Science.gov

Sample records for adaptive spatial sampling

  1. Spatial adaptive sampling in multiscale simulation

    NASA Astrophysics Data System (ADS)

    Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

    2014-07-01

    In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈50×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

  2. Autonomous spatially adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

    NASA Astrophysics Data System (ADS)

    Theunissen, Raf; Kadosh, Jesse S.; Allen, Christian B.

    2015-06-01

    Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in the number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfoil and the boundary layer characterisation of a flat plate.

  3. 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.

  4. Digital adaptive sampling.

    NASA Technical Reports Server (NTRS)

    Breazeale, G. J.; Jones, L. E.

    1971-01-01

    Discussion of digital adaptive sampling, which is consistently better than fixed sampling in noise-free cases. Adaptive sampling is shown to be feasible and, it is considered, should be studied further. It should be noted that adaptive sampling is a class of variable rate sampling in which the variability depends on system signals. Digital rather than analog laws should be studied, because cases can arise in which the analog signals are not even available. An extremely important problem is implementation.

  5. Adaptive Sampling Proxy Application

    2012-10-22

    ASPA is an implementation of an adaptive sampling algorithm [1-3], which is used to reduce the computational expense of computer simulations that couple disparate physical scales. The purpose of ASPA is to encapsulate the algorithms required for adaptive sampling independently from any specific application, so that alternative algorithms and programming models for exascale computers can be investigated more easily.

  6. 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…

  7. A Keck Adaptive Optics Survey of a Representative Sample of Gravitationally Lensed Star-forming Galaxies: High Spatial Resolution Studies of Kinematics and Metallicity Gradients

    NASA Astrophysics Data System (ADS)

    Leethochawalit, Nicha; Jones, Tucker A.; Ellis, Richard S.; Stark, Daniel P.; Richard, Johan; Zitrin, Adi; Auger, Matthew

    2016-04-01

    We discuss spatially resolved emission line spectroscopy secured for a total sample of 15 gravitationally lensed star-forming galaxies at a mean redshift of z≃ 2 based on Keck laser-assisted adaptive optics observations undertaken with the recently improved OSIRIS integral field unit (IFU) spectrograph. By exploiting gravitationally lensed sources drawn primarily from the CASSOWARY survey, we sample these sub-L{}* galaxies with source-plane resolutions of a few hundred parsecs ensuring well-sampled 2D velocity data and resolved variations in the gas-phase metallicity. Such high spatial resolution data offer a critical check on the structural properties of larger samples derived with coarser sampling using multiple-IFU instruments. We demonstrate how kinematic complexities essential to understanding the maturity of an early star-forming galaxy can often only be revealed with better sampled data. Although we include four sources from our earlier work, the present study provides a more representative sample unbiased with respect to emission line strength. Contrary to earlier suggestions, our data indicate a more diverse range of kinematic and metal gradient behavior inconsistent with a simple picture of well-ordered rotation developing concurrently with established steep metal gradients in all but merging systems. Comparing our observations with the predictions of hydrodynamical simulations suggests that gas and metals have been mixed by outflows or other strong feedback processes, flattening the metal gradients in early star-forming galaxies.

  8. 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.

  9. Adaptation Driven by Spatial Heterogeneities

    NASA Astrophysics Data System (ADS)

    Hermsen, Rutger

    2011-03-01

    Biological evolution and ecology are intimately linked, because the reproductive success or ``fitness'' of an organism depends crucially on its ecosystem. Yet, most models of evolution (or population genetics) consider homogeneous, fixed-size populations subjected to a constant selection pressure. To move one step beyond such ``mean field'' descriptions, we discuss stochastic models of evolution driven by spatial heterogeneity. We imagine a population whose range is limited by a spatially varying environmental parameter, such as a temperature or the concentration of an antibiotic drug. Individuals in the population replicate, die and migrate stochastically. Also, by mutation, they can adapt to the environmental stress and expand their range. This way, adaptation and niche expansion go hand in hand. This mode of evolution is qualitatively different from the usual notion of a population climbing a fitness gradient. We analytically calculate the rate of adaptation by solving a first passage time problem. Interestingly, the joint effects of reproduction, death, mutation and migration result in two distinct parameter regimes depending on the relative time scales of mutation and migration. We argue that the proposed scenario may be relevant for the rapid evolution of antibiotic resistance. This work was supported by the Center for Theoretical Biological Physics sponsored by the National Science Foundation (NSF) (Grant PHY-0822283).

  10. 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.

  11. 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. PMID:27154368

  12. 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.

  13. Adaptive Peer Sampling with Newscast

    NASA Astrophysics Data System (ADS)

    Tölgyesi, Norbert; Jelasity, Márk

    The peer sampling service is a middleware service that provides random samples from a large decentralized network to support gossip-based applications such as multicast, data aggregation and overlay topology management. Lightweight gossip-based implementations of the peer sampling service have been shown to provide good quality random sampling while also being extremely robust to many failure scenarios, including node churn and catastrophic failure. We identify two problems with these approaches. The first problem is related to message drop failures: if a node experiences a higher-than-average message drop rate then the probability of sampling this node in the network will decrease. The second problem is that the application layer at different nodes might request random samples at very different rates which can result in very poor random sampling especially at nodes with high request rates. We propose solutions for both problems. We focus on Newscast, a robust implementation of the peer sampling service. Our solution is based on simple extensions of the protocol and an adaptive self-control mechanism for its parameters, namely—without involving failure detectors—nodes passively monitor local protocol events using them as feedback for a local control loop for self-tuning the protocol parameters. The proposed solution is evaluated by simulation experiments.

  14. 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.

  15. 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 ...

  16. 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.

  17. Adaptive, template moderated, spatially varying statistical classification.

    PubMed

    Warfield, S K; Kaus, M; Jolesz, F A; Kikinis, R

    2000-03-01

    A novel image segmentation algorithm was developed to allow the automatic segmentation of both normal and abnormal anatomy from medical images. The new algorithm is a form of spatially varying statistical classification, in which an explicit anatomical template is used to moderate the segmentation obtained by statistical classification. The algorithm consists of an iterated sequence of spatially varying classification and nonlinear registration, which forms an adaptive, template moderated (ATM), spatially varying statistical classification (SVC). Classification methods and nonlinear registration methods are often complementary, both in the tasks where they succeed and in the tasks where they fail. By integrating these approaches the new algorithm avoids many of the disadvantages of each approach alone while exploiting the combination. The ATM SVC algorithm was applied to several segmentation problems, involving different image contrast mechanisms and different locations in the body. Segmentation and validation experiments were carried out for problems involving the quantification of normal anatomy (MRI of brains of neonates) and pathology of various types (MRI of patients with multiple sclerosis, MRI of patients with brain tumors, MRI of patients with damaged knee cartilage). In each case, the ATM SVC algorithm provided a better segmentation than statistical classification or elastic matching alone. PMID:10972320

  18. 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.

  19. 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.

  20. Adaptive video compressed sampling in the wavelet domain

    NASA Astrophysics Data System (ADS)

    Dai, Hui-dong; Gu, Guo-hua; He, Wei-ji; Chen, Qian; Mao, Tian-yi

    2016-07-01

    In this work, we propose a multiscale video acquisition framework called adaptive video compressed sampling (AVCS) that involves sparse sampling and motion estimation in the wavelet domain. Implementing a combination of a binary DMD and a single-pixel detector, AVCS acquires successively finer resolution sparse wavelet representations in moving regions directly based on extended wavelet trees, and alternately uses these representations to estimate the motion in the wavelet domain. Then, we can remove the spatial and temporal redundancies and provide a method to reconstruct video sequences from compressed measurements in real time. In addition, the proposed method allows adaptive control over the reconstructed video quality. The numerical simulation and experimental results indicate that AVCS performs better than the conventional CS-based methods at the same sampling rate even under the influence of noise, and the reconstruction time and measurements required can be significantly reduced.

  1. Spatial grid services for adaptive spatial query optimization

    NASA Astrophysics Data System (ADS)

    Gao, Bingbo; Xie, Chuanjie; Sheng, Wentao

    2008-10-01

    Spatial information sharing and integration has now become an important issue of Geographical Information Science (GIS). Web Service technologies provide a easy and standard way to share spatial resources over network, and grid technologies which aim at sharing resources such as data, storage, and computational powers can help the sharing go deeper. However, the dynamic characteristic of grid brings complexity to spatial query optimization which is more stressed in GIS domain because spatial operations are both CPU intensive and data intensive. To address this problem, a new grid framework is employed to provide standard spatial services which can also manage and report their state information to the coordinator which is responsible for distributed spatial query optimization.

  2. Adaptive importance sampling for network growth models

    PubMed Central

    Holmes, Susan P.

    2016-01-01

    Network Growth Models such as Preferential Attachment and Duplication/Divergence are popular generative models with which to study complex networks in biology, sociology, and computer science. However, analyzing them within the framework of model selection and statistical inference is often complicated and computationally difficult, particularly when comparing models that are not directly related or nested. In practice, ad hoc methods are often used with uncertain results. If possible, the use of standard likelihood-based statistical model selection techniques is desirable. With this in mind, we develop an Adaptive Importance Sampling algorithm for estimating likelihoods of Network Growth Models. We introduce the use of the classic Plackett-Luce model of rankings as a family of importance distributions. Updates to importance distributions are performed iteratively via the Cross-Entropy Method with an additional correction for degeneracy/over-fitting inspired by the Minimum Description Length principle. This correction can be applied to other estimation problems using the Cross-Entropy method for integration/approximate counting, and it provides an interpretation of Adaptive Importance Sampling as iterative model selection. Empirical results for the Preferential Attachment model are given, along with a comparison to an alternative established technique, Annealed Importance Sampling. PMID:27182098

  3. 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

  4. 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

  5. Determination and optimization of spatial samples for distributed measurements.

    SciTech Connect

    Huo, Xiaoming; Tran, Hy D.; Shilling, Katherine Meghan; Kim, Heeyong

    2010-10-01

    There are no accepted standards for determining how many measurements to take during part inspection or where to take them, or for assessing confidence in the evaluation of acceptance based on these measurements. The goal of this work was to develop a standard method for determining the number of measurements, together with the spatial distribution of measurements and the associated risks for false acceptance and false rejection. Two paths have been taken to create a standard method for selecting sampling points. A wavelet-based model has been developed to select measurement points and to determine confidence in the measurement after the points are taken. An adaptive sampling strategy has been studied to determine implementation feasibility on commercial measurement equipment. Results using both real and simulated data are presented for each of the paths.

  6. 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.

  7. The effect of spatial luminance distribution on dark adaptation.

    PubMed

    Stokkermans, Mariska G M; Vogels, Ingrid M L C; Heynderickx, Ingrid E J

    2016-06-01

    Recent studies show that dark adaptation in the visual system depends on local luminance levels surrounding the viewing direction. These studies, however, do not explain to what extent veiling luminance is responsible for the outcome. To address the latter, in this study dark adaptation was measured for three different spatial luminance distributions surrounding a target to be detected, while keeping the veiling luminance at the location of the target equivalent. The results show that a background with bright areas close to the viewing direction yields longer adaptation times than a background with bright areas at a larger visual angle. Therefore, we conclude that dark adaptation is affected to a great extent by local luminance, even when controlling for veiling luminance. Based on our results, a simple but adequate model is proposed to predict the adaptation luminance threshold for backgrounds having a nonuniform luminance distribution.

  8. Male superiority in spatial navigation: adaptation or side effect?

    PubMed

    Clint, Edward K; Sober, Elliott; Garland, Theodore; Rhodes, Justin S

    2012-12-01

    In the past few decades, sex differences in spatial cognition have often been attributed to adaptation in response to natural selection. A common explanation is that home range size differences between the sexes created different cognitive demands pertinent to wayfinding in each sex and resulted in the evolution of sex differences in spatial navigational ability in both humans and nonhuman mammals. However, the assumption of adaptation as the appropriate mode of explanation was nearly simultaneous with the discovery and subsequent verification of the male superiority effect, even without any substantive evidence establishing a causal role for adaptation. An alternate possibility that the sex difference in cognition is a genetic or hormonal side effect has not been rigorously tested using the comparative method. The present study directly evaluates how well the range hypothesis fits the available data on species differences in spatial ability by use of a phylogenetically based, cross-species, comparative analysis. We find no support for the hypothesis that species differences in home range size dimorphism are positively associated with parallel differences in spatial navigation abilities. The alternative hypothesis that sex differences in spatial cognition result as a hormonal side effect is better supported by the data.

  9. Application of adaptive cluster sampling to low-density populations of freshwater mussels

    USGS Publications Warehouse

    Smith, D.R.; Villella, R.F.; Lemarie, D.P.

    2003-01-01

    Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.

  10. Long-term efficacy of prism adaptation on spatial neglect: preliminary results on different spatial components.

    PubMed

    Rusconi, Maria Luisa; Carelli, Laura

    2012-01-01

    This study describes the long-term effectiveness on spatial neglect recovery of a 2-week treatment based on prism adaptation (PA). Seven right-brain-damaged patients affected by chronic neglect were evaluated before, after two weeks of the PA treatment and at a follow-up (variable between 8 and 30 months after the end of PA). Neglect evaluation was performed by means of BIT (conventional and behavioral), Fluff Test, and Comb and Razor Test. The results highlight an improvement, after the PA training, in both tasks performed using the hand trained in PA treatment and in behavioral tasks not requiring a manual motor response. Such effects extend, even if not significantly, to all BIT subtests. These results support previous findings, showing that PA improves neglect also on imagery tasks with no manual component, and provide further evidence for long-lasting efficacy of PA training. Dissociations have been found with regard to PA efficacy on peripersonal, personal, and representational neglect, visuospatial agraphia and neglect dyslexia. In particular, we found no significant differences between the pre-training and post-training PA session in personal neglect measures, and a poor recovery of neglect dyslexia after PA treatment. The recruitment of a larger sample could help to confirm the effectiveness of the prismatic lenses with regard to the different clinical manifestations of spatial neglect.

  11. Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes.

    PubMed

    Forester, Brenna R; Jones, Matthew R; Joost, Stéphane; Landguth, Erin L; Lasky, Jesse R

    2016-01-01

    The spatial structure of the environment (e.g. the configuration of habitat patches) may play an important role in determining the strength of local adaptation. However, previous studies of habitat heterogeneity and local adaptation have largely been limited to simple landscapes, which poorly represent the multiscale habitat structure common in nature. Here, we use simulations to pursue two goals: (i) we explore how landscape heterogeneity, dispersal ability and selection affect the strength of local adaptation, and (ii) we evaluate the performance of several genotype-environment association (GEA) methods for detecting loci involved in local adaptation. We found that the strength of local adaptation increased in spatially aggregated selection regimes, but remained strong in patchy landscapes when selection was moderate to strong. Weak selection resulted in weak local adaptation that was relatively unaffected by landscape heterogeneity. In general, the power of detection methods closely reflected levels of local adaptation. False-positive rates (FPRs), however, showed distinct differences across GEA methods based on levels of population structure. The univariate GEA approach had high FPRs (up to 55%) under limited dispersal scenarios, due to strong isolation by distance. By contrast, multivariate, ordination-based methods had uniformly low FPRs (0-2%), suggesting these approaches can effectively control for population structure. Specifically, constrained ordinations had the best balance of high detection and low FPRs and will be a useful addition to the GEA toolkit. Our results provide both theoretical and practical insights into the conditions that shape local adaptation and how these conditions impact our ability to detect selection.

  12. Prism adaptation for spatial neglect after stroke: translational practice gaps

    PubMed Central

    Barrett, A. M.; Goedert, Kelly M.; Basso, Julia C.

    2012-01-01

    Spatial neglect increases hospital morbidity and costs in around 50% of the 795,000 people per year in the USA who survive stroke, and an urgent need exists to reduce the care burden of this condition. However, effective acute treatment for neglect has been elusive. In this article, we review 48 studies of a treatment of intense neuroscience interest: prism adaptation training. Due to its effects on spatial motor ‘aiming’, prism adaptation training may act to reduce neglect-related disability. However, research failed, first, to suggest methods to identify the 50–75% of patients who respond to treatment; second, to measure short-term and long-term outcomes in both mechanism-specific and functionally valid ways; third, to confirm treatment utility during the critical first 8 weeks poststroke; and last, to base treatment protocols on systematic dose–response data. Thus, considerable investment in prism adaptation research has not yet touched the fundamentals needed for clinical implementation. We suggest improved standards and better spatial motor models for further research, so as to clarify when, how and for whom prism adaptation should be applied. PMID:22926312

  13. 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.

  14. Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.

    PubMed

    Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan

    2016-02-22

    We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved.

  15. 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.

  16. Temporal dark adaptation to spatially complex backgrounds: effect of an additional light source.

    PubMed

    Stokkermans, M G M; Heynderickx, I E J

    2014-07-01

    Visual adaptation (and especially dark adaptation) has been studied extensively in the past, however, mainly addressing adaptation to fully dark backgrounds. At this stage, it is unclear whether these results are not too simple to be applied to complex situations, such as predicting adaptation of a motorist driving at night. To fill this gap we set up a study investigating how spatially complex backgrounds influence temporal dark adaptation. Our results showed that dark adaptation to spatially complex backgrounds leads to much longer adaptation times than dark adaptation to spatially uniform backgrounds. We conclude therefore that the adaptation models based on past studies overestimate the visual system's sensitivity to detect luminance variations in spatially complex environments. Our results also showed large variations in adaptation times when varying the degree of spatial complexity of the background. Hence, we may conclude that it is important to take into account models that are based on spatially complex backgrounds when predicting dark adaptation for complex environments.

  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. Interocular transfer of spatial adaptation is weak at low spatial frequencies.

    PubMed

    Baker, Daniel H; Meese, Tim S

    2012-06-15

    Adapting one eye to a high contrast grating reduces sensitivity to similar target gratings shown to the same eye, and also to those shown to the opposite eye. According to the textbook account, interocular transfer (IOT) of adaptation is around 60% of the within-eye effect. However, most previous studies on this were limited to using high spatial frequencies, sustained presentation, and criterion-dependent methods for assessing threshold. Here, we measure IOT across a wide range of spatiotemporal frequencies, using a criterion-free 2AFC method. We find little or no IOT at low spatial frequencies, consistent with other recent observations. At higher spatial frequencies, IOT was present, but weaker than previously reported (around 35%, on average, at 8c/deg). Across all conditions, monocular adaptation raised thresholds by around a factor of 2, and observers showed normal binocular summation, demonstrating that they were not binocularly compromised. These findings prompt a reassessment of our understanding of the binocular architecture implied by interocular adaptation. In particular, the output of monocular channels may be available to perceptual decision making at low spatial frequencies.

  19. 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.

  20. 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

  1. Irregular and adaptive sampling for automatic geophysic measure systems

    NASA Astrophysics Data System (ADS)

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

    2000-07-01

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

  2. 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

  3. Effects of spatial scale of sampling on food web structure

    PubMed Central

    Wood, Spencer A; Russell, Roly; Hanson, Dieta; Williams, Richard J; Dunne, Jennifer A

    2015-01-01

    This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two-thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power-law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling. PMID:26380704

  4. 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.

  5. Spatial compression impairs prism adaptation in healthy individuals.

    PubMed

    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

  6. 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.

  7. 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.

  8. Contribution of Cerebellar Sensorimotor Adaptation to Hippocampal Spatial Memory

    PubMed Central

    Passot, Jean-Baptiste; Sheynikhovich, Denis; Duvelle, Éléonore; Arleo, Angelo

    2012-01-01

    Complementing its primary role in motor control, cerebellar learning has also a bottom-up influence on cognitive functions, where high-level representations build up from elementary sensorimotor memories. In this paper we examine the cerebellar contribution to both procedural and declarative components of spatial cognition. To do so, we model a functional interplay between the cerebellum and the hippocampal formation during goal-oriented navigation. We reinterpret and complete existing genetic behavioural observations by means of quantitative accounts that cross-link synaptic plasticity mechanisms, single cell and population coding properties, and behavioural responses. In contrast to earlier hypotheses positing only a purely procedural impact of cerebellar adaptation deficits, our results suggest a cerebellar involvement in high-level aspects of behaviour. In particular, we propose that cerebellar learning mechanisms may influence hippocampal place fields, by contributing to the path integration process. Our simulations predict differences in place-cell discharge properties between normal mice and L7-PKCI mutant mice lacking long-term depression at cerebellar parallel fibre-Purkinje cell synapses. On the behavioural level, these results suggest that, by influencing the accuracy of hippocampal spatial codes, cerebellar deficits may impact the exploration-exploitation balance during spatial navigation. PMID:22485133

  9. [Effects of spatial heterogeneity on spatial extrapolation of sampling plot data].

    PubMed

    Liang, Yu; He, Hong-Shi; Hu, Yuan-Man; Bu, Ren-Cang

    2012-01-01

    By using model combination method, this paper simulated the changes of response variable (tree species distribution area at landscape level under climate change) under three scenarios of environmental spatial heterogeneous level, analyzed the differentiation of simulated results under different scenarios, and discussed the effects of environmental spatial heterogeneity on the larger spatial extrapolation of the tree species responses to climate change observed in sampling plots. For most tree species, spatial heterogeneity had little effects on the extrapolation from plot scale to class scale; for the tree species insensitive to climate warming and the azonal species, spatial heterogeneity also had little effects on the extrapolation from plot-scale to zonal scale. By contrast, for the tree species sensitive to climate warming, spatial heterogeneity had effects on the extrapolation from plot scale to zonal scale, and the effects could be varied under different scenarios.

  10. Improving OFDR spatial resolution by reducing external clock sampling error

    NASA Astrophysics Data System (ADS)

    Feng, Bowen; Liu, Kun; Liu, Tiegen; Jiang, Junfeng; Du, Yang

    2016-03-01

    Utilizing an auxiliary interferometer to produce external clock signals as the data acquirement clock is widely used to compensate the nonlinearity of the tunable laser source (TLS) in optical frequency domain reflectometry (OFDR). However, this method is not always accurate because of the large optical length difference of both arms in the auxiliary interferometer. To investigate the deviation, we study the source and influence of the external clock sampling error in OFDR system. Based on the model, we find that the sampling error declines with the increase of the TLS's optical frequency tuning rate. The spatial resolution can be as high as 4.8 cm and the strain sensing location accuracy can be up to 0.15 m at the measurement length of 310 m under the minimum sampling error with the optical frequency tuning rate of 2500 GHz/s. Hence, the spatial resolution can be improved by reducing external clock sampling error in OFDR system.

  11. 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...

  12. 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...

  13. Adaptive importance sampling of random walks on continuous state spaces

    SciTech Connect

    Baggerly, K.; Cox, D.; Picard, R.

    1998-11-01

    The authors consider adaptive importance sampling for a random walk with scoring in a general state space. Conditions under which exponential convergence occurs to the zero-variance solution are reviewed. These results generalize previous work for finite, discrete state spaces in Kollman (1993) and in Kollman, Baggerly, Cox, and Picard (1996). This paper is intended for nonstatisticians and includes considerable explanatory material.

  14. Cooperation of a Dissatisfied Adaptive Prisoner's Dilemma in Spatial Structures

    NASA Astrophysics Data System (ADS)

    Zhang, Wen; Li, Yao-Sheng; Du, Peng; Xu, Chen

    2013-10-01

    We study the cooperative behavior of a dissatisfied adaptive prisoner's dilemma via a pair updating rule. We compare two kinds of relationship among the competing agents, one is the well-mixed population and the other is the two-dimensional square lattice. It is found that the cooperation emerges in both the cases and the frequency of cooperation is enhanced in the square lattice. Though it is impossible for the cooperators to have a higher average payoff than that of the defectors in the well-mixed case, the cooperators in the spatial square lattice could have higher average payoffs in certain regions of the game parameters. We theoretically analyze the well-mixed case exactly and the square lattice by pair approximation. The theoretic results are in agreement with the simulation data.

  15. 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

  16. 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).

  17. A review of minesoil sampling and spatial variability in Texas

    SciTech Connect

    Myers, J.C.; Brandt, J.E.; Joseph, W.L.

    1997-12-31

    Accurate characterization of minesoil overburden constituents associated with strip mining is an important part of the pre- and post-mine regulatory process. Characterization of soil material requires sampling of some kind, which implies that (1) the sample material selected must be representative of the area to be characterized, and (2) the sample volume (support), size (number of samples), and pattern must be able to support a reasonable decision making process. Therefore, the end use (baseline information, monitoring, or remediation) of this information should dictate the sampling approach; which in turn, is based on the decision to be made and the amount of uncertainty that is allowable. Uncertainties and errors are an integral part of the sampling, laboratory analysis, and spatial characterization processes, arising at each stage. Mathematical approaches such as sampling theory & practice and geostatistics can quantify the amount of error or uncertainty associated with the various stages of sampling, analysis and characterization, as well as distinguishing sampling errors from laboratory errors. These statistical tools can be used to manage errors and uncertainties at each stage of the process, providing confidence to (1) regulatory agencies that compliance has been achieved and (2) mining companies that unnecessary remedial costs will not be incurred. Statistical tools provide a framework for characterizing the wide variety of minesoil constituents and conditions encountered in mine operations. The use of statistically-defined monitoring or remedial decision units of a given area, for example, 5.7-acre grids in Texas, are shown to be consistent with the United States Protection Agency`s long-standing guidelines and recommendations for remedial activities. Site-specific variability must always be taken into account when designing a sampling program and caution is recommended in the selection of sampling methods (i.e. compositing versus discrete samples).

