Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

A realistic host-vector transmission model for describing malaria prevalence pattern.

PubMed

Mandal, Sandip; Sinha, Somdatta; Sarkar, Ram Rup

2013-12-01

Malaria continues to be a major public health concern all over the world even after effective control policies have been employed, and considerable understanding of the disease biology have been attained, from both the experimental and modelling perspective. Interactions between different general and local processes, such as dependence on age and immunity of the human host, variations of temperature and rainfall in tropical and sub-tropical areas, and continued presence of asymptomatic infections, regulate the host-vector interactions, and are responsible for the continuing disease prevalence pattern.In this paper, a general mathematical model of malaria transmission is developed considering short and long-term age-dependent immunity of human host and its interaction with pathogen-infected mosquito vector. The model is studied analytically and numerically to understand the role of different parameters related to mosquitoes and humans. To validate the model with a disease prevalence pattern in a particular region, real epidemiological data from the north-eastern part of India was used, and the effect of seasonal variation in mosquito density was modelled based on local climactic data. The model developed based on general features of host-vector interactions, and modified simply incorporating local environmental factors with minimal changes, can successfully explain the disease transmission process in the region. This provides a general approach toward modelling malaria that can be adapted to control future outbreaks of malaria.

Quantization and symmetry in periodic coverage patterns with applications to earth observation. [for satellite ground tracks

NASA Technical Reports Server (NTRS)

King, J. C.

1975-01-01

The general orbit-coverage problem in a simplified physical model is investigated by application of numerical approaches derived from basic number theory. A system of basic and general properties is defined by which idealized periodic coverage patterns may be characterized, classified, and delineated. The principal common features of these coverage patterns are their longitudinal quantization, determined by the revolution number R, and their overall symmetry.

Toward a Conceptual Pattern in Librarianship: A Model.

ERIC Educational Resources Information Center

Nitecki, Joseph Z.

1970-01-01

In an attempt to import some concepts from general systems theory to the theory of librarianship, basic elements in the theory of librarianship were identified, interrelated in a form of a static model, and projected into a possible, dynamic pattern of change. (Author/LS)

Dietary Pattern Is Associated with Obesity in Older People in China: Data from China Health and Nutrition Survey (CHNS).

PubMed

Xu, Xiaoyue; Hall, John; Byles, Julie; Shi, Zumin

2015-09-23

No studies have been conducted to explore the associations between dietary patterns and obesity among older Chinese people, by considering gender and urbanization level differences. We analyzed data from the 2009 China Health and Nutrition Survey (2745 individuals, aged ≥ 60 years). Dietary data were obtained using 24 hour-recall over three consecutive days. Height, Body Weight, and Waist Circumference were measured. Exploratory factor analysis was used to identify dietary patterns. Multinomial and Poisson regression models were used to examine the association between dietary patterns and Body Mass Index (BMI) status/central obesity. The prevalence of general and central obesity was 9.5% and 53.4%. Traditional dietary pattern (high intake of rice, pork and vegetables) was inversely associated with general/central obesity; modern dietary pattern (high intake of fruit, fast food, and processed meat) was positively associated with general/central obesity. The highest quartile of traditional dietary pattern had a lower risk of general/central obesity compared with the lowest quartile, while an inverse picture was found for the modern dietary pattern. These associations were consistent by gender and urbanization levels. Dietary patterns are associated with general/central obesity in older Chinese. This study reinforces the importance of a healthy diet in promoting healthy ageing in China.

Segments and segmental properties in cross-language perception: Korean perception of English obstruents in various prosodic locations

NASA Astrophysics Data System (ADS)

de Jong, Kenneth; Silbert, Noah; Park, Hanyong

2004-05-01

Experimental models of cross-language perception and second-language acquisition (such as PAM and SLM) typically treat language differences in terms of whether the two languages share phonological segmental categories. Linguistic models, by contrast, generally examine properties which cross classify segments, such as features, rules, or prosodic constraints. Such models predict that perceptual patterns found for one segment will generalize to other segments of the same class. This paper presents perceptual identifications of Korean listeners to a set of voiced and voiceless English stops and fricatives in various prosodic locations to determine the extent to which such generality occurs. Results show some class-general effects; for example, voicing identification patterns generalize from stops, which occur in Korean, to nonsibilant fricatives, which are new to Korean listeners. However, when identification is poor, there are clear differences between segments within the same class. For example, in identifying stops and fricatives, both point of articulation and prosodic position bias perceptions; coronals are more often labeled fricatives, and syllable initial obstruents are more often labeled stops. These results suggest that class-general perceptual patterns are not a simple consequence of the structure of the perceptual system, but need to be acquired by factoring out within-class differences.

Airborne antenna pattern calculations

NASA Technical Reports Server (NTRS)

Knerr, T. J.; Mielke, R. R.

1981-01-01

Progress on the development of modeling software, testing software against caclulated data from program VPAP and measured patterns, and calculating roll plane patterns for general aviation aircraft is reported. Major objectives are the continued development of computer software for aircraft modeling and use of this software and program OSUVOL to calculate principal plane and volumetric radiation patterns. The determination of proper placement of antennas on aircraft to meet the requirements of the Microwave Landing System is discussed. An overview of the performed work, and an example of a roll plane model for the Piper PA-31T Cheyenne aircraft and the resulting calculated roll plane radiation pattern are included.

A 1D-2D Shallow Water Equations solver for discontinuous porosity field based on a Generalized Riemann Problem

NASA Astrophysics Data System (ADS)

Ferrari, Alessia; Vacondio, Renato; Dazzi, Susanna; Mignosa, Paolo

2017-09-01

A novel augmented Riemann Solver capable of handling porosity discontinuities in 1D and 2D Shallow Water Equation (SWE) models is presented. With the aim of accurately approximating the porosity source term, a Generalized Riemann Problem is derived by adding an additional fictitious equation to the SWEs system and imposing mass and momentum conservation across the porosity discontinuity. The modified Shallow Water Equations are theoretically investigated, and the implementation of an augmented Roe Solver in a 1D Godunov-type finite volume scheme is presented. Robust treatment of transonic flows is ensured by introducing an entropy fix based on the wave pattern of the Generalized Riemann Problem. An Exact Riemann Solver is also derived in order to validate the numerical model. As an extension of the 1D scheme, an analogous 2D numerical model is also derived and validated through test cases with radial symmetry. The capability of the 1D and 2D numerical models to capture different wave patterns is assessed against several Riemann Problems with different wave patterns.

Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model

ERIC Educational Resources Information Center

Jeon, Minjeong; De Boeck, Paul; van der Linden, Wim

2017-01-01

We present a novel application of a generalized item response tree model to investigate test takers' answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated…

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

2017-01-01

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

High-dimensional inference with the generalized Hopfield model: principal component analysis and corrections.

PubMed

Cocco, S; Monasson, R; Sessak, V

2011-05-01

We consider the problem of inferring the interactions between a set of N binary variables from the knowledge of their frequencies and pairwise correlations. The inference framework is based on the Hopfield model, a special case of the Ising model where the interaction matrix is defined through a set of patterns in the variable space, and is of rank much smaller than N. We show that maximum likelihood inference is deeply related to principal component analysis when the amplitude of the pattern components ξ is negligible compared to √N. Using techniques from statistical mechanics, we calculate the corrections to the patterns to the first order in ξ/√N. We stress the need to generalize the Hopfield model and include both attractive and repulsive patterns in order to correctly infer networks with sparse and strong interactions. We present a simple geometrical criterion to decide how many attractive and repulsive patterns should be considered as a function of the sampling noise. We moreover discuss how many sampled configurations are required for a good inference, as a function of the system size N and of the amplitude ξ. The inference approach is illustrated on synthetic and biological data.

Effects of prompting and reinforcement of one response pattern upon imitation of a different modeled pattern

PubMed Central

Bondy, Andrew S.

1982-01-01

Twelve preschool children participated in a study of the effects of explicit training on the imitation of modeled behavior. The responses trained involved a marble-dropping pattern that differed from the modeled pattern. Training consisted of physical prompts and verbal praise during a single session. No prompts or praise were used during test periods. After operant levels of the experimental responses were measured, training either preceded or was interposed within a series of exposures to modeled behavior that differed from the trained behavior. Children who were initially exposed to a modeling session immediately imitated, whereas those children who were initially trained immediately performed the appropriate response. Children initially trained on one pattern generally continued to exhibit that pattern even after many modeling sessions. Children who first viewed the modeled response and then were exposed to explicit training of a different response reversed their response pattern from the trained response to the modeled response within a few sessions. The results suggest that under certain conditions explicit training will exert greater control over responding than immediate modeling stimuli. PMID:16812260

Dietary Pattern Is Associated with Obesity in Older People in China: Data from China Health and Nutrition Survey (CHNS)

PubMed Central

Xu, Xiaoyue; Hall, John; Byles, Julie; Shi, Zumin

2015-01-01

Background: No studies have been conducted to explore the associations between dietary patterns and obesity among older Chinese people, by considering gender and urbanization level differences. Methods: We analyzed data from the 2009 China Health and Nutrition Survey (2745 individuals, aged ≥ 60 years). Dietary data were obtained using 24 h-recall over three consecutive days. Height, Body Weight, and Waist Circumference were measured. Exploratory factor analysis was used to identify dietary patterns. Multinomial and Poisson regression models were used to examine the association between dietary patterns and Body Mass Index (BMI) status/central obesity. Results: The prevalence of general and central obesity was 9.5% and 53.4%. Traditional dietary pattern (high intake of rice, pork and vegetables) was inversely associated with general/central obesity; modern dietary pattern (high intake of fruit, fast food, and processed meat) was positively associated with general/central obesity. The highest quartile of traditional dietary pattern had a lower risk of general/central obesity compared with the lowest quartile, while an inverse picture was found for the modern dietary pattern. These associations were consistent by gender and urbanization levels. Conclusions: Dietary patterns are associated with general/central obesity in older Chinese. This study reinforces the importance of a healthy diet in promoting healthy ageing in China. PMID:26404368

Modeling the radiation pattern of LEDs.

PubMed

Moreno, Ivan; Sun, Ching-Cherng

2008-02-04

Light-emitting diodes (LEDs) come in many varieties and with a wide range of radiation patterns. We propose a general, simple but accurate analytic representation for the radiation pattern of the light emitted from an LED. To accurately render both the angular intensity distribution and the irradiance spatial pattern, a simple phenomenological model takes into account the emitting surfaces (chip, chip array, or phosphor surface), and the light redirected by both the reflecting cup and the encapsulating lens. Mathematically, the pattern is described as the sum of a maximum of two or three Gaussian or cosine-power functions. The resulting equation is widely applicable for any kind of LED of practical interest. We accurately model a wide variety of radiation patterns from several world-class manufacturers.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

PubMed

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher; Gail, Alexander

2015-04-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. Copyright © 2015 the American Physiological Society.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model

PubMed Central

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher

2015-01-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement (“jump”) consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. PMID:25609106

Patterns of breast cancer mortality trends in Europe.

PubMed

Amaro, Joana; Severo, Milton; Vilela, Sofia; Fonseca, Sérgio; Fontes, Filipa; La Vecchia, Carlo; Lunet, Nuno

2013-06-01

To identify patterns of variation in breast cancer mortality in Europe (1980-2010), using a model-based approach. Mortality data were obtained from the World Health Organization database and mixed models were used to describe the time trends in the age-standardized mortality rates (ASMR). Model-based clustering was used to identify clusters of countries with homogeneous variation in ASMR. Three patterns were identified. Patterns 1 and 2 are characterized by stable or slightly increasing trends in ASMR in the first half of the period analysed, and a clear decline is observed thereafter; in pattern 1 the median of the ASMR is higher, and the highest rates were achieved sooner. Pattern 3 is characterised by a rapid increase in mortality until 1999, declining slowly thereafter. This study provides a general model for the description and interpretation of the variation in breast cancer mortality in Europe, based in three main patterns. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mathematically guided approaches to distinguish models of periodic patterning

PubMed Central

Hiscock, Tom W.; Megason, Sean G.

