FVC product over heterogeneous and homogeneous surfaces

    NASA Astrophysics Data System (ADS)

    Ding, Yanling; Ge, Yong; Hu, Maogui; Zhang, Hongyan

    2016-10-01

    The development of an efficient ground sampling strategy which can sample the natural dynamics of variations in variables of interest, is critical to ensuring the validation of remotely sensed products. This study attempts to take a fresh look at geostatistical methods for ground sampling and pixel-mean estimating in remote sensing validation campaigns. Spatial random sampling (SRS), Block Kriging (BK), and Means of Surface with Non-homogeneity (MSN) were implemented to estimate the fractional vegetation cover mean values at GEVO1 1 km2 pixel level using Landsat 8 OLI and SPOT4 HRVIR1 fine-resolution FVC maps respectively derived from a homogeneous area covered by forest and a heterogeneous area covered by crop. The GEOV1 FVC product was validated using the means estimated by SRS, BK, and MSN. Root square error (RMSE), mean absolute percentage error (MAPE) and product accuracy (PA) were used to evaluate the validation. Results showed that the MSN method performs well for estimating the means of the surface with non-homogeneity, with a high accuracy of the GEOV1 FVC product (RMSE=0.12, MAPE=29.37 and PA= 77.39%). The statistical values outputted by BK were respectively 0.13, 31.46% and 76.21%. These values of SRS were respectively 0.13, 31.16% and 76.10%. For homogeneous surface, the statistical parameters outputted by these three methods were similar. These results revealed that MSN is an effective method for estimating the spatial means for heterogeneous surface and validating remote sensing product. We can conclude that choosing an appropriate sampling method has a significant impact on the validation of remote sensing product.

  20. Spatial distribution of Io's volcanic activity from near-IR adaptive optics observations on 100 nights in 2013-2015

    NASA Astrophysics Data System (ADS)

    de Kleer, Katherine; de Pater, Imke

    2016-12-01

    The extreme and time-variable volcanic activity on Jupiter's moon Io is the result of periodic tidal forcing. The spatial distribution of Io's surface heat flux provides an important constraint on models for tidal heat dissipation, yielding information on interior properties and on the depth at which the tidal heat is primarily dissipated. We analyze the spatial distribution of 48 hot spots based on more than 400 total hot spot detections in adaptive optics images taken on 100 nights in 2013-2015 (data presented in de Kleer and de Pater [2016] Time variability of Io's volcanic activity from near-IR adaptive optics 13 observations on 100 nights in 2013-2015). We present full surface maps of Io at multiple near-infrared wavelengths for three epochs during this time period, and show that the longitudinal distribution of hot spots has not changed significantly since the Galileo mission. We find that hot spots that are persistently active at moderate intensities tend to occur at different latitudes/longitudes than those that exhibit sudden brightening events characterized by high peak intensities and subsequent decay phases. While persistent hot spots are located primarily between ± 30°N, hot spots exhibiting bright eruption events occur primarily between 40° and 65° in both the northern and southern hemispheres. In addition, while persistent hot spots occur preferentially on the leading hemisphere, all bright eruptions were detected on the trailing hemisphere, despite the comparable longitudinal coverage of our observations to both hemispheres. A subset of the bright hot spots which are not intense enough to qualify as outburst eruptions resemble outbursts in terms of temporal evolution and spatial distribution, and may be outbursts whose peak emission went unobserved, or else scaled-down versions of the same phenomenon. A statistical analysis finds that large eruptions are more spatially clustered and occur at higher latitudes than 95% of simulated datasets that

  1. Female migrants in an urban setting -- the dimensions of spatial / physical adaptation. The case of Dhaka.

    PubMed

    Huq-hussain, S

    1996-01-01

    This study determines the settlement and social adjustment patterns among female migrants in Dhaka. Data were obtained from a survey conducted among migrant households in selected slums of Dhaka during 1988-90. The sample covers three zones: old, central, and peripheral. It includes 399 migrant households, which were drawn randomly among 2.5% of the poor in the city's 75 wards. Findings include a description of initial settlement patterns, housing construction materials and the organization of housing, floor space, basic facilities, type of structure, ownership, monthly rent, women's role in housing construction, choice of location, and changes in location. Findings suggest that migrants initially experienced housing shortages. Women did not have much choice and settled in highly congested areas. Relatives and friends provided assistance upon arrival. Most arrivals lived in high-density spaces with few amenities. The close contact and use of communal facilities fostered social adjustment and knowledge of urban living patterns. Length of migrant stay was associated with better housing conditions in the type of structure, access to utilities, and floor space. Long-term migrants had greater mobility and choice in housing. New migrants faced exploitation in rents and eviction problems. 63% of migrants lived in rental houses, and 37% lived rent-free. Monthly rent accounted for about 25% of total family income; food accounted for another 20%. Almost 25% of migrants lived in self-built structures on government land. 66% of slum housing was constructed of poor materials. 18% of slum dwellers lived in extremely poor housing of low height and built with flimsy materials. About 38% of slum population lived in bamboo sheds of normal height. 42% lived in tin shed structures. Most migrants lived in single-room bamboo structures.

  2. A Japanese New Altimetry Mission, COMPIRA - Towards High Temporal and Spatial Sampling of Sea Surface Height Measurement

    NASA Astrophysics Data System (ADS)

    Ito, N.; Uematsu, A.; Yajima, Y.; Isoguchi, O.

    2014-12-01

    Japan Aerospace Exploration Agency (JAXA) is working on a conceptual study of altimeter mission named Coastal and Ocean measurement Mission with Precise and Innovative Radar Altimeter (COMPIRA), which will carry a wide-swath altimeter named Synthetic aperture radar (SAR) Height Imaging Oceanic Sensor with Advanced Interferometry (SHIOSAI). Capturing meso/submeso-scale phenomena is one of important objectives of the COMPIRA mission, as well as operational oceanography and fishery. For operational oceanography including coastal forecast, swath of SHIOSAI is selected to be 80 km in left and right sides to maximize temporal and spatial sampling of the sea surface height. Orbit specifications are also designed to be better sampling especially for mid-latitude region. That is, a spatial grid sampling is 5 km and an observation times per revisit period (about 10 days) is 2 to 3 times. In order to meet both sampling frequency and spatial coverage requirements as much as possible, orbit inclination was set relatively low, 51 degrees. Although this sampling frequency is, of course, not enough high to capture time evolution of coastal phenomena, an assimilation process would compensate its time evolution if 2D SSH fields was observed at least once within decal time scale of phenomena. JAXA has launched a framework called "Coastal forecast core team" to aim at developing coastal forecast system through pre-launch activities toward COMPIRA. Assimilation segment as well as satellite and in situ data provision will play an important role on these activities. As a first step, we evaluated effects of ocean current forecast improvement with COMPIRA-simulated wide-swath and high sampling sea surface heights (SSH) data. Simulated SSH data are generated from regional ocean numerical models and the COMPIRA orbit and error specifications. Then, identical twin experiments are conducted to investigate the effect of wide-swath SSH measurements on coastal forecast in the Tohoku Pacific coast

  3. Adaptive sample size modification in clinical trials: start small then ask for more?

    PubMed

    Jennison, Christopher; Turnbull, Bruce W

    2015-12-20

    We consider sample size re-estimation in a clinical trial, in particular when there is a significant delay before the measurement of patient response. Mehta and Pocock have proposed methods in which sample size is increased when interim results fall in a 'promising zone' where it is deemed worthwhile to increase conditional power by adding more subjects. Our analysis reveals potential pitfalls in applying this approach. Mehta and Pocock use results of Chen, DeMets and Lan to identify when increasing sample size, but applying a conventional level α significance test at the end of the trial does not inflate the type I error rate: we have found the greatest gains in power per additional observation are liable to lie outside the region defined by this method. Mehta and Pocock increase sample size to achieve a particular conditional power, calculated under the current estimate of treatment effect: this leads to high increases in sample size for a small range of interim outcomes, whereas we have found it more efficient to make moderate increases in sample size over a wider range of cases. If the aforementioned pitfalls are avoided, we believe the broad framework proposed by Mehta and Pocock is valuable for clinical trial design. Working in this framework, we propose sample size rules that apply explicitly the principle of adding observations when they are most beneficial. The resulting trial designs are closely related to efficient group sequential tests for a delayed response proposed by Hampson and Jennison.

  4. Cerebellar cathodal tDCS interferes with recalibration and spatial realignment during prism adaptation procedure in healthy subjects.

    PubMed

    Panico, Francesco; Sagliano, Laura; Grossi, Dario; Trojano, Luigi

    2016-06-01

    The aim of this study is to clarify the specific role of the cerebellum during prism adaptation procedure (PAP), considering its involvement in early prism exposure (i.e., in the recalibration process) and in post-exposure phase (i.e., in the after-effect, related to spatial realignment). For this purpose we interfered with cerebellar activity by means of cathodal transcranial direct current stimulation (tDCS), while young healthy individuals were asked to perform a pointing task on a touch screen before, during and after wearing base-left prism glasses. The distance from the target dot in each trial (in terms of pixels) on horizontal and vertical axes was recorded and served as an index of accuracy. Results on horizontal axis, that was shifted by prism glasses, revealed that participants who received cathodal stimulation showed increased rightward deviation from the actual position of the target while wearing prisms and a larger leftward deviation from the target after prisms removal. Results on vertical axis, in which no shift was induced, revealed a general trend in the two groups to improve accuracy through the different phases of the task, and a trend, more visible in cathodal stimulated participants, to worsen accuracy from the first to the last movements in each phase. Data on horizontal axis allow to confirm that the cerebellum is involved in all stages of PAP, contributing to early strategic recalibration process, as well as to spatial realignment. On vertical axis, the improving performance across the different stages of the task and the worsening accuracy within each task phase can be ascribed, respectively, to a learning process and to the task-related fatigue.

  5. A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation.

    PubMed

    Joost, S; Bonin, A; Bruford, M W; Després, L; Conord, C; Erhardt, G; Taberlet, P

    2007-09-01

    The detection of adaptive loci in the genome is essential as it gives the possibility of understanding what proportion of a genome or which genes are being shaped by natural selection. Several statistical methods have been developed which make use of molecular data to reveal genomic regions under selection. In this paper, we propose an approach to address this issue from the environmental angle, in order to complement results obtained by population genetics. We introduce a new method to detect signatures of natural selection based on the application of spatial analysis, with the contribution of geographical information systems (GIS), environmental variables and molecular data. Multiple univariate logistic regressions were carried out to test for association between allelic frequencies at marker loci and environmental variables. This spatial analysis method (SAM) is similar to current population genomics approaches since it is designed to scan hundreds of markers to assess a putative association with hundreds of environmental variables. Here, by application to studies of pine weevils and breeds of sheep we demonstrate a strong correspondence between SAM results and those obtained using population genetics approaches. Statistical signals were found that associate loci with environmental parameters, and these loci behave atypically in comparison with the theoretical distribution for neutral loci. The contribution of this new tool is not only to permit the identification of loci under selection but also to establish hypotheses about ecological factors that could exert the selection pressure responsible. In the future, such an approach may accelerate the process of hunting for functional genes at the population level.

  6. Detection and spatial mapping of mercury contamination in water samples using a smart-phone.

    PubMed

    Wei, Qingshan; Nagi, Richie; Sadeghi, Kayvon; Feng, Steve; Yan, Eddie; Ki, So Jung; Caire, Romain; Tseng, Derek; Ozcan, Aydogan

    2014-02-25

    Detection of environmental contamination such as trace-level toxic heavy metal ions mostly relies on bulky and costly analytical instruments. However, a considerable global need exists for portable, rapid, specific, sensitive, and cost-effective detection techniques that can be used in resource-limited and field settings. Here we introduce a smart-phone-based hand-held platform that allows the quantification of mercury(II) ions in water samples with parts per billion (ppb) level of sensitivity. For this task, we created an integrated opto-mechanical attachment to the built-in camera module of a smart-phone to digitally quantify mercury concentration using a plasmonic gold nanoparticle (Au NP) and aptamer based colorimetric transmission assay that is implemented in disposable test tubes. With this smart-phone attachment that weighs <40 g, we quantified mercury(II) ion concentration in water samples by using a two-color ratiometric method employing light-emitting diodes (LEDs) at 523 and 625 nm, where a custom-developed smart application was utilized to process each acquired transmission image on the same phone to achieve a limit of detection of ∼ 3.5 ppb. Using this smart-phone-based detection platform, we generated a mercury contamination map by measuring water samples at over 50 locations in California (USA), taken from city tap water sources, rivers, lakes, and beaches. With its cost-effective design, field-portability, and wireless data connectivity, this sensitive and specific heavy metal detection platform running on cellphones could be rather useful for distributed sensing, tracking, and sharing of water contamination information as a function of both space and time.

  7. Spatial spectrograms of vibrating atomic force microscopy cantilevers coupled to sample surfaces

    SciTech Connect

    Wagner, Ryan; Raman, Arvind; Proksch, Roger

    2013-12-23

    Many advanced dynamic Atomic Force Microscopy (AFM) techniques such as contact resonance, force modulation, piezoresponse force microscopy, electrochemical strain microscopy, and AFM infrared spectroscopy exploit the dynamic response of a cantilever in contact with a sample to extract local material properties. Achieving quantitative results in these techniques usually requires the assumption of a certain shape of cantilever vibration. We present a technique that allows in-situ measurements of the vibrational shape of AFM cantilevers coupled to surfaces. This technique opens up unique approaches to nanoscale material property mapping, which are not possible with single point measurements alone.

  8. Vulnerability-Based Spatial Sampling Stratification for the National Children’s Study, Worcester County, Massachusetts: Capturing Health-Relevant Environmental and Sociodemographic Variability

    PubMed Central

    Downs, Timothy J.; Ogneva-Himmelberger, Yelena; Aupont, Onesky; Wang, Yangyang; Raj, Ann; Zimmerman, Paula; Goble, Robert; Taylor, Octavia; Churchill, Linda; Lemay, Celeste; McLaughlin, Thomas; Felice, Marianne

    2010-01-01

    Background The National Children’s Study is the most ambitious study ever attempted in the United States to assess how environmental factors impact child health and development. It aims to follow 100,000 children from gestation until 21 years of age. Success requires breaking new interdisciplinary ground, starting with how to select the sample of > 1,000 children in each of 105 study sites; no standardized protocol exists for stratification of the target population by factoring in the diverse environments it inhabits. Worcester County, Massachusetts, like other sites, stratifies according to local conditions and local knowledge, subject to probability sampling rules. Objectives We answer the following questions: How do we divide Worcester County into viable strata that represent its health-relevant environmental and sociodemographic heterogeneity, subject to sampling rules? What potential does our approach have to inform stratification at other sites? Results We developed a multivariable, vulnerability-based method for spatial sampling consisting of two descriptive indices: a hazards/stressors exposure index (comprising three proxy variables), and an adaptive capacity/sociodemographic character index (five variables). Multivariable, health-relevant stratification at the start of the study may improve detection power for environment–child health associations down the line. Eighteen strata capture countywide heterogeneity in the indices and have optimal relative homogeneity within each. They achieve comparable expected birth counts and conform to local concepts of space. Conclusion The approach offers moderate to high potential to inform other sites, limited by intersite differences in data availability, geodemographics, and technical capacity. Energetic community engagement from the start promotes local stratification coherence, plus vital researcher–community trust and co-ownership for sustainability. PMID:20211802

  9. Random Transect with Adaptive Clustering Sampling Design - ArcPad Applet Manual

    DTIC Science & Technology

    2011-09-01

    sampling design geodatabase ................................. 6 3.1.2 Create features in geodatabase ...developed for ArcPad®, a mobile geographical information software (GIS) for field applications developed by ESRI ® of Redlands, CA. ArcPad is designed to...occurrence maps (Rew et al. 2005) to guide future surveying and management efforts. The RTAC combines features of the two NIS sampling designs described

  10. An adaptive sampling algorithm for Doppler-shift fluorescence velocimetry in high-speed flows

    NASA Astrophysics Data System (ADS)

    Le Page, Laurent M.; O'Byrne, Sean

    2017-03-01

    We present an approach to improving the efficiency of obtaining samples over a given domain for the peak location of Gaussian line-shapes. The method uses parameter estimates obtained from previous measurements to determine subsequent sampling locations. The method may be applied to determine the location of a spectral peak, where the monetary or time cost is too high to allow a less efficient search method, such as sampling at uniformly distributed domain locations, to be used. We demonstrate the algorithm using linear least-squares fitting of log-scaled planar laser-induced fluorescence data combined with Monte-Carlo simulation of measurements, to accurately determine the Doppler-shifted fluorescence peak frequency for each pixel of a fluorescence image. A simulated comparison between this approach and a uniformly spaced sampling approach is carried out using fits both for a single pixel and for a collection of pixels representing the fluorescence images that would be obtained in a hypersonic flow facility. In all cases, the peak location of Doppler-shifted line-shapes were determined to a similar precision with fewer samples than could be achieved using the more typical uniformly distributed sampling approach.