  18. 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

  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. Stochastic, Adaptive Sampling of Information by Microvilli in Fly Photoreceptors

    PubMed Central

    Song, Zhuoyi; Postma, Marten; Billings, Stephen A.; Coca, Daniel; Hardie, Roger C.; Juusola, Mikko

    2012-01-01

    Summary Background In fly photoreceptors, light is focused onto a photosensitive waveguide, the rhabdomere, consisting of tens of thousands of microvilli. Each microvillus is capable of generating elementary responses, quantum bumps, in response to single photons using a stochastically operating phototransduction cascade. Whereas much is known about the cascade reactions, less is known about how the concerted action of the microvilli population encodes light changes into neural information and how the ultrastructure and biochemical machinery of photoreceptors of flies and other insects evolved in relation to the information sampling and processing they perform. Results We generated biophysically realistic fly photoreceptor models, which accurately simulate the encoding of visual information. By comparing stochastic simulations with single cell recordings from Drosophila photoreceptors, we show how adaptive sampling by 30,000 microvilli captures the temporal structure of natural contrast changes. Following each bump, individual microvilli are rendered briefly (∼100–200 ms) refractory, thereby reducing quantum efficiency with increasing intensity. The refractory period opposes saturation, dynamically and stochastically adjusting availability of microvilli (bump production rate: sample rate), whereas intracellular calcium and voltage adapt bump amplitude and waveform (sample size). These adapting sampling principles result in robust encoding of natural light changes, which both approximates perceptual contrast constancy and enhances novel events under different light conditions, and predict information processing across a range of species with different visual ecologies. Conclusions These results clarify why fly photoreceptors are structured the way they are and function as they do, linking sensory information to sensory evolution and revealing benefits of stochasticity for neural information processing. PMID:22704990

  2. Adaptive spatial filtering for daytime satellite quantum key distribution

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    The rate of secure key generation (SKG) in quantum key distribution (QKD) is adversely affected by optical noise and loss in the quantum channel. In a free-space atmospheric channel, the scattering of sunlight into the channel can lead to quantum bit error ratios (QBERs) sufficiently large to preclude SKG. Furthermore, atmospheric turbulence limits the degree to which spatial filtering can reduce sky noise without introducing signal losses. A system simulation quantifies the potential benefit of tracking and higher-order adaptive optics (AO) technologies to SKG rates in a daytime satellite engagement scenario. The simulations are performed assuming propagation from a low-Earth orbit (LEO) satellite to a terrestrial receiver that includes an AO system comprised of a Shack-Hartmann wave-front sensor (SHWFS) and a continuous-face-sheet deformable mirror (DM). The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain waveoptics hardware emulator. Secure key generation rates are then calculated for the decoy state QKD protocol as a function of the receiver field of view (FOV) for various pointing angles. The results show that at FOVs smaller than previously considered, AO technologies can enhance SKG rates in daylight and even enable SKG where it would otherwise be prohibited as a consequence of either background optical noise or signal loss due to turbulence effects.

  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; 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 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. 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.

  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. 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

  9. 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

  10. 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. PMID:27058283

  11. 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.

  12. 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.

  13. 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

  14. 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.

  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. Effects of prism adaptation on motor-intentional spatial bias in neglect

    PubMed Central

    Fortis, Paola; Chen, Peii; Goedert, Kelly M.; Barrett, Anna M.

    2011-01-01

    Prism adaptation may alleviate some symptoms of spatial neglect. However, the mechanism through which this technique works is still unclear. The current study investigated whether prism adaptation differentially affects dysfunction in perceptual-attentional “where” versus motor-intentional “aiming” bias. Five neglect patients performed a line bisection task in which lines were viewed under both normal and right-left reversed viewing conditions, allowing for the fractionation of “where” and “aiming” spatial bias components. Following two consecutive days of prism adaptation, participants demonstrated a significant improvement in “aiming” spatial bias, with no effect on “where” spatial bias. These findings suggest that prism adaptation may primarily affect motor-intentional “aiming” bias in post-stroke spatial neglect patients. PMID:21817924

  17. How does spatial dispersal network affect the evolution of parasite local adaptation?

    PubMed

    Vogwill, Tom; Fenton, Andy; Brockhurst, Michael A

    2010-06-01

    Studying patterns of parasite local adaptation can provide insights into the spatiotemporal dynamics of host-parasite coevolution. Many factors, both biotic and abiotic, have been identified that influence parasite local adaptation. In particular, dispersal and population structuring are considered important determinants of local adaptation. We investigated how the shape of the spatial dispersal network within experimental landscapes affected local adaptation of a bacteriophage parasite to its bacterial host. Regardless of landscape topology, dispersal always led to the evolution of phages with broader infectivity range. However, when the spatial dispersal network resulted in spatial variation in the breadth of phage infectivity range, significant levels of parasite local adaptation and local maladaptation were detected within the same landscape using the local versus foreign definition of local adaptation. By contrast, local adaptation was not detected using the home versus away or local versus global definitions of local adaptation. This suggests that spatial dispersal networks may play an important role in driving parasite local adaptation, particularly when the shape of the dispersal network generates nonuniform levels of host resistance or parasite infectivity throughout a species' range. PMID:20050909

  18. Adaptive k-space sampling design for edge-enhanced DCE-MRI using compressed sensing.

    PubMed

    Raja, Rajikha; Sinha, Neelam

    2014-09-01

    The critical challenge in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the trade-off between spatial and temporal resolution due to the limited availability of acquisition time. To address this, it is imperative to under-sample k-space and to develop specific reconstruction techniques. Our proposed method reconstructs high-quality images from under-sampled dynamic k-space data by proposing two main improvements; i) design of an adaptive k-space sampling lattice and ii) edge-enhanced reconstruction technique. A high-resolution data set obtained before the start of the dynamic phase is utilized. The sampling pattern is designed to adapt to the nature of k-space energy distribution obtained from the static high-resolution data. For image reconstruction, the well-known compressed sensing-based total variation (TV) minimization constrained reconstruction scheme is utilized by incorporating the gradient information obtained from the static high-resolution data. The proposed method is tested on seven real dynamic time series consisting of 2 breast data sets and 5 abdomen data sets spanning 1196 images in all. For data availability of only 10%, performance improvement is seen across various quality metrics. Average improvements in Universal Image Quality Index and Structural Similarity Index Metric of up to 28% and 24% on breast data and about 17% and 9% on abdomen data, respectively, are obtained for the proposed method as against the baseline TV reconstruction with variable density random sampling pattern.

  19. Spatial considerations during cryopreservation of a large volume sample.

    PubMed

    Kilbride, Peter; Lamb, Stephen; Milne, Stuart; Gibbons, Stephanie; Erro, Eloy; Bundy, James; Selden, Clare; Fuller, Barry; Morris, John

    2016-08-01

    There have been relatively few studies on the implications of the physical conditions experienced by cells during large volume (litres) cryopreservation - most studies have focused on the problem of cryopreservation of smaller volumes, typically up to 2 ml. This study explores the effects of ice growth by progressive solidification, generally seen during larger scale cryopreservation, on encapsulated liver hepatocyte spheroids, and it develops a method to reliably sample different regions across the frozen cores of samples experiencing progressive solidification. These issues are examined in the context of a Bioartificial Liver Device which requires cryopreservation of a 2 L volume in a strict cylindrical geometry for optimal clinical delivery. Progressive solidification cannot be avoided in this arrangement. In such a system optimal cryoprotectant concentrations and cooling rates are known. However, applying these parameters to a large volume is challenging due to the thermal mass and subsequent thermal lag. The specific impact of this to the cryopreservation outcome is required. Under conditions of progressive solidification, the spatial location of Encapsulated Liver Spheroids had a strong impact on post-thaw recovery. Cells in areas first and last to solidify demonstrated significantly impaired post-thaw function, whereas areas solidifying through the majority of the process exhibited higher post-thaw outcome. It was also found that samples where the ice thawed more rapidly had greater post-thaw viability 24 h post-thaw (75.7 ± 3.9% and 62.0 ± 7.2% respectively). These findings have implications for the cryopreservation of large volumes with a rigid shape and for the cryopreservation of a Bioartificial Liver Device. PMID:27256662

  20. Orientation and spatial frequency selectivity of adaptation to color and luminance gratings.

    PubMed

    Bradley, A; Switkes, E; De Valois, K

    1988-01-01

    Prolonged viewing of sinusoidal luminance gratings produces elevated contrast detection thresholds for test gratings that are similar in spatial frequency and orientation to the adaptation stimulus. We have used this technique to investigate orientation and spatial frequency selectivity in the processing of color contrast information. Adaptation to isoluminant red-green gratings produces elevated color contrast thresholds that are selective for grating orientation and spatial frequency. Only small elevations in color contrast thresholds occur after adaptation to luminance gratings, and vice versa. Although the color adaptation effects appear slightly less selective than those for luminance, our results suggest similar spatial processing of color and luminance contrast patterns by early stages of the human visual system.

  1. 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.

  2. Large sample hydrology in NZ: Spatial organisation in process diagnostics

    NASA Astrophysics Data System (ADS)

    McMillan, H. K.; Woods, R. A.; Clark, M. P.

    2013-12-01

    A key question in hydrology is how to predict the dominant runoff generation processes in any given catchment. This knowledge is vital for a range of applications in forecasting hydrological response and related processes such as nutrient and sediment transport. A step towards this goal is to map dominant processes in locations where data is available. In this presentation, we use data from 900 flow gauging stations and 680 rain gauges in New Zealand, to assess hydrological processes. These catchments range in character from rolling pasture, to alluvial plains, to temperate rainforest, to volcanic areas. By taking advantage of so many flow regimes, we harness the benefits of large-sample and comparative hydrology to study patterns and spatial organisation in runoff processes, and their relationship to physical catchment characteristics. The approach we use to assess hydrological processes is based on the concept of diagnostic signatures. Diagnostic signatures in hydrology are targeted analyses of measured data which allow us to investigate specific aspects of catchment response. We apply signatures which target the water balance, the flood response and the recession behaviour. We explore the organisation, similarity and diversity in hydrological processes across the New Zealand landscape, and how these patterns change with scale. We discuss our findings in the context of the strong hydro-climatic gradients in New Zealand, and consider the implications for hydrological model building on a national scale.

  3. 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.

  4. 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

  5. Aging and luminance-adaptation effects on spatial contrast sensitivity.

    PubMed

    Sloane, M E; Owsley, C; Jackson, C A

    1988-12-01

    Contrast sensitivity as a function of target luminance for four spatial frequencies (0.5, 2, 4, and 8 cycles/deg) was measured in younger (n = 12; age range, 19-35 years) and older (n = 11; age range, 68-79 years) adults in order to examine the feasibility of optical and neural explanations for the impairment of contrast sensitivity in older adults. All subjects were free from identifiable ocular disease and had good acuity. Sensitivity for each spatial frequency was measured at eight luminance levels spanning 3.5 log units in the photopic-mesopic range. When gratings were flickered at 0.5 Hz, functions for older adults were displaced downward on the sensitivity axis across all luminance levels, and the slopes of these functions were steeper than those for younger adults, suggesting that optical mechanisms alone cannot account for the vision loss in older adults. Further measurements, in which spatial targets were flickered at 7.5 Hz, indicated that this faster temporal modulation affected sensitivity as a function of luminance differentially in younger and older adults. These data imply that the neural mechanisms subserving human spatial vision undergo significant changes during adulthood.

  6. The Impact of Spatial Structure on Viral Genomic Diversity Generated during Adaptation to Thermal Stress

    PubMed Central

    Ally, Dilara; Wiss, Valorie R.; Deckert, Gail E.; Green, Danielle; Roychoudhury, Pavitra; Wichman, Holly A.; Brown, Celeste J.; Krone, Stephen M.

    2014-01-01

    Background Most clinical and natural microbial communities live and evolve in spatially structured environments. When changes in environmental conditions trigger evolutionary responses, spatial structure can impact the types of adaptive response and the extent to which they spread. In particular, localized competition in a spatial landscape can lead to the emergence of a larger number of different adaptive trajectories than would be found in well-mixed populations. Our goal was to determine how two levels of spatial structure affect genomic diversity in a population and how this diversity is manifested spatially. Methodology/Principal Findings We serially transferred bacteriophage populations growing at high temperatures (40°C) on agar plates for 550 generations at two levels of spatial structure. The level of spatial structure was determined by whether the physical locations of the phage subsamples were preserved or disrupted at each passage to fresh bacterial host populations. When spatial structure of the phage populations was preserved, there was significantly greater diversity on a global scale with restricted and patchy distribution. When spatial structure was disrupted with passaging to fresh hosts, beneficial mutants were spread across the entire plate. This resulted in reduced diversity, possibly due to clonal interference as the most fit mutants entered into competition on a global scale. Almost all substitutions present at the end of the adaptation in the populations with disrupted spatial structure were also present in the populations with structure preserved. Conclusions/Significance Our results are consistent with the patchy nature of the spread of adaptive mutants in a spatial landscape. Spatial structure enhances diversity and slows fixation of beneficial mutants. This added diversity could be beneficial in fluctuating environments. We also connect observed substitutions and their effects on fitness to aspects of phage biology, and we provide

  7. An efficient sampling algorithm with adaptations for Bayesian variable selection.

    PubMed

    Araki, Takamitsu; Ikeda, Kazushi; Akaho, Shotaro

    2015-01-01

    In Bayesian variable selection, indicator model selection (IMS) is a class of well-known sampling algorithms, which has been used in various models. The IMS is a class of methods that uses pseudo-priors and it contains specific methods such as Gibbs variable selection (GVS) and Kuo and Mallick's (KM) method. However, the efficiency of the IMS strongly depends on the parameters of a proposal distribution and the pseudo-priors. Specifically, the GVS determines their parameters based on a pilot run for a full model and the KM method sets their parameters as those of priors, which often leads to slow mixings of them. In this paper, we propose an algorithm that adapts the parameters of the IMS during running. The parameters obtained on the fly provide an appropriate proposal distribution and pseudo-priors, which improve the mixing of the algorithm. We also prove the convergence theorem of the proposed algorithm, and confirm that the algorithm is more efficient than the conventional algorithms by experiments of the Bayesian variable selection.

  8. Poststroke Hemiparesis Impairs the Rate but not Magnitude of Adaptation of Spatial and Temporal Locomotor Features

    PubMed Central

    Savin, Douglas N.; Tseng, Shih-Chiao; Whitall, Jill; Morton, Susanne M.

    2015-01-01

    Background Persons with stroke and hemiparesis walk with a characteristic pattern of spatial and temporal asymmetry that is resistant to most traditional interventions. It was recently shown in nondisabled persons that the degree of walking symmetry can be readily altered via locomotor adaptation. However, it is unclear whether stroke-related brain damage affects the ability to adapt spatial or temporal gait symmetry. Objective Determine whether locomotor adaptation to a novel swing phase perturbation is impaired in persons with chronic stroke and hemiparesis. Methods Participants with ischemic stroke (14) and nondisabled controls (12) walked on a treadmill before, during, and after adaptation to a unilateral perturbing weight that resisted forward leg movement. Leg kinematics were measured bilaterally, including step length and single-limb support (SLS) time symmetry, limb angle center of oscillation, and interlimb phasing, and magnitude of “initial” and “late” locomotor adaptation rates were determined. Results All participants had similar magnitudes of adaptation and similar initial adaptation rates both spatially and temporally. All 14 participants with stroke and baseline asymmetry temporarily walked with improved SLS time symmetry after adaptation. However, late adaptation rates poststroke were decreased (took more strides to achieve adaptation) compared with controls. Conclusions Mild to moderate hemiparesis does not interfere with the initial acquisition of novel symmetrical gait patterns in both the spatial and temporal domains, though it does disrupt the rate at which “late” adaptive changes are produced. Impairment of the late, slow phase of learning may be an important rehabilitation consideration in this patient population. PMID:22367915

  9. 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.

  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. 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

  12. 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.

  13. 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

  14. 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.

  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. 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.

  17. Smart adaptive optic systems using spatial light modulators.

    PubMed

    Clark, N; Banish, M; Ranganath, H S

    1999-01-01

    Many factors contribute to the aberrations induced in an optical system. Atmospheric turbulence between the object and the imaging system, physical or thermal perturbations in optical elements degrade the system's point spread function, and misaligned optics are the primary sources of aberrations that affect image quality. The design of a nonconventional real-time adaptive optic system using a micro-mirror device for wavefront correction is presented. The unconventional compensated imaging system presented offers advantages in speed, cost, power consumption, and weight. A pulsed-coupled neural network is used to as a preprocessor to enhance the performance of the wavefront sensor for low-light applications. Modeling results that characterize the system performance are presented. PMID:18252558

  18. A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables.

    PubMed

    Brus, D J; de Gruijter, J J

    2003-04-01

    In estimating spatial means of environmental variables of a region from data collected by convenience or purposive sampling, validity of the results can be ensured by collecting additional data through probability sampling. The precision of the pi estimator that uses the probability sample can be increased by interpolating the values at the nonprobability sample points to the probability sample points, and using these interpolated values as an auxiliary variable in the difference or regression estimator. These estimators are (approximately) unbiased, even when the nonprobability sample is severely biased such as in preferential samples. The gain in precision compared to the pi estimator in combination with Simple Random Sampling is controlled by the correlation between the target variable and interpolated variable. This correlation is determined by the size (density) and spatial coverage of the nonprobability sample, and the spatial continuity of the target variable. In a case study the average ratio of the variances of the simple regression estimator and pi estimator was 0.68 for preferential samples of size 150 with moderate spatial clustering, and 0.80 for preferential samples of similar size with strong spatial clustering. In the latter case the simple regression estimator was substantially more precise than the simple difference estimator.

  19. Bayesian symmetrical EEG/fMRI fusion with spatially adaptive priors

    PubMed Central

    Luessi, Martin; Babacan, S. Derin; Molina, Rafael; Booth, James R.; Katsaggelos, Aggelos K.

    2011-01-01

    In this paper, we propose a novel symmetrical EEG/fMRI fusion method which combines EEG and fMRI by means of a common generative model. We use a total variation (TV) prior to model the spatial distribution of the cortical current responses and hemodynamic response functions, and utilize spatially adaptive temporal priors to model their temporal shapes. The spatial adaptivity of the prior model allows for adaptation to the local characteristics of the estimated responses and leads to high estimation performance for the cortical current distribution and the hemodynamic response functions. We utilize a Bayesian formulation with a variational Bayesian framework and obtain a fully automatic fusion algorithm. Simulations with synthetic data and experiments with real data from a multimodal study on face perception demonstrate the performance of the proposed method. PMID:21130173

  20. Adaptive spatial combining for passive time-reversed communications.

    PubMed

    Gomes, João; Silva, António; Jesus, Sérgio

    2008-08-01

    Passive time reversal has aroused considerable interest in underwater communications as a computationally inexpensive means of mitigating the intersymbol interference introduced by the channel using a receiver array. In this paper the basic technique is extended by adaptively weighting sensor contributions to partially compensate for degraded focusing due to mismatch between the assumed and actual medium impulse responses. Two algorithms are proposed, one of which restores constructive interference between sensors, and the other one minimizes the output residual as in widely used equalization schemes. These are compared with plain time reversal and variants that employ postequalization and channel tracking. They are shown to improve the residual error and temporal stability of basic time reversal with very little added complexity. Results are presented for data collected in a passive time-reversal experiment that was conducted during the MREA'04 sea trial. In that experiment a single acoustic projector generated a 24-PSK (phase-shift keyed) stream at 200400 baud, modulated at 3.6 kHz, and received at a range of about 2 km on a sparse vertical array with eight hydrophones. The data were found to exhibit significant Doppler scaling, and a resampling-based preprocessing method is also proposed here to compensate for that scaling.

  1. 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

  2. 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. PMID:27606592

  3. 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.

  4. Simultaneous sample and spatial coherence characterisation using diffractive imaging

    NASA Astrophysics Data System (ADS)

    Clark, Jesse N.; Peele, Andrew G.

    2011-10-01

    We demonstrate an algorithm that reconstructs the complex transmission function of an object from experimental X-ray diffraction data using partially coherent 1.4 keV X-rays that does not require a priori input of the coherence function. The quality of the reconstruction is significantly better than that obtained by assuming that the illumination is fully coherent. Our approach can be readily applied to diffraction imaging problems where a model for the spatial coherence can be assumed.

  5. Spatial frequency analysis of anisotropic drug transport in tumor samples

    PubMed Central

    Russell, Stewart; Samkoe, Kimberley S.; Gunn, Jason R.; Hoopes, P. Jack; Nguyen, Thienan A.; Russell, Milo J.; Alfano, Robert R.; Pogue, Brian W.

    2014-01-01

    Abstract. Directional Fourier spatial frequency analysis was used on standard histological sections to identify salient directional bias in the spatial frequencies of stromal and epithelial patterns within tumor tissue. This directional bias is shown to be correlated to the pathway of reduced fluorescent tracer transport. Optical images of tumor specimens contain a complex distribution of randomly oriented aperiodic features used for neoplastic grading that varies with tumor type, size, and morphology. The internal organization of these patterns in frequency space is shown to provide a precise fingerprint of the extracellular matrix complexity, which is well known to be related to the movement of drugs and nanoparticles into the parenchyma, thereby identifying the characteristic spatial frequencies of regions that inhibit drug transport. The innovative computational methodology and tissue validation techniques presented here provide a tool for future investigation of drug and particle transport in tumor tissues, and could potentially be used a priori to identify barriers to transport, and to analyze real-time monitoring of transport with respect to therapeutic intervention. PMID:24395585

  6. 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.

  7. 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.

  8. Analysis of SWOT spatial and temporal samplings over continents

    NASA Astrophysics Data System (ADS)

    Biancamaria, Sylvain; Lamy, Alain; Mognard, Nelly

    2014-05-01

    The future Surface Water and Ocean Topography (SWOT) satellite mission, collaboratively developed by NASA, CNES and CSA, is a joint oceanography/continental hydrology mission planned for launch in 2020. In June 2013, a new SWOT orbit has been selected with a 77.6° inclination, a 21 days repeat cycle and a 891 km altitude. The main satellite payload (a Ka-band SAR Interferometer), will provide 2D maps of water elevation, mask and slope over two swaths, both having a 50 km extent. These two swaths will be separated by a 20 km nadir gap. Most of the studies concerning SWOT published since 2007 have considered a former orbit with a 78° inclination, 22 day repeat orbit and a 970 km altitude and a 60 km extent for each swath. None of them have studied the newly selected orbit and the impact of the 20 km nadir gap on the spatial coverage has not been much explored. The purpose of the work presented here is to investigate the spatial and temporal coverage given this new orbit and the actual swath extent (2*50 km swaths with the 20 km nadir gap in between) and compare it to the former SWOT configuration. It is shown that the new configuration will have almost no impact on the computation of monthly averages, however it will impact the spatial coverage. Because of the nadir gap, the orbit repeatitivity and the swaths extent, 3.6% of the continental surfaces in between 78°S and 78°N will never be observed by SWOT (which was previously equal to 2.2% with the former SWOT configuration). The equatorial regions will be the most impacted, as uncovered area could go up to ~14% locally, whereas it never exceeded 9% with the previous SWOT configuration.

  9. 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.

  10. 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. PMID:20555963

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

    DOE PAGES

    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,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

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Deployment of spatial attention without moving the eyes is boosted by oculomotor adaptation

    PubMed Central

    Habchi, Ouazna; Rey, Elodie; Mathieu, Romain; Urquizar, Christian; Farnè, Alessandro; Pélisson, Denis

    2015-01-01

    Vertebrates developed sophisticated solutions to select environmental visual information, being capable of moving attention without moving the eyes. A large body of behavioral and neuroimaging studies indicate a tight coupling between eye movements and spatial attention. The nature of this link, however, remains highly debated. Here, we demonstrate that deployment of human covert attention, measured in stationary eye conditions, can be boosted across space by changing the size of ocular saccades to a single position via a specific adaptation paradigm. These findings indicate that spatial attention is more widely affected by oculomotor plasticity than previously thought. PMID:26300755

  18. Application of adaptive optics in complicated and integrated spatial multisensor system and its measurement analysis

    NASA Astrophysics Data System (ADS)

    Ding, Quanxin; Guo, Chunjie; Cai, Meng; Liu, Hua

    2007-12-01

    Adaptive Optics Expand System is a kind of new concept spatial equipment, which concerns system, cybernetics and informatics deeply, and is key way to improve advanced sensors ability. Traditional Zernike Phase Contrast Method is developed, and Accelerated High-level Phase Contrast Theory is established. Integration theory and mathematical simulation is achieved. Such Equipment, which is based on some crucial components, such as, core optical system, multi mode wavefront sensor and so on, is established for AOES advantageous configuration and global design. Studies on Complicated Spatial Multisensor System Integratation and measurement Analysis including error analysis are carried out.

  19. Cognitive adaptation: spatial memory or attentional processing. a comment on Furley and Memmert (2010).

    PubMed

    Allen, R; Fioratou, E; McGeorge, P

    2011-02-01

    This commentary considers the paper by Furley and Memmert (2010) who sought to test the respective validities of the specific processing and cognitive adaptation hypotheses. That they found no evidence of a difference between experienced basketball players and nonathletes on the Corsi block task, a measure of spatial memory, led them to infer support for the specific processing hypothesis, namely that differences between experts and novices manifest themselves only in processes related specifically to the domain of expertise. An alternative interpretation is offered, indicating possible confounds and referring to recent research that suggests Corsi block and dynamic spatial tasks depend upon different neuronal networks.