2015-01-01

How periodic patterns are generated is an open question. A number of mechanisms have been proposed – most famously, Turing's reaction-diffusion model. However, many theoretical and experimental studies focus on the Turing mechanism while ignoring other possible mechanisms. Here, we use a general model of periodic patterning to show that different types of mechanism (molecular, cellular, mechanical) can generate qualitatively similar final patterns. Observation of final patterns is therefore not sufficient to favour one mechanism over others. However, we propose that a mathematical approach can help to guide the design of experiments that can distinguish between different mechanisms, and illustrate the potential value of this approach with specific biological examples. PMID:25605777

Symptom patterns in dissociative identity disorder patients and the general population.

PubMed

Ross, Colin A; Ness, Laura

2010-01-01

The authors used the Dissociative Disorders Interview Schedule to compare structured interview symptom patterns in a general population sample (N= 502) and a sample of patients with clinical diagnoses of dissociative identity disorder (N= 303). Based on the Trauma Model, the authors predicted that the patterns would be similar in the 2 samples and that symptom scores would be higher in participants reporting childhood sexual abuse in both samples. They predicted that symptom scores would be higher among women with dissociative identity disorder reporting sexual abuse than among women in the general population reporting sexual abuse, with the clinical sample reporting more severe abuse. These predictions were supported by the data. The authors conclude that symptom patterns in dissociative identity disorder are typical of the normal human response to severe, chronic childhood trauma and have ecological validity for the human race in general.

A hybrid multigroup neutron-pattern model

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

Pogosbekyan, L.R.; Lysov, D.A.

In this paper, we use the general approach to construct a multigroup hybrid model for the neutron pattern. The equations are given together with a reasonably economic and simple iterative method of solving them. The algorithm can be used to calculate the pattern and the functionals as well as to correct the constants from the experimental data and to adapt the support over the constants to the engineering programs by reference to precision ones.

Atlas Career Path Guidebook: Patterns and Common Practices in Systems Engineers’ Development

DTIC Science & Technology

2018-01-16

Overview of Atlas Proficiency Model .............................................................................. 68 5.1.2. Math /Science/General... Math /Science/General Engineering ................................ 72 Figure 42. Distribution for individuals with highest proficiency self...assessment in Math /Science/General Engineering ..................................................................................... 73 Figure 43

Sampling capacity underlies individual differences in human associative learning.

PubMed

Byrom, Nicola C; Murphy, Robin A

2014-04-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed.

Modeling and Observations of Phase-Mask Trapezoidal Profiles with Grating-Fiber Image Reproduction

NASA Technical Reports Server (NTRS)

Lyons, Donald R.; Lindesay, James V.; Lee, Hyung R.; Ndlela, Zolili U.; Thompso, Erica J.

2000-01-01

We report on an investigation of the trapezoidal design and fabrication defects in phase masks used to produce Bragg reflection gratings in optical fibers. We used a direct visualization technique to examine the nonuniformity of the interference patterns generated by several phase masks. Fringe patterns from the phase masks are compared with the analogous patterns resulting from two-beam interference. Atomic force microscope imaging of the actual phase gratings that give rise to anomalous fringe patterns is used to determine input parameters for a general theoretical model. Phase masks with pitches of 0.566 and 1.059 microns are modeled and investigated.

Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment

ERIC Educational Resources Information Center

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2005-01-01

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of self-disclosure. The model was used to analyze the data…

Selective memory generalization by spatial patterning of protein synthesis

PubMed Central

O’Donnell, Cian; Sejnowski, Terrence J.

2014-01-01

Summary Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings we proposed a novel two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. PMID:24742462

Selective memory generalization by spatial patterning of protein synthesis.

PubMed

O'Donnell, Cian; Sejnowski, Terrence J

2014-04-16

Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

A General Model of Negative Frequency Dependent Selection Explains Global Patterns of Human ABO Polymorphism

PubMed Central

Villanea, Fernando A.; Safi, Kristin N.; Busch, Jeremiah W.

2015-01-01

The ABO locus in humans is characterized by elevated heterozygosity and very similar allele frequencies among populations scattered across the globe. Using knowledge of ABO protein function, we generated a simple model of asymmetric negative frequency dependent selection and genetic drift to explain the maintenance of ABO polymorphism and its loss in human populations. In our models, regardless of the strength of selection, models with large effective population sizes result in ABO allele frequencies that closely match those observed in most continental populations. Populations must be moderately small to fall out of equilibrium and lose either the A or B allele (Ne ≤ 50) and much smaller (N e ≤ 25) for the complete loss of diversity, which nearly always involved the fixation of the O allele. A pattern of low heterozygosity at the ABO locus where loss of polymorphism occurs in our model is consistent with small populations, such as Native American populations. This study provides a general evolutionary model to explain the observed global patterns of polymorphism at the ABO locus and the pattern of allele loss in small populations. Moreover, these results inform the range of population sizes associated with the recent human colonization of the Americas. PMID:25946124

Shape Transformations of Epithelial Shells

PubMed Central

Misra, Mahim; Audoly, Basile; Kevrekidis, Ioannis G.; Shvartsman, Stanislav Y.