  11. Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples.

    PubMed

    Clair, Geremy; Piehowski, Paul D; Nicola, Teodora; Kitzmiller, Joseph A; Huang, Eric L; Zink, Erika M; Sontag, Ryan L; Orton, Daniel J; Moore, Ronald J; Carson, James P; Smith, Richard D; Whitsett, Jeffrey A; Corley, Richard A; Ambalavanan, Namasivayam; Ansong, Charles

    2016-12-22

    Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, impacting measurement robustness, quantification and throughput. Here, we coupled LCM with a proteomics workflow that provides fully automated analysis of proteomes from microdissected tissues. Benchmarking against the current state-of-the-art in ultrasensitive global proteomics (FASP workflow), our approach demonstrated significant improvements in quantification (~2-fold lower variance) and throughput (>5 times faster). Using our approach we for the first time characterized, to a depth of >3,400 proteins, the ontogeny of protein changes during normal lung development in microdissected alveolar tissue containing only 4,000 cells. Our analysis revealed seven defined modules of coordinated transcription factor-signaling molecule expression patterns, suggesting a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes.

  12. Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

    PubMed Central

    Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora; Kitzmiller, Joseph A.; Huang, Eric L.; Zink, Erika M.; Sontag, Ryan L.; Orton, Daniel J.; Moore, Ronald J.; Carson, James P.; Smith, Richard D.; Whitsett, Jeffrey A.; Corley, Richard A.; Ambalavanan, Namasivayam; Ansong, Charles

    2016-01-01

    Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, impacting measurement robustness, quantification and throughput. Here, we coupled LCM with a proteomics workflow that provides fully automated analysis of proteomes from microdissected tissues. Benchmarking against the current state-of-the-art in ultrasensitive global proteomics (FASP workflow), our approach demonstrated significant improvements in quantification (~2-fold lower variance) and throughput (>5 times faster). Using our approach we for the first time characterized, to a depth of >3,400 proteins, the ontogeny of protein changes during normal lung development in microdissected alveolar tissue containing only 4,000 cells. Our analysis revealed seven defined modules of coordinated transcription factor-signaling molecule expression patterns, suggesting a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. PMID:28004771

  13. Evaluating spatial distribution and seasonal variation of phthalates using passive air sampling in southern India.

    PubMed

    Sampath, Srimurali; Selvaraj, Krishna Kumar; Shanmugam, Govindaraj; Krishnamoorthy, Vimalkumar; Chakraborty, Paromita; Ramaswamy, Babu Rajendran

    2017-02-01

    Usage of phthalates as plasticizers has resulted in worldwide occurrence and is becoming a serious concern to human health and environment. However, studies on phthalates in Indian atmosphere are lacking. Therefore, we studied the spatio-temporal trends of six major phthalates in Tamil Nadu, southern India, using passive air samplers. Phthalates were ubiquitously detected in all the samples and the average total phthalates found in decreasing order is pre-monsoon (61 ng m(-3)) > summer (52 ng m(-3)) > monsoon (17 ng m(-3)). Largely used phthalates, dibutylphthalate (DBP) and diethylhexlphthalate (DEHP) were predominantly found in all the seasons with contribution of 11-31% and 59-68%, respectively. The highest total phthalates was observed in summer at an urban location (836 ng m(-3)). Furthermore, through principal component analysis, potential sources were identified as emissions from additives of plasticizers in the polymer industry and the productions of adhesives, building materials and vinyl flooring. Although inhalation exposure of infants was higher than other population segments (toddlers, children and adults), exposure levels were found to be safe for people belonging to all ages based on reference dose (RfD) and tolerable daily intake (TDI) values. This study first attempted to report seasonal trend based on atmospheric monitoring using passive air sampling technique and exposure risk together.

  14. Spatial pattern of adaptive and neutral genetic diversity across different biomes in the lesser anteater (Tamandua tetradactyla).

    PubMed

    Clozato, Camila L; Mazzoni, Camila J; Moraes-Barros, Nadia; Morgante, João S; Sommer, Simone

    2015-11-01

    The genes of the major histocompatibility complex (MHC) code for proteins involved in antigen recognition and activation of the adaptive immune response and are thought to be regulated by natural selection, especially due to pathogen-driven selective pressure. In this study, we investigated the spatial distribution of MHC class II DRB exon 2 gene diversity of the lesser anteater (Tamandua tetradactyla) across five Brazilian biomes using next-generation sequencing and compared the MHC pattern with that of neutral markers (microsatellites). We found a noticeable high level of diversity in DRB (60 amino acid alleles in 65 individuals) and clear signatures of historical positive selection acting on this gene. Higher allelic richness and proportion of private alleles were found in rain forest biomes, especially Amazon forest, a megadiverse biome, possibly harboring greater pathogen richness as well. Neutral markers, however, showed a similar pattern to DRB, demonstrating the strength of demography as an additional force to pathogen-driven selection in shaping MHC diversity and structure. This is the first characterization and description of diversity of a MHC gene for any member of the magna-order Xenarthra, one of the basal lineages of placental mammals.

  15. Closed-loop adaptive optics using a spatial light modulator for sensing and compensating of optical aberrations in ophthalmic applications

    NASA Astrophysics Data System (ADS)

    Akondi, Vyas; Jewel, Md. Atikur Rahman; Vohnsen, Brian

    2014-09-01

    Sensing and compensating of optical aberrations in closed-loop mode using a single spatial light modulator (SLM) for ophthalmic applications is demonstrated. Notwithstanding the disadvantages of the SLM, in certain cases, this multitasking capability of the device makes it advantageous over existing deformable mirrors (DMs), which are expensive and in general used for aberration compensation alone. A closed-loop adaptive optics (AO) system based on a single SLM was built. Beam resizing optics were used to utilize the large active area of the device and hence make it feasible to generate 137 active subapertures for wavefront sensing. While correcting Zernike aberrations up to fourth order introduced with the help of a DM (for testing purposes), diffraction-limited resolution was achieved. It is shown that matched filter and intensity-weighted centroiding techniques stand out among others. Closed-loop wavefront correction of aberrations in backscattered light from the eyes of three healthy human subjects was demonstrated after satisfactory results were obtained using an artificial eye, which was simulated with a short focal length lens and a sheet of white paper as diffuser. It is shown that the closed-loop AO system based on a single SLM is capable of diffraction-limited correction for ophthalmic applications.

  16. Spatial and temporal trends of contaminants in mussel sampled around the Icelandic coastline.

    PubMed

    Sturludottir, Erla; Gunnlaugsdottir, Helga; Jorundsdottir, Hronn O; Magnusdottir, Elin V; Olafsdottir, Kristin; Stefansson, Gunnar

    2013-06-01

    Contaminants have been determined in blue mussels (Mytilus edulis) at 11 locations around the Icelandic coastline from 1990 to 2010. The aim of the present study was to investigate if there has been a change in concentration of contaminants around the Icelandic coastline for the last two decades and if the concentrations and changes, if present, were consistent between locations. Concentrations of the persistent organic pollutants, p,p'-dichlorodiphenyldichloroethene (p,p'-DDE), hexachlorobenzene (HCB), α-hexachlorocyclohexane (α-HCH), polychlorinated biphenyl (PCB-153) and trans-nonachlor, have decreased at most of the sampling locations in Iceland in recent years. However, an increasing trend was found at a few locations that could be explained by anthropogenic activity. The concentration levels of the persistent organics were much lower than found at the Norwegian, USA and Chinese coasts, especially levels of p,p'-DDE. The concentration of copper and selenium had a consistent pattern of change and concentration between locations over the period which showed a decreasing trend in recent years. The trace elements arsenic, cadmium, mercury and zinc showed more variation in concentration between locations, the concentration of arsenic, mercury and zinc was fairly stable over the period, whereas there were fluctuations in cadmium concentrations. The concentrations of cadmium and zinc were observed to be somewhat higher than found in mussels from Norway, USA and China but values of mercury and lead were much lower in the mussel sampled in Iceland. The higher concentrations of cadmium and zinc can be explained by the volcanic activity in Iceland but no major anthropogenic sources of trace elements are known in Iceland.

  17. Numerical Modeling of Hohlraum Radiation Conditions: Spatial and Spectral Variations due to Sample Position, Beam Pointing, and Hohlraum Geometry

    SciTech Connect

    Cohen, D H; Landen, O L; MacFarlane, J J

    2005-01-25

    View-factor simulations are presented of the spatially varying radiation conditions inside double-ended gold hohlraums and single-ended gold hohlraums (''halfraums'') used in inertial confinement fusion (ICF) and high energy density (HED) physics experiments [J. Lindl, Phys. Plasmas 11, 339 (2004); M. D. Rosen, Phys. Plasmas 3, 1803 (1996)]. It is shown that in many circumstances, the common assumption that the hohlraum ''drive'' can be characterized by a single temperature is too simplistic. Specifically, the radiation conditions seen by an experimental package can differ significantly from the wall reemission measured through diagnostic holes or laser entrance holes (LEHs) by absolutely calibrated detectors. Furthermore, even in situations where the radiation temperature is roughly the same for diagnostics and experimental packages, or for packages at different locations, the spectral energy distributions can vary significantly, due to the differing fractions of reemitting wall, laser hot spots, and LEHs seen from different locations. We find that the spatial variation of temperature, and especially the differences between what diagnostics looking in the LEH measure vs. the radiation temperature on wall-mounted experimental packages, is generally greater for double-ended hohlraums than it is for halfraums. View-factor simulations can also be used to explore experimental variables (halfraum length and geometry, sample position, and beam pointing) that can be adjusted in order to, for example, maximize the radiation flux onto a sample, or other package. In this vein, simulations of hohlraums and halfraums with LEH shields are also presented.

  18. Numerical modeling of Hohlraum radiation conditions: Spatial and spectral variations due to sample position, beam pointing, and Hohlraum geometry

    NASA Astrophysics Data System (ADS)

    Cohen, David H.; Landen, Otto L.; MacFarlane, Joseph J.

    2005-12-01

    View-factor simulations are presented of the spatially varying radiation conditions inside double-ended gold Hohlraums and single-ended gold Hohlraums ("halfraums") used in inertial confinement fusion and high-energy density physics experiments [J. Lindl, Phys. Plasmas 11, 339 (2004); M. D. Rosen, Phys. Plasmas 3, 1803 (1996)]. It is shown that in many circumstances, the common assumption that the Hohlraum "drive" can be characterized by a single temperature is too simplistic. Specifically, the radiation conditions seen by an experimental package can differ significantly from the wall reemission measured through diagnostic holes or laser entrance holes (LEHs) by absolutely calibrated detectors. Furthermore, even in situations where the radiation temperature is roughly the same for diagnostics and experimental packages, or for packages at different locations, the spectral energy distributions can vary significantly, due to the differing fractions of reemitting wall, laser hot spots, and LEHs seen from different locations. We find that the spatial variation of temperature and especially the differences between what diagnostics looking in the LEH measure versus the radiation temperature on wall-mounted experimental packages are generally greater for double-ended Hohlraums than for halfraums. View-factor simulations can also be used to explore experimental variables (halfraum length and geometry, sample position, and beam pointing) that can be adjusted in order to, for example, maximize the radiation flux onto a sample, or other package. In this vein, simulations of Hohlraums and halfraums with LEH shields are also presented.

  19. Spatial distribution and vertical migrations of fish larvae communities off Northwestern Iberia sampled with LHPR and Bongo nets

    NASA Astrophysics Data System (ADS)

    Garrido, Susana; Santos, A. Miguel P.; dos Santos, Antonina; Ré, Pedro

    2009-10-01

    The spatial distribution and diel vertical migration of fish larvae were studied in relation to the environmental conditions off NW Iberia during May 2002. Larvae from 23 families were identified, the most abundant were the Clupeidae, Gobiidae, Callionymidae, Blenniidae, Sparidae and Labridae. Sardina pilchardus was the most abundant species, mean concentrations 1 order of magnitude higher than the other fish larvae species. Larval horizontal distribution was mainly related to upwelling-driven circulation, resulting in an offshore increase of larval abundance while the vertical distribution was closely associated to the Western Iberia Buoyant Plume. Despite this general trend, taxon-specific relationships between the distribution of larvae and environmental variables were observed, and temperature was an important regressor explaining the distribution of most taxa. A comparison between ichthyoplankton samples collected alternatively with the LHPR and Bongo nets resulted in captures of larvae ≈1 order of magnitude higher for the LHPR, probably related to its higher towing speed. The spatial distribution and relative composition of larvae were also different for both nets, although the most frequent/abundant groups were the same. A fixed station sampled for 69-h showed diel vertical migrations performed by the larvae, with the highest larval concentrations occurring at surface layers during the night and most larvae being found in the neuston layer only during that period.

  20. Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions.

    PubMed

    Wojtas-Niziurski, Wojciech; Meng, Yilin; Roux, Benoit; Bernèche, Simon

    2013-04-09

    The potential of mean force describing conformational changes of biomolecules is a central quantity that determines the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates might require a lot of computational power, making some of multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The self-learning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems, and then applied to two non-trivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy.

  1. Acquiring Peak Samples from Phytoplankton Thin Layers and Intermediate Nepheloid Layers by an Autonomous Underwater Vehicle with Adaptive Triggering

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; McEwen, R.; Ryan, J. P.; Bellingham, J. G.; Harvey, J.; Vrijenhoek, R.