  20. A stochastic optimization method to estimate the spatial distribution of a pathogen from a sample.

    PubMed

    Parnell, S; Gottwald, T R; Irey, M S; Luo, W; van den Bosch, F

    2011-10-01

    Information on the spatial distribution of plant disease can be utilized to implement efficient and spatially targeted disease management interventions. We present a pathogen-generic method to estimate the spatial distribution of a plant pathogen using a stochastic optimization process which is epidemiologically motivated. Based on an initial sample, the method simulates the individual spread processes of a pathogen between patches of host to generate optimized spatial distribution maps. The method was tested on data sets of Huanglongbing of citrus and was compared with a kriging method from the field of geostatistics using the well-established kappa statistic to quantify map accuracy. Our method produced accurate maps of disease distribution with kappa values as high as 0.46 and was able to outperform the kriging method across a range of sample sizes based on the kappa statistic. As expected, map accuracy improved with sample size but there was a high amount of variation between different random sample placements (i.e., the spatial distribution of samples). This highlights the importance of sample placement on the ability to estimate the spatial distribution of a plant pathogen and we thus conclude that further research into sampling design and its effect on the ability to estimate disease distribution is necessary. PMID:21916625

  1. 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.

  2. Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

    NASA Technical Reports Server (NTRS)

    Mcgwire, K.; Friedl, M.; Estes, J. E.

    1993-01-01

    This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

  3. [Spatial Heterogeneity of Soil Respiration in a Larch Plantation of North China at Different Sampling Scales].

    PubMed

    Yan, Jun-xia; Liang, Ya-nan; Li, Hong-jian; Li, Jun-jian

    2015-12-01

    Based on observations of soil respiration rate (Rs) and both biotic and abiotic factors in Pangquangou Nature Reserve at three sampling scales (4, 2, and 1 m), we studied the spatial heterogeneity of Rs and the factors, and analyzed impacts of soil temperature at the 5, 10 and 15 cm depth (T5, T10, T15), soil moisture over the depth of 0-10 cm (Ws), and soil total nitrogen (N), soil total organic carbon (C), ratio of carbon and nitrogen (C/N), soil total sulfur (S), litter fall mass (Lw) and litter fall moisture (Lm) on the spatial heterogeneity of Rs, respectively. We also calculated the minimum sampling number of all the factors at different confidence levels and under the responding estimation accuracy. The results showed that: (1) the spatial heterogeneity of C/N at 4 m sampling scale, Ws at 2 m sampling scale and T10, T15 at 1 m sampling scale had low variability, while the spatial variation of Rs and other related factors had medium variability. Coefficients of variation of Rs, C/N and S decreased with the increase of the sampling scales, but those of N, C, Ws, T₅, T₁₀, T₁₅, Lw and Lm showed contrary trend; (2) the spatial autocorrelation of Rs, Ws, T₅, T₁₀, T₁₅, Lw and Lm decreased with the decrease of sampling scales but the spatial autocorrelation of C, N, C/N increased with the decrease of sampling scales, and the spatial autocorrelation of S decreased with the decrease of the sampling scales at initial stage and then increased; (3) the key factors that influenced the spatial heterogeneity of soil respiration were different at different sampling scales. Soil temperature was the key factor influencing the spatial heterogeneity of Rs at a larger scale. However, at a smaller scale, the spatial heterogeneity of Rs was influenced by C, Lw and Lm; (4) the minimum sampling number for soil respiration measurement and its influencing factors reduced greatly with the decrease of confidence level and responding estimation accuracy. The sampling

  4. [Spatial Heterogeneity of Soil Respiration in a Larch Plantation of North China at Different Sampling Scales].

    PubMed

    Yan, Jun-xia; Liang, Ya-nan; Li, Hong-jian; Li, Jun-jian

    2015-12-01

    Based on observations of soil respiration rate (Rs) and both biotic and abiotic factors in Pangquangou Nature Reserve at three sampling scales (4, 2, and 1 m), we studied the spatial heterogeneity of Rs and the factors, and analyzed impacts of soil temperature at the 5, 10 and 15 cm depth (T5, T10, T15), soil moisture over the depth of 0-10 cm (Ws), and soil total nitrogen (N), soil total organic carbon (C), ratio of carbon and nitrogen (C/N), soil total sulfur (S), litter fall mass (Lw) and litter fall moisture (Lm) on the spatial heterogeneity of Rs, respectively. We also calculated the minimum sampling number of all the factors at different confidence levels and under the responding estimation accuracy. The results showed that: (1) the spatial heterogeneity of C/N at 4 m sampling scale, Ws at 2 m sampling scale and T10, T15 at 1 m sampling scale had low variability, while the spatial variation of Rs and other related factors had medium variability. Coefficients of variation of Rs, C/N and S decreased with the increase of the sampling scales, but those of N, C, Ws, T₅, T₁₀, T₁₅, Lw and Lm showed contrary trend; (2) the spatial autocorrelation of Rs, Ws, T₅, T₁₀, T₁₅, Lw and Lm decreased with the decrease of sampling scales but the spatial autocorrelation of C, N, C/N increased with the decrease of sampling scales, and the spatial autocorrelation of S decreased with the decrease of the sampling scales at initial stage and then increased; (3) the key factors that influenced the spatial heterogeneity of soil respiration were different at different sampling scales. Soil temperature was the key factor influencing the spatial heterogeneity of Rs at a larger scale. However, at a smaller scale, the spatial heterogeneity of Rs was influenced by C, Lw and Lm; (4) the minimum sampling number for soil respiration measurement and its influencing factors reduced greatly with the decrease of confidence level and responding estimation accuracy. The sampling

  5. 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

  6. Pre-Surgical fMRI Data Analysis Using a Spatially Adaptive Conditionally Autoregressive Model

    PubMed Central

    Liu, Zhuqing; Berrocal, Veronica J.; Bartsch, Andreas J.; Johnson, Timothy D.

    2015-01-01

    Spatial smoothing is an essential step in the analysis of functional magnetic resonance imaging (fMRI) data. One standard smoothing method is to convolve the image data with a three-dimensional Gaussian kernel that applies a fixed amount of smoothing to the entire image. In pre-surgical brain image analysis where spatial accuracy is paramount, this method, however, is not reasonable as it can blur the boundaries between activated and deactivated regions of the brain. Moreover, while in a standard fMRI analysis strict false positive control is desired, for pre-surgical planning false negatives are of greater concern. To this end, we propose a novel spatially adaptive conditionally autoregressive model with variances in the full conditional of the means that are proportional to error variances, allowing the degree of smoothing to vary across the brain. Additionally, we present a new loss function that allows for the asymmetric treatment of false positives and false negatives. We compare our proposed model with two existing spatially adaptive conditionally autoregressive models. Simulation studies show that our model outperforms these other models; as a real model application, we apply the proposed model to the pre-surgical fMRI data of two patients to assess peri- and intra-tumoral brain activity. PMID:27042244

  7. 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. PMID:27380070

  8. 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.

  9. Using hierarchical sampling to understand scales of spatial variation in early coral recruitment

    NASA Astrophysics Data System (ADS)

    O'Leary, J. K.; Potts, D. C.

    2011-12-01

    Ecological patterns are created by processes acting over multiple spatial and temporal scales. By combining spatially explicit sampling with variance components models, the relative importance of spatial scale to overall variability can be determined. We used a spatially structured experimental design in the Mombasa Marine National Park in Kenya to quantify variation in coral recruitment across four spatial scales (~1-1,000 m) and to generate hypotheses about processes affecting recruitment and potential sources of post-settlement mortality during early life history. For the dominant recruiting corals ( Pocillopora spp.), variation in recruitment on surfaces protected from fish grazing was greatest at the largest spatial scale examined (1,000 m). We hypothesize that recruitment on protected surfaces varies mainly with larval delivery due to different lagoonal circulation and water flow between sites. Conversely, variation on surfaces exposed to fishes was greatest at the smallest spatial scale (1 m). We hypothesize that recruitment on exposed surfaces mainly reflects local differences in the scale and intensity of fish grazing, which may obscure larval delivery patterns. Spatial variation in recruitment can affect many ecological processes and factors, including growth, survival to maturity, the distribution of habitat, and variation in species interaction strengths. This study demonstrates how spatially explicit sampling, followed by variance components modeling to partition variance across scales, can help to identify potential drivers of patterns at each relevant scale.

  10. 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. PMID:25527435

  11. 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

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

    DOE PAGES

    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 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

  13. 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.

  14. Human Topological Task Adapted for Rats: Spatial Information Processes of the Parietal Cortex

    PubMed Central

    Goodrich-Hunsaker, Naomi J.; Howard, Brian P.; Hunsaker, Michael R.; Kesner, Raymond P.

    2008-01-01

    Human research has shown that lesions of the parietal cortex disrupt spatial information processing, specifically topological information. Similar findings have been found in nonhumans. It has been difficult to determine homologies between human and non-human mnemonic mechanisms for spatial information processing because methodologies and neuropathology differ. The first objective of the present study was to adapt a previously established human task for rats. The second objective was to better characterize the role of parietal cortex (PC) and dorsal hippocampus (dHPC) for topological spatial information processing. Rats had to distinguish whether a ball inside a ring or a ball outside a ring was the correct, rewarded object. After rats reached criterion on the task (>95%) they were randomly assigned to a lesion group (control, PC, dHPC). Animals were then re-tested. Post-surgery data show that controls were 94% correct on average, dHPC rats were 89% correct on average, and PC rats were 56% correct on average. The results from the present study suggest that the parietal cortex, but not the dHPC processes topological spatial information. The present data are the first to support comparable topological spatial information processes of the parietal cortex in humans and rats. PMID:18571941

  15. 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

  16. Prism adaptation and spatial neglect: the need for dose-finding studies

    PubMed Central

    Goedert, Kelly M.; Zhang, Jeffrey Y.; Barrett, A. M.

    2015-01-01

    Spatial neglect is a devastating disorder in 50–70% of right-brain stroke survivors, who have problems attending to, or making movements towards, left-sided stimuli, and experience a high risk of chronic dependence. Prism adaptation is a promising treatment for neglect that involves brief, daily visuo-motor training sessions while wearing optical prisms. Its benefits extend to functional behaviors such as dressing, with effects lasting 6 months or longer. Because one to two sessions of prism adaptation induce adaptive changes in both spatial-motor behavior (Fortis et al., 2011) and brain function (Saj et al., 2013), it is possible stroke patients may benefit from treatment periods shorter than the standard, intensive protocol of ten sessions over two weeks—a protocol that is impractical for either US inpatient or outpatient rehabilitation. Demonstrating the effectiveness of a lower dose will maximize the availability of neglect treatment. We present preliminary data suggesting that four to six sessions of prism treatment may induce a large treatment effect, maintained three to four weeks post-treatment. We call for a systematic, randomized clinical trial to establish the minimal effective dose suitable for stroke intervention. PMID:25983688

  17. 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

  18. 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,…

  19. A robust adaptive sampling method for faster acquisition of MR images.

    PubMed

    Vellagoundar, Jaganathan; Machireddy, Ramasubba Reddy

    2015-06-01

    A robust adaptive k-space sampling method is proposed for faster acquisition and reconstruction of MR images. In this method, undersampling patterns are generated based on magnitude profile of a fully acquired 2-D k-space data. Images are reconstructed using compressive sampling reconstruction algorithm. Simulation experiments are done to assess the performance of the proposed method under various signal-to-noise ratio (SNR) levels. The performance of the method is better than non-adaptive variable density sampling method when k-space SNR is greater than 10dB. The method is implemented on a fully acquired multi-slice raw k-space data and a quality assurance phantom data. Data reduction of up to 60% is achieved in the multi-slice imaging data and 75% is achieved in the phantom imaging data. The results show that reconstruction accuracy is improved over non-adaptive or conventional variable density sampling method. The proposed sampling method is signal dependent and the estimation of sampling locations is robust to noise. As a result, it eliminates the necessity of mathematical model and parameter tuning to compute k-space sampling patterns as required in non-adaptive sampling methods.

  20. Building blocks for developing spatial skills: evidence from a large, representative U.S. sample.

    PubMed

    Jirout, Jamie J; Newcombe, Nora S

    2015-03-01

    There is evidence suggesting that children's play with spatial toys (e.g., puzzles and blocks) correlates with spatial development. Females play less with spatial toys than do males, which arguably accounts for males' spatial advantages; children with high socioeconomic status (SES) also show an advantage, though SES-related differences in spatial play have been less studied than gender-related differences. Using a large, nationally representative sample from the standardization study of the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition, and controlling for other cognitive abilities, we observed a specific relation between parent-reported frequency of spatial play and Block Design scores that was invariant across gender and SES. Reported spatial play was higher for boys than for girls, but controlling for spatial play did not eliminate boys' relative advantage on this subtest. SES groups did not differ in reported frequency of spatial play. Future research should consider quality as well as quantity of play, and should explore underlying mechanisms to evaluate causality.

  1. Building blocks for developing spatial skills: evidence from a large, representative U.S. sample.

    PubMed

    Jirout, Jamie J; Newcombe, Nora S

    2015-03-01

    There is evidence suggesting that children's play with spatial toys (e.g., puzzles and blocks) correlates with spatial development. Females play less with spatial toys than do males, which arguably accounts for males' spatial advantages; children with high socioeconomic status (SES) also show an advantage, though SES-related differences in spatial play have been less studied than gender-related differences. Using a large, nationally representative sample from the standardization study of the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition, and controlling for other cognitive abilities, we observed a specific relation between parent-reported frequency of spatial play and Block Design scores that was invariant across gender and SES. Reported spatial play was higher for boys than for girls, but controlling for spatial play did not eliminate boys' relative advantage on this subtest. SES groups did not differ in reported frequency of spatial play. Future research should consider quality as well as quantity of play, and should explore underlying mechanisms to evaluate causality. PMID:25626442

  2. 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

  3. 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

  4. Spatial sampling considerations of the CERES (Clouds and Earth Radiant Energy System) instrument

    NASA Astrophysics Data System (ADS)

    Smith, G. L.; Manalo-Smith, Natividdad; Priestley, Kory

    2014-10-01

    The CERES (Clouds and Earth Radiant Energy System) instrument is a scanning radiometer with three channels for measuring Earth radiation budget. At present CERES models are operating aboard the Terra, Aqua and Suomi/NPP spacecraft and flights of CERES instruments are planned for the JPSS-1 spacecraft and its successors. CERES scans from one limb of the Earth to the other and back. The footprint size grows with distance from nadir simply due to geometry so that the size of the smallest features which can be resolved from the data increases and spatial sampling errors increase with nadir angle. This paper presents an analysis of the effect of nadir angle on spatial sampling errors of the CERES instrument. The analysis performed in the Fourier domain. Spatial sampling errors are created by smoothing of features which are the size of the footprint and smaller, or blurring, and inadequate sampling, that causes aliasing errors. These spatial sampling errors are computed in terms of the system transfer function, which is the Fourier transform of the point response function, the spacing of data points and the spatial spectrum of the radiance field.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. 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. PMID:27126469

  7. Spatial orientation, adaptation, and motion sickness in real and virtual environments

    NASA Technical Reports Server (NTRS)

    Dizio, Paul; Lackner, James R.

    1992-01-01

    Reason and Brand (1975) noted that motion sickness occurs in many situations involving either passive body motion or active interaction with the world via indirect sensorimotor interfaces (e.g., prism spectacles). As might be expected, motion sickness is being reported in VEs that involve apparent self-motion through space, the best known examples being flight simulators (Kennedy et al., 1990). The goals of this paper are to introduce the motion-sickness symptomatology; to outline some concepts that are central to theories of motion sickness, spatial orientation, and adaptation; and to discuss the implications of some trends in VE research and development.

  8. 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

  9. 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.

  10. Multigrid iterative method with adaptive spatial support for computed tomography reconstruction from few-view data

    NASA Astrophysics Data System (ADS)

    Lee, Ping-Chang

    2014-03-01

    Computed tomography (CT) plays a key role in modern medical system, whether it be for diagnosis or therapy. As an increased risk of cancer development is associated with exposure to radiation, reducing radiation exposure in CT becomes an essential issue. Based on the compressive sensing (CS) theory, iterative based method with total variation (TV) minimization is proven to be a powerful framework for few-view tomographic image reconstruction. Multigrid method is an iterative method for solving both linear and nonlinear systems, especially when the system contains a huge number of components. In medical imaging, image background is often defined by zero intensity, thus attaining spatial support of the image, which is helpful for iterative reconstruction. In the proposed method, the image support is not considered as a priori knowledge. Rather, it evolves during the reconstruction process. Based on the CS framework, we proposed a multigrid method with adaptive spatial support constraint. The simultaneous algebraic reconstruction (SART) with TV minimization is implemented for comparison purpose. The numerical result shows: 1. Multigrid method has better performance while less than 60 views of projection data were used, 2. Spatial support highly improves the CS reconstruction, and 3. When few views of projection data were measured, our method performs better than the SART+TV method with spatial support constraint.

  11. On efficient two-stage adaptive designs for clinical trials with sample size adjustment.

    PubMed

    Liu, Qing; Li, Gang; Anderson, Keaven M; Lim, Pilar

    2012-01-01

    Group sequential designs are rarely used for clinical trials with substantial over running due to fast enrollment or long duration of treatment and follow-up. Traditionally, such trials rely on fixed sample size designs. Recently, various two-stage adaptive designs have been introduced to allow sample size adjustment to increase statistical power or avoid unnecessarily large trials. However, these adaptive designs can be seriously inefficient. To address this infamous problem, we propose a likelihood-based two-stage adaptive design where sample size adjustment is derived from a pseudo group sequential design using cumulative conditional power. We show through numerical examples that this design cannot be improved by group sequential designs. In addition, the approach may uniformly improve any existing two-stage adaptive designs with sample size adjustment. For statistical inference, we provide methods for sequential p-values and confidence intervals, as well as median unbiased and minimum variance unbiased estimates. We show that the claim of inefficiency of adaptive designs by Tsiatis and Mehta ( 2003 ) is logically flawed, and thereby provide a strong defense of Cui et al. ( 1999 ). PMID:22651105

  12. 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.

  13. 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.

  14. 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.

  15. Projection-based spatially adaptive reconstruction of block-transform compressed images.

    PubMed

    Yang, Y; Galatsanos, N P; Katsaggelos, A K

    1995-01-01

    At the present time, block-transform coding is probably the most popular approach for image compression. For this approach, the compressed images are decoded using only the transmitted transform data. We formulate image decoding as an image recovery problem. According to this approach, the decoded image is reconstructed using not only the transmitted data but, in addition, the prior knowledge that images before compression do not display between-block discontinuities. A spatially adaptive image recovery algorithm is proposed based on the theory of projections onto convex sets. Apart from the data constraint set, this algorithm uses another new constraint set that enforces between-block smoothness. The novelty of this set is that it captures both the local statistical properties of the image and the human perceptual characteristics. A simplified spatially adaptive recovery algorithm is also proposed, and the analysis of its computational complexity is presented. Numerical experiments are shown that demonstrate that the proposed algorithms work better than both the JPEG deblocking recommendation and our previous projection-based image decoding approach.

  16. 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. PMID:26764748

  17. 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. PMID:22174944

  18. 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. PMID:26210748

  19. 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.

  20. Effects of sampling interval on spatial patterns and statistics of watershed nitrogen concentration

    USGS Publications Warehouse

    Wu, S.-S.D.; Usery, E.L.; Finn, M.P.; Bosch, D.D.

    2009-01-01

    This study investigates how spatial patterns and statistics of a 30 m resolution, model-simulated, watershed nitrogen concentration surface change with sampling intervals from 30 m to 600 m for every 30 m increase for the Little River Watershed (Georgia, USA). The results indicate that the mean, standard deviation, and variogram sills do not have consistent trends with increasing sampling intervals, whereas the variogram ranges remain constant. A sampling interval smaller than or equal to 90 m is necessary to build a representative variogram. The interpolation accuracy, clustering level, and total hot spot areas show decreasing trends approximating a logarithmic function. The trends correspond to the nitrogen variogram and start to level at a sampling interval of 360 m, which is therefore regarded as a critical spatial scale of the Little River Watershed. Copyright ?? 2009 by Bellwether Publishing, Ltd. All right reserved.

  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. 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.

  3. 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

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

    PubMed

    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

  5. 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

  6. 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. PMID:25799224

  7. 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.

  8. Prototype adaptive bow-tie filter based on spatial exposure time modulation

    NASA Astrophysics Data System (ADS)

    Badal, Andreu

    2016-03-01

    In recent years, there has been an increased interest in the development of dynamic bow-tie filters that are able to provide patient-specific x-ray beam shaping. We introduce the first physical prototype of a new adaptive bow-tie filter design based on the concept of "spatial exposure time modulation." While most existing bow-tie filters operate by attenuating the radiation beam differently in different locations using partially attenuating objects, the presented filter shapes the radiation field using two movable completely radio-opaque collimators. The aperture and speed of the collimators is modulated in synchrony with the x-ray exposure to selectively block the radiation emitted to different parts of the object. This mode of operation does not allow the reproduction of every possible attenuation profile, but it can reproduce the profile of any object with an attenuation profile monotonically decreasing from the center to the periphery, such as an object with an elliptical cross section. Therefore, the new adaptive filter provides the same advantages as the currently existing static bow-tie filters, which are typically designed to work for a pre-determined cylindrical object at a fixed distance from the source, and provides the additional capability to adapt its performance at image acquisition time to better compensate for the actual diameter and location of the imaged object. A detailed description of the prototype filter, the implemented control methods, and a preliminary experimental validation of its performance are presented.

  9. 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.

  10. 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. PMID:25794375

  11. 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.

  12. 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

  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

    2016-09-01

    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

  14. Contrast sensitivity loss with aging: sampling efficiency and equivalent noise at different spatial frequencies.

    PubMed

    Pardhan, Shahina

    2004-02-01

    The relative contributions of optical and neural factors to the decrease in visual function with aging were investigated by measurement of contrast detection at three different spatial frequencies, in the presence of external noise, on young and older subjects. Contrast detection in noise functions allows two parameters to be measured: sampling efficiency, which indicates neural changes, and equivalent noise, which demonstrates optical effects. Contrast thresholds were measured in the presence of four levels (including zero) of externally added visual noise. Measurements were obtained from eight young and eight older visually normal observers. Compared with young subjects, older subjects showed significantly (p < 0.05) lower sampling efficiencies at spatial frequencies of 1 and 4 cycles per degree (c/deg) and significantly higher equivalent noise levels for gratings of 10 c/deg. Neural and optical factors affect contrast sensitivity loss with aging differently, depending on the spatial frequency tested, implying the existence of different mechanisms.

  15. Modified shifted angular spectrum method for numerical propagation at reduced spatial sampling rates.

    PubMed

    Ritter, André

    2014-10-20

    The shifted angular spectrum method allows a reduction of the number of samples required for numerical off-axis propagation of scalar wave fields. In this work, a modification of the shifted angular spectrum method is presented. It allows a further reduction of the spatial sampling rate for certain wave fields. We calculate the benefit of this method for spherical waves. Additionally, a working implementation is presented showing the example of a spherical wave propagating through a circular aperture. PMID:25401659

  16. 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.

  17. Integrity of medial temporal structures may predict better improvement of spatial neglect with prism adaptation treatment

    PubMed Central

    Goedert, Kelly M.; Shah, Priyanka; Foundas, Anne L.; Barrett, A. M.

    2013-01-01

    Prism adaptation treatment (PAT) is a promising rehabilitative method for functional recovery in persons with spatial neglect. Previous research suggests that PAT improves motor-intentional “aiming” deficits that frequently occur with frontal lesions. To test whether presence of frontal lesions predicted better improvement of spatial neglect after PAT, the current study evaluated neglect-specific improvement in functional activities (assessment with the Catherine Bergego Scale) over time in 21 right-brain-damaged stroke survivors with left-sided spatial neglect. The results demonstrated that neglect patients' functional activities improved after two weeks of PAT and continued improving for four weeks. Such functional improvement did not occur equally in all of the participants: Neglect patients with lesions involving the frontal cortex (n=13) experienced significantly better functional improvement than did those without frontal lesions (n=8). More importantly, voxel-based lesion-behavior mapping (VLBM) revealed that in comparison to the group of patients without frontal lesions, the frontal-lesioned neglect patients had intact regions in the medial temporal areas, the superior temporal areas, and the inferior longitudinal fasciculus. The medial cortical and subcortical areas in the temporal lobe were especially distinguished in the “frontal lesion” group. The findings suggest that the integrity of medial temporal structures may play an important role in supporting functional improvement after PAT. PMID:22941243

  18. 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.

  19. Integrity of medial temporal structures may predict better improvement of spatial neglect with prism adaptation treatment.

    PubMed

    Chen, Peii; Goedert, Kelly M; Shah, Priyanka; Foundas, Anne L; Barrett, A M

    2014-09-01

    Prism adaptation treatment (PAT) is a promising rehabilitative method for functional recovery in persons with spatial neglect. Previous research suggests that PAT improves motor-intentional "aiming" deficits that frequently occur with frontal lesions. To test whether presence of frontal lesions predicted better improvement of spatial neglect after PAT, the current study evaluated neglect-specific improvement in functional activities (assessment with the Catherine Bergego Scale) over time in 21 right-brain-damaged stroke survivors with left-sided spatial neglect. The results demonstrated that neglect patients' functional activities improved after two weeks of PAT and continued improving for four weeks. Such functional improvement did not occur equally in all of the participants: Neglect patients with lesions involving the frontal cortex (n = 13) experienced significantly better functional improvement than did those without frontal lesions (n = 8). More importantly, voxel-based lesion-behavior mapping (VLBM) revealed that in comparison to the group of patients without frontal lesions, the frontal-lesioned neglect patients had intact regions in the medial temporal areas, the superior temporal areas, and the inferior longitudinal fasciculus. The medial cortical and subcortical areas in the temporal lobe were especially distinguished in the "frontal lesion" group. The findings suggest that the integrity of medial temporal structures may play an important role in supporting functional improvement after PAT.