2016-01-01

Regulated deformations of epithelial sheets are frequently foreshadowed by patterning of their mechanical properties. The connection between patterns of cell properties and the emerging tissue deformations is studied in multiple experimental systems, but the general principles remain poorly understood. For instance, it is in general unclear what determines the direction in which the patterned sheet is going to bend and whether the resulting shape transformation will be discontinuous or smooth. Here these questions are explored computationally, using vertex models of epithelial shells assembled from prismlike cells. In response to rings and patches of apical cell contractility, model epithelia smoothly deform into invaginated or evaginated shapes similar to those observed in embryos and tissue organoids. Most of the observed effects can be captured by a simpler model with polygonal cells, modified to include the effects of the apicobasal polarity and natural curvature of epithelia. Our models can be readily extended to include the effects of multiple constraints and used to describe a wide range of morphogenetic processes. PMID:27074691

Predicting synchrony in heterogeneous pulse coupled oscillators

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Miliotis, Abraham; Carney, Paul R.; Ditto, William L.

2009-08-01

Pulse coupled oscillators (PCOs) represent an ubiquitous model for a number of physical and biological systems. Phase response curves (PRCs) provide a general mathematical framework to analyze patterns of synchrony generated within these models. A general theoretical approach to account for the nonlinear contributions from higher-order PRCs in the generation of synchronous patterns by the PCOs is still lacking. Here, by considering a prototypical example of a PCO network, i.e., two synaptically coupled neurons, we present a general theory that extends beyond the weak-coupling approximation, to account for higher-order PRC corrections in the derivation of an approximate discrete map, the stable fixed point of which can predict the domain of 1:1 phase locked synchronous states generated by the PCO network.

Demographic Accounting and Model-Building. Education and Development Technical Reports.

ERIC Educational Resources Information Center

Stone, Richard

This report describes and develops a model for coordinating a variety of demographic and social statistics within a single framework. The framework proposed, together with its associated methods of analysis, serves both general and specific functions. The general aim of these functions is to give numerical definition to the pattern of society and…

Sampling Capacity Underlies Individual Differences in Human Associative Learning

PubMed Central

2014-01-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed. PMID:24446699

Host contact and shedding patterns clarify variation in pathogen exposure and transmission in threatened tortoise Gopherus agassizii: implications for disease modelling and management

USGS Publications Warehouse

Aiello, Christina M.; Nussear, Kenneth E.; Esque, Todd C.; Emblidge, Patrick G.; Sah, Pratha; Bansal, Shweta; Hudson, Peter J.

2016-01-01

Mean field models may misrepresent natural transmission patterns in this and other populations depending on the distribution of high-risk contact and shedding events. Rapid outbreaks in generally solitary species may result from changes to their naturally low-risk contact patterns or due to increases in the frequency of severe infections or super-shedding events – population characteristics that should be further investigated to develop effective management strategies.

Pattern recognition tool based on complex network-based approach

NASA Astrophysics Data System (ADS)

Casanova, Dalcimar; Backes, André Ricardo; Martinez Bruno, Odemir

2013-02-01

This work proposed a generalization of the method proposed by the authors: 'A complex network-based approach for boundary shape analysis'. Instead of modelling a contour into a graph and use complex networks rules to characterize it, here, we generalize the technique. This way, the work proposes a mathematical tool for characterization signals, curves and set of points. To evaluate the pattern description power of the proposal, an experiment of plat identification based on leaf veins image are conducted. Leaf vein is a taxon characteristic used to plant identification proposes, and one of its characteristics is that these structures are complex, and difficult to be represented as a signal or curves and this way to be analyzed in a classical pattern recognition approach. Here, we model the veins as a set of points and model as graphs. As features, we use the degree and joint degree measurements in a dynamic evolution. The results demonstrates that the technique has a good power of discrimination and can be used for plant identification, as well as other complex pattern recognition tasks.

Slug to churn transition analysis using wire-mesh sensor

NASA Astrophysics Data System (ADS)

H. F. Velasco, P.; Ortiz-Vidal, L. E.; Rocha, D. M.; Rodriguez, O. M. H.

2016-06-01

A comparison between some theoretical slug to churn flow-pattern transition models and experimental data is performed. The flow-pattern database considers vertical upward air-water flow at standard temperature and pressure for 50 mm and 32 mm ID pipes. A briefly description of the models and its phenomenology is presented. In general, the performance of the transition models is poor. We found that new experimental studies describing objectively both stable and unstable slug flow-pattern are required. In this sense, the Wire Mesh Sensor (WMS) can assist to that aim. The potential of the WMS is outlined.

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

A general model to explore complex dominance patterns in plant sporophytic self-incompatibility systems.

PubMed

Billiard, Sylvain; Castric, Vincent; Vekemans, Xavier

2007-03-01

We developed a general model of sporophytic self-incompatibility under negative frequency-dependent selection allowing complex patterns of dominance among alleles. We used this model deterministically to investigate the effects on equilibrium allelic frequencies of the number of dominance classes, the number of alleles per dominance class, the asymmetry in dominance expression between pollen and pistil, and whether selection acts on male fitness only or both on male and on female fitnesses. We show that the so-called "recessive effect" occurs under a wide variety of situations. We found emerging properties of finite population models with several alleles per dominance class such as that higher numbers of alleles are maintained in more dominant classes and that the number of dominance classes can evolve. We also investigated the occurrence of homozygous genotypes and found that substantial proportions of those can occur for the most recessive alleles. We used the model for two species with complex dominance patterns to test whether allelic frequencies in natural populations are in agreement with the distribution predicted by our model. We suggest that the model can be used to test explicitly for additional, allele-specific, selective forces.

Heuristic pattern correction scheme using adaptively trained generalized regression neural networks.

PubMed

Hoya, T; Chambers, J A

2001-01-01

In many pattern classification problems, an intelligent neural system is required which can learn the newly encountered but misclassified patterns incrementally, while keeping a good classification performance over the past patterns stored in the network. In the paper, an heuristic pattern correction scheme is proposed using adaptively trained generalized regression neural networks (GRNNs). The scheme is based upon both network growing and dual-stage shrinking mechanisms. In the network growing phase, a subset of the misclassified patterns in each incoming data set is iteratively added into the network until all the patterns in the incoming data set are classified correctly. Then, the redundancy in the growing phase is removed in the dual-stage network shrinking. Both long- and short-term memory models are considered in the network shrinking, which are motivated from biological study of the brain. The learning capability of the proposed scheme is investigated through extensive simulation studies.