    2010-12-01

    Phytoplankton thin layers (PTLs) affect many fundamental aspects of coastal ocean ecology including primary productivity, development of harmful algal blooms (HABs) and the survival and growth of zooplankton and fish larvae. Intermediate nepheloid layers (INLs) that contain suspended particulate matter transported from the bottom boundary layer of continental shelves and slopes also affect biogeochemistry and ecology of ocean margins. To better understand the impacts of these types of layers, we have developed an adaptive sampling method for an autonomous underwater vehicle (AUV) to detect a layer (adjusting detection parameters in situ), acquire water samples from peaks in the layer, and acquire control samples outside the layer. We have used the method in a number of field experiments with the AUV Dorado, which is equipped with ten water samplers (called "gulpers"). In real time, the algorithm tracks background levels of fluorescence and optical backscatter and the peaks' baseline to ensure that detection is tuned to the ambient conditions. The algorithm cross-checks fluorescence and backscatter signals to differentiate PTLs from INLs. To capture peak water samples with minimal delay, the algorithm exploits the AUV's sawtooth (i.e., yo-yo) trajectory: the vehicle crosses the detected layer twice in one yo-yo cycle. At the first crossing, it detects the layer's peak and saves its signal height. Sampling is triggered at the second crossing when the signal reaches the saved peak height plus meeting additional timing and depth conditions. The algorithm is also capable of triggering gulpers to acquire control samples outside the layer for comparison with ambient water. The sequence of peak and control samples can be set based on need. In recent AUV Dorado missions, the algorithm triggered the gulpers to acquire peak and control samples from INLs and PTLs in Monterey Bay. Zooplankton analysis of some peak samples showed very high concentrations of mussel and barnacle

  2. Reliability and Validity of the Spanish Adaptation of EOSS, Comparing Normal and Clinical Samples

    ERIC Educational Resources Information Center

    Valero-Aguayo, Luis; Ferro-Garcia, Rafael; Lopez-Bermudez, Miguel Angel; de Huralde, Ma. Angeles Selva-Lopez

    2012-01-01

    The Experiencing of Self Scale (EOSS) was created for the evaluation of Functional Analytic Psychotherapy (Kohlenberg & Tsai, 1991, 2001, 2008) in relation to the concept of the experience of personal self as socially and verbally constructed. This paper presents a reliability and validity study of the EOSS with a Spanish sample (582…

  3. Social Daydreaming and Adjustment: An Experience-Sampling Study of Socio-Emotional Adaptation During a Life Transition

    PubMed Central

    Poerio, Giulia L.; Totterdell, Peter; Emerson, Lisa-Marie; Miles, Eleanor

    2016-01-01

    Estimates suggest that up to half of waking life is spent daydreaming; that is, engaged in thought that is independent of, and unrelated to, one’s current task. Emerging research indicates that daydreams are predominately social suggesting that daydreams may serve socio-emotional functions. Here we explore the functional role of social daydreaming for socio-emotional adjustment during an important and stressful life transition (the transition to university) using experience-sampling with 103 participants over 28 days. Over time, social daydreams increased in their positive characteristics and positive emotional outcomes; specifically, participants reported that their daydreams made them feel more socially connected and less lonely, and that the content of their daydreams became less fanciful and involved higher quality relationships. These characteristics then predicted less loneliness at the end of the study, which, in turn was associated with greater social adaptation to university. Feelings of connection resulting from social daydreams were also associated with less emotional inertia in participants who reported being less socially adapted to university. Findings indicate that social daydreaming is functional for promoting socio-emotional adjustment to an important life event. We highlight the need to consider the social content of stimulus-independent cognitions, their characteristics, and patterns of change, to specify how social thoughts enable socio-emotional adaptation. PMID:26834685

  4. Whole genome resequencing of a laboratory-adapted Drosophila melanogaster population sample.

    PubMed

    Gilks, William P; Pennell, Tanya M; Flis, Ilona; Webster, Matthew T; Morrow, Edward H

    2016-01-01

    As part of a study into the molecular genetics of sexually dimorphic complex traits, we used high-throughput sequencing to obtain data on genomic variation in an outbred laboratory-adapted fruit fly ( Drosophila melanogaster) population. We successfully resequenced the whole genome of 220 hemiclonal females that were heterozygous for the same Berkeley reference line genome (BDGP6/dm6), and a unique haplotype from the outbred base population (LH M). The use of a static and known genetic background enabled us to obtain sequences from whole-genome phased haplotypes. We used a BWA-Picard-GATK pipeline for mapping sequence reads to the dm6 reference genome assembly, at a median depth-of coverage of 31X, and have made the resulting data publicly-available in the NCBI Short Read Archive (Accession number SRP058502). We used Haplotype Caller to discover and genotype 1,726,931 small genomic variants (SNPs and indels, <200bp). Additionally we detected and genotyped 167 large structural variants (1-100Kb in size) using GenomeStrip/2.0. Sequence and genotype data are publicly-available at the corresponding NCBI databases: Short Read Archive, dbSNP and dbVar (BioProject PRJNA282591). We have also released the unfiltered genotype data, and the code and logs for data processing and summary statistics ( https://zenodo.org/communities/sussex_drosophila_sequencing/).

  5. Whole genome resequencing of a laboratory-adapted Drosophila melanogaster population sample

    PubMed Central

    Gilks, William P.; Pennell, Tanya M.; Flis, Ilona; Webster, Matthew T.; Morrow, Edward H.

    2016-01-01

    As part of a study into the molecular genetics of sexually dimorphic complex traits, we used high-throughput sequencing to obtain data on genomic variation in an outbred laboratory-adapted fruit fly ( Drosophila melanogaster) population. We successfully resequenced the whole genome of 220 hemiclonal females that were heterozygous for the same Berkeley reference line genome (BDGP6/dm6), and a unique haplotype from the outbred base population (LH M). The use of a static and known genetic background enabled us to obtain sequences from whole-genome phased haplotypes. We used a BWA-Picard-GATK pipeline for mapping sequence reads to the dm6 reference genome assembly, at a median depth-of coverage of 31X, and have made the resulting data publicly-available in the NCBI Short Read Archive (Accession number SRP058502). We used Haplotype Caller to discover and genotype 1,726,931 small genomic variants (SNPs and indels, <200bp). Additionally we detected and genotyped 167 large structural variants (1-100Kb in size) using GenomeStrip/2.0. Sequence and genotype data are publicly-available at the corresponding NCBI databases: Short Read Archive, dbSNP and dbVar (BioProject PRJNA282591). We have also released the unfiltered genotype data, and the code and logs for data processing and summary statistics ( https://zenodo.org/communities/sussex_drosophila_sequencing/). PMID:27928499

  6. Psychometric properties of the Schedule for Nonadaptive and Adaptive Personality in a PTSD sample.

    PubMed

    Wolf, Erika J; Harrington, Kelly M; Miller, Mark W

    2011-12-01

    This study evaluated the psychometric characteristics of the Schedule for Nonadaptive and Adaptive Personality (SNAP; Clark, 1996) in 280 individuals who screened positive for posttraumatic stress disorder (PTSD). The SNAP validity, trait, temperament, and personality disorder (PD) scales were compared with scales on the Brief Form of the Multidimensional Personality Questionnaire (Patrick, Curtin, & Tellegen, 2002). In a subsample of 86 veterans, the SNAP PD, trait, and temperament scales were also evaluated in comparison to the International Personality Disorder Examination (IPDE; Loranger, 1999), a semistructured diagnostic interview. Results revealed that the SNAP scales have good convergent validity, as evidenced by their pattern of associations with related measures of personality and PD. However, evidence for their discriminant validity in relationship to other measures of personality and PD was more mixed, and test scores on the SNAP trait and temperament scales left much unexplained variance in IPDE-assessed PDs. The diagnostic scoring of the SNAP PD scales greatly inflated prevalence estimates of PDs relative to the IPDE and showed poor agreement with the IPDE. In contrast, the dimensional SNAP scores yielded far stronger associations with continuous scores on the IPDE. The SNAP scales also largely evidenced expected patterns of association with a measure of PTSD severity. Overall, findings support the use of this measure in this population and contribute to our conceptualization of the association between temperament, PTSD, and Axis II psychopathology.

  7. The Application of Adaptive Sampling and Analysis Program (ASAP) Techniques to NORM Sites

    SciTech Connect

    Johnson, Robert; Smith, Karen P.; Quinn, John

    1999-10-29

    The results from the Michigan demonstration establish that this type of approach can be very effective for NORM sites. The advantages include (1) greatly reduced per sample analytical costs; (2) a reduced reliance on soil sampling and ex situ gamma spectroscopy analyses; (3) the ability to combine characterization with remediation activities in one fieldwork cycle; (4) improved documentation; and (5) ultimately better remediation, as measured by greater precision in delineating soils that are not in compliance with requirements from soils that are in compliance. In addition, the demonstration showed that the use of real-time technologies, such as the RadInSoil, can facilitate the implementation of a Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM)-based final status survey program

  8. Adaptive robust image registration approach based on adequately sampling polar transform and weighted angular projection function

    NASA Astrophysics Data System (ADS)

    Wei, Zhao; Tao, Feng; Jun, Wang

    2013-10-01

    An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.

  9. How urban system vulnerabilities to flooding could be assessed to improve resilience and adaptation in spatial planning

    NASA Astrophysics Data System (ADS)

    Pasi, Riccardo; Viavattene, Christophe; La Loggia, Goffredo

    2016-04-01

    Natural hazards damage assets and infrastructure inducing disruptions to urban functions and key daily services. These disruptions may be short or long with a variable spatial scale of impact. From an urban planning perspective, measuring these disruptions and their consequences at an urban scale is fundamental in order to develop more resilient cities. Whereas the assessment of physical vulnerabilities and direct damages is commonly addressed, new methodologies for assessing the systemic vulnerability at the urban scale are required to reveal these disruptions and their consequences. Physical and systemic vulnerability should be measured in order to reflect the multifaceted fragility of cities in the face of external stress, both in terms of the natural/built environment and socio-economic sphere. Additionally, a systemic approach allows the consideration of vulnerability across different spatial scales, as impacts may vary and be transmitted across local, regional or national levels. Urban systems are spatially distributed and the nature of this can have significant effects on flood impacts. The proposed approach identifies the vulnerabilities of flooding within urban contexts, including both in terms of single elementary units (buildings, infrastructures, people, etc.) and systemic functioning (urban functions and daily life networks). Direct losses are appraised initially using conventional methodologies (e.g. depth-damage functions). This aims to both understand the spatial distribution of physical vulnerability and associated losses and, secondly, to identify the most vulnerable building types and ways to improve the physical adaptation of our cities, proposing changes to building codes, design principles and other municipal regulation tools. The subsequent systemic approach recognises the city as a collection of sub-systems or functional units (such as neighbourhoods and suburbs) providing key daily services for inhabitants (e.g. healthcare facilities

  10. Compact Ocean Models Enable Onboard AUV Autonomy and Decentralized Adaptive Sampling

    DTIC Science & Technology

    2013-09-30

    synoptic information on-board a mobile platform. 2. To benefit from additional information provided by synoptic models, we developed a combination...properties ( chlorophyll -a and absorption due to phytoplankton), the model was able to reproduce intensity and tendencies in surface and subsurface... chlorophyll distributions observed at water samples locations in the Monterey Bay, CA (Figure 3). 5 2a) MODIS Chl-a 2b) without data

  11. Adaptive use of bubble wrap for storing liquid samples and performing analytical assays.

    PubMed

    Bwambok, David K; Christodouleas, Dionysios C; Morin, Stephen A; Lange, Heiko; Phillips, Scott T; Whitesides, George M

    2014-08-05

    This paper demonstrates that the gas-filled compartments in the packing material commonly called "bubble wrap" can be repurposed in resource-limited regions as containers to store liquid samples, and to perform bioanalyses. The bubbles of bubble wrap are easily filled by injecting the samples into them using a syringe with a needle or a pipet tip, and then sealing the hole with nail hardener. The bubbles are transparent in the visible range of the spectrum, and can be used as "cuvettes" for absorbance and fluorescence measurements. The interiors of these bubbles are sterile and allow storage of samples without the need for expensive sterilization equipment. The bubbles are also permeable to gases, and can be used to culture and store micro-organisms. By incorporating carbon electrodes, these bubbles can be used as electrochemical cells. This paper demonstrates the capabilities of the bubbles by culturing E. coli, growing C. elegans, measuring glucose and hemoglobin spectrophotometrically, and measuring ferrocyanide electrochemically, all within the bubbles.

  12. Virtual-system-coupled adaptive umbrella sampling to compute free-energy landscape for flexible molecular docking.

    PubMed

    Higo, Junichi; Dasgupta, Bhaskar; Mashimo, Tadaaki; Kasahara, Kota; Fukunishi, Yoshifumi; Nakamura, Haruki

    2015-07-30

    A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35 ) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did.

  13. Massively parallel sampling of lattice proteins reveals foundations of thermal adaptation

    NASA Astrophysics Data System (ADS)

    Venev, Sergey V.; Zeldovich, Konstantin B.

    2015-08-01

    Evolution of proteins in bacteria and archaea living in different conditions leads to significant correlations between amino acid usage and environmental temperature. The origins of these correlations are poorly understood, and an important question of protein theory, physics-based prediction of types of amino acids overrepresented in highly thermostable proteins, remains largely unsolved. Here, we extend the random energy model of protein folding by weighting the interaction energies of amino acids by their frequencies in protein sequences and predict the energy gap of proteins designed to fold well at elevated temperatures. To test the model, we present a novel scalable algorithm for simultaneous energy calculation for many sequences in many structures, targeting massively parallel computing architectures such as graphics processing unit. The energy calculation is performed by multiplying two matrices, one representing the complete set of sequences, and the other describing the contact maps of all structural templates. An implementation of the algorithm for the CUDA platform is available at http://www.github.com/kzeldovich/galeprot and calculates protein folding energies over 250 times faster than a single central processing unit. Analysis of amino acid usage in 64-mer cubic lattice proteins designed to fold well at different temperatures demonstrates an excellent agreement between theoretical and simulated values of energy gap. The theoretical predictions of temperature trends of amino acid frequencies are significantly correlated with bioinformatics data on 191 bacteria and archaea, and highlight protein folding constraints as a fundamental selection pressure during thermal adaptation in biological evolution.

  14. Adaption of egg and larvae sampling techniques for lake sturgeon and broadcast spawning fishes in a deep river

    USGS Publications Warehouse

    Roseman, E.F.; Boase, J.; Kennedy, G.; Craig, J.; Soper, K.

    2011-01-01

    In this report we describe how we adapted two techniques for sampling lake sturgeon (Acipenser fulvescens) and other fish early life history stages to meet our research needs in the Detroit River, a deep, flowing Great Lakes connecting channel. First, we developed a buoy-less method for sampling fish eggs and spawning activity using egg mats deployed on the river bottom. The buoy-less method allowed us to fish gear in areas frequented by boaters and recreational anglers, thus eliminating surface obstructions that interfered with recreational and boating activities. The buoy-less method also reduced gear loss due to drift when masses of floating aquatic vegetation would accumulate on buoys and lines, increasing the drag on the gear and pulling it downstream. Second, we adapted a D-frame drift net system formerly employed in shallow streams to assess larval lake sturgeon dispersal for use in the deeper (>8m) Detroit River using an anchor and buoy system. ?? 2011 Blackwell Verlag, Berlin.

  15. Adaptive decision making in a dynamic environment: a test of a sequential sampling model of relative judgment.

    PubMed

    Vuckovic, Anita; Kwantes, Peter J; Neal, Andrew

    2013-09-01

    Research has identified a wide range of factors that influence performance in relative judgment tasks. However, the findings from this research have been inconsistent. Studies have varied with respect to the identification of causal variables and the perceptual and decision-making mechanisms underlying performance. Drawing on the ecological rationality approach, we present a theory of the judgment and decision-making processes involved in a relative judgment task that explains how people judge a stimulus and adapt their decision process to accommodate their own uncertainty associated with those judgments. Undergraduate participants performed a simulated air traffic control conflict detection task. Across two experiments, we systematically manipulated variables known to affect performance. In the first experiment, we manipulated the relative distances of aircraft to a common destination while holding aircraft speeds constant. In a follow-up experiment, we introduced a direct manipulation of relative speed. We then fit a sequential sampling model to the data, and used the best fitting parameters to infer the decision-making processes responsible for performance. Findings were consistent with the theory that people adapt to their own uncertainty by adjusting their criterion and the amount of time they take to collect evidence in order to make a more accurate decision. From a practical perspective, the paper demonstrates that one can use a sequential sampling model to understand performance in a dynamic environment, allowing one to make sense of and interpret complex patterns of empirical findings that would otherwise be difficult to interpret using standard statistical analyses.

  16. Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain

    PubMed Central

    Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

    2016-01-01

    Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during “frequent inversion” hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis

  17. Variation in spatial and temporal incidence of the crustacean pathogen Hematodinium perezi in environmental samples from Atlantic Coastal Bays

    PubMed Central

    2013-01-01

    Background Hematodinium perezi, a parasitic dinoflagellate, infects and kills blue crabs, Callinectes sapidus, along the Atlantic and Gulf coasts of the United States. The parasite proliferates within host hemolymph and tissues, and also produces free-swimming biflagellated dinospores that emerge from infected crabs. Infections in C. sapidus recur annually, and it is not known if biotic or environmental reservoirs contribute to reinfection and outbreaks. To address this data gap, a quantitative PCR assay based on the internal transcribed spacer 2 (ITS2) region of H. perezi rRNA genes was developed to asses the temporal and spatial incidence of the parasite in Delaware and Maryland coastal bays. Results A previously-used PCR assay for H. perezi, based on the small subunit rRNA gene sequence, was found to lack adequate species specificity to discriminate non-Hematodinium sp. dinoflagellate species in environmental samples. A new ITS2-targeted assay was developed and validated to detect H. perezi DNA in sediment and water samples using E. coli carrying the H. perezi rDNA genes. Application of the method to environmental samples identified potential hotspots in sediment in Indian River Inlet, DE and Chincoteague Bay, MD and VA. H. perezi DNA was not detected in co-occurring shrimp or snails, even during an outbreak of the parasite in C. sapidus. Conclusions H. perezi is present in water and sediment samples in Maryland and Delaware coastal bays from April through November with a wide spatial and temporal variability in incidence. Sampling sites with high levels of H. perezi DNA in both bays share characteristics of silty, organic sediments and low tidal currents. The environmental detection of H. perezi in spring, ahead of peak prevalence in crabs, points to gaps in our understanding of the parasite’s life history prior to infection in crabs as well as the mode of environmental transmission. To better understand the H. perezi life cycle will require further

  18. Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

    protocol rules for its overseas department. The latter estimates come from a sample of nearly 17,000 plots analyzed from same spatial imagery acquired between year 1990 and year 2006. This sampling scheme is derived from the traditional forest inventory methods carried out by IFN (Inventaire Forestier National). Our intensified global sampling scheme leads to an estimate of 96,650 ha deforested between 1990 and 2006, which is within the 95% confidence interval of the IFN sampling scheme, which gives an estimate of 91,722 ha, representing a relative difference from the IFN of 5.4%. These results demonstrate that the intensification of the global sampling scheme can provide forest area change estimates close to those achieved by official forest inventories (<6%), with precisions of between 4% and 7%, although we only estimate errors from sampling, not from the use of surrogate data. Such methods could be used by developing countries to demonstrate that they are fulfilling requirements for reducing emissions from deforestation in the framework of an REDD (Reducing Emissions from Deforestation in Developing Countries) mechanism under discussion within the United Nations Framework Convention on Climate Change (UNFCCC). Monitoring systems at national levels in tropical countries can also benefit from pan-tropical and regional observations, to ensure consistency between different national monitoring systems.