  20. 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...

  1. 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…

  2. 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.

  3. 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.

  4. Spatially coherent colour image reconstruction from a trichromatic mosaic with random arrangement of chromatic samples.

    PubMed

    Alleysson, David

    2010-09-01

    Recent high resolution imaging of the human retina confirms that the trichromatic cone mosaic follows a random arrangement. Moreover, both the cones' arrangements and proportion widely differ from individual to individual. These findings provide new insights to our understanding of colour vision as most of the previous vision models ignored the mosaic sampling. Here, we propose a cone mosaic sampling simulation applied to colour images. From the simulation, we can infer the processing needs for retrieving spatial and chromatic information from the mosaic without spatial ambiguity. In particular, the focus is on the ability of the visual system to reconstruct coherent spatial information from a plurality of local neighbourhoods. We show that normalized linear processing allows the recovery of achromatic and chromatic information from a mosaic of trichromatic samples arranged randomly. Also, low frequency components of achromatic information can serve to coarsely estimate orientation, which in turn improves the interpolation of chromatic information. An implication for the visual system is the possibility that, in the cortex, the low frequency achromatic spatial information of the magnocellular pathway helps separate chromatic information from the mixed achromatic/chromatic information carried by the parvocellular pathway. PMID:20883332

  5. Alternate spatial sampling approaches for ecosystem structure inventory using spaceborne lidar

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    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, ICESat-2). In contrast, vegetation inventories distribute field observations either in regular grids or within patches that are delineated to represent uniform conditions. In the context of supporting large scale inventories of ecosystem structure, a transect sampling pattern is inefficient because multiple observations are made of a spatially autocorrelated phenomenon while large areas of the landscape are left unsampled. This results in higher uncertainty in estimates of average ecosystem structure across landscapes than would be obtained using sampling in regular grids. As the pulses generated by a spaceborne laser are a valuable resource to be conserved, any strategy that decreases the number of observations required to develop large scale inventories with a given level of confidence should be pursued. Data fusion between lidar data and a spatially complete data source (e.g. polarmetric or interferrometric SAR) will also benefit from a spatially distributed sample of lidar as the average distance between any point and a lidar observation is greatly reduced. This study demonstrates that more flexible spatial arrangements of observations can result in estimates of average landscape height that have as little as one-third of the uncertainty of estimates made with an equal number of observations along transects. The method of sampling described here can be implemented by a technology, Electronically Steerable Flash Lidar, that can distribute observations in the patterns described here and simultaneously support transect sampling.

  6. 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.

  7. 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.

  8. 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

  9. Non-equilibrium molecular dynamics simulation of nanojet injection with adaptive-spatial decomposition parallel algorithm.

    PubMed

    Shin, Hyun-Ho; Yoon, Woong-Sup

    2008-07-01

    An Adaptive-Spatial Decomposition parallel algorithm was developed to increase computation efficiency for molecular dynamics simulations of nano-fluids. Injection of a liquid argon jet with a scale of 17.6 molecular diameters was investigated. A solid annular platinum injector was also solved simultaneously with the liquid injectant by adopting a solid modeling technique which incorporates phantom atoms. The viscous heat was naturally discharged through the solids so the liquid boiling problem was avoided with no separate use of temperature controlling methods. Parametric investigations of injection speed, wall temperature, and injector length were made. A sudden pressure drop at the orifice exit causes flash boiling of the liquid departing the nozzle exit with strong evaporation on the surface of the liquids, while rendering a slender jet. The elevation of the injection speed and the wall temperature causes an activation of the surface evaporation concurrent with reduction in the jet breakup length and the drop size.

  10. 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.

  11. The Vineland Adaptive Behavior Scale in a sample of normal French Children: a research note.

    PubMed

    Fombonne, E; Achard, S

    1993-09-01

    The Vineland Adaptive Behavior scale (survey form) was used in a sample of 151 normal children under age 18. Standardized mean scores of French children were comparable to those of the American normative sample. From the age of 6 onwards, French children scored consistently lower in the Daily Living Skills domain though the magnitude of this difference remained moderate. While the overall findings support the cross-cultural stability of the psychometric properties of this instrument, attention is drawn to potential problems in the use of the Vineland scales, with special reference to autistic samples.

  12. 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. PMID:26719593

  13. 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.

  14. 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.

  15. Temporal and spatial adaptation to food restriction in mice under naturalistic conditions.

    PubMed

    Dell'Omo, G; Ricceri, L; Wolfer, D P; Poletaeva, I I; Lipp, H

    2000-10-01

    Free-living female laboratory mice, adapted to outdoor life in large pens providing a naturalistic environment, were tested for their ability to modify their foraging habits to controlled food supply. An automatic feeder box delivered a small portion of the daily quantity of seeds to each individual mouse. Eight such boxes were placed into an outdoor pen. Each day, mice had to visit all boxes to gather the daily amount of food and were rewarded only at the first visit to each box. Mice were individually recognised by an implanted microchip. Throughout a 16-day period, feeding activity concentrated in an interval time around the beginning of the daily session. During the same period, the number of different feeders visited every day by mice increased irrespective of variation in exploratory activity. The experimental set-up allowed detecting temporal and spatial adaptations to the food restriction, as well as behavioural differences due to territorial and social factors. These data permit the design of novel tests assessing behavioural changes, memory and learning in normal and genetically modified mice, both in the laboratory and in naturalistic settings.

  16. 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

  17. Sampling the soil in long-term forest plots: the implications of spatial variation.

    PubMed

    Kirwan, N; Oliver, M A; Moffat, A J; Morgan, G W

    2005-12-01

    Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design. PMID:16311827

  18. 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. PMID:24603033

  19. 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.

  20. Spatial and sampling analysis for a sensor viewing a pixelized projector

    NASA Astrophysics Data System (ADS)

    Sieglinger, Breck A.; Flynn, David S.; Coker, Charles F.

    1997-07-01

    This paper presents an analysis of spatial blurring and sampling effects for a sensor viewing a pixelized scene projector. It addresses the ability of a projector to simulate an arbitrary continuous radiance scene using a field of discrete elements. The spatial fidelity of the projector as seen by an imaging sensor is shown to depend critically on the width of the sensor MTF or spatial response function, and the angular spacing between projector pixels. Quantitative results are presented based on a simulation that compares the output of a sensor viewing a reference scene to the output of the sensor viewing a projector display of the reference scene. Dependence on the blur of the sensor and projector, the scene content, and alignment both of features in the scene and sensor samples with the projector pixel locations are addressed. We attempt to determine the projector characteristics required to perform hardware-in-the-loop testing with adequate spatial realism to evaluate seeker functions like autonomous detection, measuring radiant intensities and angular positions or unresolved objects, or performing autonomous recognition and aimpoint selection for resolved objects.

  1. 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

  2. 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

  3. 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

  4. Spatial distributions and seasonal variations of organochlorine pesticides in water and soil samples in Bolu, Turkey.

    PubMed

    Karadeniz, Hatice; Yenisoy-Karakaş, Serpil

    2015-03-01

    In this study, a total of 75 water samples (38 groundwater and 37 surface water samples) and 54 surface soil samples were collected from the five districts of Bolu, which is located in the Western Black Sea Region of Turkey in the summer season of 2009. In the autumn season, 17 water samples (surface water and groundwater samples) and 17 soil samples were collected within the city center to observe the seasonal changes of organochlorine pesticides (OCPs). Groundwater and surface water samples were extracted using solid phase extraction. Soil samples were extracted ultrasonically. Sixteen OCP compounds in the standard solution were detected by a gas chromatography-electron capture detector (GC-ECD). Therefore, the method validation was performed for those 16 OCP compounds. However, 13 OCP compounds could be observed in the samples. The concentrations of most OCPs were higher in samples collected in the summer than those in the autumn. The most frequently observed pesticides were endosulfan sulfate and 4,4'-dichlorodiphenyltrichloroethane (DDT) in groundwater samples, α-HCH in surface water samples, and endosulfan sulfate in soil samples. The average concentration of endosulfan sulfate was the highest in water and soil samples. Compared to the literature values, the average concentrations in this study were lower values. Spatial distribution of OCPs was evaluated with the aid of contour maps for the five districts of Bolu. Generally, agricultural processes affected the water and soil quality in the region. However, non-agricultural areas were also affected by pesticides. The concentrations of pesticides were below the legal limits of European directives for each pesticide.

  5. 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.

  6. On the efficacy of spatial sampling using manual scanning paths to determine the spatial average sound pressure level in rooms.

    PubMed

    Hopkins, Carl

    2011-05-01

    In architectural acoustics, noise control and environmental noise, there are often steady-state signals for which it is necessary to measure the spatial average, sound pressure level inside rooms. This requires using fixed microphone positions, mechanical scanning devices, or manual scanning. In comparison with mechanical scanning devices, the human body allows manual scanning to trace out complex geometrical paths in three-dimensional space. To determine the efficacy of manual scanning paths in terms of an equivalent number of uncorrelated samples, an analytical approach is solved numerically. The benchmark used to assess these paths is a minimum of five uncorrelated fixed microphone positions at frequencies above 200 Hz. For paths involving an operator walking across the room, potential problems exist with walking noise and non-uniform scanning speeds. Hence, paths are considered based on a fixed standing position or rotation of the body about a fixed point. In empty rooms, it is shown that a circle, helix, or cylindrical-type path satisfy the benchmark requirement with the latter two paths being highly efficient at generating large number of uncorrelated samples. In furnished rooms where there is limited space for the operator to move, an efficient path comprises three semicircles with 45°-60° separations.

  7. An adapted tissue microarray for the development of a matrix arrangement of tissue samples.

    PubMed

    Gurgel, Daniel C; Dornelas, Conceição A; Lima-Júnior, Roberto C P; Ribeiro, Ronaldo A; Almeida, Paulo R C

    2012-03-15

    The arrangement of tissue samples in a matrix, known as the tissue microarray (TMA) method, is a well-recognized method worldwide. This technique makes it possible to assess the expression of molecular markers on a large scale with high yields in terms of time, costs, and archived material. Some researchers are trying to adapt the technique to expand the research possibilities. This study proposes an adaptive simplification of low-cost instruments for obtaining samples that will be used in the construction of the TMA. The use of a manual leather puncher, which has a very low cost and a long expected life and eliminates the need to use a press machine, is a simple and effective alternative to building blocks of tissue microarrays.

  8. 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.

  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 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.

  11. 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

  12. Detecting the land-cover changes induced by large-physical disturbances using landscape metrics, spatial sampling, simulation and spatial analysis.

    PubMed

    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

  13. 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.

  14. 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. PMID:26692381

  15. 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.

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

    PubMed

    Vallejo-Medina, Pablo; Sierra, Juan Carlos

    2015-01-01

    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. PMID:25896498

  17. A Predictive Approach to Nonparametric Inference for Adaptive Sequential Sampling of Psychophysical Experiments

    PubMed Central

    Benner, Philipp; Elze, Tobias

    2012-01-01

    We present a predictive account on adaptive sequential sampling of stimulus-response relations in psychophysical experiments. Our discussion applies to experimental situations with ordinal stimuli when there is only weak structural knowledge available such that parametric modeling is no option. By introducing a certain form of partial exchangeability, we successively develop a hierarchical Bayesian model based on a mixture of Pólya urn processes. Suitable utility measures permit us to optimize the overall experimental sampling process. We provide several measures that are either based on simple count statistics or more elaborate information theoretic quantities. The actual computation of information theoretic utilities often turns out to be infeasible. This is not the case with our sampling method, which relies on an efficient algorithm to compute exact solutions of our posterior predictions and utility measures. Finally, we demonstrate the advantages of our framework on a hypothetical sampling problem. PMID:22822269

  18. Determination of the optimum sampling frequency of noisy images by spatial statistics

    SciTech Connect

    Sanchez-Brea, Luis Miguel; Bernabeu, Eusebio

    2005-06-01

    In optical metrology the final experimental result is normally an image acquired with a CCD camera. Owing to the sampling at the image, an interpolation is usually required. For determining the error in the measured parameters with that image, knowledge of the uncertainty at the interpolation is essential. We analyze how kriging, an estimator used in spatial statistics, can generate convolution kernels for filtering noise in regularly sampled images. The convolution kernel obtained with kriging explicitly depends on the spatial correlation and also on metrological conditions, such as the random fluctuations of the measured quantity, and the resolution of the measuring devices. Kriging, in addition, allows us to determine the uncertainty of the interpolation, and we have analyzed it in terms of the sampling frequency and the random fluctuations of the image, comparing it with Nyquist criterion. By use of kriging, it is possible to determine the optimum-required sampling frequency for a noisy image so that the uncertainty at interpolation is below a threshold value.

  19. Spatial adaptive upsampling filter for HDR image based on multiple luminance range

    NASA Astrophysics Data System (ADS)

    Chen, Qian; Su, Guan-ming; Peng, Yin

    2014-03-01

    In this paper, we propose an adaptive upsampling filter to spatially upscale HDR image based on luminance range of the HDR picture in each color channel. It first searches for the optimal luminance range values to partition an HDR image to three different parts: dark, mid-tone and highlight. Then we derive the optimal set of filter coefficients both vertically and horizontally for each part. When the HDR pixel is within the dark area, we apply one set of filter coefficients to vertically upsample the pixel. If the HDR pixel falls in mid-tone area, we apply another set of filter for vertical upsampling. Otherwise the HDR pixel is in highlight area, another set of filter will be applied for vertical upsampling. Horizontal upsampling will be carried out likewise based on its luminance. The inherent idea to partition HDR image to different luminance areas is based on the fact that most HDR images are created from multiple exposures. Different exposures usually demonstrate slight variation in captured signal statistics, such as noise level, subtle misalignment etc. Hence, to group different regions to three luminance partitions actually helps to eliminate the variation between signals, and to derive optimal filter for each group with signals of lesser variation is certainly more efficient than for the entire HDR image. Experimental results show that the proposed adaptive upsampling filter based on luminance ranges outperforms the optimal upsampling filter around 0.57dB for R channel, 0.44dB for G channel and 0.31dB for B channel.

  20. 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

  1. Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter

    PubMed Central

    2014-01-01

    Background In magnetic resonance electrical impedance tomography (MREIT), we reconstruct conductivity images using magnetic flux density data induced by externally injected currents. Since we extract magnetic flux density data from acquired MR phase images, the amount of measurement noise increases in regions of weak MR signals. Especially for local regions of MR signal void, there may occur excessive amounts of noise to deteriorate the quality of reconstructed conductivity images. In this paper, we propose a new conductivity image enhancement method as a postprocessing technique to improve the image quality. Methods Within a magnetic flux density image, the amount of noise varies depending on the position-dependent MR signal intensity. Using the MR magnitude image which is always available in MREIT, we estimate noise levels of measured magnetic flux density data in local regions. Based on the noise estimates, we adjust the window size and weights of a spatial averaging filter, which is applied to reconstructed conductivity images. Without relying on a partial differential equation, the new method is fast and can be easily implemented. Results Applying the novel conductivity image enhancement method to experimental data, we could improve the image quality to better distinguish local regions with different conductivity contrasts. From phantom experiments, the estimated conductivity values had 80% less variations inside regions of homogeneous objects. Reconstructed conductivity images from upper and lower abdominal regions of animals showed much less artifacts in local regions of weak MR signals. Conclusion We developed the fast and simple method to enhance the conductivity image quality by adaptively adjusting the weights and window size of the spatial averaging filter using MR magnitude images. Since the new method is implemented as a postprocessing step, we suggest adopting it without or with other preprocessing methods for application studies where conductivity

  2. Assessing efficiency of spatial sampling using combined coverage analysis in geographical and feature spaces

    NASA Astrophysics Data System (ADS)

    Hengl, Tomislav

    2015-04-01

    Efficiency of spatial sampling largely determines success of model building. This is especially important for geostatistical mapping where an initial sampling plan should provide a good representation or coverage of both geographical (defined by the study area mask map) and feature space (defined by the multi-dimensional covariates). Otherwise the model will need to extrapolate and, hence, the overall uncertainty of the predictions will be high. In many cases, geostatisticians use point data sets which are produced using unknown or inconsistent sampling algorithms. Many point data sets in environmental sciences suffer from spatial clustering and systematic omission of feature space. But how to quantify these 'representation' problems and how to incorporate this knowledge into model building? The author has developed a generic function called 'spsample.prob' (Global Soil Information Facilities package for R) and which simultaneously determines (effective) inclusion probabilities as an average between the kernel density estimation (geographical spreading of points; analysed using the spatstat package in R) and MaxEnt analysis (feature space spreading of points; analysed using the MaxEnt software used primarily for species distribution modelling). The output 'iprob' map indicates whether the sampling plan has systematically missed some important locations and/or features, and can also be used as an input for geostatistical modelling e.g. as a weight map for geostatistical model fitting. The spsample.prob function can also be used in combination with the accessibility analysis (cost of field survey are usually function of distance from the road network, slope and land cover) to allow for simultaneous maximization of average inclusion probabilities and minimization of total survey costs. The author postulates that, by estimating effective inclusion probabilities using combined geographical and feature space analysis, and by comparing survey costs to representation

  3. A statistical method for evaluating sampling configurations of spatially variable parameters in environmental site audits

    SciTech Connect

    Molash, E.; McTernan, W.F.

    1995-11-01

    In hazardous waste sites the existence, number, and areal distributions of buried drums are unknown factors and are critical in defining the extent of contamination and defining decision models for remediation system design. The location and removal of these drums are appropriate first actions in responding to hazardous waste disposal sites which threaten groundwater resources. Magnetometry utilizes the earth`s natural magnetic field as an inducing element for the detection of ferrometallic objects in the subsurface. The contrast between most earth materials, which tend to have very low magnetic susceptibilities, and steel drums, which have very high magnetic susceptibilities, provide the basis for detecting and locating these objects using magnetic field attributes. The results of the geostatistical analysis for the magnetometry surveys over the Western Processing Superfund site showed that the total field intensity and vertical gradient data displayed distinctly different spatial statistical properties. The total magnetic intensity data had an experimental semivariogram was easily defined mathematically using the 3.05 meter (10 foot) triangular sampling grid. The subsequent kriged estimates for the total magnetic field intensity had very good statistical correlations with the original sampled data, with some minor distortions of the probability distributions of the results. These minor distortions were concluded to be intrinsic products of the mathematics of the kriging process. Contrastingly, the experimental semivariogram for the vertical magnetic gradient indicated that more than 69% of the correlation structure existed at spatial wavelengths less than that of the 10 foot triangular sampling grid, indicating much higher spatial frequencies. This implies that a field measurements for vertical magnetic gradient data, with the intent of locating buried steel drums, should be designed with sampling grids at distances considerably less than 10 feet.

  4. Characterizing spatial structure of sediment E. coli populations to inform sampling design.

    PubMed

    Piorkowski, Gregory S; Jamieson, Rob C; Hansen, Lisbeth Truelstrup; Bezanson, Greg S; Yost, Chris K

    2014-01-01

    Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p = 0.002) among monitoring sites during baseflow, and significant interactive effects (p = 0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D 10) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D 50) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.

  5. Adaptive Sampling approach to environmental site characterization at Joliet Army Ammunition Plant: Phase 2 demonstration

    SciTech Connect

    Bujewski, G.E.; Johnson, R.L.

    1996-04-01

    Adaptive sampling programs provide real opportunities to save considerable time and money when characterizing hazardous waste sites. This Strategic Environmental Research and Development Program (SERDP) project demonstrated two decision-support technologies, SitePlanner{trademark} and Plume{trademark}, that can facilitate the design and deployment of an adaptive sampling program. A demonstration took place at Joliet Army Ammunition Plant (JAAP), and was unique in that it was tightly coupled with ongoing Army characterization work at the facility, with close scrutiny by both state and federal regulators. The demonstration was conducted in partnership with the Army Environmental Center`s (AEC) Installation Restoration Program and AEC`s Technology Development Program. AEC supported researchers from Tufts University who demonstrated innovative field analytical techniques for the analysis of TNT and DNT. SitePlanner{trademark} is an object-oriented database specifically designed for site characterization that provides an effective way to compile, integrate, manage and display site characterization data as it is being generated. Plume{trademark} uses a combination of Bayesian analysis and geostatistics to provide technical staff with the ability to quantitatively merge soft and hard information for an estimate of the extent of contamination. Plume{trademark} provides an estimate of contamination extent, measures the uncertainty associated with the estimate, determines the value of additional sampling, and locates additional samples so that their value is maximized.

  6. Insights into a spatially embedded social network from a large-scale snowball sample

    NASA Astrophysics Data System (ADS)

    Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

    2011-12-01

    Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

  7. 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.

  8. Spatial pattern and sequential sampling of squash bug (Heteroptera: Coreidae) adults in watermelon.

    PubMed

    Dogramaci, Mahmut; Shrefler, James W; Giles, Kristopher; Edelson, J V

    2006-04-01

    Spatial distribution patterns of adult squash bugs were determined in watermelon, Citrullus lanatus (Thunberg) Matsumura and Nakai, during 2001 and 2002. Results of analysis using Taylor's power law regression model indicated that squash bugs were aggregated in watermelon. Taylor's power law provided a good fit with r2 = 0.94. A fixed precision sequential sampling plan was developed for estimating adult squash bug density at fixed precision levels in watermelon. The plan was tested using a resampling simulation method on nine and 13 independent data sets ranging in density from 0.15 to 2.52 adult squash bugs per plant. Average estimated means obtained in 100 repeated simulation runs were within the 95% CI of the true means for all the data. Average estimated levels of precision were similar to the desired level of precision, particularly when the sampling plan was tested on data having an average mean density of 1.19 adult squash bugs per plant. Also, a sequential sampling for classifying adult squash bug density as below or above economic threshold was developed to assist in the decision-making process. The classification sampling plan is advantageous in that it requires smaller sample sizes to estimate the population status when the population density differs greatly from the action threshold. However, the plan may require excessively large sample sizes when the density is close to the threshold. Therefore, an integrated sequential sampling plan was developed using a combination of a fixed precision and classification sequential sampling plans. The integration of sampling plans can help reduce sampling requirements. PMID:16686160

  9. Simulation of mid-infrared clutter rejection. 1: One-dimensional LMS spatial filter and adaptive threshold algorithms.

    PubMed

    Longmire, M S; Milton, A F; Takken, E H

    1982-11-01

    Several 1-D signal processing techniques have been evaluated by simulation with a digital computer using high-spatial-resolution (0.15 mrad) noise data gathered from back-lit clouds and uniform sky with a scanning data collection system operating in the 4.0-4.8-microm spectral band. Two ordinary bandpass filters and a least-mean-square (LMS) spatial filter were evaluated in combination with a fixed or adaptive threshold algorithm. The combination of a 1-D LMS filter and a 1-D adaptive threshold sensor was shown to reject extreme cloud clutter effectively and to provide nearly equal signal detection in a clear and cluttered sky, at least in systems whose NEI (noise equivalent irradiance) exceeds 1.5 x 10(-13) W/cm(2) and whose spatial resolution is better than 0.15 x 0.36 mrad. A summary gives highlights of the work, key numerical results, and conclusions.

  10. 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.

  11. 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.

  12. Advantages and limitations of the spatially adaptive program SAPRO in clinical perimetry.

    PubMed

    Fankhauser, F; Funkhouser, A; Kwasniewska, S

    1986-05-01

    The SAPRO program devised for the OCTOPUS 201 automated perimeter, consists of a number of program components. It is designed to be used on the Octopus 201 computer. In its measurement mode, it employs an algorithm which achieves high speed and efficiency. This is made possible by a threshold bracketing strategy which is simpler than the normal OCTOPUS bracketing. Moreover, three grids with test location distributions of increasing resolution are superimposed in succession on the whole or on part of the visual field to be analyzed. Out of the distribution of test locations, only those which fulfill a number of criteria are actually utilized. These criteria must be given and are adaptable to any given clinical problem. As a result, despite the high spatial resolution achieved, only a fraction of the test locations are utilized using SAPRO as compared with a program using a fixed pattern of test locations. The algorithm is thus able to imitate human intelligence, which tends to concentrate stimuli at places which appear to be relevant for the solution of a problem. The results of program SAPRO are disturbed by short- and long-term fluctuations. Their validity is limited, in a manner similar to that encountered in any other threshold determination procedure. A number of printout modes is available which are oriented towards an optimal understanding of the information contained in various examinations. These principles will be illustrated by one case of inactive disseminated chorioretinitis. PMID:3755124

  13. 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.

  14. 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

    2014-06-01

    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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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. PMID:23614628

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

    PubMed

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

    2016-02-01

    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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. A method for classification training samples spatial-time expanding of remote sensing image

    NASA Astrophysics Data System (ADS)

    Ren, Guangbo; Zhang, Jie; Ma, Yi; Zheng, Rong-Er

    2009-12-01

    Because of the environment conditions of the ground targets have been changing when the remote sensing images are acquired, so it is known that labeled samples from one remote sensing image is almost imposable to be used in another image classification, because the spectral signatures are various. But once it can be done successfully it will lead to great resource preserving and high work efficiency. This article proposes a classification samples spatial-time domain expanding method to address this issue. In this method, we choose training samples from a reference image, then classify the images in space and time neighborhood of the reference image by the classifier which is trained with these labeled samples. Before classifying, the relative radio-correcting (or to say radiometric normalization) of the images to be classified need be done, and it is the key step. Three classification experiments, which were the reference image and the image need be classified have only different acquisition time, only different cover region, and both the different acquisition time and different cover region, are successfully carried out. The results prove that our method has done well in classification samples expanding application in time domain, in space domain and both in the two domains.