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Common Warming Pattern Emerges Irrespective of Forcing Location

NASA Astrophysics Data System (ADS)

Kang, Sarah M.; Park, Kiwoong; Jin, Fei-Fei; Stuecker, Malte F.

2017-10-01

The Earth's climate is changing due to the existence of multiple radiative forcing agents. It is under question whether different forcing agents perturb the global climate in a distinct way. Previous studies have demonstrated the existence of similar climate response patterns in response to aerosol and greenhouse gas (GHG) forcings. In this study, the sensitivity of tropospheric temperature response patterns to surface heating distributions is assessed by forcing an atmospheric general circulation model coupled to an aquaplanet slab ocean with a wide range of possible forcing patterns. We show that a common climate pattern emerges in response to localized forcing at different locations. This pattern, characterized by enhanced warming in the tropical upper troposphere and the polar lower troposphere, resembles the historical trends from observations and models as well as the future projections. Atmospheric dynamics in combination with thermodynamic air-sea coupling are primarily responsible for shaping this pattern. Identifying this common pattern strengthens our confidence in the projected response to GHG and aerosols in complex climate models.

From Patterns to Function in Living Systems: Dryland Ecosystems as a Case Study

NASA Astrophysics Data System (ADS)

Meron, Ehud

2018-03-01

Spatial patterns are ubiquitous in animate matter. Besides their intricate structure and beauty they generally play functional roles. The capacity of living systems to remain functional in changing environments is a question of utmost importance, but its intimate relationship to pattern formation is largely unexplored. Here, we address this relationship using dryland vegetation as a case study. Following a brief introduction to pattern-formation theory, we describe a mathematical model that captures several mechanisms of vegetation pattern formation and discuss ecological contexts that showcase different mechanisms. Using this model, we unravel the different vegetation patterns that keep dryland ecosystems viable along the rainfall gradient, identify multistability ranges where fronts separating domains of alternative stable states exist, and highlight the roles of front dynamics in mitigating or reversing desertification. The utility of satellite images in testing model predictions is discussed. An outlook on outstanding open problems concludes this paper.

A Reinforcement Learning Model Equipped with Sensors for Generating Perception Patterns: Implementation of a Simulated Air Navigation System Using ADS-B (Automatic Dependent Surveillance-Broadcast) Technology.

PubMed

Álvarez de Toledo, Santiago; Anguera, Aurea; Barreiro, José M; Lara, Juan A; Lizcano, David

2017-01-19

Over the last few decades, a number of reinforcement learning techniques have emerged, and different reinforcement learning-based applications have proliferated. However, such techniques tend to specialize in a particular field. This is an obstacle to their generalization and extrapolation to other areas. Besides, neither the reward-punishment (r-p) learning process nor the convergence of results is fast and efficient enough. To address these obstacles, this research proposes a general reinforcement learning model. This model is independent of input and output types and based on general bioinspired principles that help to speed up the learning process. The model is composed of a perception module based on sensors whose specific perceptions are mapped as perception patterns. In this manner, similar perceptions (even if perceived at different positions in the environment) are accounted for by the same perception pattern. Additionally, the model includes a procedure that statistically associates perception-action pattern pairs depending on the positive or negative results output by executing the respective action in response to a particular perception during the learning process. To do this, the model is fitted with a mechanism that reacts positively or negatively to particular sensory stimuli in order to rate results. The model is supplemented by an action module that can be configured depending on the maneuverability of each specific agent. The model has been applied in the air navigation domain, a field with strong safety restrictions, which led us to implement a simulated system equipped with the proposed model. Accordingly, the perception sensors were based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology, which is described in this paper. The results were quite satisfactory, and it outperformed traditional methods existing in the literature with respect to learning reliability and efficiency.

A Reinforcement Learning Model Equipped with Sensors for Generating Perception Patterns: Implementation of a Simulated Air Navigation System Using ADS-B (Automatic Dependent Surveillance-Broadcast) Technology

PubMed Central

Álvarez de Toledo, Santiago; Anguera, Aurea; Barreiro, José M.; Lara, Juan A.; Lizcano, David

2017-01-01

Over the last few decades, a number of reinforcement learning techniques have emerged, and different reinforcement learning-based applications have proliferated. However, such techniques tend to specialize in a particular field. This is an obstacle to their generalization and extrapolation to other areas. Besides, neither the reward-punishment (r-p) learning process nor the convergence of results is fast and efficient enough. To address these obstacles, this research proposes a general reinforcement learning model. This model is independent of input and output types and based on general bioinspired principles that help to speed up the learning process. The model is composed of a perception module based on sensors whose specific perceptions are mapped as perception patterns. In this manner, similar perceptions (even if perceived at different positions in the environment) are accounted for by the same perception pattern. Additionally, the model includes a procedure that statistically associates perception-action pattern pairs depending on the positive or negative results output by executing the respective action in response to a particular perception during the learning process. To do this, the model is fitted with a mechanism that reacts positively or negatively to particular sensory stimuli in order to rate results. The model is supplemented by an action module that can be configured depending on the maneuverability of each specific agent. The model has been applied in the air navigation domain, a field with strong safety restrictions, which led us to implement a simulated system equipped with the proposed model. Accordingly, the perception sensors were based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology, which is described in this paper. The results were quite satisfactory, and it outperformed traditional methods existing in the literature with respect to learning reliability and efficiency. PMID:28106849

Abiotic and biotic controls of spatial pattern at alpine treeline

USGS Publications Warehouse

Malanson, George P.; Xiao, Ningchuan; Alftine, K.J.; Bekker, Mathew; Butler, David R.; Brown, Daniel G.; Cairns, David M.; Fagre, Daniel; Walsh, Stephen J.