  19. Spatial and seasonal variations of biogenic tracer compounds in ambient PM 10 and PM 1 samples in Berlin, Germany

    NASA Astrophysics Data System (ADS)

    Wagener, Sandra; Langner, Marcel; Hansen, Ute; Moriske, Heinz-Jörn; Endlicher, Wilfried R.

    2012-02-01

    PM 10 and PM 1 aerosol samples were collected between February and October, 2010 at three sites in Berlin that were characterized by different vegetation influences. The aim of the study was to determine the spatial and seasonal variations of several, mainly biogenic secondary and primary tracers in an urban area. Selected tracers including isoprene and α-pinene markers, fatty acids and levoglucosan were detected with GC-MS. The highest median concentrations, up to 45.1 ng m -3, were found for the combustion product levoglucosan. The concentration range of the secondary compounds was 0.3 ng m -3 for the isoprene markers 2-methyltetrols up to 35.7 ng m -3 for malic acid. The occurrence of these compounds was mainly affected by the seasons, which could be described by three patterns. Whereas secondary compounds were mainly characterized by significantly higher concentrations during the warmer months, levoglucosan showed significantly higher concentrations during the colder months. No significant concentration differences between the two periods were rather observed for the primary compounds but also for the α-pinene degradation product pinonic acid. The secondary compounds and levoglucosan could be associated with the fine mode (particles with an aerodynamic diameter (AD) < 1 μm), while primary compounds are rather associated with the coarse mode (AD > 1 μm). Spatial variations were emphasized with a tendency toward higher concentrations for most compounds at sites that were influenced by vegetation, especially evident for the PM 10 fraction. Besides concentration differences, spatial variations could also be described by differences in seasonal behavior and the size distribution, indicating major complexity in the composition of biogenic PM within the city of Berlin.

  20. Estimating site occupancy rates for aquatic plants using spatial sub-sampling designs when detection probabilities are less than one

    USGS Publications Warehouse

    Nielson, Ryan M.; Gray, Brian R.; McDonald, Lyman L.; Heglund, Patricia J.

    2011-01-01

    Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.

  1. Adaptive beam steering implemented in a ferroelectric liquid-crystal spatial-light-modulator free-space, fiber-optic switch.

    PubMed

    Johansson, Mathias; Hård, Sverker; Robertson, Brian; Manolis, Ilias; Wilkinson, Timothy; Crossland, William

    2002-08-10

    Active alignment of a 1 x 8 free-space optical switch was studied experimentally. Optical signals, carried on single-mode fibers, were switched by a ferroelectric liquid-crystal-on-silicon spatial light modulator. Continuous measurement of the in-coupled power to the fibers provided feedback for the switch control. The switch automatically located and locked to the output fibers. An advantage with adaptive switches of a similar kind is relaxed geometrical tolerances in the switch assembly. Further, such switches can adapt to possible geometrical changes and light wavelength drift during operation.

  2. Spatial patterns of neutral and functional genetic variations reveal patterns of local adaptation in raccoon (Procyon lotor) populations exposed to raccoon rabies.

    PubMed

    Kyle, Christopher J; Rico, Yessica; Castillo, Sarrah; Srithayakumar, Vythegi; Cullingham, Catherine I; White, Bradley N; Pond, Bruce A

    2014-05-01

    Local adaptation is necessary for population survival and depends on the interplay between responses to selective forces and demographic processes that introduce or retain adaptive and maladaptive attributes. Host-parasite systems are dynamic, varying in space and time, where both host and parasites must adapt to their ever-changing environment in order to survive. We investigated patterns of local adaptation in raccoon populations with varying temporal exposure to the raccoon rabies virus (RRV). RRV infects approximately 85% of the population when epizootic and has been presumed to be completely lethal once contracted; however, disease challenge experiments and varying spatial patterns of RRV spread suggest some level of immunity may exist. We first assessed patterns of local adaptation in raccoon populations along the eastern seaboard of North America by contrasting spatial patterns of neutral (microsatellite loci) and functional, major histocompatibility complex (MHC) genetic diversity and structure. We explored variation of MHC allele frequencies in the light of temporal population exposure to RRV (0-60 years) and specific RRV strains in infected raccoons. Our results revealed high levels of MHC variation (66 DRB exon 2 alleles) and pronounced genetic structure relative to neutral microsatellite loci, indicative of local adaptation. We found a positive association linking MHC genetic diversity and temporal RRV exposure, but no association with susceptibility and resistance to RRV strains. These results have implications for landscape epidemiology studies seeking to predict the spread of RRV and present an example of how population demographics influence the degree to which populations adapt to local selective pressures.

  3. Enhanced Spatial & Temporal Sampling of Air/Sea Interaction with the NASA CYGNSS MicroSat Constellation

    NASA Astrophysics Data System (ADS)

    Ruf, C. S.; Ridley, A. J.; O'Brien, A.; Johnson, J.; Yi, Y.

    2013-12-01

    The NASA Cyclone Global Navigation Satellite System (CYGNSS) is a new spaceborne mission to address the deficiencies with current tropical cyclone (TC) intensity forecasts related to inadequate observations and modeling of the inner core. The inadequacy results from two causes: 1) much of the inner core ocean surface is obscured from conventional remote sensing instruments by intense precipitation in the eye wall and inner rain bands; and 2) the rapidly evolving (genesis and intensification) stages of the TC life cycle are poorly sampled by conventional polar-orbiting imagers. CYGNSS is specifically designed to address these two limitations by combining the all-weather performance of GNSS-R bistatic ocean surface scatterometry with the enhanced sampling properties of a constellation of satellites. CYGNSS will provide surface wind measurements of the TC inner core that could not previously be measured from space. Mission simulations predict a median(mean) revisit time of 2(5) hours. The CYGNSS wind fields, when combined with as-frequent precipitation fields (e.g. produced by the upcoming Global Precipitation Measurement mission), will resolve the evolution of both the precipitation and underlying wind fields throughout the TC life cycle. They will provide near simultaneous and continuous observations and enable new insights into TC inner core dynamics and energetics. The use of a dense constellation of GNSS-R microsats results in spatial and temporal sampling properties that are markedly different from previous wide swath polar imagers. In particular, revisit times in the tropics are characterized by a probability distribution rather than a single, deterministic number of hours. The asymmetric shape of the probability distribution results in median revisit times that are less than half that of the mean, and mean revisit times that are less than half that of current polar orbiting imagers. CYGNSS is currently in Phase B project development. In parallel with the

  4. Examining Temporal Sample Scale and Model Choice with Spatial Capture-Recapture Models in the Common Leopard Panthera pardus

    PubMed Central

    Goldberg, Joshua F.; Tempa, Tshering; Norbu, Nawang; Hebblewhite, Mark; Mills, L. Scott; Wangchuk, Tshewang R.; Lukacs, Paul

    2015-01-01

    Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010–2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or quarterly periods did not appreciably affect median abundance or density, but did influence precision. We observed the largest gains in precision when moving from quarterly to shorter intervals. We therefore recommend daily sampling intervals for monitoring rare or elusive species where practicable, but note that monthly or quarterly sample periods can have similar informative value. We further develop a novel application of Bayes factors to select models where multiple ecological factors are integrated into density estimation. Our simulations demonstrate that these methods can help identify the “true” explanatory mechanisms underlying the data. Using this method, we found strong evidence for sex-specific movement distributions in leopards, suggesting that sexual patterns of space-use influence density. This model estimated a density of 10.0 leopards/100 km2 (95% credibility interval: 6.25–15.93), comparable to contemporary estimates in Asia. These SCR methods provide a guide

  5. Examining Temporal Sample Scale and Model Choice with Spatial Capture-Recapture Models in the Common Leopard Panthera pardus.

    PubMed

    Goldberg, Joshua F; Tempa, Tshering; Norbu, Nawang; Hebblewhite, Mark; Mills, L Scott; Wangchuk, Tshewang R; Lukacs, Paul

    2015-01-01

    Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010-2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or quarterly periods did not appreciably affect median abundance or density, but did influence precision. We observed the largest gains in precision when moving from quarterly to shorter intervals. We therefore recommend daily sampling intervals for monitoring rare or elusive species where practicable, but note that monthly or quarterly sample periods can have similar informative value. We further develop a novel application of Bayes factors to select models where multiple ecological factors are integrated into density estimation. Our simulations demonstrate that these methods can help identify the "true" explanatory mechanisms underlying the data. Using this method, we found strong evidence for sex-specific movement distributions in leopards, suggesting that sexual patterns of space-use influence density. This model estimated a density of 10.0 leopards/100 km2 (95% credibility interval: 6.25-15.93), comparable to contemporary estimates in Asia. These SCR methods provide a guide to

  6. An enhanced droplet-based liquid microjunction surface sampling system coupled with HPLC-ESI-MS/MS for spatially resolved analysis

    SciTech Connect

    Van Berkel, Gary J.; Weiskittel, Taylor M.; Kertesz, Vilmos

    2014-11-07

    Droplet-based liquid microjunction surface sampling coupled with high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) for spatially resolved analysis provides the possibility of effective analysis of complex matrix samples and can provide a greater degree of chemical information from a single spot sample than is typically possible with a direct analysis of an extract. Described here is the setup and enhanced capabilities of a discrete droplet liquid microjunction surface sampling system employing a commercially available CTC PAL autosampler. The system enhancements include incorporation of a laser distance sensor enabling unattended analysis of samples and sample locations of dramatically disparate height as well as reliably dispensing just 0.5 μL of extraction solvent to make the liquid junction to the surface, wherein the extraction spot size was confined to an area about 0.7 mm in diameter; software modifications improving the spatial resolution of sampling spot selection from 1.0 to 0.1 mm; use of an open bed tray system to accommodate samples as large as whole-body rat thin tissue sections; and custom sample/solvent holders that shorten sampling time to approximately 1 min per sample. Lastly, the merit of these new features was demonstrated by spatially resolved sampling, HPLC separation, and mass spectral detection of pharmaceuticals and metabolites from whole-body rat thin tissue sections and razor blade (“crude”) cut mouse tissue.

  7. An enhanced droplet-based liquid microjunction surface sampling system coupled with HPLC-ESI-MS/MS for spatially resolved analysis

    DOE PAGES

    Van Berkel, Gary J.; Weiskittel, Taylor M.; Kertesz, Vilmos

    2014-11-07

    Droplet-based liquid microjunction surface sampling coupled with high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) for spatially resolved analysis provides the possibility of effective analysis of complex matrix samples and can provide a greater degree of chemical information from a single spot sample than is typically possible with a direct analysis of an extract. Described here is the setup and enhanced capabilities of a discrete droplet liquid microjunction surface sampling system employing a commercially available CTC PAL autosampler. The system enhancements include incorporation of a laser distance sensor enabling unattended analysis of samples and sample locations of dramatically disparatemore » height as well as reliably dispensing just 0.5 μL of extraction solvent to make the liquid junction to the surface, wherein the extraction spot size was confined to an area about 0.7 mm in diameter; software modifications improving the spatial resolution of sampling spot selection from 1.0 to 0.1 mm; use of an open bed tray system to accommodate samples as large as whole-body rat thin tissue sections; and custom sample/solvent holders that shorten sampling time to approximately 1 min per sample. Lastly, the merit of these new features was demonstrated by spatially resolved sampling, HPLC separation, and mass spectral detection of pharmaceuticals and metabolites from whole-body rat thin tissue sections and razor blade (“crude”) cut mouse tissue.« less

  8. The association of physical activity to neural adaptability during visuo-spatial processing in healthy elderly adults: A multiscale entropy analysis.

    PubMed

    Wang, Chun-Hao; Tsai, Chia-Liang; Tseng, Philip; Yang, Albert C; Lo, Men-Tzung; Peng, Chung-Kang; Wang, Hsin-Yi; Muggleton, Neil G; Juan, Chi-Hung; Liang, Wei-Kuang

    2014-10-29

    Physical activity has been shown to benefit brain and cognition in late adulthood. However, this effect is still unexplored in terms of brain signal complexity, which reflects the level of neural adaptability and efficiency during cognitive processing that cannot be acquired via averaged neuroelectric signals. Here we employed multiscale entropy analysis (MSE) of electroencephalography (EEG), a new approach that conveys important information related to the temporal dynamics of brain signal complexity across multiple time scales, to reveal the association of physical activity with neural adaptability and efficiency in elderly adults. A between-subjects design that included 24 participants (aged 66.63±1.31years; female=12) with high physical activity and 24 age- and gender-matched low physical activity participants (aged 67.29±1.20years) was conducted to examine differences related to physical activity in performance and MSE of EEG signals during a visuo-spatial cognition task. We observed that physically active elderly adults had better accuracy on both visuo-spatial attention and working memory conditions relative to their sedentary counterparts. Additionally, these physically active elderly adults displayed greater MSE values at larger time scales at the Fz electrode in both attention and memory conditions. The results suggest that physical activity may be beneficial for adaptability of brain systems in tasks involving visuo-spatial information. MSE thus might be a promising approach to test the effects of the benefits of exercise on cognition.

  9. Speed-up of Markov Chain Monte Carlo Simulation Using Self-Adaptive Different Evolution with Subspace Sampling

    NASA Astrophysics Data System (ADS)

    Vrugt, J. A.

    2007-12-01

    Markov chain Monte Carlo (MCMC) methods are widely used in fields ranging from physics and chemistry, to finance, economics and statistical inference for estimating the average properties of complex systems. The convergence rate of MCMC schemes is often observed, however to be disturbingly low, limiting its practical use in many applications. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves. Here we show that significant improvements to the efficiency of MCMC algorithms can be made by using a self-adaptive Differential Evolution search strategy within a population-based evolutionary framework. This scheme differs fundamentally from existing MCMC algorithms, in that trial jumps are simply a fixed multiple of the difference of randomly chosen members of the population using various genetic operators that are adaptively updated during the search. In addition, the algorithm includes randomized subspace sampling to further improve convergence and acceptance rate. Detailed balance and ergodicity of the algorithm are proved, and hydrologic examples show that the proposed method significantly enhances the efficiency and applicability of MCMC simulations to complex, multi-modal search problems.

  10. Particle System Based Adaptive Sampling on Spherical Parameter Space to Improve the MDL Method for Construction of Statistical Shape Models

    PubMed Central

    Zhou, Xiangrong; Hirano, Yasushi; Tachibana, Rie; Hara, Takeshi; Kido, Shoji; Fujita, Hiroshi

    2013-01-01

    Minimum description length (MDL) based group-wise registration was a state-of-the-art method to determine the corresponding points of 3D shapes for the construction of statistical shape models (SSMs). However, it suffered from the problem that determined corresponding points did not uniformly spread on original shapes, since corresponding points were obtained by uniformly sampling the aligned shape on the parameterized space of unit sphere. We proposed a particle-system based method to obtain adaptive sampling positions on the unit sphere to resolve this problem. Here, a set of particles was placed on the unit sphere to construct a particle system whose energy was related to the distortions of parameterized meshes. By minimizing this energy, each particle was moved on the unit sphere. When the system became steady, particles were treated as vertices to build a spherical mesh, which was then relaxed to slightly adjust vertices to obtain optimal sampling-positions. We used 47 cases of (left and right) lungs and 50 cases of livers, (left and right) kidneys, and spleens for evaluations. Experiments showed that the proposed method was able to resolve the problem of the original MDL method, and the proposed method performed better in the generalization and specificity tests. PMID:23861721

  11. Adaptation of a speciation sampling cartridge for measuring ammonia flux from cattle feedlots using relaxed eddy accumulation

    NASA Astrophysics Data System (ADS)

    Baum, K. A.; Ham, J. M.