  6. Free-space fluorescence tomography with adaptive sampling based on anatomical information from microCT

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaofeng; Badea, Cristian T.; Hood, Greg; Wetzel, Arthur W.; Stiles, Joel R.; Johnson, G. Allan

    2010-02-01

    Image reconstruction is one of the main challenges for fluorescence tomography. For in vivo experiments on small animals, in particular, the inhomogeneous optical properties and irregular surface of the animal make free-space image reconstruction challenging because of the difficulties in accurately modeling the forward problem and the finite dynamic range of the photodetector. These two factors are fundamentally limited by the currently available forward models and photonic technologies. Nonetheless, both limitations can be significantly eased using a signal processing approach. We have recently constructed a free-space panoramic fluorescence diffuse optical tomography system to take advantage of co-registered microCT data acquired from the same animal. In this article, we present a data processing strategy that adaptively selects the optical sampling points in the raw 2-D fluorescent CCD images. Specifically, the general sampling area and sampling density are initially specified to create a set of potential sampling points sufficient to cover the region of interest. Based on 3-D anatomical information from the microCT and the fluorescent CCD images, data points are excluded from the set when they are located in an area where either the forward model is known to be problematic (e.g., large wrinkles on the skin) or where the signal is unreliable (e.g., saturated or low signal-to-noise ratio). Parallel Monte Carlo software was implemented to compute the sensitivity function for image reconstruction. Animal experiments were conducted on a mouse cadaver with an artificial fluorescent inclusion. Compared to our previous results using a finite element method, the newly developed parallel Monte Carlo software and the adaptive sampling strategy produced favorable reconstruction results.

  7. 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.

  8. 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. PMID:27371709

  9. 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.

  10. Spatial distribution and sampling plans for Mesoplatys ochroptera (Coleoptera: Chrysomelidae) on sesbania.

    PubMed

    Leshi, G; Baumgärtner, J; Sithanantham, S; Ogol, K P O

    2002-04-01

    With the widespread introduction of the nitrogen-fixing legume sesbania, Sesbania sesban (L.) Merril, in agroforestry systems, the defoliating beetle Mesoplatys ochroptera Stål has become a serious pest of the trees in Africa. To determine within-field and within-plant spatial distribution of M. ochroptera on both seedlings and trees of sesbania, distribution statistics were computed using Iwao's mean crowding regression model. In 1- to 3-mo-old seedlings, the model accounted for 29.8, 32.2, and 61.0% of the variation observed in mean crowding to mean relationships in egg masses, larvae and adults, respectively. The model slopes of the regression were greater than unity for all stages indicating aggregated spatial distribution. Values of the intercept were greater than zero for egg masses, larvae and adults indicating that the basic components of the population are groups of individuals. The highest density (>80%) of mating and feeding adults was found in the upper third of 1- to 2-mo-old seedlings, while most of the egg masses were found in the lower half of seedlings. In trees, >60% of the individuals of all stages were found in the lower third of the foliage canopy, while <10% were found in the upper third. Sampling adults was found to be easier and gave better density estimates of M. ochroptera population than egg masses and larvae. Therefore, sampling plans useful for population studies and decision-making in pest management were developed for adults.

  11. 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

  12. 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.

  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. PMID:25014964

  14. Adaptive sampling in two-phase designs: a biomarker study for progression in arthritis

    PubMed Central

    McIsaac, Michael A; Cook, Richard J

    2015-01-01

    Response-dependent two-phase designs are used increasingly often in epidemiological studies to ensure sampling strategies offer good statistical efficiency while working within resource constraints. Optimal response-dependent two-phase designs are difficult to implement, however, as they require specification of unknown parameters. We propose adaptive two-phase designs that exploit information from an internal pilot study to approximate the optimal sampling scheme for an analysis based on mean score estimating equations. The frequency properties of estimators arising from this design are assessed through simulation, and they are shown to be similar to those from optimal designs. The design procedure is then illustrated through application to a motivating biomarker study in an ongoing rheumatology research program. Copyright © 2015 © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. PMID:25951124

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. A collaborative adaptive Wiener filter for image restoration using a spatial-domain multi-patch correlation model

    NASA Astrophysics Data System (ADS)

    Mohamed, Khaled M.; Hardie, Russell C.

    2015-12-01

    We present a new patch-based image restoration algorithm using an adaptive Wiener filter (AWF) with a novel spatial-domain multi-patch correlation model. The new filter structure is referred to as a collaborative adaptive Wiener filter (CAWF). The CAWF employs a finite size moving window. At each position, the current observation window represents the reference patch. We identify the most similar patches in the image within a given search window about the reference patch. A single-stage weighted sum of all of the pixels in the similar patches is used to estimate the center pixel in the reference patch. The weights are based on a new multi-patch correlation model that takes into account each pixel's spatial distance to the center of its corresponding patch, as well as the intensity vector distances among the similar patches. One key advantage of the CAWF approach, compared with many other patch-based algorithms, is that it can jointly handle blur and noise. Furthermore, it can also readily treat spatially varying signal and noise statistics. To the best of our knowledge, this is the first multi-patch algorithm to use a single spatial-domain weighted sum of all pixels within multiple similar patches to form its estimate and the first to use a spatial-domain multi-patch correlation model to determine the weights. The experimental results presented show that the proposed method delivers high performance in image restoration in a variety of scenarios.

  1. 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.

  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. 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.

  5. In situ sampling in coastal waters - in search for an adequate spatial resolution for chlorophyll monitoring

    NASA Astrophysics Data System (ADS)

    Tolvanen, H.; Suominen, T.

    2012-04-01

    Shallow coastal archipelagos give rise to highly dynamic water quality patterns. In situ sampling inevitably loses detail of this spatio-temporal variation, regardless of the spatial and temporal resolution of the monitoring. In the shallow coastal areas of SW Finland in the Baltic Sea, the spatio-temporal variation of water properties is especially high due to the complexity of the archipelago environment and its bathymetry. Water quality monitoring is traditionally carried out in situ on a point network with 5-20 km distance between the sampling stations. Also the temporal coverage is irregular and often focused to the high summer (late July to early August) to capture the highest algal occurrences resulting from eutrophication. The amount of phytoplankton may have irregular vertical variation caused by local prevailing conditions, and therefore the biomass within the productive layer is usually measured by the amount of chlorophyll as a collective sample of the single vertical profile per station. However, the amount of phytoplankton varies also horizontally over short distances in the coastal water that may be homogenous in temperature and salinity. We tested the representativeness of the traditional single sampling station method by expanding the measurement station into six parallel sampling points within a 0.25 km2 area around the station. We measured the chlorophyll content in depth profiles from 1 m to 10 m depth using an optical water quality sonde. This sampling scheme provides us with a better understanding of the occurrence and distribution of phytoplankton in the water mass. The data include three six-point stations in different parts of the coastal archipelago. All stations were sampled several times during the growing season of 2007. In this paper, we compare the results of the established one-point collective depth sampling with the locally extended sampling scheme that portrays also the small-scale horizontal variation of phytoplankton. We

  6. Integrating field sampling, spatial statistics and remote sensing to map wetland vegetation in the Pantanal, Brazil

    NASA Astrophysics Data System (ADS)

    Arieira, J.; Karssenberg, D.; de Jong, S. M.; Addink, E. A.; Couto, E. G.; Nunes da Cunha, C.; Skøien, J. O.

    2010-09-01

    To improve the protection of wetlands, it is imperative to have a thorough understanding of their structuring elements and of the identification of efficient methods to describe and monitor them. This article uses sophisticated statistical classification, interpolation and error propagation techniques, in order to describe vegetation spatial patterns, map plant community distribution and evaluate the capability of statistical approaches to produce high-quality vegetation maps. The approach results in seven vegetation communities with a known floral composition that can be mapped over large areas using remotely sensed data. The relations between remotely sensing data and vegetation patterns, captured in four factorial axes, were formalized mathematically in multiple linear regression models and used in a universal kriging procedure to reduce the uncertainty in mapped communities. Universal kriging has shown to be a valuable interpolation technique because parts of vegetation variability not explained by the images could be modeled as spatially correlated residuals, increasing prediction accuracy. Differences in spatial dependence of the vegetation gradients evidenced the multi-scale nature of vegetation communities. Cross validation procedures and Monte Carlo simulations were used to quantify the uncertainty in the resulting map. Cross-validation showed that accuracy in classification varies according with the community type, as a result of sampling density and configuration. A map of uncertainty resulted from Monte Carlo simulations displayed the spatial variation in classification accuracy, showing that the quality of classification varies spatially, even though the proportion and arrangement of communities observed in the original map is preserved to a great extent. These results suggested that mapping improvement could be achieved by increasing the number of field observations of those communities with a scattered and small patch size distribution; or by

  7. 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.

  8. Eye movements and visuoverbal descriptions exhibit heterogeneous and dissociated patterns before and after prismatic adaptation in unilateral spatial neglect.

    PubMed

    Datié, A-M; Paysant, J; Destainville, S; Sagez, A; Beis, J-M; André, J-M

    2006-07-01

    This prospective study examined the effects of prismatic adaptation on visual exploration strategies in patients with left unilateral spatial neglect (USN). Photo-oculographic gaze recordings were obtained, as the subjects (28 brain-damaged; 15 control) performed a free visual exploration task before and after a session of prismatic adaptation. (i) Before prismatic adaptation, the pattern of visual exploration described two subgroups of patients (symmetrical exploration of hemispaces - similar to the control subjects, deficient exploration of left hemispace). Twelve of 20 patients failed to describe significant elements in the left part of the displayed image. Several visuoverbal patterns were observed, some dissociating visual exploration and verbal description. (ii) Immediately after prismatic adaptation, patients with asymmetrical visual exploration presented a significant increase in the number of point fixations and saccades in the left hemispace. Patients with symmetrical exploration presented the opposite pattern. Improved pattern of visual exploration contrasted with an absence of improved verbal description. Eye movements and visuoverbal descriptions exhibit heterogeneous and dissociated patterns before and after prismatic adaptation. This results demonstrate that prismatic adaptation has no effect in certain patients, suggesting that therapeutic indications and evaluation of prismatic test results should take into consideration the heterogeneous nature of USN.

  9. 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.

  10. Regional Insect Inventories Require Long Time, Extensive Spatial Sampling and Good Will

    PubMed Central

    Fattorini, Simone

    2013-01-01

    Understanding how faunistic knowledge develops is of paramount importance to correctly evaluate completeness of insect inventories and to plan future research at regional scale, yet this is an unexplored issue. Aim of this paper was to investigate the processes that lead to a complete species inventory at a regional level for a beetle family. The tenebionid beetles of Latium region (Italy) were analysed as a case study representative of general situations. A comprehensive faunistic database including 3,561 records spanning from 1871 to 2010 was realized examining 25,349 museum specimens and published data. Accumulation curves and non-parametric estimators of species richness were applied to model increase in faunistic knowledge over time, through space and by collectors’ number. Long time, large spatial extent and contribution of many collectors were needed to obtain a reliable species inventory. Massive sampling was not effective in recovering more species. Amateur naturalists (here called parafaunists) were more efficient collectors than professional entomologists. Museum materials collected by parafaunists over long periods and large spatial extent resulted to be a cost effective source of faunistic information with small number of collected individuals. It is therefore important to valuate and facilitate the work of parafaunists as already suggested for parataxonomists. By contrast, massive collections by standardized techniques for ecological research seem to be of scarce utility in improving faunistic knowledge, but their value for faunistic studies may be enhanced if they are conducted in poorly surveyed areas. PMID:23630627

  11. 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.

  12. Adapting Existing Spatial Data Sets to New Uses: An Example from Energy Modeling

    SciTech Connect

    Johanesson, G; Stewart, J S; Barr, C; Sabeff, L B; George, R; Heimiller, D; Milbrandt, A

    2006-06-23

    Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, and economic projections. These data are available at various spatial and temporal scales, which may be different from those needed by the energy modeling community. If the translation from the original format to the format required by the energy researcher is incorrect, then resulting models can produce misleading conclusions. This is of increasing importance, because of the fine resolution data required by models for new alternative energy sources such as wind and distributed generation. This paper addresses the matter by applying spatial statistical techniques which improve the usefulness of spatial data sets (maps) that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) imputing missing data and (3) merging spatial data sets.

  13. 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

  14. Grab vs. composite sampling of particulate materials with significant spatial heterogeneity--a simulation study of "correct sampling errors".

    PubMed

    Minkkinen, Pentti O; Esbensen, Kim H

    2009-10-19

    Sampling errors can be divided into two classes, incorrect sampling and correct sampling errors. Incorrect sampling errors arise from incorrectly designed sampling equipment or procedures. Correct sampling errors are due to the heterogeneity of the material in sampling targets. Excluding the incorrect sampling errors, which can all be eliminated in practice although informed and diligent work is often needed, five factors dominate sampling variance: two factors related to material heterogeneity (analyte concentration; distributional heterogeneity) and three factors related to the sampling process itself (sample type, sample size, sampling modus). Due to highly significant interactions, a comprehensive appreciation of their combined effects is far from trivial and has in fact never been illustrated in detail. Heterogeneous materials can be well characterized by the two first factors, while all essential sampling process characteristics can be summarized by combinations of the latter three. We here present simulations based on an experimental design that varies all five factors. Within the framework of the Theory of Sampling, the empirical Total Sampling Error is a function of the fundamental sampling error and the grouping and segregation error interacting with a specific sampling process. We here illustrate absolute and relative sampling variance levels resulting from a wide array of simulated repeated samplings and express the effects by pertinent lot mean estimates and associated Root Mean Squared Errors/sampling variances, covering specific combinations of materials' heterogeneity and typical sampling procedures as used in current science, technology and industry. Factors, levels and interactions are varied within limits selected to match realistic materials and sampling situations that mimic, e.g., sampling for genetically modified organisms; sampling of geological drill cores; sampling during off-loading 3-dimensional lots (shiploads, railroad cars, truckloads

  15. 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.

  16. 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.

  17. 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

  18. Adaptively biased molecular dynamics: An umbrella sampling method with a time-dependent potential

    NASA Astrophysics Data System (ADS)

    Babin, Volodymyr; Karpusenka, Vadzim; Moradi, Mahmoud; Roland, Christopher; Sagui, Celeste

    We discuss an adaptively biased molecular dynamics (ABMD) method for the computation of a free energy surface for a set of reaction coordinates. The ABMD method belongs to the general category of umbrella sampling methods with an evolving biasing potential. It is characterized by a small number of control parameters and an O(t) numerical cost with simulation time t. The method naturally allows for extensions based on multiple walkers and replica exchange mechanism. The workings of the method are illustrated with a number of examples, including sugar puckering, and free energy landscapes for polymethionine and polyproline peptides, and for a short β-turn peptide. ABMD has been implemented into the latest version (Case et al., AMBER 10; University of California: San Francisco, 2008) of the AMBER software package and is freely available to the simulation community.

  19. 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.

  20. 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. PMID:15096676

  1. 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

    2016-01-01

    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

  2. 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

  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. 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.

  5. 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.

  6. Design of Field Experiments for Adaptive Sampling of the Ocean with Autonomous Vehicles

    NASA Astrophysics Data System (ADS)

    Zheng, H.; Ooi, B. H.; Cho, W.; Dao, M. H.; Tkalich, P.; Patrikalakis, N. M.

    2010-05-01

    Due to the highly non-linear and dynamical nature of oceanic phenomena, the predictive capability of various ocean models depends on the availability of operational data. A practical method to improve the accuracy of the ocean forecast is to use a data assimilation methodology to combine in-situ measured and remotely acquired data with numerical forecast models of the physical environment. Autonomous surface and underwater vehicles with various sensors are economic and efficient tools for exploring and sampling the ocean for data assimilation; however there is an energy limitation to such vehicles, and thus effective resource allocation for adaptive sampling is required to optimize the efficiency of exploration. In this paper, we use physical oceanography forecasts of the coastal zone of Singapore for the design of a set of field experiments to acquire useful data for model calibration and data assimilation. The design process of our experiments relied on the oceanography forecast including the current speed, its gradient, and vorticity in a given region of interest for which permits for field experiments could be obtained and for time intervals that correspond to strong tidal currents. Based on these maps, resources available to our experimental team, including Autonomous Surface Craft (ASC) are allocated so as to capture the oceanic features that result from jets and vortices behind bluff bodies (e.g., islands) in the tidal current. Results are summarized from this resource allocation process and field experiments conducted in January 2009.

  7. Iterative Monte Carlo with bead-adapted sampling for complex-time correlation functions.

    PubMed

    Jadhao, Vikram; Makri, Nancy

    2010-03-14

    In a recent communication [V. Jadhao and N. Makri, J. Chem. Phys. 129, 161102 (2008)], we introduced an iterative Monte Carlo (IMC) path integral methodology for calculating complex-time correlation functions. This method constitutes a stepwise evaluation of the path integral on a grid selected by a Monte Carlo procedure, circumventing the exponential growth of statistical error with increasing propagation time, while realizing the advantageous scaling of importance sampling in the grid selection and integral evaluation. In the present paper, we present an improved formulation of IMC, which is based on a bead-adapted sampling procedure; thus leading to grid point distributions that closely resemble the absolute value of the integrand at each iteration. We show that the statistical error of IMC does not grow upon repeated iteration, in sharp contrast to the performance of the conventional path integral approach which leads to exponential increase in statistical uncertainty. Numerical results on systems with up to 13 degrees of freedom and propagation up to 30 times the "thermal" time variant Planck's over 2pibeta/2 illustrate these features.

  8. Iterative Monte Carlo with bead-adapted sampling for complex-time correlation functions

    NASA Astrophysics Data System (ADS)

    Jadhao, Vikram; Makri, Nancy

    2010-03-01

    In a recent communication [V. Jadhao and N. Makri, J. Chem. Phys. 129, 161102 (2008)], we introduced an iterative Monte Carlo (IMC) path integral methodology for calculating complex-time correlation functions. This method constitutes a stepwise evaluation of the path integral on a grid selected by a Monte Carlo procedure, circumventing the exponential growth of statistical error with increasing propagation time, while realizing the advantageous scaling of importance sampling in the grid selection and integral evaluation. In the present paper, we present an improved formulation of IMC, which is based on a bead-adapted sampling procedure; thus leading to grid point distributions that closely resemble the absolute value of the integrand at each iteration. We show that the statistical error of IMC does not grow upon repeated iteration, in sharp contrast to the performance of the conventional path integral approach which leads to exponential increase in statistical uncertainty. Numerical results on systems with up to 13 degrees of freedom and propagation up to 30 times the "thermal" time ℏβ /2 illustrate these features.

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

    PubMed Central

    Lu, George J.; Opella, Stanley J.

    2013-01-01

    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. PMID:24006989

  10. Adapting hydrological model structure to catchment characteristics: A large-sample experiment

    NASA Astrophysics Data System (ADS)

    Addor, Nans; Clark, Martyn P.; Nijssen, Bart

    2016-04-01

    Current hydrological modeling frameworks do not offer a clear way to systematically investigate the relationship between model complexity and model fidelity. The characterization of this relationship has so far relied on comparisons of different modules within the same model or comparisons of entirely different models. This lack of granularity in the differences between the model constructs makes it difficult to pinpoint model features that contribute to good simulations and means that the number of models or modeling hypotheses evaluated is usually small. Here we use flexible modeling frameworks to comprehensively and systematically compare modeling alternatives across the continuum of model complexity. A key goal is to explore which model structures are most adequate for catchments in different hydroclimatic conditions. Starting from conceptual models based on the Framework for Understanding Structural Errors (FUSE), we progressively increase model complexity by replacing conceptual formulations by physically explicit ones (process complexity) and by refining model spatial resolution (spatial complexity) using the newly developed Structure for Unifying Multiple Modeling Alternatives (SUMMA). To investigate how to best reflect catchment characteristics using model structure, we rely on a recently released data set of 671 catchments in the continuous United States. Instead of running hydrological simulations in every catchment, we use clustering techniques to define catchment clusters, run hydrological simulations for representative members of each cluster, develop hypotheses (e.g., when specific process representations have useful explanatory power) and test these hypotheses using other members of the cluster. We thus refine our catchment clustering based on insights into dominant hydrological processes gained from our modeling approach. With this large-sample experiment, we seek to uncover trade-offs between realism and practicality, and formulate general

  11. 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.

  12. Improving the performance of the signal space separation method by comprehensive spatial sampling.

    PubMed

    Nurminen, J; Taulu, S; Okada, Y

    2010-03-01

    Biomagnetic instruments usually employ sensors with approximately radial normal vectors arranged on a near-spherical surface. The multipole expansion employed in the recently introduced signal space separation method (SSS) reveals limitations in this traditional sensor array design. Specifically, we show that the excessive symmetry of the sensor array impedes separation of multipole components arising from inside and outside of the array. This motivates consideration of novel instrument designs that would sample the field in a more comprehensive way. We evaluated several simulated sensor arrays that employ vector sensors in one or two layers, giving information on multiple field components and the radial dependence of the field. Our results indicate that this kind of sensor array design could significantly improve SSS performance, leading to enhanced shielding against external interference and reduced noise after signal reconstruction. The best two-layer array evaluated here attains a shielding factor of nearly 1000 or 60 dB with about 400 sensors. Due to limited spatial coverage, a traditional reference array geometry does not give the same level of improvement. In addition to improved software shielding, enhanced detection of different multipole components increases the information obtained about the magnetic field, which has fundamental importance. PMID:20157231

  13. Adaptive correction of vortex laser beam in a closed-loop system with phase only liquid crystal spatial light modulator

    NASA Astrophysics Data System (ADS)

    Ma, Haotong; Liu, Zejin; Wu, Huiyun; Xu, Xiaojun; Chen, Jinbao

    2012-03-01

    We propose and demonstrate the wave front correction of a vortex laser beam by using dual phase only liquid crystal spatial light modulators (LC-SLMs) and a stochastic parallel gradient descent (SPGD) algorithm. One phase only LC-SLM is used to generate vortex laser beam by loading spiral phase screen onto the wave front of input quasi-Gaussian beam. The other phase only LC-SLM under SPGD controller based on the subzone control method adaptively compensates the wave front of vortex laser beam. Numerical simulation and experimental results show that after correction, vortex doughnut like beam is focused into a beam with airy disk pattern distribution in the far field. The adaptive corrections of vortex laser beam with different optical topological charges are studied. The results show that the optical topological charge has little influence on adaptive correction. The powers in the main lobe of far field intensity distributions of vortex laser beams with different optical topological charges are all greatly improved by adaptive correction. The technique proposed in this paper can be used in optical communication, relay mirror and atmospheric turbulence correction.

  14. 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.

  15. DMD-based software-configurable spatially-offset Raman spectroscopy for spectral depth-profiling of optically turbid samples.

    PubMed

    Liao, Zhiyu; Sinjab, Faris; Gibson, Graham; Padgett, Miles; Notingher, Ioan

    2016-06-13

    Spectral depth-profiling of optically turbid samples is of high interest to a broad range of applications. We present a method for measuring spatially-offset Raman spectroscopy (SORS) over a range of length scales by incorporating a digital micro-mirror device (DMD) into a sample-conjugate plane in the detection optical path. The DMD can be arbitrarily programmed to collect/reject light at spatial positions in the 2D sample-conjugate plane, allowing spatially offset Raman measurements. We demonstrate several detection geometries, including annular and simultaneous multi-offset modalities, for both macro- and micro-SORS measurements, all on the same instrument. Compared to other SORS modalities, DMD-based SORS provides more flexibility with only minimal additional experimental complexity for subsurface Raman collection. PMID:27410290

  16. An intelligent computational algorithm based on neural network for spatial data mining in adaptability evaluation

    NASA Astrophysics Data System (ADS)

    Miao, Zuohua; Xu, Hong; Chen, Yong; Zeng, Xiangyang

    2009-10-01

    Back-propagation neural network model (BPNN) is an intelligent computational model based on stylebook learning. This model is different from traditional adaptability symbolic logic reasoning method based on knowledge and rules. At the same time, BPNN model has shortcoming such as: slowly convergence speed and partial minimum. During the process of adaptability evaluation, the factors were diverse, complicated and uncertain, so an effectual model should adopt the technique of data mining method and fuzzy logical technology. In this paper, the author ameliorated the backpropagation of BPNN and applied fuzzy logical theory for dynamic inference of fuzzy rules. Authors also give detail description on training and experiment process of the novel model.