2000-01-01

At alpine treeline, trees and krummholz forms affect the environment in ways that increase their growth and reproduction. We assess the way in which these positive feedbacks combine in spatial patterns to alter the environment in the neighborhood of existing plants. The research is significant because areas of alpine tundra are susceptible to encroachment by woody species as climate changes. Moreover, understanding the general processes of plant invasion is important. The importance of spatial pattern has been recognized, but the spatial pattern of positive feedbacks per se has not been explored in depth. We present a linked set of models of vegetation change at an alpine forest-tundra ecotone. Our aim is to create models that are as simple as possible in order to test specific hypotheses. We present results from a model of the resource averaging hypothesis and the positive feedback switch hypothesis of treelines. We compare the patterns generated by the models to patterns observed in fine scale remotely sensed data.

Bursts of Vertex Activation and Epidemics in Evolving Networks

PubMed Central

Rocha, Luis E. C.; Blondel, Vincent D.

2013-01-01

The dynamic nature of contact patterns creates diverse temporal structures. In particular, empirical studies have shown that contact patterns follow heterogeneous inter-event time intervals, meaning that periods of high activity are followed by long periods of inactivity. To investigate the impact of these heterogeneities in the spread of infection from a theoretical perspective, we propose a stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event intervals, and may leave and enter the system. We study how these properties affect the prevalence of an infection and estimate , the number of secondary infections of an infectious individual in a completely susceptible population, by modeling simulated infections (SI and SIR) that co-evolve with the network structure. We find that heterogeneous contact patterns cause earlier and larger epidemics in the SIR model in comparison to homogeneous scenarios for a vast range of parameter values, while smaller epidemics may happen in some combinations of parameters. In the case of SI and heterogeneous patterns, the epidemics develop faster in the earlier stages followed by a slowdown in the asymptotic limit. For increasing vertex turnover rates, heterogeneous patterns generally cause higher prevalence in comparison to homogeneous scenarios with the same average inter-event interval. We find that is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability. PMID:23555211

Towards a General Model of Temporal Discounting

ERIC Educational Resources Information Center

van den Bos, Wouter; McClure, Samuel M.

2013-01-01

Psychological models of temporal discounting have now successfully displaced classical economic theory due to the simple fact that many common behavior patterns, such as impulsivity, were unexplainable with classic models. However, the now dominant hyperbolic model of discounting is itself becoming increasingly strained. Numerous factors have…

Automatic pattern identification of rock moisture based on the Staff-RF model

NASA Astrophysics Data System (ADS)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

PubMed

Tendeiro, Jorge N

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

Recognition of building group patterns in topographic maps based on graph partitioning and random forest

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

Predictions and retrodictions of the hierarchical representation of habitat in heterogeneous environments

USGS Publications Warehouse

Kolasa, Jurek; Allen, Craig R.; Sendzimir, Jan; Stow, Craig A.

2012-01-01

Interaction between habitat and species is central in ecology. Habitat structure may be conceived as being hierarchical, where larger, more diverse, portions or categories contain smaller, more homogeneous portions. When this conceptualization is combined with the observation that species have different abilities to relate to portions of the habitat that differ in their characteristics, a number of known patterns can be derived and new patterns hypothesized. We propose a quantitative form of this habitat–species relationship by considering species abundance to be a function of habitat specialization, habitat fragmentation, amount of habitat, and adult body mass. The model reproduces and explains patterns such as variation in rank–abundance curves, greater variation and extinction probabilities of habitat specialists, discontinuities in traits (abundance, ecological range, pattern of variation, body size) among species sharing a community or area, and triangular distribution of body sizes, among others. The model has affinities to Holling's textural discontinuity hypothesis and metacommunity theory but differs from both by offering a more general perspective. In support of the model, we illustrate its general potential to capture and explain several empirical observations that historically have been treated independently.

Dissipative neutrino oscillations in randomly fluctuating matter

NASA Astrophysics Data System (ADS)

Benatti, F.; Floreanini, R.

2005-01-01

The generalized dynamics describing the propagation of neutrinos in randomly fluctuating media is analyzed: It takes into account matter-induced, decoherence phenomena that go beyond the standard Mikheyev-Smirnov-Wolfenstein (MSW) effect. A widely adopted density fluctuation pattern is found to be physically untenable: A more general model needs to be instead considered, leading to flavor changing effective neutrino-matter interactions. They induce new, dissipative effects that modify the neutrino oscillation pattern in a way amenable to a direct experimental analysis.

Automated real time constant-specificity surveillance for disease outbreaks.

PubMed

Wieland, Shannon C; Brownstein, John S; Berger, Bonnie; Mandl, Kenneth D

2007-06-13

For real time surveillance, detection of abnormal disease patterns is based on a difference between patterns observed, and those predicted by models of historical data. The usefulness of outbreak detection strategies depends on their specificity; the false alarm rate affects the interpretation of alarms. We evaluate the specificity of five traditional models: autoregressive, Serfling, trimmed seasonal, wavelet-based, and generalized linear. We apply each to 12 years of emergency department visits for respiratory infection syndromes at a pediatric hospital, finding that the specificity of the five models was almost always a non-constant function of the day of the week, month, and year of the study (p < 0.05). We develop an outbreak detection method, called the expectation-variance model, based on generalized additive modeling to achieve a constant specificity by accounting for not only the expected number of visits, but also the variance of the number of visits. The expectation-variance model achieves constant specificity on all three time scales, as well as earlier detection and improved sensitivity compared to traditional methods in most circumstances. Modeling the variance of visit patterns enables real-time detection with known, constant specificity at all times. With constant specificity, public health practitioners can better interpret the alarms and better evaluate the cost-effectiveness of surveillance systems.

User's manual for generalized ILSGLD-ILS glide slope performance prediction : multipath scattering

DOT National Transportation Integrated Search

1976-11-01

This manual presents the computer program package for the generalized ILSGLD scattering model. The text includes a complete description of the program itself as well as 3 brief descriptions : of the ILS system and antenna patterns. The program listin...