    Improved measurements of ammonia losses from cattle feedlots are needed to quantify the national NH 3 emissions inventory and evaluate management techniques for reducing emissions. Speciation cartridges composed of glass honeycomb denuders and filter packs were adapted to measure gaseous NH 3 and aerosol NH 4+ fluxes using relaxed eddy accumulation (REA). Laboratory testing showed that a cartridge equipped with four honeycomb denuders had a total capture capacity of 1800 μg of NH 3. In the field, a pair of cartridges was deployed adjacent to a sonic anemometer and an open-path gas analyzer on a mobile tower. High-speed valves were attached to the inlets of the cartridges and controlled by a datalogger so that up- and down-moving eddies were independently sampled based on direction of the vertical wind speed and a user-defined deadband. Air flowed continuously through the cartridges even when not sampling by means of a recirculating air handling system. Eddy covariance measurement of CO 2 and H 2O, as measured by the sonic and open-path gas analyzer, were used to determine the relaxation factor needed to compute REA-based fluxes. The REA system was field tested at the Beef Research Unit at Kansas State University in the summer and fall of 2007. Daytime NH 3 emissions ranged between 68 and 127 μg m -2 s -1; fluxes tended to follow a diurnal pattern correlated with latent heat flux. Daily fluxes of NH 3 were between 2.5 and 4.7 g m -2 d -1 and on average represented 38% of fed nitrogen. Aerosol NH 4+ fluxes were negligible compared with NH 3 emissions. An REA system designed around the high-capacity speciation cartridges can be used to measure NH 3 fluxes from cattle feedlots and other strong sources. The system could be adapted to measure fluxes of other gases and aerosols.

  12. Adaptively Forward Modelling the Spatial Magnetic Effects Due to a Magnetized Structure by Tesseroids in Spherical Coordinate System

    NASA Astrophysics Data System (ADS)

    Du, Jinsong; Chen, Chao

    2015-04-01

    The continually accumulated magnetic measurements and also the reliable global lithospheric magnetic anomaly field models obtained by CHAMP satellite and Swarm constellation of three satellites, now present a requirement and also a challenge to develop the realistic forward modeling methods for the magnetic effects (i.e. magnetic potential, vector and gradient tensor) that take into account the curvature of the Earth. The spatial discretization by a series of elementary tesseroids (spherical prisms, SPs) is utilized to approximate the complex magnetized source by the principle of superposition and saturate the source volume without "holes". Since there is no analytic solution for the magnetic effects of the SP, we explicitly present three kinds of efficient forward modeling methods for approximate calculation using Taylor's series expansion (TSE) to fourth-order, Gauss-Legendre quadrature integration (GLQI) and approximations by Cartesian elements including the magnetic dipole (MD) and rectangular prism (RP). Our derived new formulas do not suffer from the polar singularity and using the approximate approaches and subdivision technique, therefore, can be employed for any computing point with a required level of accuracy on the globe. Both theoretical analysis and numerical investigations suggest that the accuracy of modeling by the SP is significantly dependent on its geometric shape (i.e. size, latitude and depth) and particularly the distance between the source and the observation (DSO for short). Accuracies of forward modeling by all methods are relatively worse near the source but better far away the source. Besides, the numerical analysis shows that the error of magnetic potential is lower than those of magnetic vector and gradient tensor, and that of the gradient tensor is the highest but the error's decay of the tensor is the fastest. Analysis of accuracy shows that MD method is equivalent to GLQI when node is zero, and TSE method is nearly equivalent to

  13. Spatially resolved analysis of plutonium isotopic signatures in environmental particle samples by laser ablation-MC-ICP-MS.

    PubMed

    Konegger-Kappel, Stefanie; Prohaska, Thomas

    2016-01-01

    Laser ablation-multi-collector-inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) was optimized and investigated with respect to its performance for determining spatially resolved Pu isotopic signatures within radioactive fuel particle clusters. Fuel particles had been emitted from the Chernobyl nuclear power plant (ChNPP) where the 1986 accident occurred and were deposited in the surrounding soil, where weathering processes caused their transformation into radioactive clusters, so-called micro-samples. The size of the investigated micro-samples, which showed surface alpha activities below 40 mBq, ranged from about 200 to 1000 μm. Direct single static point ablations allowed to identify variations of Pu isotopic signatures not only between distinct fuel particle clusters but also within individual clusters. The resolution was limited to 100 to 120 μm as a result of the applied laser ablation spot sizes and the resolving power of the nuclear track radiography methodology that was applied for particle pre-selection. The determined (242)Pu/(239)Pu and (240)Pu/(239)Pu isotope ratios showed a variation from low to high Pu isotope ratios, ranging from 0.007(2) to 0.047(8) for (242)Pu/(239)Pu and from 0.183(13) to 0.577(40) for (240)Pu/(239)Pu. In contrast to other studies, the applied methodology allowed for the first time to display the Pu isotopic distribution in the Chernobyl fallout, which reflects the differences in the spent fuel composition over the reactor core. The measured Pu isotopic signatures are in good agreement with the expected Pu isotopic composition distribution that is typical for a RBMK-1000 reactor, indicating that the analyzed samples are originating from the ill-fated Chernobyl reactor. The average Pu isotope ratios [(240)Pu/(239)Pu = 0.388(86), (242)Pu/(239)Pu = 0.028(11)] that were calculated from all investigated samples (n = 48) correspond well to previously published results of Pu analyses in contaminated samples from

  14. Spatial resolution of synchrotron x-ray microtomography in high energy range: Effect of x-ray energy and sample-to-detector distance

    NASA Astrophysics Data System (ADS)

    Seo, D.; Tomizato, F.; Toda, H.; Uesugi, K.; Takeuchi, A.; Suzuki, Y.; Kobayashi, M.

    2012-12-01

    Spatial resolution of three-dimensional images obtained by synchrotron X-ray microtomography technique is evaluated using cyclic bar patterns machined on a steel wire. Influences of X-ray energy and the sample-to-detector distance on spatial resolution were investigated. High X-ray energies of 33-78 keV are applied due to the high X-ray absorption of transition metals. Best spatial resolution of about 1.2 μm pitch was observed at the sample-to-detector distance range of 20-110 mm and at the energy range of 68-78 keV. Several factors such as X-ray scattering and diffraction phenomena affecting the degradation of spatial resolution are also discussed.

  15. ADAPTIVE ANNEALED IMPORTANCE SAMPLING FOR MULTIMODAL POSTERIOR EXPLORATION AND MODEL SELECTION WITH APPLICATION TO EXTRASOLAR PLANET DETECTION

    SciTech Connect

    Liu, Bin

    2014-07-01

    We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior. To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.

  16. Exploring equivalence domain in nonlinear inverse problems using Covariance Matrix Adaption Evolution Strategy (CMAES) and random sampling

    NASA Astrophysics Data System (ADS)

    Grayver, Alexander V.; Kuvshinov, Alexey V.

    2016-05-01

    This paper presents a methodology to sample equivalence domain (ED) in nonlinear partial differential equation (PDE)-constrained inverse problems. For this purpose, we first applied state-of-the-art stochastic optimization algorithm called Covariance Matrix Adaptation Evolution Strategy (CMAES) to identify low-misfit regions of the model space. These regions were then randomly sampled to create an ensemble of equivalent models and quantify uncertainty. CMAES is aimed at exploring model space globally and is robust on very ill-conditioned problems. We show that the number of iterations required to converge grows at a moderate rate with respect to number of unknowns and the algorithm is embarrassingly parallel. We formulated the problem by using the generalized Gaussian distribution. This enabled us to seamlessly use arbitrary norms for residual and regularization terms. We show that various regularization norms facilitate studying different classes of equivalent solutions. We further show how performance of the standard Metropolis-Hastings Markov chain Monte Carlo algorithm can be substantially improved by using information CMAES provides. This methodology was tested by using individual and joint inversions of magneotelluric, controlled-source electromagnetic (EM) and global EM induction data.

  17. Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study.

    PubMed

    Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Luo, Ouyang; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

    2014-10-21

    With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSEs) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3-6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1-3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART.

  18. Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study

    NASA Astrophysics Data System (ADS)

    Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Ouyang, Luo; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

    2014-10-01

    With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSEs) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3-6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1-3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART.

  19. Reconstructing Cone-beam CT with Spatially Varying Qualities for Adaptive Radiotherapy, a Proof-of-Principle Study1

    PubMed Central

    Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Luo, Ouyang; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

    2014-01-01

    With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSE) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3–6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1–3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART. PMID:25255957

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

    PubMed

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

    2012-12-01

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

  1. Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

    NASA Astrophysics Data System (ADS)

    Greco, R.; Sorriso-Valvo, M.

    2013-09-01

    Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

  2. Water availability drives signatures of local adaptation in whitebark pine (Pinus albicaulis Englm.) across fine spatial scales of the Lake Tahoe Basin, USA.

    PubMed

    Lind, Brandon M; Friedline, Christopher J; Wegrzyn, Jill L; Maloney, Patricia E; Vogler, Detlev R; Neale, David B; Eckert, Andrew J

    2017-03-17

    Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116,231 SNPs) to describe signatures of fine-scale adaptation within eight whitebark pine (Pinus albicaulis Engelm.) populations across the local extent of the environmentally heterogeneous Lake Tahoe Basin, USA. We show that despite highly shared genetic variation (FST = 0.0069) there is strong evidence for adaptation to the rain shadow experienced across the eastern Sierra Nevada. Specifically, we build upon evidence from a common garden study and find that allele frequencies of loci associated with four phenotypes (mean = 236 SNPs), 18 environmental variables (mean = 99 SNPs), and those detected through genetic differentiation (n = 110 SNPs) exhibit significantly higher signals of selection (covariance of allele frequencies) than could be expected to arise, given the data. We also provide evidence that this covariance tracks environmental measures related to soil water availability through subtle allele frequency shifts across populations. Our results replicate empirical support for theoretical expectations of local adaptation for populations exhibiting strong gene flow and high selective pressures, and suggest that ongoing adaptation of many P. albicaulis populations within the Lake Tahoe Basin will not be constrained by the lack of genetic variation. Even so, some populations exhibit low levels of heritability for the traits presumed to be related to fitness. These instances could be used to prioritize management to maintain adaptive potential. Overall, we suggest that established practices regarding whitebark pine conservation be maintained, with the additional context of fine-scale adaptation. This article is protected by copyright. All rights reserved.

  3. Adaptive Function in Preschoolers in Relation to Developmental Delay and Diagnosis of Autism Spectrum Disorders: Insights from a Clinical Sample

    ERIC Educational Resources Information Center

    Milne, Susan L.; McDonald, Jenny L.; Comino, Elizabeth J.

    2013-01-01

    This study aims to explore the relationship between developmental ability, autism and adaptive skills in preschoolers. Adaptive function was assessed in 152 preschoolers with autism, with and without developmental delay, and without autism, with and without developmental delay. Their overall adaptive function, measured by the general adaptive…

  4. Spatial variability and source apportionment of PM2.5 across multiple sampling locations in southwest China

    NASA Astrophysics Data System (ADS)

    Shi, F.; Xie, S.

    2015-12-01

    The Chengdu Plain, which is located in the west of the Sichuan Basin, is the largest plain and the fastest-growing area in southwest China. The Chengdu Plain is considered one of the hotspot areas in China. The pollution pattern in this area is unique due to the hilly topography, humid and stagnant weather. To investigate the composition and major sources of the ambient PM2.5, a one-year observation was performed at five sites in the Chengdu Plain during August, 2013 to August, 2014. The five sites contained three urban background sites and two rural background sites. Samples were analyzed for major water-soluble ions, organic carbon (OC), element carbon (EC), and trace elements. The Positive Matrix Factorization (PMF) receptor model based on the combined data from five locations was applied to identify and quantify the likely sources. The annual mean mass concentration of PM2.5 in Chengdu Plain was 81 μg·m-3 with the maximum in winter and the minimum in summer. Eight main factors were identified for the PM2.5 fraction: vehicle emission, secondary nitrate, biomass burning and waste incineration emission, secondary sulfate, Mo-related manufacturing, fugitive dust, coal combustion and industry pollution. The five-site annual mean contributions of each source were 13%, 19%, 9%, 25%, 2%, 13%, 9% and 10%,respectively, to PM2.5, while exhibiting large spatial variability. The contribution of secondary sulfate to the PM2.5 mass was largest at all sites, indicating severe secondary pollution in the region. Biomass burning and waste incineration emission made larger proportion at rural sites than that of urban sites, while the vehicle emission was larger at urban sites. The Enrichment factors for Cd, Zn, Pb, As, Cu and Mo in PM2.5 were larger than 100 indicated that those elements were largely from anthropogenic origins. Cd, As and Cu can mainly originate from nonferrous metal industry, while Mo may mainly generated from ferromolybdenum and Mo powder manufacture. The

  5. Spatial variability of organic layer thickness and carbon stocks in mature boreal forest stands--implications and suggestions for sampling designs.

    PubMed

    Kristensen, Terje; Ohlson, Mikael; Bolstad, Paul; Nagy, Zoltan

    2015-08-01

    Accurate field measurements from inventories across fine spatial scales are critical to improve sampling designs and to increase the precision of forest C cycling modeling. By studying soils undisturbed from active forest management, this paper gives a unique insight in the naturally occurring variability of organic layer C and provides valuable references against which subsequent and future sampling schemes can be evaluated. We found that the organic layer C stocks displayed great short-range variability with spatial autocorrelation distances ranging from 0.86 up to 2.85 m. When spatial autocorrelations are known, we show that a minimum of 20 inventory samples separated by ∼5 m is needed to determine the organic layer C stock with a precision of ±0.5 kg C m(-2). Our data also demonstrates a strong relationship between the organic layer C stock and horizon thickness (R (2) ranging from 0.58 to 0.82). This relationship suggests that relatively inexpensive measurements of horizon thickness can supplement soil C sampling, by reducing the number of soil samples collected, or to enhance the spatial resolution of organic layer C mapping.

  6. Effect of selective suppression of spatial frequency domain noise on visual detection of a sample object in an inhomogeneous background

    NASA Astrophysics Data System (ADS)

    Pietrzyk, Mariusz W.; McDonald, J. Scott; Brennan, Patrick C.; Bourne, Roger M.

    2012-02-01

    This study aims to investigate the effect of selective suppression of spatial frequency (SF) domain Gaussian white noise on visibility of a sample object in inhomogeneous backgrounds. SF-specific variation in signal-to-noise ratio due to selective signal averaging in the SF domain is a consequence of some of MRI acquisition methods. This study models the potential effect on visibility of an object in a complex image. A single disc was randomly positioned in 25 of 50 synthetic clustered lumpy background images. Neutral, low mid and high frequency suppressed Gaussian white noise was added in the frequency domain to simulate SF-weighted MRI signal averaging. Twelve readers performed visual searching and localization tasks on ordered sets. Subjects were asked to detect and locate discs and to rank confidence level. Sensitivity, specificity and ROC analyses were performed. Readers achieved significantly higher ROC AUC - Azscores - (p<0.001) and case-based sensitivity (p<0.001) and target-based sensitivity (p<0.001) with images in which low SF noise was suppressed. Also, significant higher cased-based sensitivity (p=0.005), target-based sensitivity (p=0.022) and Az-values (p=0.01) were scored under mid SF noise filtration. No significant differences were observed when images with SF-neutral noise suppression were compared with high SF noise suppression. In conclusion, increase of low and also mid SF signal signal-to-noise ratio significantly improves human performance in visual detection of simple targets in inhomogeneous backgrounds and suggests that a low SF bias in MRI signal averaging may enhance diagnostic quality.