  17. Experimental spatial sampling study of the real-time ultrasonic pulse-echo BAI-mode imaging technique.

    PubMed

    Yin, Xiangtao; Morris, Scott A; O'Brien, William D

    2003-04-01

    The ultrasonic pulse-echo backscattered amplitude integral (BAI)-mode imaging technique has been developed to inspect the seal integrity of hermetically sealed, flexible food packages. With a focused 17.3-MHz transducer acquiring radio frequency (RF) echo data in a static rectilinear stop-and-go pattern, this technique was able to reliably detect channel defects as small as 38 microm in diameter and occasionally detect 6-microm-diameter channels. This contribution presents our experimental spatial sampling study of the BAI-mode imaging technique with a continuous zigzag scanning protocol that simulates a real-time production line inspection method in continuous motion. Two transducers (f/2 17.3 MHz and f/3 20.3 MHz) were used to acquire RF echo data in a zigzag raster pattern from plastic film samples bearing rectilinear point reflector arrays of varying grid spacings. The average BAI-value difference (deltaBAI) between defective and intact regions and the contrast-to-noise ratio (CNR) were used to assess image quality as a function of three spatial sampling variables: transducer spatial scanning step size, array sample grid spacing, and transducer -6-dB pulse-echo focal beam spot size. For a given grid size, the deltaBAI and CNR degraded as scanning step size in each spatial dimension increased. There is an engineering trade-off between the BAI-mode image quality and the transducer spatial sampling. The optimal spatial sampling step size has been identified to be between one and two times the -6-dB pulse-echo focal beam lateral diameter. PMID:12744399

  18. 120nm resolution in thick samples with structured illumination and adaptive optics

    NASA Astrophysics Data System (ADS)

    Thomas, Benjamin; Sloan, Megan; Wolstenholme, Adrian J.; Kner, Peter

    2014-03-01

    μLinear Structured Illumination Microscopy (SIM) provides a two-fold increase over the diffraction limited resolution. SIM produces excellent images with 120nm resolution in tissue culture cells in two and three dimensions. For SIM to work correctly, the point spread function (PSF) and optical transfer function (OTF) must be known, and, ideally, should be unaberrated. When imaging through thick samples, aberrations will be introduced into the optical system which will reduce the peak intensity and increase the width of the PSF. This will lead to reduced resolution and artifacts in SIM images. Adaptive optics can be used to correct the optical wavefront restoring the PSF to its unaberrated state, and AO has been used in several types of fluorescence microscopy. We demonstrate that AO can be used with SIM to achieve 120nm resolution through 25m of tissue by imaging through the full thickness of an adult C. elegans roundworm. The aberrations can be corrected over a 25μm × 45μm field of view with one wavefront correction setting, demonstrating that AO can be used effectively with widefield superresolution techniques.

  19. A new spectral variable selection pattern using competitive adaptive reweighted sampling combined with successive projections algorithm.

    PubMed

    Tang, Guo; Huang, Yue; Tian, Kuangda; Song, Xiangzhong; Yan, Hong; Hu, Jing; Xiong, Yanmei; Min, Shungeng

    2014-10-01

    The competitive adaptive reweighted sampling-successive projections algorithm (CARS-SPA) method was proposed as a novel variable selection approach to process multivariate calibration. The CARS was first used to select informative variables, and then SPA to refine the variables with minimum redundant information. The proposed method was applied to near-infrared (NIR) reflectance data of nicotine in tobacco lamina and NIR transmission data of active ingredient in pesticide formulation. As a result, fewer but more informative variables were selected by CARS-SPA than by direct CARS. In the system of pesticide formulation, a multiple linear regression (MLR) model using variables selected by CARS-SPA provided a better prediction than the full-range partial least-squares (PLS) model, successive projections algorithm (SPA) model and uninformative variables elimination-successive projections algorithm (UVE-SPA) processed model. The variable subsets selected by CARS-SPA included the spectral ranges with sufficient chemical information, whereas the uninformative variables were hardly selected.

  20. 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.

  1. 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

  2. Spatially adaptive stochastic methods for fluid-structure interactions subject to thermal fluctuations in domains with complex geometries

    SciTech Connect

    Plunkett, Pat; Hu, Jonathan; Siefert, Christopher; Atzberger, Paul J.

    2014-08-07

    We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid–structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation–dissipation balance condition to develop compatible stochastic driving fields for our discretization. We also perform analysis that shows our condition is sufficient to ensure results consistent with statistical mechanics. We show the Gibbs–Boltzmann distribution is invariant under the stochastic dynamics of the semi-discretization. To generate efficiently the required stochastic driving fields, we develop a Gibbs sampler based on iterative methods and multigrid to generate fields with O(N) computational complexity. Our stochastic methods provide an alternative to uniform discretizations on periodic domains that rely on Fast Fourier Transforms. To demonstrate in practice our stochastic computational methods, we investigate within channel geometries having internal obstacles and no-slip walls how the mobility/diffusivity of particles depends on location. Furthermore, our methods extend the applicability of fluctuating hydrodynamic approaches by allowing for spatially adaptive resolution of the mechanics and for domains that have complex geometries relevant in many applications.

  3. Spatially adaptive stochastic methods for fluid–structure interactions subject to thermal fluctuations in domains with complex geometries

    SciTech Connect

    Plunkett, Pat; Hu, Jonathan; Siefert, Christopher; Atzberger, Paul J.

    2014-11-15

    We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid–structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation–dissipation balance condition to develop compatible stochastic driving fields for our discretization. We perform analysis that shows our condition is sufficient to ensure results consistent with statistical mechanics. We show the Gibbs–Boltzmann distribution is invariant under the stochastic dynamics of the semi-discretization. To generate efficiently the required stochastic driving fields, we develop a Gibbs sampler based on iterative methods and multigrid to generate fields with O(N) computational complexity. Our stochastic methods provide an alternative to uniform discretizations on periodic domains that rely on Fast Fourier Transforms. To demonstrate in practice our stochastic computational methods, we investigate within channel geometries having internal obstacles and no-slip walls how the mobility/diffusivity of particles depends on location. Our methods extend the applicability of fluctuating hydrodynamic approaches by allowing for spatially adaptive resolution of the mechanics and for domains that have complex geometries relevant in many applications.

  4. 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

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

    PubMed

    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

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

    PubMed

    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.

  7. 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

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

    PubMed

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

    2007-11-01

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

  9. Spatial and temporal task characteristics as stress: a test of the dynamic adaptability theory of stress, workload, and performance.

    PubMed

    Szalma, James L; Teo, Grace W L

    2012-03-01

    The goal for this study was to test assertions of the dynamic adaptability theory of stress, which proposes two fundamental task dimensions, information rate (temporal properties of a task) and information structure (spatial properties of a task). The theory predicts adaptive stability across stress magnitudes, with progressive and precipitous changes in adaptive response manifesting first as increases in perceived workload and stress and then as performance failure. Information structure was manipulated by varying the number of displays to be monitored (1, 2, 4 or 8 displays). Information rate was manipulated by varying stimulus presentation rate (8, 12, 16, or 20 events/min). A signal detection task was used in which critical signals were pairs of digits that differed by 0 or 1. Performance accuracy declined and workload and stress increased as a function of increased task demand, with a precipitous decline in accuracy at the highest demand levels. However, the form of performance change as well as the pattern of relationships between speed and accuracy and between performance and workload/stress indicates that some aspects of the theory need revision. Implications of the results for the theory and for future research are discussed.

  10. A Novel approach to monitor chlorophyll-a concentration using an adaptive model from MODIS data at 250 metres spatial resolution

    NASA Astrophysics Data System (ADS)

    El Alem, A.; Chokmani, K.; Laurion, I.; El Adlouni, S.

    2013-12-01

    Occurrence and extent of Harmful Algal Bloom (HAB) has increased in inland water bodies around the world. The appearance of these blooms reflects the advanced state of eutrophication of several aquatic systems caused by urban, agricultural, and industrial development. Algal blooms, especially those cyanobacterial origins, are capable to produce and release toxins, threatening human and animal health, quality of drinking water, and recreational water bodies. Conventional monitoring networks, based on infrequent sampling in a few fixed monitoring stations, cannot provide the information needed as HABs are spatially and temporally heterogeneous. Remote sensing represents an interesting alternative to provide the required spatial and temporal coverage. The usefulness of air-borne and satellite remote sensing data to detect HABs was demonstrated since three decades ago, and since several empirical and semi-empirical models, using satellite imagery, were developed to estimate chlorophyll-a concentration [Chl-a] as a proxy to detect bloom proliferations. However, most of those models presented several weaknesses that are generally linked to the range of [Chl-a] to be estimated. Indeed, models originally calibrated for high [Chl-a] fail to estimate low concentrations and vice versa. In this study, an adaptive model to estimate [Chl-a], spread over a wide range of concentrations, is developed for optically complex inland water bodies based on combination of water spectral response classification and three developed semi-empirical algorithms using a multivariate regression. Three distinct water types (low, medium, and high [Chl-a]) are first identified using the Classification and Regression Tree (CART) method performed on remote sensing reflectance over a dataset of 44 [Chl-a] samples collected from Lakes over Quebec province. Based on the water classification, a specific multivariate model to each water type is developed using the same dataset and the MODIS data at 250-m

  11. 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…

  12. 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…

  13. 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

  14. An Efficient Sampling Technique for Observing Topographically-Dependent Spatial Variability in Catchment-Scale Soil Moisture Patterns

    NASA Astrophysics Data System (ADS)

    Werbylo, K. L.; Niemann, J. D.

    2012-12-01

    Catchment-scale variability in soil moisture plays an important role in many hydrologic applications. The magnitude of spatial variability in soil moisture patterns affects the catchment-scale evapotranspiration rate, while the spatial structure of soil moisture patterns affects runoff production. In many cases, spatial variations in soil moisture are associated with variations in topographic attributes such as drainage area, slope, and curvature. In the past, large soil moisture datasets have been collected on uniform grids at experimental catchments to characterize the spatial and temporal variability, but this approach is very time-consuming and expensive with most grids containing hundreds of locations monitored over several dates. Although many studies have focused on efficient strategies to observe the catchment-average soil moisture, few have advanced improved strategies to characterize the spatial variability. In this study, we propose a new stratified sampling technique that aims to reduce the number of observations that are required to observe the main variations in soil moisture. The method is applied to soil moisture patterns with topographically-induced variability, but it can be generalized to consider patterns with other sources of variation. In the method, topographic attributes that potentially introduce variability are preselected, and the observed range of values for each attribute is divided into sub-ranges or stratifications. Because multiple topographic attributes are considered, any given location in the catchment will fall into a joint stratification that corresponds to a particular combination of individual stratifications. The sampling locations are then randomly selected from the locations in each joint stratification. The method thus assures that all combinations of low and high terrain attribute values that exist in the catchment are represented in the dataset. The number of sampling locations can be controlled by changing the number of

  15. 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. PMID:22320891

  16. 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.

  17. The role of vestibular system and the cerebellum in adapting to gravitoinertial, spatial orientation and postural challenges of REM sleep.

    PubMed

    Dharani, Nataraj E

    2005-01-01

    The underlying reasons for, and mechanisms of rapid eye movement (REM) sleep events remain a mystery. The mystery has arisen from interpreting REM sleep events as occurring in 'isolation' from the world at large, and phylogenetically ancient brain areas using 'primal' gravity-dependent coordinates, reflexes and stimuli parameters to relay and process information about self and environment. This paper views REM sleep as a phylogenetically older form of wakefulness, wherein the brain uses a gravitoinertial-centred reference frame and an internal self-object model to evaluate and integrate inputs from several sensory systems and to adapt to spatial-temporal disintegration and malignant cholinergic-induced vasodepressor/ventilatory threat. The integration of vestibular and non-vestibular sensory graviceptor signals enables estimation and control of centre of the body mass, position and spatial relationship of body parts, gaze, head and whole-body tilt, spatial orientation and autonomic functions relative to gravity. The vestibulocerebellum and vermis, via vestibular and fastigial nucleus, coordinate inputs and outputs from several sensory systems and modulate the amplitude and duration of 'fight-or-flight' vestibulo-orienting and autonomic 'burst' responses to overcome the ongoing challenges. Resolving multisystem conflicts during the unique stresses (gravitoinertial, hypoxic, thermal, immobilisation, etc.) of REM sleep enables learning, cross-modal plasticity, higher-order integration and multidimensional spatial updating of sensory-motor-cognitive components. This paper aims to generate discussion, reinterpretation and creative testing of this novel hypothesis, which, if experimentally confirmed, has major implications across medicine, bioscience and space physiology, from developmental, clinical, research and theoretical perspectives.

  18. 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

  19. The impact of spatial scale and habitat configuration on patterns of trait variation and local adaptation in a wild plant parasite.

    PubMed

    Tack, Ayco J M; Horns, Felix; Laine, Anna-Liisa

    2014-01-01

    Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host-pathogen interactions. Yet, we lack empirical data to translate the theory to natural host-parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0-40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host-parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health.

  20. The impact of spatial scale and habitat configuration on patterns of trait variation and local adaptation in a wild plant parasite.

    PubMed

    Tack, Ayco J M; Horns, Felix; Laine, Anna-Liisa

    2014-01-01

    Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host-pathogen interactions. Yet, we lack empirical data to translate the theory to natural host-parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0-40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host-parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health. PMID:24372603

  1. THE IMPACT OF SPATIAL SCALE AND HABITAT CONFIGURATION ON PATTERNS OF TRAIT VARIATION AND LOCAL ADAPTATION IN A WILD PLANT PARASITE

    PubMed Central

    Tack, Ayco J M; Horns, Felix; Laine, Anna-Liisa

    2014-01-01

    Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host–pathogen interactions. Yet, we lack empirical data to translate the theory to natural host–parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0–40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host–parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health. PMID:24372603

  2. A spatial multicriteria model for determining air pollution at sample locations.

    PubMed

    Réquia Júnior, Weeberb João; Roig, Henrique Llacer; Koutrakis, Petros

    2015-02-01

    Atmospheric pollution in urban centers has been one of the main causes of human illness related to the respiratory and circulatory system. Efficient monitoring of air quality is a source of information for environmental management and public health. This study investigates the spatial patterns of atmospheric pollution using a spatial multicriteria model that helps target locations for air pollution monitoring sites. The main objective was to identify high-priority areas for measuring human exposures to air pollutants as they relate to emission sources. The method proved to be viable and flexible in its application to various areas.

  3. Spatially adaptive log-euclidean polyaffine registration based on sparse matches.

    PubMed

    Taquet, Maxime; Macq, Benoît; Warfield, Simon K

    2011-01-01

    Log-euclidean polyaffine transforms have recently been introduced to characterize the local affine behavior of the deformation in principal anatomical structures. The elegant mathematical framework makes them a powerful tool for image registration. However, their application is limited to large structures since they require the pre-definition of affine regions. This paper extends the polyaffine registration to adaptively fit a log-euclidean polyaffine transform that captures deformations at smaller scales. The approach is based on the sparse selection of matching points in the images and the formulation of the problem as an expectation maximization iterative closest point problem. The efficiency of the algorithm is shown through experiments on inter-subject registration of brain MRI between a healthy subject and patients with multiple sclerosis.

  4. High-order total variation-based multiplicative noise removal with spatially adapted parameter selection.

    PubMed

    Liu, Jun; Huang, Ting-Zhu; Xu, Zongben; Lv, Xiao-Guang

    2013-10-01

    Multiplicative noise is one common type of noise in imaging science. For coherent image-acquisition systems, such as synthetic aperture radar, the observed images are often contaminated by multiplicative noise. Total variation (TV) regularization has been widely researched for multiplicative noise removal in the literature due to its edge-preserving feature. However, the TV-based solutions sometimes have an undesirable staircase artifact. In this paper, we propose a model to take advantage of the good nature of the TV norm and high-order TV norm to balance the edge and smoothness region. Besides, we adopt a spatially regularization parameter updating scheme. Numerical results illustrate the efficiency of our method in terms of the signal-to-noise ratio and structure similarity index.

  5. 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.

  6. 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...

  7. 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

  8. A co-adaptive sensory motor rhythms Brain-Computer Interface based on common spatial patterns and Random Forest.

    PubMed

    Schwarz, Andreas; Scherer, Reinhold; Steyrl, David; Faller, Josef; Muller-Putz, Gernot R

    2015-08-01

    Sensorimotor rhythm (SMR) based Brain-Computer Interfaces (BCI) typically require lengthy user training. This can be exhausting and fatiguing for the user as data collection may be monotonous and typically without any feedback for user motivation. Hence new ways to reduce user training and improve performance are needed. We recently introduced a two class motor imagery BCI system which continuously adapted with increasing run-time to the brain patterns of the user. The system was designed to provide visual feedback to the user after just five minutes. The aim of the current work was to improve user-specific online adaptation, which was expected to lead to higher performances. To maximize SMR discrimination, the method of filter-bank common spatial patterns (fbCSP) and Random Forest (RF) classifier were combined. In a supporting online study, all volunteers performed significantly better than chance. Overall peak accuracy of 88.6 ± 6.1 (SD) % was reached, which significantly exceeded the performance of our previous system by 13%. Therefore, we consider this system the next step towards fully auto-calibrating motor imagery BCIs. PMID:26736445

  9. 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.

  10. 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)

  11. A general condition for adaptive genetic polymorphism in temporally and spatially heterogeneous environments.

    PubMed

    Svardal, Hannes; Rueffler, Claus; Hermisson, Joachim

    2015-02-01

    Both evolution and ecology have long been concerned with the impact of variable environmental conditions on observed levels of genetic diversity within and between species. We model the evolution of a quantitative trait under selection that fluctuates in space and time, and derive an analytical condition for when these fluctuations promote genetic diversification. As ecological scenario we use a generalized island model with soft selection within patches in which we incorporate generation overlap. We allow for arbitrary fluctuations in the environment including spatio-temporal correlations and any functional form of selection on the trait. Using the concepts of invasion fitness and evolutionary branching, we derive a simple and transparent condition for the adaptive evolution and maintenance of genetic diversity. This condition relates the strength of selection within patches to expectations and variances in the environmental conditions across space and time. Our results unify, clarify, and extend a number of previous results on the evolution and maintenance of genetic variation under fluctuating selection. Individual-based simulations show that our results are independent of the details of the genetic architecture and whether reproduction is clonal or sexual. The onset of increased genetic variance is predicted accurately also in small populations in which alleles can go extinct due to environmental stochasticity.

  12. 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…

  13. Adaptive deployment of spatial and feature-based attention before saccades

    PubMed Central

    White, Alex L.; Rolfs, Martin; Carrasco, Marisa

    2012-01-01

    What you see depends not only on where you are looking but also on where you will look next. The pre-saccadic attention shift is an automatic enhancement of visual sensitivity at the target of the next saccade. We investigated whether and how perceptual factors independent of the oculomotor plan modulate pre-saccadic attention within and across trials. Observers made saccades to one (the target) of six patches of moving dots and discriminated a brief luminance pulse (the probe) that appeared at an unpredictable location. Sensitivity to the probe was always higher at the target’s location (spatial attention), and this attention effect was stronger if the previous probe appeared at the previous target’s location. Furthermore, sensitivity was higher for probes moving in directions similar to the target’s direction (feature-based attention), but only when the previous probe moved in the same direction as the previous target. Therefore, implicit cognitive processes permeate pre-saccadic attention, so that–contingent on recent experience–it flexibly distributes resources to potentially relevant locations and features. PMID:23147690

  14. 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.

  15. Evaluation of endoscopically obtained duodenal biopsy samples from cats and dogs in an adapter-modified Ussing chamber

    PubMed Central

    DeBiasio, John V.; Suchodolski, Jan S.; Newman, Shelley; Musch, Mark W.; Steiner, Jörg M.

    2014-01-01

    This study was conducted to evaluate an adapter-modified Ussing chamber for assessment of transport physiology in endoscopically obtained duodenal biopsies from healthy cats and dogs, as well as dogs with chronic enteropathies. 17 duodenal biopsies from five cats and 51 duodenal biopsies from 13 dogs were obtained. Samples were transferred into an adapter-modified Ussing chamber and sequentially exposed to various absorbagogues and secretagogues. Overall, 78.6% of duodenal samples obtained from cats responded to at least one compound. In duodenal biopsies obtained from dogs, the rate of overall response ranged from 87.5% (healthy individuals; n = 8), to 63.6% (animals exhibiting clinical signs of gastrointestinal disease and histopathological unremarkable duodenum; n = 15), and 32.1% (animals exhibiting clinical signs of gastrointestinal diseases and moderate to severe histopathological lesions; n = 28). Detailed information regarding the magnitude and duration of the response are provided. The adapter-modified Ussing chamber enables investigation of the absorptive and secretory capacity of endoscopically obtained duodenal biopsies from cats and dogs and has the potential to become a valuable research tool. The response of samples was correlated with histopathological findings. PMID:24378587

  16. Effects of electrofishing gear type on spatial and temporal variability in fish community sampling

    USGS Publications Warehouse

    Meador, M.R.; McIntyre, J.P.

    2003-01-01

    Fish community data collected from 24 major river basins between 1993 and 1998 as part of the U.S. Geological Survey's National Water-Quality Assessment Program were analyzed to assess multiple-reach (three consecutive reaches) and multiple-year (three consecutive years) variability in samples collected at a site. Variability was assessed using the coefficient of variation (CV; SD/mean) of species richness, the Jaccard index (JI), and the percent similarity index (PSI). Data were categorized by three electrofishing sample collection methods: backpack, towed barge, and boat. Overall, multiple-reach CV values were significantly lower than those for multiple years, whereas multiple-reach JI and PSI values were significantly greater than those for multiple years. Multiple-reach and multiple-year CV values did not vary significantly among electrofishing methods, although JI and PSI values were significantly greatest for backpack electrofishing across multiple reaches and multiple years. The absolute difference between mean species richness for multiple-reach samples and mean species richness for multiple-year samples was 0.8 species (9.5% of total species richness) for backpack samples, 1.7 species (10.1%) for towed-barge samples, and 4.5 species (24.4%) for boat-collected samples. Review of boat-collected fish samples indicated that representatives of four taxonomic families - Catostomidae, Centrarchidae, Cyprinidae, and Ictaluridae - were collected at all sites. Of these, catostomids exhibited greater interannual variability than centrarchids, cyprinids, or ictalurids. Caution should be exercised when combining boat-collected fish community data from different years because of relatively high interannual variability, which is primarily due to certain relatively mobile species. Such variability may obscure longer-term trends.

  17. The Spatial-sampling Charcteristics of Global Optical Imagers: Implications on Product Interconsistency over Land And Coastal Waters

    NASA Astrophysics Data System (ADS)

    Pahlevan, N.; Sarkar, S.; Wolfe, R. E.; Franz, B. A.

    2015-12-01

    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-NPP mission provides continuity in monitoring the Earth's surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard NASA's Terra and Aqua satellites. The reflective properties of the Earth surface, including land surface reflectance (LSR) and remote sensing reflectance (Rrs) in costal waters, are among the essential climate variables from which higher-level products relevant to biological and biogeochemical activities can be explored. In this study, we aim at quantifying consistency amongst Aqua-MODIS, Terra-MODS, and the Suomi-NPP VIIRS LSRs as well as Rrs in coastal waters (Level-2). 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 (BRDF), the MODIS and VIIRS Level-2 products are simulated using the Landsat-8's Operational Land Imager (OLI) Level-2 products. The simulations are performed using the instruments' point spread functions on a daily basis for various OLI scenes over a 16-day revisit cycle. Preliminary results over land targets show that the daily mean biases (computed over the entire OLI area) in LSRs due to spatial sampling remain below 0.0015 (1%) in absolute surface reflectance. Overall, the disparity increases when VIIRS viewing zenith angle is larger than that of MODIS. Similar trends were observed for the simulated NDVI products. Depending on the spatial heterogeneity of the OLI scenes, per-grid-cell differences can reach up to . Further spatial analysis of the NDVI and LSR products revealed that depending on the user requirements for product

  18. 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.

  19. A Monte Carlo approach to estimate the uncertainty in soil CO2 emissions caused by spatial and sample size variability.

    PubMed

    Shi, Wei-Yu; Su, Li-Jun; Song, Yi; Ma, Ming-Guo; Du, Sheng

    2015-10-01

    The soil CO2 emission is recognized as one of the largest fluxes in the global carbon cycle. Small errors in its estimation can result in large uncertainties and have important consequences for climate model predictions. Monte Carlo approach is efficient for estimating and reducing spatial scale sampling errors. However, that has not been used in soil CO2 emission studies. Here, soil respiration data from 51 PVC collars were measured within farmland cultivated by maize covering 25 km(2) during the growing season. Based on Monte Carlo approach, optimal sample sizes of soil temperature, soil moisture, and soil CO2 emission were determined. And models of soil respiration can be effectively assessed: Soil temperature model is the most effective model to increasing accuracy among three models. The study demonstrated that Monte Carlo approach may improve soil respiration accuracy with limited sample size. That will be valuable for reducing uncertainties of global carbon cycle.

  20. A Monte Carlo approach to estimate the uncertainty in soil CO2 emissions caused by spatial and sample size variability.

    PubMed

    Shi, Wei-Yu; Su, Li-Jun; Song, Yi; Ma, Ming-Guo; Du, Sheng

    2015-10-01

    The soil CO2 emission is recognized as one of the largest fluxes in the global carbon cycle. Small errors in its estimation can result in large uncertainties and have important consequences for climate model predictions. Monte Carlo approach is efficient for estimating and reducing spatial scale sampling errors. However, that has not been used in soil CO2 emission studies. Here, soil respiration data from 51 PVC collars were measured within farmland cultivated by maize covering 25 km(2) during the growing season. Based on Monte Carlo approach, optimal sample sizes of soil temperature, soil moisture, and soil CO2 emission were determined. And models of soil respiration can be effectively assessed: Soil temperature model is the most effective model to increasing accuracy among three models. The study demonstrated that Monte Carlo approach may improve soil respiration accuracy with limited sample size. That will be valuable for reducing uncertainties of global carbon cycle. PMID:26664693

  1. 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. PMID:27031676

  2. Small sample properties of an adaptive filter with application to low volume statistical process control

    SciTech Connect

    Crowder, S.V.; Eshleman, L.

    1998-08-01

    In many manufacturing environments such as the nuclear weapons complex, emphasis has shifted from the regular production and delivery of large orders to infrequent small orders. However, the challenge to maintain the same high quality and reliability standards white building much smaller lot sizes remains. To meet this challenge, specific areas need more attention, including fast and on-target process start-up, low volume statistical process control, process characterization with small experiments, and estimating reliability given few actual performance tests of the product. In this paper the authors address the issue of low volume statistical process control. They investigate an adaptive filtering approach to process monitoring with a relatively short time series of autocorrelated data. The emphasis is on estimation and minimization of mean squared error rather than the traditional hypothesis testing and run length analyses associated with process control charting. The authors develop an adaptive filtering technique that assumes initial process parameters are unknown, and updates the parameters as more data become available. Using simulation techniques, they study the data requirements (the length of a time series of autocorrelated data) necessary to adequately estimate process parameters. They show that far fewer data values are needed than is typically recommended for process control applications. And they demonstrate the techniques with a case study from the nuclear weapons manufacturing complex.