OPTIMIZATION METHODOLOGY FOR LAND USE PATTERNS-EVALUATION BASED ON MULTISCALE HABITAT PATTERN COMPARISON. (R827169)

EPA Science Inventory

In this paper, the methodological concept of landscape optimization presented by Seppelt and Voinov [Ecol. Model. 151 (2/3) (2002) 125] is analyzed. Two aspects are chosen for detailed study. First, we generalize the performance criterion to assess a vector of ecosystem functi...

Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints.

PubMed

Colwell, Robert K; Gotelli, Nicholas J; Ashton, Louise A; Beck, Jan; Brehm, Gunnar; Fayle, Tom M; Fiedler, Konrad; Forister, Matthew L; Kessler, Michael; Kitching, Roger L; Klimes, Petr; Kluge, Jürgen; Longino, John T; Maunsell, Sarah C; McCain, Christy M; Moses, Jimmy; Noben, Sarah; Sam, Katerina; Sam, Legi; Shapiro, Arthur M; Wang, Xiangping; Novotny, Vojtech

2016-09-01

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness. © 2016 John Wiley & Sons Ltd/CNRS.

Elevational Gradients in Fish Diversity in the Himalaya: Water Discharge Is the Key Driver of Distribution Patterns

PubMed Central

Bhatt, Jay P.; Manish, Kumar; Pandit, Maharaj K.

2012-01-01

Background Studying diversity and distribution patterns of species along elevational gradients and understanding drivers behind these patterns is central to macroecology and conservation biology. A number of studies on biogeographic gradients are available for terrestrial ecosystems, but freshwater ecosystems remain largely neglected. In particular, we know very little about the species richness gradients and their drivers in the Himalaya, a global biodiversity hotspot. Methodology/Principal Findings We collated taxonomic and distribution data of fish species from 16 freshwater Himalayan rivers and carried out empirical studies on environmental drivers and fish diversity and distribution in the Teesta river (Eastern Himalaya). We examined patterns of fish species richness along the Himalayan elevational gradients (50–3800 m) and sought to understand the drivers behind the emerging patterns. We used generalized linear models (GLM) and generalized additive models (GAM) to examine the richness patterns; GLM was used to investigate relationship between fish species richness and various environmental variables. Regression modelling involved stepwise procedures, including elimination of collinear variables, best model selection, based on the least Akaike’s information criterion (AIC) and the highest percentage of deviance explained (D2). This maiden study on the Himalayan fishes revealed that total and non-endemic fish species richness monotonously decrease with increasing elevation, while endemics peaked around mid elevations (700–1500 m). The best explanatory model (synthetic model) indicated that water discharge is the best predictor of fish species richness patterns in the Himalayan rivers. Conclusions/Significance This study, carried out along one of the longest bioclimatic elevation gradients of the world, lends support to Rapoport’s elevational rule as opposed to mid domain effect hypothesis. We propose a species-discharge model and contradict species-area model in predicting fish species richness. We suggest that drivers of richness gradients in terrestrial and aquatic ecosystems are likely to be different. These studies are crucial in context of the impacts of unprecedented on-going river regulation on fish diversity and distribution in the Himalaya. PMID:23029444

A generalized reaction diffusion model for spatial structure formed by motile cells.

PubMed

Ochoa, F L

1984-01-01

A non-linear stability analysis using a multi-scale perturbation procedure is carried out on a model of a generalized reaction diffusion mechanism which involves only a single equation but which nevertheless exhibits bifurcation to non-uniform states. The patterns generated by this model by variation in a parameter related to the scalar dimensions of domain of definition, indicate its capacity to represent certain key morphogenetic features of multicellular systems formed by motile cells.

Multiple hypotheses testing of fish incidence patterns in an urbanized ecosystem

USGS Publications Warehouse

Chizinski, C.J.; Higgins, C.L.; Shavlik, C.E.; Pope, K.L.

2006-01-01

Ecological and evolutionary theories have focused traditionally on natural processes with little attempt to incorporate anthropogenic influences despite the fact that humans are such an integral part of virtually all ecosystems. A series of alternate models that incorporated anthropogenic factors and traditional ecological mechanisms of invasion to account for fish incidence patterns in urban lakes was tested. The models were based on fish biology, human intervention, and habitat characteristics. However, the only models to account for empirical patterns were those that included fish invasiveness, which incorporated species-specific information about overall tolerance and fecundity. This suggests that species-specific characteristics are more important in general distributional patterns than human-mediated dispersal. Better information of illegal stocking activities is needed to improve human-mediated models, and more insight into basic life history of ubiquitous species is needed to truly understand underlying mechanisms of biotic homogenization. ?? Springer 2005.

A musculoskeletal model of the elbow joint complex

NASA Technical Reports Server (NTRS)

Gonzalez, Roger V.; Barr, Ronald E.; Abraham, Lawrence D.

1993-01-01

This paper describes a musculoskeletal model that represents human elbow flexion-extension and forearm pronation-supination. Musculotendon parameters and the skeletal geometry were determined for the musculoskeletal model in the analysis of ballistic elbow joint complex movements. The key objective was to develop a computational model, guided by optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and movement kinematics. The model was verified using experimental kinematic, torque, and electromyographic data from volunteer subjects performing both isometric and ballistic elbow joint complex movements. In general, the model predicted kinematic and muscle excitation patterns similar to what was experimentally measured.

Emergent Vortex Patterns in Systems of Self-Propelled, Chiral Particles

NASA Astrophysics Data System (ADS)

Huber, Lorenz; Denk, Jonas; Reithmann, Emanuel; Frey, Erwin

Self-organization of FtsZ polymers is vital for Z-ring assembly during bacterial cell division, and has been studied using reconstituted in vitro model systems. Employing Brownian dynamics simulations and a Boltzmann approach, we model FtsZ polymers as active particles moving along chiral circular paths. With both theoretical approaches we find self-organization into vortex structures and characterize different states in parameter states. Our work demonstrates that these patterns are robust and are generic for active chiral matter. Moreover, we show that the dynamics at the onset of pattern formation is described by a generalized complex Ginzburg-Landau equation.