  7. Assessing The Spatial Dependence of Adaptive Loci in 43 European and Western Asian Goat Breeds Using AFLP Markers

    PubMed Central

    Negrini, Riccardo; Nicoloso, Letizia; Crepaldi, Paola; Ajmone-Marsan, Paolo

    2014-01-01

    Background During the past decades, neutral DNA markers have been extensively employed to study demography, population genetics and structure in livestock, but less interest has been devoted to the evaluation of livestock adaptive potential through the identification of genomic regions likely to be under natural selection. Methodology/Principal findings Landscape genomics can greatly benefit the entire livestock system through the identification of genotypes better adapted to specific or extreme environmental conditions. Therefore we analyzed 101 AFLP markers in 43 European and Western Asian goat breeds both with Matsam software, based on a correlative approach (SAM), and with Mcheza and Bayescan, two FST based software able to detect markers carrying signatures of natural selection. Matsam identified four loci possibly under natural selection – also confirmed by FST-outlier methods – and significantly associated with environmental variables such as diurnal temperature range, frequency of precipitation, relative humidity and solar radiation. Conclusions/Significance These results show that landscape genomics can provide useful information on the environmental factors affecting the adaptive potential of livestock living in specific climatic conditions. Besides adding conservation value to livestock genetic resources, this knowledge may lead to the development of novel molecular tools useful to preserve the adaptive potential of local breeds during genetic improvement programs, and to increase the adaptability of industrial breeds to changing environments. PMID:24497965

  8. Evolution at ‘Sutures’ and ‘Centers’: Recombination Can Aid Adaptation of Spatially Structured Populations on Rugged Fitness Landscapes

    PubMed Central

    Cooper, Jacob D.; Kerr, Benjamin

    2016-01-01

    Epistatic interactions among genes can give rise to rugged fitness landscapes, in which multiple “peaks” of high-fitness allele combinations are separated by “valleys” of low-fitness genotypes. How populations traverse rugged fitness landscapes is a long-standing question in evolutionary biology. Sexual reproduction may affect how a population moves within a rugged fitness landscape. Sex may generate new high-fitness genotypes by recombination, but it may also destroy high-fitness genotypes by shuffling the genes of a fit parent with a genetically distinct mate, creating low-fitness offspring. Either of these opposing aspects of sex require genotypic diversity in the population. Spatially structured populations may harbor more diversity than well-mixed populations, potentially amplifying both positive and negative effects of sex. On the other hand, spatial structure leads to clumping in which mating is more likely to occur between like types, diminishing the effects of recombination. In this study, we use computer simulations to investigate the combined effects of recombination and spatial structure on adaptation in rugged fitness landscapes. We find that spatially restricted mating and offspring dispersal may allow multiple genotypes inhabiting suboptimal peaks to coexist, and recombination at the “sutures” between the clusters of these genotypes can create genetically novel offspring. Sometimes such an offspring genotype inhabits a new peak on the fitness landscape. In such a case, spatially restricted mating allows this fledgling subpopulation to avoid recombination with distinct genotypes, as mates are more likely to be the same genotype. Such population “centers” can allow nascent peaks to establish despite recombination. Spatial structure may therefore allow an evolving population to enjoy the creative side of sexual recombination while avoiding its destructive side. PMID:27973606

  9. A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

    PubMed Central

    Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

    2016-01-01

    Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa

  10. A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

    PubMed

    Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I; Midgley, Guy

    2016-01-01

    Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa

  11. Accuracy Sampling Design Bias on Coarse Spatial Resolution Land Cover Data in the Great Lakes Region (United States and Canada)

    EPA Science Inventory

    A number of articles have investigated the impact of sampling design on remotely sensed landcover accuracy estimates. Gong and Howarth (1990) found significant differences for Kappa accuracy values when comparing purepixel sampling, stratified random sampling, and stratified sys...

  12. MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  13. SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  14. MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  15. Developing an Instructional Material Using a Concept Cartoon Adapted to the 5E Model: A Sample of Teaching Erosion

    ERIC Educational Resources Information Center

    Birisci, Salih; Metin, Mustafa

    2010-01-01

    Using different instructional materials adapted within the constructivist learning theory will enhance students' conceptual understanding. From this point of view, an instructional instrument using a concept cartoon adapted with 5E model has developed and introduced in this study. The study has some deficiencies in investigating students'…

  16. Diagnosing Intellectual Disability in a Forensic Sample: Gender and Age Effects on the Relationship between Cognitive and Adaptive Functioning

    ERIC Educational Resources Information Center

    Hayes, Susan C.

    2005-01-01

    Background: The relationship between adaptive behaviour and cognitive functioning in offenders with intellectual disabilities is not well researched. This study aims to examine gender and age effects on the relationship between these two areas of functioning. Method: The "Vineland Adaptive Behavior Scales" (VABS) and the "Kaufman…

  17. Cost-effective sampling of (137)Cs-derived net soil redistribution: part 2 - estimating the spatial mean change over time.

    PubMed

    Chappell, A; Li, Y; Yu, H Q; Zhang, Y Z; Li, X Y

    2015-06-01

    The caesium-137 ((137)Cs) technique for estimating net, time-integrated soil redistribution by the processes of wind, water and tillage is increasingly being used with repeated sampling to form a baseline to evaluate change over small (years to decades) timeframes. This interest stems from knowledge that since the 1950s soil redistribution has responded dynamically to different phases of land use change and management. Currently, there is no standard approach to detect change in (137)Cs-derived net soil redistribution and thereby identify the driving forces responsible for change. We outline recent advances in space-time sampling in the soil monitoring literature which provide a rigorous statistical and pragmatic approach to estimating the change over time in the spatial mean of environmental properties. We apply the space-time sampling framework, estimate the minimum detectable change of net soil redistribution and consider the information content and cost implications of different sampling designs for a study area in the Chinese Loess Plateau. Three phases (1954-1996, 1954-2012 and 1996-2012) of net soil erosion were detectable and attributed to well-documented historical change in land use and management practices in the study area and across the region. We recommend that the design for space-time sampling is considered carefully alongside cost-effective use of the spatial mean to detect and correctly attribute cause of change over time particularly across spatial scales of variation.

  18. Contouring Of Tooth Imprints By Means Of A Fluorescence Technique Adapted To A Spatially Filtered Moire Illumination

    NASA Astrophysics Data System (ADS)

    Jongsma, Frans H. M.; Lambrechts, Paul; Vanherle, Guido

    1983-07-01

    A technique has been developed to produce plane equidistant contouring surfaces on tooth-imprints. This technique consists of spatially filtering a negative obtained by photographing the imprint under a Moire illumination. Unfortunately this technique turned out to be very sensitive for a non-uniform surface reflectivity. To obtain an object-brightness depending only upon the contouring mechanism, the imprint has been coated with a fluorescent dye. A HeCd-laser (λ=422 nm) served as a lightsource for the projection of the Moire-interference pattern on the imprint. The radiation of the fluorescent coating (λ=530 nm) is used to form an image on the negative. In this way the surface with specular reflection properties is transformed into a Labertian surface. The spatial filtering technique allows multiple exposures of the final negative enabling an increased depth of field. Contour mappings with a resolution in depth of less than 10 μm have been obtained.

  19. An Adaptive Framework for Image and Video Sensing

    DTIC Science & Technology

    2005-03-01

    bandwidth on the camera transmission or memory is not optimally utilized. In this paper we outline a framework for an adaptive sensor where the spatial and...scene can be realized, with small distortion. Keywords: Adaptive Imaging, Varying Sampling Rate, Image Content Measure, Scene Adaptive, Camera ...second order effect on the spatio-temporal trade-off. Figure 1 is an example of the spatio-temporal sampling rate tradeoff in a typical camera (e.g

  20. A technique for estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The validation of satellite surface soil moisture retrievals requires the spatial aggregation of point-scale ground soil moisture measurements up to coarse resolution satellite footprint scales (>10 km). In regions containing a limited number of ground measurements per satellite footprint, a large c...

  1. Spatial characteristics of white mould epidemics and the development of sequential sampling plans in Australian bean fields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    White mould, caused by Sclerotinia sclerotiorum, causes losses to bean through reducing the marketable yield of pods by flower infections and stem rot. In Australia, entire fields may be rejected due to high disease incidence. The spatial characteristics of white mould epidemics were characterised...

  2. Spatial Structure and Climatic Adaptation in African Maize Revealed by Surveying SNP Diversity in Relation to Global Breeding and Landrace Panels

    PubMed Central

    Westengen, Ola T.; Berg, Paul R.; Kent, Matthew P.; Brysting, Anne K.

    2012-01-01

    Background Climate change threatens maize productivity in sub-Saharan Africa. To ensure food security, access to locally adapted genetic resources and varieties is an important adaptation measure. Most of the maize grown in Africa is a genetic mix of varieties introduced at different historic times following the birth of the trans-Atlantic economy, and knowledge about geographic structure and local adaptations is limited. Methodology A panel of 48 accessions of maize representing various introduction routes and sources of historic and recent germplasm introductions in Africa was genotyped with the MaizeSNP50 array. Spatial genetic structure and genetic relationships in the African panel were analysed separately and in the context of a panel of 265 inbred lines representing global breeding material (based on 26,900 SNPs) and a panel of 1127 landraces from the Americas (270 SNPs). Environmental association analysis was used to detect SNPs associated with three climatic variables based on the full 43,963 SNP dataset. Conclusions The genetic structure is consistent between subsets of the data and the markers are well suited for resolving relationships and admixture among the accessions. The African accessions are structured in three clusters reflecting historical and current patterns of gene flow from the New World and within Africa. The Sahelian cluster reflects original introductions of Meso-American landraces via Europe and a modern introduction of temperate breeding material. The Western cluster reflects introduction of Coastal Brazilian landraces, as well as a Northeast-West spread of maize through Arabic trade routes across the continent. The Eastern cluster most strongly reflects gene flow from modern introduced tropical varieties. Controlling for population history in a linear model, we identify 79 SNPs associated with maximum temperature during the growing season. The associations located in genes of known importance for abiotic stress tolerance are

  3. Spatial and temporal variability of compound-specific stable isotope (CSSI) biomarkers in soil and sediment tracing: towards improved sampling protocols

    NASA Astrophysics Data System (ADS)

    Reiffarth, Dominic; Petticrew, Ellen; Owens, Philip; Lobb, David

    2016-04-01

    The use of CSSI in biomarkers, specifically fatty acids and derivatives thereof, has recently been investigated as a potential tracer in soil and sediment fingerprinting. The use of CSSIs is of interest because of the potential to discern sediment providence based on land use, which is often difficult or not possible with other tracing techniques alone, such as geochemistry and fallout radionuclides. However, challenges exist in producing a representative sample of potential source materials. This presentation focuses on the development of improved protocols for sample collection. The data presented here are part of a larger investigation into using CSSIs as tracers in an agricultural watershed (South Tobacco Creek) in southern Manitoba, Canada. Extensive sampling was performed throughout the 2012 and 2013 growing seasons in several locations within the watershed, with a focus on capturing within and between field spatial and temporal variability in one particular sub-watershed (the "Stepler" watershed). The Stepler watershed provided a unique opportunity to perform sampling in a natural environment where agricultural crops were hydrologically separated, thereby allowing for a sampling regime of transects strategically placed with little influence from nearby crops. A portion of the data which has been analyzed, showing temporal and spatial variability in terms of carbon stable isotope signal, biomarker concentrations and soil organic carbon, is presented. As CSSI protocols for tracing are still in development, these data aid in determining the robustness of the technique as well as helping to inform sampling approaches.

  4. Spatial distribution, sampling precision and survey design optimisation with non-normal variables: The case of anchovy (Engraulis encrasicolus) recruitment in Spanish Mediterranean waters

    NASA Astrophysics Data System (ADS)

    Tugores, M. Pilar; Iglesias, Magdalena; Oñate, Dolores; Miquel, Joan

    2016-02-01

    In the Mediterranean Sea, the European anchovy (Engraulis encrasicolus) displays a key role in ecological and economical terms. Ensuring stock sustainability requires the provision of crucial information, such as species spatial distribution or unbiased abundance and precision estimates, so that management strategies can be defined (e.g. fishing quotas, temporal closure areas or marine protected areas MPA). Furthermore, the estimation of the precision of global abundance at different sampling intensities can be used for survey design optimisation. Geostatistics provide a priori unbiased estimations of the spatial structure, global abundance and precision for autocorrelated data. However, their application to non-Gaussian data introduces difficulties in the analysis in conjunction with low robustness or unbiasedness. The present study applied intrinsic geostatistics in two dimensions in order to (i) analyse the spatial distribution of anchovy in Spanish Western Mediterranean waters during the species' recruitment season, (ii) produce distribution maps, (iii) estimate global abundance and its precision, (iv) analyse the effect of changing the sampling intensity on the precision of global abundance estimates and, (v) evaluate the effects of several methodological options on the robustness of all the analysed parameters. The results suggested that while the spatial structure was usually non-robust to the tested methodological options when working with the original dataset, it became more robust for the transformed datasets (especially for the log-backtransformed dataset). The global abundance was always highly robust and the global precision was highly or moderately robust to most of the methodological options, except for data transformation.

  5. Effects of spatial pattern of green space on land surface temperature: implications for sustainable urban planning and climate change adaptation

    NASA Astrophysics Data System (ADS)

    Maimaitiyiming, M.; Ghulam, A.

    2013-12-01

    The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Numerous studies have shown that increased percent cover of green space (PLAND) can significantly decrease land surface temperatures (LST). Fewer studies, however, have investigated the effects of configuration of green space on LST. This paper aims at to fill this gap using oasis city Aksu in northwestern China as a case study. PLAND along with two configuration metrics are used to measure the composition and configuration of green space. The metrics are calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data are retrieved from Landsat TM thermal band. Normalized mutual information measure is employed to investigate the relationship between LST and the spatial pattern of green space. The results show that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. In addition, the variance of LST is largely explained by both composition and configuration of green space. Results from this study can expand our understanding of the relationship between LST and vegetation, and provide insights for sustainable urban planning and management under changing climate.

  6. Effect of spatial configuration of an extended nonlinear Kierstead-Slobodkin reaction-transport model with adaptive numerical scheme.

    PubMed

    Owolabi, Kolade M; Patidar, Kailash C

    2016-01-01

    In this paper, we consider the numerical simulations of an extended nonlinear form of Kierstead-Slobodkin reaction-transport system in one and two dimensions. We employ the popular fourth-order exponential time differencing Runge-Kutta (ETDRK4) schemes proposed by Cox and Matthew (J Comput Phys 176:430-455, 2002), that was modified by Kassam and Trefethen (SIAM J Sci Comput 26:1214-1233, 2005), for the time integration of spatially discretized partial differential equations. We demonstrate the supremacy of ETDRK4 over the existing exponential time differencing integrators that are of standard approaches and provide timings and error comparison. Numerical results obtained in this paper have granted further insight to the question 'What is the minimal size of the spatial domain so that the population persists?' posed by Kierstead and Slobodkin (J Mar Res 12:141-147, 1953), with a conclusive remark that the population size increases with the size of the domain. In attempt to examine the biological wave phenomena of the solutions, we present the numerical results in both one- and two-dimensional space, which have interesting ecological implications. Initial data and parameter values were chosen to mimic some existing patterns.

  7. Comparing the performances of Diggle's tests of spatial randomness for small samples with and without edge-effect correction: application to ecological data.

    PubMed

    Gignoux, J; Duby, C; Barot, S

    1999-03-01

    Diggle's tests of spatial randomness based on empirical distributions of interpoint distances can be performed with and without edge-effect correction. We present here numerical results illustrating that tests without the edge-effect correction proposed by Diggle (1979, Biometrics 35, 87-101) have a higher power for small sample sizes than those with correction. Ignoring the correction enables detection of departure from spatial randomness with smaller samples (down to 10 points vs. 30 points for the tests with correction). These results are confirmed by an example with ecological data consisting of maps of two species of trees in a West African savanna. Tree numbers per species per map were often less than 20. For one of the species, for which maps strongly suggest an aggregated pattern, tests without edge-effect correction enabled rejection of the null hypothesis on three plots out of five vs. on only one for the tests with correction.

  8. Testing Set-Point Theory in a Swiss National Sample: Reaction and Adaptation to Major Life Events

    PubMed Central

    Anusic, Ivana; Yap, Stevie C. Y.; Lucas, Richard E.

    2014-01-01

    Set-point theory posits that individuals react to the experience of major life events, but quickly adapt back to pre-event baseline levels of subjective well-being in the years following the event. A large, nationally representative panel study of Swiss households was used to examine set-point theory by investigating the extent of adaptation following the experience of marriage, childbirth, widowhood, unemployment, and disability. Our results demonstrate that major life events are associated with marked change in life satisfaction and, for some events (e.g., marriage, disability), these changes are relatively long lasting even when accounting for normative, age related change. PMID:25419036

  9. Prism adaptation changes perceptual awareness for chimeric visual objects but not for chimeric faces in spatial neglect after right-hemisphere stroke.