  3. Small Sample Properties of an Adaptive Filter with Application to Low Volume Statistical Process Control

    SciTech Connect

    CROWDER, STEPHEN V.

    1999-09-01

    In many manufacturing environments such as the nuclear weapons complex, emphasis has shifted from the regular production and delivery of large orders to infrequent small orders. However, the challenge to maintain the same high quality and reliability standards while building much smaller lot sizes remains. To meet this challenge, specific areas need more attention, including fast and on-target process start-up, low volume statistical process control, process characterization with small experiments, and estimating reliability given few actual performance tests of the product. In this paper we address the issue of low volume statistical process control. We investigate an adaptive filtering approach to process monitoring with a relatively short time series of autocorrelated data. The emphasis is on estimation and minimization of mean squared error rather than the traditional hypothesis testing and run length analyses associated with process control charting. We develop an adaptive filtering technique that assumes initial process parameters are unknown, and updates the parameters as more data become available. Using simulation techniques, we study the data requirements (the length of a time series of autocorrelated data) necessary to adequately estimate process parameters. We show that far fewer data values are needed than is typically recommended for process control applications. We also demonstrate the techniques with a case study from the nuclear weapons manufacturing complex.

  4. 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

  5. Spatial scales of optical variability in the coastal ocean: Implications for remote sensing and in situ sampling

    NASA Astrophysics Data System (ADS)

    Moses, Wesley J.; Ackleson, Steven G.; Hair, Johnathan W.; Hostetler, Chris A.; Miller, W. David

    2016-06-01

    Use of ocean color remote sensing to understand the effects of environmental changes and anthropogenic activities on estuarine and coastal waters requires the capability to measure and track optically detectable complex biogeochemical processes. An important remote sensor design consideration is the minimum spatial resolution required to resolve key ocean features of physical and biological significance. The spatial scale of variability in optical properties of coastal waters has been investigated using continuous, along-track measurements collected using instruments deployed from ships, aircraft, and satellites. We defined the average coefficient of variance, CV¯a, within an image pixel as the primary statistical measure of subpixel variability and investigated how CV¯a changes as a function of the Ground Sampling Distance (GSD). In general, dCV¯a/dGSD is positive, indicating that the subpixel variability increases with GSD. The relationship between CV¯a and GSD is generally nonlinear and the greatest rate of change occurs at small spatial scales. Points of distinct transition in the relationship between CV¯a and GSD are evident between 75 and 600 m, varying depending on the location and the optical parameter, and representing the GSD above which most of the spatial variability due to small-scale features is subsumed within a pixel. At GSDs greater than the transition point, most of the small-scale variability occurs at subpixel scales and, therefore, cannot be resolved. On average, the transition GSD is around 200 m. The results have application in both sensor design and in situ sampling strategy in support of coastal remote sensing operations.

  6. 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

  7. 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.

  8. 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.

  9. 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. PMID:26640672

  10. 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.

  11. 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-

  12. 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

  13. Adaptation of Cryo-Sectioning for IEM Labeling of Asymmetric Samples: A Study Using Caenorhabditis elegans.

    PubMed

    Nicolle, Ophélie; Burel, Agnès; Griffiths, Gareth; Michaux, Grégoire; Kolotuev, Irina

    2015-08-01

    Cryo-sectioning procedures, initially developed by Tokuyasu, have been successfully improved for tissues and cultured cells, enabling efficient protein localization on the ultrastructural level. Without a standard procedure applicable to any sample, currently existing protocols must be individually modified for each model organism or asymmetric sample. Here, we describe our method that enables reproducible cryo-sectioning of Caenorhabditis elegans larvae/adults and embryos. We have established a chemical-fixation procedure in which flat embedding considerably simplifies manipulation and lateral orientation of larvae or adults. To bypass the limitations of chemical fixation, we have improved the hybrid cryo-immobilization-rehydration technique and reduced the overall time required to complete this procedure. Using our procedures, precise cryo-sectioning orientation can be combined with good ultrastructural preservation and efficient immuno-electron microscopy protein localization. Also, GFP fluorescence can be efficiently preserved, permitting a direct correlation of the fluorescent signal and its subcellular localization. Although developed for C. elegans samples, our method addresses the challenge of working with small asymmetric samples in general, and thus could be used to improve the efficiency of immuno-electron localization in other model organisms.

  14. 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 participants,…

  15. 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.

  16. 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. PMID:24437470

  17. Thriving while engaging in risk? Examining trajectories of adaptive functioning, delinquency, and substance use in a nationally representative sample of U.S. adolescents.

    PubMed

    Warren, Michael T; Wray-Lake, Laura; Rote, Wendy M; Shubert, Jennifer

    2016-02-01

    Recent advances in positive youth development theory and research explicate complex associations between adaptive functioning and risk behavior, acknowledging that high levels of both co-occur in the lives of some adolescents. However, evidence on nuanced overlapping developmental trajectories of adaptive functioning and risk has been limited to 1 sample of youth and a single conceptualization of adaptive functioning. We build on prior work by utilizing a nationally representative sample of U.S. adolescents (N = 1,665) followed from 7th grade until after high school and using a measure of adaptive functioning that was validated in a secondary sample of older adolescents (N = 93). In using dual trajectory growth mixture modeling to investigate links between developmental trajectories of adaptive functioning and delinquency and substance use, respectively, results provided evidence of heterogeneity in the overlap between adaptive functioning and risk trajectories. Males were more likely to be in the highest adaptive functioning group as well as the most at-risk delinquency class. The magnitude of negative associations between adaptive functioning and both risk behaviors decreased at Wave 3, indicating a decoupling of adaptive functioning and risk as youth aged. These findings converge in underscoring the need to generate a cohesive theory that specifies factors that promote adaptive functioning and risk in concert.

  18. 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

  19. 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

  20. 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.

  1. A Scale-Adaptive Approach for Spatially-Varying Urban Morphology Characterization in Boundary Layer Parametrization Using Multi-Resolution Analysis

    NASA Astrophysics Data System (ADS)

    Mouzourides, P.; Kyprianou, A.; Neophytou, M. K.-A.

    2013-12-01

    Urban morphology characterization is crucial for the parametrization of boundary-layer development over urban areas. One complexity in such a characterization is the three-dimensional variation of the urban canopies and textures, which are customarily reduced to and represented by one-dimensional varying parametrization such as the aerodynamic roughness length and zero-plane displacement . The scope of the paper is to provide novel means for a scale-adaptive spatially-varying parametrization of the boundary layer by addressing this 3-D variation. Specifically, the 3-D variation of urban geometries often poses questions in the multi-scale modelling of air pollution dispersion and other climate or weather-related modelling applications that have not been addressed yet, such as: (a) how we represent urban attributes (parameters) appropriately for the multi-scale nature and multi-resolution basis of weather numerical models, (b) how we quantify the uniqueness of an urban database in the context of modelling urban effects in large-scale weather numerical models, and (c) how we derive the impact and influence of a particular building in pre-specified sub-domain areas of the urban database. We illustrate how multi-resolution analysis (MRA) addresses and answers the afore-mentioned questions by taking as an example the Central Business District of Oklahoma City. The selection of MRA is motivated by its capacity for multi-scale sampling; in the MRA the "urban" signal depicting a city is decomposed into an approximation, a representation at a higher scale, and a detail, the part removed at lower scales to yield the approximation. Different levels of approximations were deduced for the building height and planar packing density . A spatially-varying characterization with a scale-adaptive capacity is obtained for the boundary-layer parameters (aerodynamic roughness length and zero-plane displacement ) using the MRA-deduced results for the building height and the planar packing

  2. Social Daydreaming and Adjustment: An Experience-Sampling Study of Socio-Emotional Adaptation During a Life Transition.

    PubMed

    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.

  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. Differential sampling for fast frequency acquisition via adaptive extended least squares algorithm

    NASA Technical Reports Server (NTRS)

    Kumar, Rajendra

    1987-01-01

    This paper presents a differential signal model along with appropriate sampling techinques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in mesurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can made small.

  5. 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

  6. Evaluating the roles of biotransformation, spatial concentration differences, organism home range, and field sampling design on trophic magnification factors.

    PubMed

    Kim, Jaeshin; Gobas, Frank A P C; Arnot, Jon A; Powell, David E; Seston, Rita M; Woodburn, Kent B

    2016-05-01

    Trophic magnification factors (TMFs) are field-based measurements of the bioaccumulation behavior of chemicals in food-webs. TMFs can provide valuable insights into the bioaccumulation behavior of chemicals. However, bioaccumulation metrics such as TMF may be subject to considerable uncertainty as a consequence of systematic bias and the influence of confounding variables. This study seeks to investigate the role of systematic bias resulting from spatially-variable concentrations in water and sediments and biotransformation rates on the determination of TMF. For this purpose, a multibox food-web bioaccumulation model was developed to account for spatial concentration differences and movement of organisms on chemical concentrations in aquatic biota and TMFs. Model calculated and reported field TMFs showed good agreement for persistent polychlorinated biphenyl (PCB) congeners and biotransformable phthalate esters (PEs) in a marine aquatic food-web. Model testing showed no systematic bias and good precision in the estimation of the TMF for PCB congeners but an apparent underestimation of model calculated TMFs, relative to reported field TMFs, for PEs. A model sensitivity analysis showed that sampling designs that ignore the presence of concentration gradients may cause systematically biased and misleading TMF values. The model demonstrates that field TMFs are most sensitive to concentration gradients and species migration patterns for substances that are subject to a low degree of biomagnification or trophic dilution. The model is useful in anticipating the effect of spatial concentration gradients on the determination of the TMF; guiding species collection strategies in TMF studies; and interpretation of the results of field bioaccumulation studies in study locations where spatial differences in chemical concentration exist.

  7. 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

  8. 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.

  9. Parameterizing Spatial Models of Infectious Disease Transmission that Incorporate Infection Time Uncertainty Using Sampling-Based Likelihood Approximations.

    PubMed

    Malik, Rajat; Deardon, Rob; Kwong, Grace P S

    2016-01-01

    A class of discrete-time models of infectious disease spread, referred to as individual-level models (ILMs), are typically fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework. These models quantify probabilistic outcomes regarding the risk of infection of susceptible individuals due to various susceptibility and transmissibility factors, including their spatial distance from infectious individuals. The infectious pressure from infected individuals exerted on susceptible individuals is intrinsic to these ILMs. Unfortunately, quantifying this infectious pressure for data sets containing many individuals can be computationally burdensome, leading to a time-consuming likelihood calculation and, thus, computationally prohibitive MCMC-based analysis. This problem worsens when using data augmentation to allow for uncertainty in infection times. In this paper, we develop sampling methods that can be used to calculate a fast, approximate likelihood when fitting such disease models. A simple random sampling approach is initially considered followed by various spatially-stratified schemes. We test and compare the performance of our methods with both simulated data and data from the 2001 foot-and-mouth disease (FMD) epidemic in the U.K. Our results indicate that substantial computation savings can be obtained--albeit, of course, with some information loss--suggesting that such techniques may be of use in the analysis of very large epidemic data sets. PMID:26731666

  10. Parameterizing Spatial Models of Infectious Disease Transmission that Incorporate Infection Time Uncertainty Using Sampling-Based Likelihood Approximations

    PubMed Central

    Malik, Rajat; Deardon, Rob; Kwong, Grace P. S.

    2016-01-01

    A class of discrete-time models of infectious disease spread, referred to as individual-level models (ILMs), are typically fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework. These models quantify probabilistic outcomes regarding the risk of infection of susceptible individuals due to various susceptibility and transmissibility factors, including their spatial distance from infectious individuals. The infectious pressure from infected individuals exerted on susceptible individuals is intrinsic to these ILMs. Unfortunately, quantifying this infectious pressure for data sets containing many individuals can be computationally burdensome, leading to a time-consuming likelihood calculation and, thus, computationally prohibitive MCMC-based analysis. This problem worsens when using data augmentation to allow for uncertainty in infection times. In this paper, we develop sampling methods that can be used to calculate a fast, approximate likelihood when fitting such disease models. A simple random sampling approach is initially considered followed by various spatially-stratified schemes. We test and compare the performance of our methods with both simulated data and data from the 2001 foot-and-mouth disease (FMD) epidemic in the U.K. Our results indicate that substantial computation savings can be obtained—albeit, of course, with some information loss—suggesting that such techniques may be of use in the analysis of very large epidemic data sets. PMID:26731666

  11. Multi-Modal Spatial Analysis of Metals within Individual Aerosol Particles Sampled from the Asian Continental Outflow

    NASA Astrophysics Data System (ADS)

    Moffet, R.; Harder, T.; Williams, G.; Chen-Wiegart, Y. C. K.; Furutani, H.; Gilles, M. K.; Laskin, A.; Schoonen, M. A.; Thieme, J.; Uematsu, M.

    2015-12-01

    Aerosols represent an important source of iron and other metals into oceanic surface waters. In some regions of the ocean, the productivity is limited by iron. Thus, iron is an important variable in the carbon cycles of both marine and atmospheric environments. Here, we build upon previous work characterizing the source and oxidation state of iron in atmospheric particles to provide more information on the mineralogy of the iron phases using the newly built Sub-Micron Resolution X-ray Spectroscopy (SRX) beamline at the National Synchrotron Light Source II (NSLS II). The SRX beamline covers energies from 4.6 to 24 keV, allowing mapping of elements from Z=15 (P) to Z=95 (Am) at a sub-micrometer and a sub-100 nm spatial scale. This new method of aerosol analysis will provide outstanding performance for the spectromicroscopy of trace elements. Moreover, this technique will provide multiple modes of detection (fluorescence, absorption, diffraction, and tomographic imaging) to allow for a more complete characterization of the molecular nature of natural samples having nanometer scale structural features. Simultaneously measured X-ray absorption and fluorescence spectra from Asian mineral dust standards and deposited atmospheric particles will be presented. Application of this technique to atmospheric particle samples will broaden the scope of elements over which detailed spectral information can be obtained at a high spatial resolution and will complement existing imaging methods used to determine aerosol chemical and physical properties.

  12. 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.

  13. Avoidance and activation as keys to depression: adaptation of the Behavioral Activation for Depression Scale in a Spanish sample.

    PubMed

    Barraca, Jorge; Pérez-Alvarez, Marino; Lozano Bleda, José Héctor

    2011-11-01

    In this paper we present the adaptation of the Behavioral Activation for Depression Scale (BADS), developed by Kanter, Mulick, Busch, Berlin, and Martell (2007), in a Spanish sample. The psychometric properties were tested in a sample of 263 participants (124 clinical and 139 non-clinical). The results show that, just as in the original English version, the Spanish BADS is a valid and internally consistent scale. Construct validity was examined by correlation with the BDI-II, AAQ, ATQ, MCQ-30, STAI and EROS. Factor analysis justified the four-dimensions of the original instrument (Activation, Avoidance/Rumination, Work/School Impairment and Social Impairment), although with some differences in the factor loadings of the items. Further considerations about the usefulness of the BADS in the clinical treatment of depressed patients are also suggested.

  14. 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.

  15. 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.

  16. Assessment of Different Sampling Methods for Measuring and Representing Macular Cone Density Using Flood-Illuminated Adaptive Optics

    PubMed Central

    Feng, Shu; Gale, Michael J.; Fay, Jonathan D.; Faridi, Ambar; Titus, Hope E.; Garg, Anupam K.; Michaels, Keith V.; Erker, Laura R.; Peters, Dawn; Smith, Travis B.; Pennesi, Mark E.

    2015-01-01

    Purpose To describe a standardized flood-illuminated adaptive optics (AO) imaging protocol suitable for the clinical setting and to assess sampling methods for measuring cone density. Methods Cone density was calculated following three measurement protocols: 50 × 50-μm sampling window values every 0.5° along the horizontal and vertical meridians (fixed-interval method), the mean density of expanding 0.5°-wide arcuate areas in the nasal, temporal, superior, and inferior quadrants (arcuate mean method), and the peak cone density of a 50 × 50-μm sampling window within expanding arcuate areas near the meridian (peak density method). Repeated imaging was performed in nine subjects to determine intersession repeatability of cone density. Results Cone density montages could be created for 67 of the 74 subjects. Image quality was determined to be adequate for automated cone counting for 35 (52%) of the 67 subjects. We found that cone density varied with different sampling methods and regions tested. In the nasal and temporal quadrants, peak density most closely resembled histological data, whereas the arcuate mean and fixed-interval methods tended to underestimate the density compared with histological data. However, in the inferior and superior quadrants, arcuate mean and fixed-interval methods most closely matched histological data, whereas the peak density method overestimated cone density compared with histological data. Intersession repeatability testing showed that repeatability was greatest when sampling by arcuate mean and lowest when sampling by fixed interval. Conclusions We show that different methods of sampling can significantly affect cone density measurements. Therefore, care must be taken when interpreting cone density results, even in a normal population. PMID:26325414

  17. [Characterizing spatial patterns of NO(x), SO2 and O3 in Pearl River Delta by passive sampling].

    PubMed

    Zhao, Yang; Shao, Min; Wang, Chen; Wang, Bo-Guang; Lu, Si-Hua; Zhong, Liu-Ju

    2011-02-01

    Concentrations of NO(x), SO2 and O3 were measured by passive sampling within 200km x 200km grid in Pearl River Delta (PRD). Sampling period was two weeks in November, 2009. Spatial distributions of NO(x), SO2 and O3 were obtained by Kriging interpolation method. The results were compared with emission inventories and modeling results. The transportations of O3 were evaluated by using backward trajectories of air parcels. During the sampling period, the mean concentrations of NO(x), SO2 and O3 were 75.9 microg/m3, 37.3 microg/m3 and 36.2 microg/m3, respectively. And the highest concentrations of NO(x), SO2 and O3 were 195.7 microg/m3, 95.9 microg/m3 and 81.8 microg/m3. Comparing with routine measurements from the regional monitoring network in PRD, the results by passive method were 18.6%, 33.5% and 37.5% lower for NO(x), SO2 and O3, respectively. The spatial patterns demonstrated that higher NO(x) concentrations often appeared in cities such as Guangzhou, Foshan and Shenzhen. SO2 concentrations were higher in west and lower in east. High SO2 concentrations are mainly from emission of power plants and industrial sources. Concentrations of O3 showed the highest levels in the south of PRD. Backward trajectory analysis for higher ozone areas indicated that 53% of the air masses were from the region with high concentration of NO(x). The horizontal transportation caused higher ozone in the south while lower in north in PRD.

  18. 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.

  19. Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain.

    PubMed

    Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

    2016-06-01

    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 produced

  20. Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain.

    PubMed

    Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

    2016-06-01

    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 produced

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. [The short version of Critical Care Family Needs Inventory (CCFNI): adaptation and validation for a spanish sample].

    PubMed

    Gómez-Martíinez, S; Arnal, R Ballester; Juliá, B Gil

    2011-01-01

    Relatives play an important role in the disease process of patients admitted to Intensive Care Units (ICU). It is therefore important to know the needs of people close to the patient in order to try to improve their adaption to a situation as difficult as an ICU admission. The aim of this study was the adaptation and validation of the short version of the Critical Care Family Needs Inventory (CCFNI) for a Spanish sample. The inventory was applied to 55 relatives of patients admitted to the ICU of the Hospital General de Castellón. After the removal of three items for different reasons, we performed an Exploratory Factor Analysis with the 11 remaining items to determine the factor structure of the questionnaire. We also made a descriptive analysis of the items, and internal consistency and construct validity were calculated through Cronbach's α and Pearson correlation coefficient respectively. The results of the principal components factor analysis using varimax rotation indicated a four-factor solution. These four factors corresponded to: medical attention to the patient, personal attention to the relatives, communication between the family and the doctor, and perceived improvements in the Unit. The short version of CCFNI showed good internal consistency for both the total scale and factors. The results suggest that the CCFNI is a suitable measure for assessing the different needs presented by the relatives of patients admitted to an Intensive Care Unit, showing adequate psychometric properties.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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.

  14. Assessing the geographic coverage and spatial clustering of illicit drug users recruited through respondent-driven sampling in New York City.

    PubMed

    Rudolph, Abby E; Young, April M; Lewis, Crystal Fuller

    2015-04-01

    We assess the geographic coverage and spatial clustering of drug users recruited through respondent-driven sampling (RDS) and discuss the potential for biased RDS prevalence estimates. Illicit drug users aged 18-40 were recruited through RDS (N = 401) and targeted street outreach (TSO) (N = 210) in New York City. Using the Google Maps API™, we calculated travel distances and times using public transportation between each participant's recruitment location and the study office and between RDS recruiter-recruit pairs. We used K function analysis to evaluate and compare spatial clustering of (1) RDS vs. TSO respondents and (2) RDS seeds vs. RDS peer recruits. All participant recruitment locations clustered around the study office; however, RDS participants were significantly more likely to be recruited within walking distance of the study office than TSO participants. The TSO sample was also less spatially clustered than the RDS sample, which likely reflects (1) the van's ability to increase the sample's geographic heterogeneity and (2) that more TSO than RDS participants were enrolled on the van. Among RDS participants, individuals recruited spatially proximal peers, geographic coverage did not increase as recruitment waves progressed, and peer recruits were not less spatially clustered than seeds. Using a mobile van to recruit participants had a greater impact on the geographic coverage and spatial dependence of the TSO than the RDS sample. Future studies should consider and evaluate the impact of the recruitment approach on the geographic/spatial representativeness of the sample and how spatial biases, including the preferential recruitment of proximal peers, could impact the precision and accuracy of estimates. PMID:25694223

  15. Assessing the geographic coverage and spatial clustering of illicit drug users recruited through respondent-driven sampling in New York City.

    PubMed

    Rudolph, Abby E; Young, April M; Lewis, Crystal Fuller

    2015-04-01

    We assess the geographic coverage and spatial clustering of drug users recruited through respondent-driven sampling (RDS) and discuss the potential for biased RDS prevalence estimates. Illicit drug users aged 18-40 were recruited through RDS (N = 401) and targeted street outreach (TSO) (N = 210) in New York City. Using the Google Maps API™, we calculated travel distances and times using public transportation between each participant's recruitment location and the study office and between RDS recruiter-recruit pairs. We used K function analysis to evaluate and compare spatial clustering of (1) RDS vs. TSO respondents and (2) RDS seeds vs. RDS peer recruits. All participant recruitment locations clustered around the study office; however, RDS participants were significantly more likely to be recruited within walking distance of the study office than TSO participants. The TSO sample was also less spatially clustered than the RDS sample, which likely reflects (1) the van's ability to increase the sample's geographic heterogeneity and (2) that more TSO than RDS participants were enrolled on the van. Among RDS participants, individuals recruited spatially proximal peers, geographic coverage did not increase as recruitment waves progressed, and peer recruits were not less spatially clustered than seeds. Using a mobile van to recruit participants had a greater impact on the geographic coverage and spatial dependence of the TSO than the RDS sample. Future studies should consider and evaluate the impact of the recruitment approach on the geographic/spatial representativeness of the sample and how spatial biases, including the preferential recruitment of proximal peers, could impact the precision and accuracy of estimates.

  16. A comparison of spatial sampling techniques enabling first principles modeling of a synthetic aperture RADAR imaging platform

    NASA Astrophysics Data System (ADS)

    Gartley, Michael; Goodenough, Adam; Brown, Scott; Kauffman, Russel P.

    2010-04-01

    Simulation of synthetic aperture radar (SAR) imagery may be approached in many different ways. One method treats a scene as a radar cross section (RCS) map and simply evaluates the radar equation, convolved with a system impulse response to generate simulated SAR imagery. Another approach treats a scene as a series of primitive geometric shapes, for which a closed form solution for the RCS exists (such as boxes, spheres and cylinders), and sums their contribution at the antenna level by again solving the radar equation. We present a ray-tracing approach to SAR image simulation that treats a scene as a series of arbitrarily shaped facetized objects, each facet potentially having a unique radio frequency optical property and time-varying location and orientation. A particle based approach, as compared to a wave based approach, presents a challenge for maintaining coherency of sampled scene points between pulses that allows the reconstruction of an exploitable image from the modeled complex phase history. We present a series of spatial sampling techniques and their relative success at producing accurate phase history data for simulations of spotlight, stripmap and SAR-GMTI collection scenarios.

  17. 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.

  18. 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.

  19. Measurement of the Viscoelastic Properties of Damping Materials: Adaptation of the Wave Propagation Method to Test Samples of Short Length

    NASA Astrophysics Data System (ADS)

    LEMERLE, P.

    2002-02-01

    Wave propagation methods allow the deduction of the viscoelastic damping properties of materials from the waveform pattern of a transitory wave: the wave profile is recorded at two travel distances in a thin bar made of the medium studied. In the case of linear viscoelasticity, the characteristics of the material are deduced directly from the transfer function of the two pulses measured. From a theoretical point of view, these methods are of great interest as they bridge a gap between vibratory methods and ultrasonic methods, allowing results to be obtained in a frequency range covering one and a half to two decades in the audiometric range (20 Hz-20 kHz). However, they have not been used much in industrial applications due to the difficulty and cost involved in producing samples in the form of bars. This study shows how this type of method can be adapted to measuring the viscoelastic properties of damping materials using reduced size and common shaped samples such as end-stop buffers.

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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…

  5. A new calculation method adapted to the experimental conditions for determining samples γ-activities induced by 14 MeV neutrons

    NASA Astrophysics Data System (ADS)

    Rzama, A.; Erramli, H.; Misdaq, M. A.

    1994-09-01

    Induced gamma-activities of different disk shaped irradiated samples and standards with 14 MeV neutrons have been determined by using a Monte Carlo calculation method adapted to the experimental conditions. The self-absorption of the multienergetic emitted gamma rays has been taken into account in the final samples activities. The influence of the different activation parameters has been studied. Na, K, Cl and P contents in biological (red beet) samples have been determined.

  6. 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.

  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. 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

  9. 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

  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. 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

  12. 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.

  13. 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. PMID:26205281

  14. 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 Brief…

  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. Determining the spatial autocorrelation of dengue vector populations: influences of mosquito sampling method, covariables, and vector control.

    PubMed

    Azil, Aishah H; Bruce, David; Williams, Craig R

    2014-06-01

    We investigated spatial autocorrelation of female Aedes aegypti L. mosquito abundance from BG-Sentinel trap and sticky ovitrap collections in Cairns, north Queensland, Australia. BG-Sentinel trap collections in 2010 show a significant spatial autocorrelation across the study site and over a smaller spatial extent, while sticky ovitrap collections only indicate a non-significant, weak spatial autocorrelation. The BG-Sentinel trap collections were suitable for spatial interpolation using ordinary kriging and cokriging techniques. The uses of Premise Condition Index and potential breeding container data have helped improve our prediction of vector abundance. Semiovariograms and prediction maps indicate that the spatial autocorrelation of mosquito abundance determined by BG-Sentinel traps extends farther compared to sticky ovitrap collections. Based on our data, fewer BG-Sentinel traps are required to represent vector abundance at a series of houses compared to sticky ovitraps. A lack of spatial structure was observed following vector control treatment in the area. This finding has implications for the design and costs of dengue vector surveillance programs. PMID:24820568

  17. Spatial variation in inversion-focused vs 24-h integrated samples of PM2.5 and black carbon across Pittsburgh, PA

    PubMed Central

    Tunno, Brett J; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Cambal, Leah; Tripathy, Sheila; Gillooly, Sara; Roper, Courtney; Chubb, Lauren; Clougherty, Jane E

    2016-01-01

    A growing literature explores intra-urban variation in pollution concentrations. Few studies, however, have examined spatial variation during “peak” hours of the day (e.g., rush hours, inversion conditions), which may have strong bearing for source identification and epidemiological analyses. We aimed to capture “peak” spatial variation across a region of complex terrain, legacy industry, and frequent atmospheric inversions. We hypothesized stronger spatial contrast in concentrations during hours prone to atmospheric inversions and heavy traffic, and designed a 2-year monitoring campaign to capture spatial variation in fine particles (PM2.5) and black carbon (BC). Inversion-focused integrated monitoring (0600–1100 hours) was performed during year 1 (2011–2012) and compared with 1-week 24-h integrated results from year 2 (2012–2013). To allocate sampling sites, we explored spatial distributions in key sources (i.e., traffic, industry) and potential modifiers (i.e., elevation) in geographic information systems (GIS), and allocated 37 sites for spatial and source variability across the metropolitan domain (~388 km2). Land use regression (LUR) models were developed and compared by pollutant, season, and sampling method. As expected, we found stronger spatial contrasts in PM2.5 and BC using inversion-focused sampling, suggesting greater differences in peak exposures across urban areas than is captured by most integrated saturation campaigns. Temporal variability, commercial and industrial land use, PM2.5 emissions, and elevation were significant predictors, but did not more strongly predict concentrations during peak hours. PMID:25921079

  18. Spatial variation in inversion-focused vs 24-h integrated samples of PM2.5 and black carbon across Pittsburgh, PA.

    PubMed

    Tunno, Brett J; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Cambal, Leah; Tripathy, Sheila; Gillooly, Sara; Roper, Courtney; Chubb, Lauren; Clougherty, Jane E

    2016-06-01

    A growing literature explores intra-urban variation in pollution concentrations. Few studies, however, have examined spatial variation during "peak" hours of the day (e.g., rush hours, inversion conditions), which may have strong bearing for source identification and epidemiological analyses. We aimed to capture "peak" spatial variation across a region of complex terrain, legacy industry, and frequent atmospheric inversions. We hypothesized stronger spatial contrast in concentrations during hours prone to atmospheric inversions and heavy traffic, and designed a 2-year monitoring campaign to capture spatial variation in fine particles (PM2.5) and black carbon (BC). Inversion-focused integrated monitoring (0600-1100 hours) was performed during year 1 (2011-2012) and compared with 1-week 24-h integrated results from year 2 (2012-2013). To allocate sampling sites, we explored spatial distributions in key sources (i.e., traffic, industry) and potential modifiers (i.e., elevation) in geographic information systems (GIS), and allocated 37 sites for spatial and source variability across the metropolitan domain (~388 km(2)). Land use regression (LUR) models were developed and compared by pollutant, season, and sampling method. As expected, we found stronger spatial contrasts in PM2.5 and BC using inversion-focused sampling, suggesting greater differences in peak exposures across urban areas than is captured by most integrated saturation campaigns. Temporal variability, commercial and industrial land use, PM2.5 emissions, and elevation were significant predictors, but did not more strongly predict concentrations during peak hours. PMID:25921079

  19. Development of an Abbreviated Form of the Penn Line Orientation Test Using Large Samples and Computerized Adaptive Test Simulation

    PubMed Central

    Moore, Tyler M.; Scott, J. Cobb; Reise, Steven P.; Port, Allison M.; Jackson, Chad T.; Ruparel, Kosha; Savitt, Adam P.; Gur, Raquel E.; Gur, Ruben C.

    2015-01-01

    Visuospatial processing is a commonly assessed neurocognitive domain, with deficits linked to dysfunction in right posterior regions of the brain. With the growth of large-scale clinical research studies there is an increased need for efficient and scalable assessments of neurocognition, including visuospatial processing. The purpose of the current study was to use a novel method that combines item response theory (IRT) and computerized adaptive testing (CAT) approaches to create an abbreviated form of the computerized Penn Line Orientation Test (PLOT). The 24-item PLOT was administered to 8,498 youths (aged 8 to 21) as part of the Philadelphia Neurodevelopmental Cohort study and, by web-based data collection, in an independent sample of 4,593 adults from Great Britain as part of a television documentary. IRT-based CAT simulations were used to select the best PLOT items for an abbreviated form by performing separate simulations in each group and choosing only items that were selected as useful (i.e., high item discrimination and in the appropriate difficulty range) in at least one of the simulations. Fifteen items were chosen for the final, short form of the PLOT, indicating substantial agreement among the models in how they evaluated each item's usefulness. Moreover, this abbreviated version performed comparably to the full version in tests of sensitivity to age and sex effects. This abbreviated version of the PLOT cuts administration time by 50% without detectable loss of information, which points to its feasibility for large-scale clinical and genomic studies. PMID:25822834

  20. Analysis of the effect of spatial and temporal sampling densities on accuracy of predicting the heating profile in windrowed broiler litter

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A standard method for monitoring temperature in windrow piles of broiler litter to predict microbial population reductions is described. Temperature data collected every 2 min on a 10 cm x 10 cm spatial sampling grid in five identically-constructed litter windrow piles was utilized in this study. ...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. Evaluating spatial memory function in mice: a within-subjects comparison between the water maze test and its adaptation to dry land.

    PubMed

    Llano Lopez, L; Hauser, J; Feldon, J; Gargiulo, P A; Yee, B K

    2010-05-01

    The Morris water maze (WM) is a common spatial memory test in rats. It has been adapted for evaluating genetic manipulations in mice. One major acknowledged problem of this cross-species translation is floating. We investigated here in mice the feasibility and practicality of an alternative paradigm-the cheeseboard (CB), which is a dry version of the WM, in a within-subject design allowing direct comparison with the conventional WM. Under identical task demands (reference or working memory), mice learned in the CB as efficiently as in the WM. Furthermore, individual differences in learning rate correlated between the two reference memory tests conducted separately in the two mazes. However, no such correlation was found with respect to reference memory retention or working memory performance. This study demonstrated that the CB is an effective alternative to the WM as spatial cognition test. Additional tests in the CB confirmed that the mice relied on extra maze cues in their spatial search. We would recommend the CB as a valuable addition to, rather than a replacement of the WM in phenotyping transgenic mice, because the two apparatus might diverge in the ability to detect individual differences in various domains of mnemonic functions.

  6. Effect of Site Level Environmental Variables, Spatial Autocorrelation and Sampling Intensity on Arthropod Communities in an Ancient Temperate Lowland Woodland Area

    PubMed Central

    Horak, Jakub

    2013-01-01

    The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment. PMID:24349087

  7. Effect of site level environmental variables, spatial autocorrelation and sampling intensity on arthropod communities in an ancient temperate lowland woodland area.

    PubMed

    Horak, Jakub

    2013-01-01

    The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.

  8. 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.

  9. 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. PMID:25779553

  10. Polarizing phase shifting interferometry of total internal reflection light for measurement of refractive index and its spatial variation in liquid samples

    NASA Astrophysics Data System (ADS)

    Das, Tania; Bhattacharya, Kallol

    2016-07-01

    It is well known that the phase change in total internal reflection (TIR) is a function of the refractive indices of the pair of media involved. The spatial phase variations in a totally internally reflected beam are accurately measured using a Mach Zehnder interferometer employing polarization phase shifting technique. The evaluated phase change is then related to the refractive index variations of the rarer medium. One of the salient features of the proposed technique is that, unlike most interferometric methods where the measured phase is a function of the sample thickness, TIR phase is independent of the sample thickness as long as the evanescent wave field is fully confined within the sample. The theory of the technique is discussed and experimental results showing the three-dimensional profiles of the measured refractive indices and its spatial variations are presented.

  11. 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

  12. Prism adaptation aftereffects in stroke patients with spatial neglect: Pathological effects on subjective straight ahead but not visual open-loop pointing

    PubMed Central

    Sarri, Margarita; Greenwood, Richard; Kalra, Lalit; Papps, Ben; Husain, Masud; Driver, Jon

    2008-01-01

    Prism adaptation to rightward optical shifts during visually guided pointing is considered a promising intervention in right-hemisphere stroke patients with left spatial neglect. Conventionally, prism adaptation is assessed via aftereffects, on subjective straight ahead (SSA) pointing with eyes closed; or by visual open-loop pointing (VOL), i.e. pointing to a visual target without seeing the hand. Previous data suggest indirectly that prism aftereffects in neglect patients may be larger (pathologically so) when assessed by SSA than by VOL. But these measures have never been directly compared within the same patients after identical prism exposure. Accordingly we implemented both measures here within the same group of 13 neglect patients and 13 controls. Prism aftereffects were much larger for SSA than VOL in neglect patients, falling outside the normative range only for SSA. This may arise because the SSA task can itself involve aspects of neglect that may be ameliorated by the prism intervention, hence showing abnormal changes after prisms. The extent of SSA change after prisms varied between patients, and correlated with improvements on a standard cancellation measure for neglect. The lesions of patients who did versus did not show neglect improvement immediately after prisms provide an initial indication that lack of improvement may potentially relate to cortical damage in right intraparietal sulcus and white matter damage in inferior parietal lobe and middle frontal gyrus. Future studies of possible rehabilitative impact from prisms upon neglect may need to consider carefully how to measure prism adaptation per se, separately from any impact of such adaptation upon manifestations of neglect. PMID:18083203

  13. Exploratory studies of PM10 receptor and source profiling by GC/MS and principal component analysis of temporally and spatially resolved ambient samples.

    PubMed

    Jeon, S J; Meuzelaar, H L; Sheya, S A; Lighty, J S; Jarman, W M; Kasteler, C; Sarofim, A F; Simoneit, B R

    2001-05-01

    For a recent exploratory study of particulate matter (PM) compositions, origins, and impacts in the El Paso/Juarez (Paso del Norte) airshed, the authors relied on solvent extraction (SX)-gas chromatography/mass spectrometry (GC/MS) procedures to characterize 24-hr quartz fiber (QF) filter samples obtained from nine spatially distributed high-volume (Hi-Vol) PM10 samplers as well as on thermal desorption (TD)-GC/MS methods to characterize 45 time-resolved (2-hr) filter samples obtained with modified 1-m3/hr PM10 samplers. Principal component analysis and related chemometric techniques were used for data reduction and data fusion as well as for multiway data correlation. A high degree of correspondence (R2 = 0.821) was found between the rapid TD-GC/MS method (which can be carried out on 2-hr filter slices containing only microgram amounts of sample) and conventional SX-GC/MS procedures. The four main source patterns of organic PM components observed in GC/MS profiles of both temporally and spatially resolved receptor samples obtained in the El Paso/Juarez border airshed during the study period are interpreted to represent (1) vehicular emissions plus resuspended urban dust; (2) biomass combustion; (3) native vegetation detritus and resuspended agricultural dust; and (4) waste burning. Moreover, principal component analysis of combined, variance-weighted, temporally resolved TD-GC/MS data and spatially resolved SX-GC/MS data was used to determine approximate source locations for specific PM components identified in time-resolved receptor sample profiles. The same approach can be used to determine approximate circadian concentration profiles of specific PM components identified in spatially resolved receptor sample profiles.

  14. 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.

  15. 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.

  16. Luminance and opponent-color contributions to visual detection and adaptation and to temporal and spatial integration.

    PubMed

    King-Smith, P E; Carden, D

    1976-07-01

    We show how the processes of visual detection and of temporal and spatial summation may be analyzed in terms of parallel luminance (achromatic) and opponent-color systems; a test flash is detected if it exceeds the threshold of either system. The spectral sensitivity of the luminance system may be determined by a flicker method, and has a single broad peak near 555 nm; the spectral sensitivity of the opponent-color system corresponds to the color recognition threshold, and has three peaks at about 440, 530, and 600 nm (on a white background). The temporal and spatial integration of the opponent-color system are generally greater than for the luminance system; further, a white background selectively depresses the sensitivity of the luminance system relative to the opponent-color system. Thus relatively large (1 degree) and long (200 msec) spectral test flashes on a white background are detected by the opponent-color system except near 570 nm; the contribution of the luminance system becomes more prominent if the size or duration of the test flash is reduced, or if the white background is extinguished. The present analysis is discussed in relation to Stiles' model of independent eta mechanisms.

  17. Spatial Patterns of bphA Gene Diversity Reveal Local Adaptation of Microbial Communities to PCB and PAH Contaminants.

    PubMed

    Hoostal, Matthew J; Bouzat, Juan L

    2016-10-01

    Biphenyl dioxygenases, encoded by the bphA gene, initiate the oxidation of polychlorinated biphenyls (PCBs) and specify the substrate range of PCB congeners metabolized by bacteria. Increased bphA gene diversity within microbial communities may allow a broader range of PCB congeners to be catabolized, thus resulting in greater PCB degradation. To assess the role of PCBs in modulating bphA gene diversity, 16S ribosomal RNA (rRNA) gene and bphA environmental DNA libraries were generated from bacterial communities in sediments with a steep gradient of PCB contamination. Multiple measures of sequence diversity revealed greater heterogeneity of bphA sequences in polluted compared to unpolluted locations. Codon-based signatures of selection in bphA sequences provided evidence of purifying selection. Unifrac analysis of 16S rRNA sequences revealed independent taxonomic lineages from polluted and unpolluted locations, consistent with the presence of locally adapted bacterial communities. Phylogenetic analysis of bphA sequences indicated that dioxygenases from sediments were closely related to previously characterized dioxygenases that metabolize PCBs and polynuclear aromatic hydrocarbons (PAHs), consistent with high levels of these contaminants within the studied sediments. Structural analyses indicated that the BphA protein of Rhodococcus jostii, capable of metabolizing both PCBs and PAHs, provided a more optimal modeling template for bphA sequences reported in this study than a BphA homologue with more restricted substrate specificity. Results from this study suggest that PCBs and PAHs may drive local adaptation of microbial communities by acting as strong selective agents for biphenyl dioxygenases capable of metabolizing a wide range of congeners.

  18. Testing Set-Point Theory in a Swiss National Sample: Reaction and Adaptation to Major Life Events.

    PubMed

    Anusic, Ivana; Yap, Stevie C Y; Lucas, Richard E

    2014-12-01

    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.

  19. 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.

  20. Nonbulk motion system for simultaneously measuring the refractive index and thickness of a sample using tunable optics and spatial signal processing-based Gaussian beam imaging.

    PubMed

    Reza, Syed Azer; Qasim, Muhammad

    2016-01-10

    This paper presents a novel approach to simultaneously measuring the thickness and refractive index of a sample. The design uses an electronically controlled tunable lens (ECTL) and a microelectromechanical-system-based digital micromirror device (DMD). The method achieves the desired results by using the DMD to characterize the spatial profile of a Gaussian laser beam at different focal length settings of the ECTL. The ECTL achieves tunable lensing through minimal motion of liquid inside a transparent casing, whereas the DMD contains an array of movable micromirrors, which make it a reflective spatial light modulator. As the proposed system uses an ECTL, a DMD, and other fixed optical components, it measures the thickness and refractive index without requiring any motion of bulk components such as translational and rotational stages. A motion-free system improves measurement repeatability and reliability. Moreover, the measurement of sample thickness and refractive index can be completely automated because the ECTL and DMD are controlled through digital signals. We develop and discuss the theory in detail to explain the measurement methodology of the proposed system and present results from experiments performed to verify the working principle of the method. Refractive index measurement accuracies of 0.22% and 0.2% were achieved for two BK-7 glass samples used, and the thicknesses of the two samples were measured with a 0.1 mm accuracy for each sample, corresponding to a 0.39% and 0.78% measurement error, respectively, for the aforementioned samples.

  1. 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.

  2. Adaptive beamforming at very low frequencies in spatially coherent, cluttered noise environments with low signal-to-noise ratio and finite-averaging times

    PubMed

    Nuttall; Wilson

    2000-11-01

    Realistic simulations with spatially coherent noise have been run in order to compare the performance of adaptive beamforming (ABF), inverse beamforming (IBF), and conventional beamforming (CBF) for the case of finite-averaging times, where the actual spatial coherence of the acoustic field, or covariance matrix, is not known a priori, but must be estimated. These estimation errors cause large errors in the ABF estimate of the directionality of the acoustic field, partly because ABF is a highly nonlinear algorithm. In addition, it is shown that ABF is fundamentally limited in its suppression capability at very low frequency (VLF), based on the sidelobe level of the conventional beampattern in the direction of the noise interferer [G. L. Mohnkern, "Effects of Errors and Limitations on Interference Suppression," NOSC Technical Document 1478, Naval Ocean Systems Center (1989)]. The simulations include a low-level plane wave signal of interest, a stronger noise plane wave interferer, and spatially random background noise. Both IBF and ABF performed significantly better than CBF, and IBF's performance was slightly better than ABF's performance. The performances of IBF and the ABF algorithm, the minimum variance distortionless response (MVDR) [A. H. Nuttall and D. W. Hyde, "Unified Approach to Optimum and Suboptimum Processing for Arrays," USL Report Number 992, Naval Underwater Systems Center, New London, CT (22 April 1969)] were recently compared independently [J. S. D. Solomon, A. J. Knight, and M. V. Greening, "Sonar Array Signal Processing for Sparse Linear Arrays," Defense Science and Technology Organization (DSTO) Technical Report (June 1999)] using measured data, with the result that IBF outperformed MVDR. This result is significant because MVDR requires orders of magnitude more processing power than IBF or CBF.

  3. 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

  4. Coping with spatial heterogeneity and temporal variability in resources and risks: adaptive movement behaviour by a large grazing herbivore.

    PubMed

    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.

  5. Spatial and seasonal toxicity in a stormwater management facility: evidence obtained by adapting an integrated sediment quality assessment approach.

    PubMed

    Tixier, Guillaume; Rochfort, Quintin; Grapentine, Lee; Marsalek, Jiri; Lafont, Michel

    2012-12-15

    Stormwater ponds have been widely used to control increased surface runoff resulting from urbanization, and to enhance runoff quality. As receiving waters, they are impacted by intermittent stormwater pollution while also serving as newly created aquatic habitats, which partly offset changes of aquatic ecosystems and their biodiversity by urbanization. Thus, determining ecological risks in stormwater ponds is important for the preservation and rehabilitation of biodiversity in urban areas. Limitations of the conventional toxicity assessment techniques in stormwater ponds have led us to use the sediment quality triad approach with the specific analyses of oligochaetes. The latter analyses build on the earlier work by the Cemagref (Lyon, France) and use the oligochaetes as bioindicators of the sediment quality. This integrative approach was tested at eight sites in the Terraview-Willowfield stormwater facility in Toronto, Ontario, in all four seasons (summer 2008-spring 2009). The facility receives direct runoff from the MacDonald-Cartier freeway with a traffic intensity of 340,000 vehicles/d. Sediment chemistry results indicate that several heavy metals and PAH compounds exceeded the Ontario sediment quality guidelines in the facility. Regardless of the season, laboratory bioassays revealed a strong spatial variation in sediment toxicity along the flow path from the inlet to the outlet, agreeing with decreasing concentrations of contaminants in sediment, especially of heavy metals. However, in situ assessments of the benthic macroinvertebrate community structure and in particular of the oligochaete community revealed an overriding influence of seasonally varying toxicity. This seasonal pattern was described as high toxicity in spring and recovery in fall and corresponded to the influx and flushing-out of road salts and of several heavy metals within the facility.

  6. Spatial and seasonal toxicity in a stormwater management facility: evidence obtained by adapting an integrated sediment quality assessment approach.

    PubMed

    Tixier, Guillaume; Rochfort, Quintin; Grapentine, Lee; Marsalek, Jiri; Lafont, Michel

    2012-12-15

    Stormwater ponds have been widely used to control increased surface runoff resulting from urbanization, and to enhance runoff quality. As receiving waters, they are impacted by intermittent stormwater pollution while also serving as newly created aquatic habitats, which partly offset changes of aquatic ecosystems and their biodiversity by urbanization. Thus, determining ecological risks in stormwater ponds is important for the preservation and rehabilitation of biodiversity in urban areas. Limitations of the conventional toxicity assessment techniques in stormwater ponds have led us to use the sediment quality triad approach with the specific analyses of oligochaetes. The latter analyses build on the earlier work by the Cemagref (Lyon, France) and use the oligochaetes as bioindicators of the sediment quality. This integrative approach was tested at eight sites in the Terraview-Willowfield stormwater facility in Toronto, Ontario, in all four seasons (summer 2008-spring 2009). The facility receives direct runoff from the MacDonald-Cartier freeway with a traffic intensity of 340,000 vehicles/d. Sediment chemistry results indicate that several heavy metals and PAH compounds exceeded the Ontario sediment quality guidelines in the facility. Regardless of the season, laboratory bioassays revealed a strong spatial variation in sediment toxicity along the flow path from the inlet to the outlet, agreeing with decreasing concentrations of contaminants in sediment, especially of heavy metals. However, in situ assessments of the benthic macroinvertebrate community structure and in particular of the oligochaete community revealed an overriding influence of seasonally varying toxicity. This seasonal pattern was described as high toxicity in spring and recovery in fall and corresponded to the influx and flushing-out of road salts and of several heavy metals within the facility. PMID:22212882

  7. Estimating number of species and relative abundances in stream-fish communities: effects of sampling effort and discontinuous spatial distributions

    USGS Publications Warehouse

    Angermeier, Paul L.; Smogor, Roy A.

    1995-01-01

    We sampled fishes and measured microhabitat in series of contiguous habitat units (riffles, runs, pools) in three Virginia streams. We used Monte Carlo simulations to construct hypothetical series of habitat units, then examined how number of species, similarity in relative abundances, and number of microhabitats accumulated with increasing number of habitat units (i.e., sampling effort). Proportions of all species and microhabitats represented were relatively low and variable at low sampling effort, but increased asymptotically and became less variable with greater sampling effort. To facilitate comparisons among streams, we fitted simulation results to negative exponential curves. The curves indicated that 90% of the species present were usually found by sampling 5 to 14 habitat units (stream length of 22–67 stream widths). Estimates of species relative abundances required less sampling effort for a given accuracy than estimates of number of species. Rates of species accumulation (with effort) varied among streams and reflected discontinuity in species distributions among habitat units. Most discontinuity seemed to be due to low population density rather than to habitat selectivity. Results from an Illinois stream corroborated our findings from Virginia, and suggested that greater sampling effort is needed to characterize fish community structure in more homogeneous stream reaches.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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. PMID:25368044

  13. 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

  14. 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.

  15. 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.

  16. Assessment of the spatial and temporal distribution of legacy persistent organic pollutants and recommendations for sample collection from the surficial sediments of estuaries and seas in China.

    PubMed

    Peng, Lihong; Dai, Xuhong; Yu, Ang

    2015-01-01

    With the rapid economic development in China, environmental pollution has become a major concern, particularly pollution by persistent organic pollutants (POPs). Thus, these pollutants must be monitored over the long term. In this study, we analyze the distribution levels and sources of POPs in the surficial sediments of Chinese estuaries and seas. Results showed that POPs in sediments significantly distribute spatially and temporally. Furthermore, POPs not only concentrate in densely populated cities, bays, and industrial areas, but also follow the natural distribution of and temporal changes in local industrial structures. Hence, we recommend sampling sites and frequencies to monitor POPs in China over the long term and to defer their analysis.

  17. Sample selection and spatial models of housing price indexes, and, A disequilibrium analysis of the U.S. gasoline market using panel data