    PubMed

    Sarri, Margarita; Kalra, Lalit; Greenwood, Richard; Driver, Jon

    2006-06-01

    Prism adaptation can ameliorate some symptoms of left spatial neglect after right-hemisphere stroke. The mechanisms behind this remain unclear. Prism therapy may increase exploration towards the contralesional side, yet without improving perceptual awareness, as apparently for the left side of chimeric face stimuli (Ferber et al. 2003). However, other prism studies suggest that perceptual awareness might be improved (e.g., Maravita et al., 2003). We tested the impact of prism therapy on visual awareness for the left side of chimeric objects as well as chimeric faces, in three neglect patients. Prism therapy dramatically improved awareness for the identity of the left side of chimeric non-face objects, but had no effect on judging expressions for chimeric faces. The latter may thus be unique in showing no prism benefit.

  10. Diffeomorphic registration with self-adaptive spatial regularization for the segmentation of non-human primate brains.

    PubMed

    Risser, Laurent; Dolius, Lionel; Fonta, Caroline; Mescam, Muriel

    2014-01-01

    Cerebral aging has been linked to structural and functional changes in the brain throughout life. Here, we study the marmoset, a small non-human primate, in order to get insights into the mechanisms of brain aging in normal and pathological conditions. Imaging the brain of small animals with techniques such as MRI, quickly becomes a challenging task when compared with human brain imaging. Very often, a simple pre-processing step such as brain extraction cannot be achieved with classical tools. In this paper, we propose a diffeomorphic registration algorithm, which makes use of learned constraints to propagate the manual segmentation of a marmoset brain template to other MR images of marmoset brains. The main methological contribution of our paper is to explore a new strategy to automatically tune the spatial regularization of the deformations. Results show that we obtain a robust segmentation of the brain, even for images with a low contrast.

  11. A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

    PubMed Central

    Otero, Jorge; Guerrero, Hector; Gonzalez, Laura; Puig-Vidal, Manel

    2012-01-01

    The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. PMID:22368491

  12. Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group, group sequential, and adaptive selection design on sample size requirements.

    PubMed

    Boessen, Ruud; van der Baan, Frederieke; Groenwold, Rolf; Egberts, Antoine; Klungel, Olaf; Grobbee, Diederick; Knol, Mirjam; Roes, Kit

    2013-01-01

    Two-stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two-stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family-wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed 'true' subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two-stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design.

  13. Detecting short spatial scale local adaptation and epistatic selection in climate-related candidate genes in European beech (Fagus sylvatica) populations.

    PubMed

    Csilléry, Katalin; Lalagüe, Hadrien; Vendramin, Giovanni G; González-Martínez, Santiago C; Fady, Bruno; Oddou-Muratorio, Sylvie

    2014-10-01

    Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech (Fagus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south-eastern France). We performed both single and multilocus analysis of selection based on 53 climate-related candidate genes containing 546 SNPs. FST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by Ohta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an FST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.

  14. Human cytomegalovirus and human umbilical vein endothelial cells: restriction of primary isolation to blood samples and susceptibilities of clinical isolates from other sources to adaptation.

    PubMed

    Gerna, Giuseppe; Percivalle, Elena; Sarasini, Antonella; Revello, M Grazia

    2002-01-01

    In immunocompromised patients with disseminated infection, human cytomegalovirus (HCMV) is widespread in the microvascular endothelium of multiple organs. Human umbilical vein endothelial cells (HUVEC) were used in parallel to human embryonic lung fibroblasts (HELF) to recover HCMV from blood samples of immunocompromised patients. Using the shell vial technique, comparable median numbers of p72-positive HUVEC and HELF cells were found with the 26 HCMV-positive buffy coat samples out of 150 examined. Analysis of other clinical samples inoculated as controls revealed, in the presence of highly infected HELF monolayers, either the presence of very few infected HUVEC with urine specimens (n = 10 samples) or the lack of infected HUVEC with throat washes (n = 3) or amniotic fluid samples (n = 2). Thus, peripheral blood leukocytes (PBL) appear essential for primary isolation of HCMV in HUVEC. In this respect, HCMV strains, recovered from clinical samples other than buffy coats in HELF only, could be readily adapted to growth in HUVEC by coculturing PBL from healthy blood donors with infected HELF and then inoculating infected PBL onto HUVEC. Recently elucidated mechanisms of interaction of leukocytes and HUVEC with bidirectional transfer of virus seem to provide the basis for the restriction of HCMV primary isolation in HUVEC to blood samples. However, virus strains recovered from only HELF could be adapted to growth in HUVEC when inoculated with HELF-derived (either cell-associated or cell-free) HCMV strains upon primary isolation. In conclusion, due to the in vitro selection of virus variants provided with both PBL tropism and HUVEC tropism, HCMV recovery in HUVEC is PBL mediated and substantially restricted to blood samples. Lack of HCMV recovery in HUVEC from clinical samples other than blood leads to the assumption that epithelial cells, such as urinary, amniotic, or pharyngeal cells, do not possess adequate adhesion molecules to establish close contacts with HUVEC.

  15. Continuous Flow Liquid Microjunction Surface Sampling Probe Connected On-line with HPLC/MS for Spatially Resolved Analysis of Small Molecules and Proteins

    SciTech Connect

    Van Berkel, Gary J; Kertesz, Vilmos

    2013-01-01

    RATIONALE: A continuous flow liquid microjunction surface sampling probe extracts soluble material from surfaces for direct ionization and detection by MS. Demonstrated here is the on-line coupling of such a probe with HPLC/MS enabling extraction, separation and detection of small molecules and proteins from surfaces in a spatially resolved (~0.5 mm diameter spots) manner. Methods: A continuous flow liquid microjunction surface sampling probe was connected to a 6-port, 2-position valve for extract collection and injection to an HPLC column. A QTRAP 5500 hybrid triple quadrupole linear ion trap equipped with a Turbo V ion source operated in positive ESI mode was used for all experiments. System operation was tested with extraction, separation and detection of propranolol and associated metabolites from drug dosed tissues and proteins from dried sheep blood spots on paper. Results: Confirmed in the tissue were the parent drug and two different hydroxypropranolol glucuronides. The mass spectrometric response for these compounds from different locations in the liver showed an increase with increasing extraction time (5, 20 and 40 s extractions). For on-line separation and detection/identification of extracted proteins from dried sheep blood spots, two major protein peaks dominated the chromatogram and could be correlated with the expected masses for the hemoglobin and chains. Conclusions: Spatially resolved sampling, separation, and detection of small molecules and proteins from surfaces can be accomplished using a continuous flow liquid microjunction surface sampling probe coupled on-line with HPLC/MS detection.

  16. Analyses at High Spatial Resolution of Organic Molecules in Extraterrestrial Samples: Two-Step Laser Mass Spectrometry: Search for Polycyclic Aromatic Hydrocarbons in Antarctic Meteorite and Micrometeorite Samples

    NASA Technical Reports Server (NTRS)

    Zare, Richard N.

    1998-01-01

    Perhaps the best way to summarize the past three-year grant period is to cite the publications and present a brief synopsis of each: 1. "Indigenous Polycyclic Aromatic Hydrocarbon Molecules in Circumstellar Graphite Grains." Bulk C-12/C-13 isotope ratios observed in some graphite grains extracted from primitive meteorites point strongly to a circumstellar origin. By applying our technique of microprobe two-step laser desorption laser ionization mass spectrometry ((mu)L(sup 2)MS) to individual circumstellar graphite grains we have measured the C-12/C-13 isotope ratio of various polycyclic aromatic hydrocarbons (PAHS) found in these grains. 2. "Deuterium Enrichments in Cluster IDPS," Large enrichments in the D/H isotope ratios in IDPs likely arise from the preservation of presolar molecules. 3. "Evidence for thermalization of surface-disorder molecules at heating rates of 10(exp 8) K/s". A careful study of the ((mu)L(sup 2)MS) of aniline-d(sub 7) from a single-crystal surface (0001) of sapphire (al2O3) shows that all measured properties are consistent with a thermal mechanism for desorption. 4. "Search for past life on Mars; possible relic biogenic activity in Martian meteorite ALH 84001. The authors examined the Martian meteorite ALH 84001 and found several lines of evidence compatible with existence of past primitive (single-cell) life on early Mars. 5. "Microprobe two-step laser mass spectrometry as an analytical tool for meteorite samples". THis paper presents a comprehensive review of (mu)L(sup 2)MS and how this technique can be applied to meteoritic samples. 6. "Indigenous polycyclic aromatic hydrocarbons in circumstellar graphite grains from primitive meteorites". The C-12/C-13 isotope ratios were measured for PAHs in a total of 89 spherical graphite grains. 7. "Observation of indigenous polycyclic aromatic hydrocarbons in "Giant" carbonaceous antarctic micrometeorites." The (mu)L(sup 2)MS method was used to establish the nature and distribution of PAHs in

  17. Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

    DOEpatents

    Maris, Humphrey J.

    2003-01-01

    A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

  18. Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

    DOEpatents

    Maris, Humphrey J.

    2002-01-01

    A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

  19. Coping with Spatial Heterogeneity and Temporal Variability in Resources and Risks: Adaptive Movement Behaviour by a Large Grazing Herbivore

    PubMed Central

    Martin, Jodie; Benhamou, Simon; Yoganand, K.; Owen-Smith, Norman

    2015-01-01

    Movement is a key mean for mobile species to cope with heterogeneous environments. While in herbivorous mammals large-scale migration has been widely investigated, fine-scale movement responses to local variations in resources and predation risk remain much less studied, especially in savannah environments. We developed a novel approach based on complementary movement metrics (residence time, frequency of visits and regularity of visits) to relate movement patterns of a savannah grazer, the blue wildebeest Connochaetes taurinus, to fine-scale variations in food availability, predation risk and water availability in the Kruger National Park, South Africa. Wildebeests spent more time in grazing lawns where the grass is of higher quality but shorter than in seep zones, where the grass is of lower quality but more abundant. Although the daily distances moved were longer during the wet season compared to the dry season, the daily net displacement was lower, and the residence time higher, indicating a more frequent occurrence of area-concentred searching. In contrast, during the late dry season the foraging sessions were more fragmented and wildebeests moved more frequently between foraging areas. Surprisingly, predation risk appeared to be the second factor, after water availability, influencing movement during the dry season, when resources are limiting and thus expected to influence movement more. Our approach, using complementary analyses of different movement metrics, provided an integrated view of changes in individual movement with varying environmental conditions and predation risk. It makes it possible to highlight the adaptive behavioral decisions made by wildebeest to cope with unpredictable environmental variations and provides insights for population conservation. PMID:25719494

  20. A sampling procedure to guide the collection of narrow-band, high-resolution spatially and spectrally representative reflectance data. [satellite imagery of earth resources

    NASA Technical Reports Server (NTRS)

    Brand, R. R.; Barker, J. L.

    1983-01-01

    A multistage sampling procedure using image processing, geographical information systems, and analytical photogrammetry is presented which can be used to guide the collection of representative, high-resolution spectra and discrete reflectance targets for future satellite sensors. The procedure is general and can be adapted to characterize areas as small as minor watersheds and as large as multistate regions. Beginning with a user-determined study area, successive reductions in size and spectral variation are performed using image analysis techniques on data from the Multispectral Scanner, orbital and simulated Thematic Mapper, low altitude photography synchronized with the simulator, and associated digital data. An integrated image-based geographical information system supports processing requirements.

  1. Development of a Spatially Targeted Field Sampling Technique for the Southern Cattle Tick, Rhipicephalus microplus, by Mapping Whitetailed Deer, Odocoileus virginianus, Habitat in South Texas

    PubMed Central

    Phillips, Pamela L.; Welch, John B.; Kramer, Matthew

    2014-01-01

    The objective of our study was to determine whether satellite remote sensed data could be used to identify white-tailed deer, Odocoileus virginianus (Zimmerman) (Artiodactyla: Cervidae), habitat and target locations for sampling free-living larvae of the southern cattle tick, Rhipicephalus (Boophilus) microplus (Canestrini) (Ixodida: Ixodidae) in South Texas. Two methods for mapping white-tailed deer habitat were used, an object-oriented method to identify closed canopies and waterways for deer movement and two vegetation indices: the Normalized Difference Vegetation Index and the Modified Soil Adjusted Vegetation Index to identify forage for deer. These two data sets of favorable white-tailed deer habitat were combined within a geographic information system to identify locations for sampling ticks. Larvae of R. (B.) microplus, were sampled in Zapata County, Texas, by walking transects with attached flannel panels to jeans. Although the data set and sampling period were limited, data analysis demonstrated that sampling of free-living larvae of R. (B.) microplus can be conducted in South Texas, and larvae were most abundant in areas that harbored O. virginianus. Spatial analysis of satellite imagery to classify white-tailed deer/southern cattle tick habitat proved efficacious and may be useful in directing sampling activities in the field. PMID:25368044

  2. Development of a spatially targeted field sampling technique for the southern cattle tick, Rhipicephalus microplus, by mapping white-tailed deer, Odocoileus virginianus, habitat in South Texas.

    PubMed

    Phillips, Pamela L; Welch, John B; Kramer, Matthew

    2014-01-01

    The objective of our study was to determine whether satellite remote sensed data could be used to identify white-tailed deer, Odocoileus virginianus (Zimmerman) (Artiodactyla: Cervidae), habitat and target locations for sampling free-living larvae of the southern cattle tick, Rhipicephalus (Boophilus) microplus (Canestrini) (Ixodida: Ixodidae) in South Texas. Two methods for mapping white-tailed deer habitat were used, an object-oriented method to identify closed canopies and waterways for deer movement and two vegetation indices: the Normalized Difference Vegetation Index and the Modified Soil Adjusted Vegetation Index to identify forage for deer. These two data sets of favorable white-tailed deer habitat were combined within a geographic information system to identify locations for sampling ticks. Larvae of R. (B.) microplus, were sampled in Zapata County, Texas, by walking transects with attached flannel panels to jeans. Although the data set and sampling period were limited, data analysis demonstrated that sampling of free-living larvae of R. (B.) microplus can be conducted in South Texas, and larvae were most abundant in areas that harbored O. virginianus. Spatial analysis of satellite imagery to classify white-tailed deer/southern cattle tick habitat proved efficacious and may be useful in directing sampling activities in the field.

  3. Photon event distribution sampling: an image formation technique for scanning microscopes that permits tracking of sub-diffraction particles with high spatial and temporal resolutions.

    PubMed

    Larkin, J D; Publicover, N G; Sutko, J L

    2011-01-01

    In photon event distribution sampling, an image formation technique for scanning microscopes, the maximum likelihood position of origin of each detected photon is acquired as a data set rather than binning photons in pixels. Subsequently, an intensity-related probability density function describing the uncertainty associated with the photon position measurement is applied to each position and individual photon intensity distributions are summed to form an image. Compared to pixel-based images, photon event distribution sampling images exhibit increased signal-to-noise and comparable spatial resolution. Photon event distribution sampling is superior to pixel-based image formation in recognizing the presence of structured (non-random) photon distributions at low photon counts and permits use of non-raster scanning patterns. A photon event distribution sampling based method for localizing single particles derived from a multi-variate normal distribution is more precise than statistical (Gaussian) fitting to pixel-based images. Using the multi-variate normal distribution method, non-raster scanning and a typical confocal microscope, localizations with 8 nm precision were achieved at 10 ms sampling rates with acquisition of ~200 photons per frame. Single nanometre precision was obtained with a greater number of photons per frame. In summary, photon event distribution sampling provides an efficient way to form images when low numbers of photons are involved and permits particle tracking with confocal point-scanning microscopes with nanometre precision deep within specimens.

  4. The influence of sampling strategies and spatial variation on the detected soil bacterial communities under three different land-use types.

    PubMed

    Osborne, Catherine A; Zwart, Alexander B; Broadhurst, Linda M; Young, Andrew G; Richardson, Alan E

    2011-10-01

    To determine the influence of pooling strategies on detected soil bacterial communities, we sampled 45 soil cores each from a eucalypt woodland, a sown pasture and a revegetated site in an Australian landscape. We assessed the spatial variation within each land-use plot, including the influence of sampling distance, soil chemical characteristics and, where appropriate, proximity to trees on the soil bacterial community, by generating terminal restriction fragment length polymorphism profiles of the bacterial 16S rRNA genes. The soil bacterial community under the revegetated site was more similar to the original woodland than the pasture, and this result was found regardless of the soil- or the DNA-pooling strategy used. Analyzing as few as eight cores per plot was sufficient to detect significant differences between the bacterial communities under the different plots to be distinguished. Soil pH was found to be most strongly associated with soil bacterial community composition within the plots and there was no association found with proximity to trees. This study has investigated sampling strategies for further research into the transitions of soil microbial communities with land-use change across broader temporal and spatial scales.

  5. Long-term sensorimotor and therapeutical effects of a mild regime of prism adaptation in spatial neglect. A double-blind RCT essay.

    PubMed

    Rode, G; Lacour, S; Jacquin-Courtois, S; Pisella, L; Michel, C; Revol, P; Alahyane, N; Luauté, J; Gallagher, S; Halligan, P; Pélisson, D; Rossetti, Y

    2015-04-01

    Spatial neglect (SN) is commonly associated with poor functional outcome. Adaptation to a rightward optical deviation of vision has been shown to benefit to SN rehabilitation. The neurophysiological foundations and the optimal modalities of prism adaptation (PA) therapy however remain to be validated. This study is aimed at exploring the long-term sensory-motor, cognitive and functional effects produced by weekly PA sessions over a period of four weeks. A double-blind, monocentric randomized and controlled trial (RCT) was carried out. Twenty patients with left SN secondary to stroke were included, 10 in the "prism" group and 10 in the "control" group. The sensory-motor effects of PA were evaluated by measurement of manual and visual straight-ahead, and also by precision of pointing without visual feedback before and after each PA session. The functional independence measure (FIM) was evaluated before and at 1, 3 and 6 months after PA, while SN severity was assessed using the Behavioural Inattention Test (BIT) before and 6 months after PA. Before the intervention, only manual straight-ahead pointing constituted a reproducible sensory-motor measurement. During prism exposure, a questionnaire showed that not a single patient were aware of the direct effects of optical deviation on pointing movement performance. The sensory-motor after-effects produced by the PA produced a more rapid reduction of the rightward manual straight-ahead, which was secondarily followed by visual straight-ahead. These sensory-motor effects helped to clarify the action mechanisms of PA on SN. At the conclusion of the 6-month follow-up, the two groups showed similar improvement, indicating that a weekly PA session over 4 weeks was not sufficient to produce long-term functional benefit. This improvement was correlated with the evolution of visual straight-ahead, which can be proposed as a marker for patients outcome.

  6. In absence of local adaptation, plasticity and spatially varying selection rule: a view from genomic reaction norms in a panmictic species (Anguilla rostrata)

    PubMed Central

    2014-01-01

    Background American eel (Anguilla rostrata) is one of the few species for which panmixia has been demonstrated at the scale of the entire species. As such, the development of long term local adaptation is impossible. However, both plasticity and spatially varying selection have been invoked in explaining how American eel may cope with an unusual broad scope of environmental conditions. Here, we address this question through transcriptomic analyses and genomic reaction norms of eels from two geographic origins reared in controlled environments. Results The null hypothesis of no difference in gene expression between eels from the two origins was rejected. Many unique transcripts and two out of seven gene clusters showed significant difference in expression, both at time of capture and after three months of common rearing. Differences in expression were observed at numerous genes representing many functional groups when comparing eels from a same origin reared under different salinity conditions. Plastic response to different rearing conditions varied among gene clusters with three clusters showing significant origin-environment interactions translating into differential genomic norms of reaction. Most genes and functional categories showing differences between origins were previously shown to be differentially expressed in a study comparing transcription profiles between adult European eels acclimated to different salinities. Conclusions These results emphasize that while plasticity in expression may be important, there is also a role for local genetic (and/or epigenetic) differences in explaining differences in gene expression between eels from different geographic origins. Such differences match those reported in genetically distinct populations in other fishes, both in terms of the proportion of genes that are differentially expressed and the diversity of biological functions involved. We thus propose that genetic differences between glass eels of different

  7. Delineating high-density areas in spatial Poisson fields from strip-transect sampling using indicator geostatistics: application to unexploded ordnance removal.

    PubMed

    Saito, Hirotaka; McKenna, Sean A

    2007-07-01

    An approach for delineating high anomaly density areas within a mixture of two or more spatial Poisson fields based on limited sample data collected along strip transects was developed. All sampled anomalies were transformed to anomaly count data and indicator kriging was used to estimate the probability of exceeding a threshold value derived from the cdf of the background homogeneous Poisson field. The threshold value was determined so that the delineation of high-density areas was optimized. Additionally, a low-pass filter was applied to the transect data to enhance such segmentation. Example calculations were completed using a controlled military model site, in which accurate delineation of clusters of unexploded ordnance (UXO) was required for site cleanup.

  8. Adapting the semi-explicit assembly solvation model for estimating water-cyclohexane partitioning with the SAMPL5 molecules

    NASA Astrophysics Data System (ADS)

    Brini, Emiliano; Paranahewage, S. Shanaka; Fennell, Christopher J.; Dill, Ken A.

    2016-11-01

    We describe here some tests we made in the SAMPL5 communal event of `Semi-Explicit Assembly' (SEA), a recent method for computing solvation free energies. We combined the prospective tests of SAMPL5 with followup retrospective calculations, to improve two technical aspects of the field variant of SEA. First, SEA uses an approximate analytical surface around the solute on which a water potential is computed. We have improved and simplified the mathematical model of that surface. Second, some of the solutes in SAMPL5 were large enough to need a way to treat solvating waters interacting with `buried atoms', i.e. interior atoms of the solute. We improved SEA with a buried-atom correction. We also compare SEA to Thermodynamic Integration molecular dynamics simulations, so that we can sort out force field errors.

  9. Sample selection and spatial models of housing price indexes, and, A disequilibrium analysis of the U.S. gasoline market using panel data

    NASA Astrophysics Data System (ADS)

    Hu, Haixin

    This dissertation consists of two parts. The first part studies the sample selection and spatial models of housing price index using transaction data on detached single-family houses of two California metropolitan areas from 1990 through 2008. House prices are often spatially correlated due to shared amenities, or when the properties are viewed as close substitutes in a housing submarket. There have been many studies that address spatial correlation in the context of housing markets. However, none has used spatial models to construct housing price indexes at zip code level for the entire time period analyzed in this dissertation to the best of my knowledge. In this paper, I study a first-order autoregressive spatial model with four different weighing matrix schemes. Four sets of housing price indexes are constructed accordingly. Gatzlaff and Haurin (1997, 1998) study the sample selection problem in housing index by using Heckman's two-step method. This method, however, is generally inefficient and can cause multicollinearity problem. Also, it requires data on unsold houses in order to carry out the first-step probit regression. Maximum likelihood (ML) method can be used to estimate a truncated incidental model which allows one to correct for sample selection based on transaction data only. However, convergence problem is very prevalent in practice. In this paper I adopt Lewbel's (2007) sample selection correction method which does not require one to model or estimate the selection model, except for some very general assumptions. I then extend this method to correct for spatial correlation. In the second part, I analyze the U.S. gasoline market with a disequilibrium model that allows lagged-latent variables, endogenous prices, and panel data with fixed effects. Most existing studies (see the survey of Espey, 1998, Energy Economics) of the gasoline market assume equilibrium. In practice, however, prices do not always adjust fast enough to clear the market

  10. A New Framework for Adaptive Sampling and Analysis During Long-Term Monitoring and Remedial Action Management

    SciTech Connect

    Minsker, Barbara; Albert Valocchi; Barbara Bailey

    2008-01-27

    DOE and other Federal agencies are making a significant investment in the development of field analytical techniques, nonintrusive technologies, and sensor technologies that will have a profound impact on the way environmental monitoring is conducted. Monitoring and performance evaluation networks will likely be base on suites of in situ sensors, with physical sampling playing a much more limited role. Designing and using these types of networks effectively will require development of a new paradigm for sampling and analysis of remedial actions, which is the overall goal of this project.

  11. Temporal-spatial analysis of U.S.-Mexico border environmental fine and coarse PM air sample extract activity in human bronchial epithelial cells

    SciTech Connect

    Lauer, Fredine T.; Mitchell, Leah A.; Bedrick, Edward; McDonald, Jacob D.; Lee, Wen-Yee; Li, Wen-Whai; Olvera, Hector; Amaya, Maria A.; Berwick, Marianne; Gonzales, Melissa; Currey, Robert; Pingitore, Nicholas E.

    2009-07-01

    Particulate matter less than 10 {mu}m (PM10) has been shown to be associated with aggravation of asthma and respiratory and cardiopulmonary morbidity. There is also great interest in the potential health effects of PM2.5. Particulate matter (PM) varies in composition both spatially and temporally depending on the source, location and seasonal condition. El Paso County which lies in the Paso del Norte airshed is a unique location to study ambient air pollution due to three major points: the geological land formation, the relatively large population and the various sources of PM. In this study, dichotomous filters were collected from various sites in El Paso County every 7 days for a period of 1 year. The sampling sites were both distant and near border crossings, which are near heavily populated areas with high traffic volume. Fine (PM2.5) and Coarse (PM10-2.5) PM filter samples were extracted using dichloromethane and were assessed for biologic activity and polycyclic aromatic (PAH) content. Three sets of marker genes human BEAS2B bronchial epithelial cells were utilized to assess the effects of airborne PAHs on biologic activities associated with specific biological pathways associated with airway diseases. These pathways included in inflammatory cytokine production (IL-6, IL-8), oxidative stress (HMOX-1, NQO-1, ALDH3A1, AKR1C1), and aryl hydrocarbon receptor (AhR)-dependent signaling (CYP1A1). Results demonstrated interesting temporal and spatial patterns of gene induction for all pathways, particularly those associated with oxidative stress, and significant differences in the PAHs detected in the PM10-2.5 and PM2.5 fractions. Temporally, the greatest effects on gene induction were observed in winter months, which appeared to correlate with inversions that are common in the air basin. Spatially, the greatest gene expression increases were seen in extracts collected from the central most areas of El Paso which are also closest to highways and border crossings.

  12. Temporal-spatial analysis of U.S.-Mexico border environmental fine and coarse PM air sample extract activity in human bronchial epithelial cells.

    PubMed

    Lauer, Fredine T; Mitchell, Leah A; Bedrick, Edward; McDonald, Jacob D; Lee, Wen-Yee; Li, Wen-Whai; Olvera, Hector; Amaya, Maria A; Berwick, Marianne; Gonzales, Melissa; Currey, Robert; Pingitore, Nicholas E; Burchiel, Scott W

    2009-07-01

    Particulate matter less than 10 microm (PM10) has been shown to be associated with aggravation of asthma and respiratory and cardiopulmonary morbidity. There is also great interest in the potential health effects of PM2.5. Particulate matter (PM) varies in composition both spatially and temporally depending on the source, location and seasonal condition. El Paso County which lies in the Paso del Norte airshed is a unique location to study ambient air pollution due to three major points: the geological land formation, the relatively large population and the various sources of PM. In this study, dichotomous filters were collected from various sites in El Paso County every 7 days for a period of 1 year. The sampling sites were both distant and near border crossings, which are near heavily populated areas with high traffic volume. Fine (PM2.5) and Coarse (PM10-2.5) PM filter samples were extracted using dichloromethane and were assessed for biologic activity and polycyclic aromatic (PAH) content. Three sets of marker genes human BEAS2B bronchial epithelial cells were utilized to assess the effects of airborne PAHs on biologic activities associated with specific biological pathways associated with airway diseases. These pathways included in inflammatory cytokine production (IL-6, IL-8), oxidative stress (HMOX-1, NQO-1, ALDH3A1, AKR1C1), and aryl hydrocarbon receptor (AhR)-dependent signaling (CYP1A1). Results demonstrated interesting temporal and spatial patterns of gene induction for all pathways, particularly those associated with oxidative stress, and significant differences in the PAHs detected in the PM10-2.5 and PM2.5 fractions. Temporally, the greatest effects on gene induction were observed in winter months, which appeared to correlate with inversions that are common in the air basin. Spatially, the greatest gene expression increases were seen in extracts collected from the central most areas of El Paso which are also closest to highways and border crossings.

  13. Spatial variability of "Did You Feel It?" intensity data: insights into sampling biases in historical earthquake intensity distributions

    USGS Publications Warehouse

    Hough, Susan E.

    2013-01-01

    Recent parallel development of improved quantitative methods to analyze intensity distributions for historical earthquakes and of web‐based systems for collecting intensity data for modern earthquakes provides an opportunity to reconsider not only important individual historical earthquakes but also the overall characterization of intensity distributions for historical events. The focus of this study is a comparison between intensity distributions of historical earthquakes with those from modern earthquakes for which intensities have been determined by the U.S. Geological Survey “Did You Feel It?” (DYFI) website (see Data and Resources). As an example of a historical earthquake, I focus initially on the 1843 Marked Tree, Arkansas, event. Its magnitude has been previously estimated as 6.0–6.2. I first reevaluate the macroseismic effects of this earthquake, assigning intensities using a traditional approach, and estimate a preferred magnitude of 5.4. Modified Mercalli intensity (MMI) values for the Marked Tree earthquake are higher, on average, than those from the 2011 >Mw 5.8 Mineral, Virginia, earthquake for distances ≤500  km but comparable or lower on average at larger distances, with a smaller overall felt extent. Intensity distributions for other moderate historical earthquakes reveal similar discrepancies; the discrepancy is also even more pronounced using earlier published intensities for the 1843 earthquake. I discuss several hypotheses to explain the discrepancies, including the possibility that intensity values associated with historical earthquakes are commonly inflated due to reporting/sampling biases. A detailed consideration of the DYFI intensity distribution for the Mineral earthquake illustrates how reporting and sampling biases can account for historical earthquake intensity biases as high as two intensity units and for the qualitative difference in intensity distance decays for modern versus historical events. Thus, intensity maps for

  14. Adaptation of the Participant Role Scale (PRS) in a Spanish youth sample: measurement invariance across gender and relationship with sociometric status.

    PubMed

    Lucas-Molina, Beatriz; Williamson, Ariel A; Pulido, Rosa; Calderón, Sonsoles

    2014-11-01

    In recent years, bullying research has transitioned from investigating the characteristics of the bully-victim dyad to examining bullying as a group-level process, in which the majority of children play some kind of role. This study used a shortened adaptation of the Participant Role Scale (PRS) to identify these roles in a representative sample of 2,050 Spanish children aged 8 to 13 years. Confirmatory factor analysis revealed three different roles, indicating that the adapted scale remains a reliable way to distinguish the Bully, Defender, and Outsider roles. In addition, measurement invariance of the adapted scale was examined to analyze possible gender differences among the roles. Peer status was assessed separately by gender through two sociometric procedures: the nominations-based method and the ratings-based method. Across genders, children in the Bully role were more often rated as rejected, whereas Defenders were more popular. Results suggest that although the PRS can reveal several different peer roles in the bullying process, a more clear distinction between bullying roles (i.e., Bully, Assistant, and Reinforcer) could better inform strategies for bullying interventions.

  15. Spatial distributions of the red palm mite, Raoiella indica (Acari: Tenuipalpidae) on coconut and their implications for development of efficient sampling plans.

    PubMed

    Roda, A; Nachman, G; Hosein, F; Rodrigues, J C V; Peña, J E

    2012-08-01

    The red palm mite (Raoiella indica), an invasive pest of coconut, entered the Western hemisphere in 2004, then rapidly spread through the Caribbean and into Florida, USA. Developing effective sampling methods may aid in the timely detection of the pest in a new area. Studies were conducted to provide and compare intra tree spatial distribution of red palm mite populations on coconut in two different geographical areas, Trinidad and Puerto Rico, recently invaded by the mite. The middle stratum of a palm hosted significantly more mites than fronds from the upper or lower canopy and fronds from the lower stratum, on average, had significantly fewer mites than the two other strata. The mite populations did not vary within a frond. Mite densities on the top section of the pinna had significantly lower mite densities than the two other sections, which were not significantly different from each other. In order to improve future sampling plans for the red palm mite, the data was used to estimate the variance components associated with the various levels of the hierarchical sampling design. Additionally, presence-absenc