A New Kinematic Model for Polymodal Faulting: Implications for Fault Connectivity

NASA Astrophysics Data System (ADS)

Healy, D.; Rizzo, R. E.

2015-12-01

Conjugate, or bimodal, fault patterns dominate the geological literature on shear failure. Based on Anderson's (1905) application of the Mohr-Coulomb failure criterion, these patterns have been interpreted from all tectonic regimes, including normal, strike-slip and thrust (reverse) faulting. However, a fundamental limitation of the Mohr-Coulomb failure criterion - and others that assume faults form parallel to the intermediate principal stress - is that only plane strain can result from slip on the conjugate faults. However, deformation in the Earth is widely accepted as being three-dimensional, with truly triaxial stresses and strains. Polymodal faulting, with three or more sets of faults forming and slipping simultaneously, can generate three-dimensional strains from truly triaxial stresses. Laboratory experiments and outcrop studies have verified the occurrence of the polymodal fault patterns in nature. The connectivity of polymodal fault networks differs significantly from conjugate fault networks, and this presents challenges to our understanding of faulting and an opportunity to improve our understanding of seismic hazards and fluid flow. Polymodal fault patterns will, in general, have more connected nodes in 2D (and more branch lines in 3D) than comparable conjugate (bimodal) patterns. The anisotropy of permeability is therefore expected to be very different in rocks with polymodal fault patterns in comparison to conjugate fault patterns, and this has implications for the development of hydrocarbon reservoirs, the genesis of ore deposits and the management of aquifers. In this contribution, I assess the published evidence and models for polymodal faulting before presenting a novel kinematic model for general triaxial strain in the brittle field.

Model-based guiding pattern synthesis for robust assembly of contact layers using directed self-assembly

NASA Astrophysics Data System (ADS)

Mitra, Joydeep; Torres, Andres; Ma, Yuansheng; Pan, David Z.

2018-01-01

Directed self-assembly (DSA) has emerged as one of the most compelling next-generation patterning techniques for sub 7 nm via or contact layers. A key issue in enabling DSA as a mainstream patterning technique is the generation of grapho-epitaxy-based guiding pattern (GP) shapes to assemble the contact patterns on target with high fidelity and resolution. Current GP generation is mostly empirical, and limited to a very small number of via configurations. We propose the first model-based GP synthesis algorithm and methodology for on-target and robust DSA, on general via pattern configurations. The final postoptical proximity correction-printed GPs derived from our original synthesized GPs are resilient to process variations and continue to maintain the same DSA fidelity in terms of placement error and target shape.

Pattern formation in mass conserving reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Brauns, Fridtjof; Halatek, Jacob; Frey, Erwin

We present a rigorous theoretical framework able to generalize and unify pattern formation for quantitative mass conserving reaction-diffusion models. Mass redistribution controls chemical equilibria locally. Separation of diffusive mass redistribution on the level of conserved species provides a general mathematical procedure to decompose complex reaction-diffusion systems into effectively independent functional units, and to reveal the general underlying bifurcation scenarios. We apply this framework to Min protein pattern formation and identify the mechanistic roles of both involved protein species. MinD generates polarity through phase separation, whereas MinE takes the role of a control variable regulating the existence of MinD phases. Hence, polarization and not oscillations is the generic core dynamics of Min proteins in vivo. This establishes an intrinsic mechanistic link between the Min system and a broad class of intracellular pattern forming systems based on bistability and phase separation (wave-pinning). Oscillations are facilitated by MinE redistribution and can be understood mechanistically as relaxation oscillations of the polarization direction.

Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

EPA Science Inventory

Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...

Generative electronic background music system

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

Mazurowski, Lukasz

In this short paper-extended abstract the new approach to generation of electronic background music has been presented. The Generative Electronic Background Music System (GEBMS) has been located between other related approaches within the musical algorithm positioning framework proposed by Woller et al. The music composition process is performed by a number of mini-models parameterized by further described properties. The mini-models generate fragments of musical patterns used in output composition. Musical pattern and output generation are controlled by container for the mini-models - a host-model. General mechanism has been presented including the example of the synthesized output compositions.

Do attachment patterns predict aggression in a context of social rejection? An executive functioning account.

PubMed

Ma, Yuanxiao; Ma, Haijing; Chen, Xu; Ran, Guangming; Zhang, Xing

2017-07-01

People tend to respond to rejection and attack with aggression. The present research examined the modulation role of attachment patterns on provoked aggression following punishment and proposed an executive functioning account of attachment patterns' modulating influence based on the General Aggression Model. Attachment style was measured using the Experiences in Close Relationships inventory. Experiments 1a and b and 2 adopted a social rejection task and assessed subsequent unprovoked and provoked aggression with different attachment patterns. Moreover, Experiment 1b and 2 used a Stroop task to examine whether differences in provoked aggression by attachment patterns are due to the amount of executive functioning following social rejection, or after unprovoked punishment, or even before social rejection. Anxiously attached participants displayed significant more provoked aggression than securely and avoidantly attached participants in provoked aggression following unprovoked punishment in Experiments 1 and 2. Meanwhile, subsequent Stroop tests indicated anxiously attached participants experienced more executive functioning depletion after social rejection and unprovoked aggression. The present findings support the General Aggression Model and suggest that provoked aggression is predicted by attachment patterns in the context of social rejection; different provoked aggression may depend on the degree of executive functioning that individuals preserved in aggressive situations. The current study contributes to our understanding of the importance of the role of attachment patterns in modulating aggressive behavior accompanying unfair social encounters. © 2017 Wiley Periodicals, Inc.

Numerical treatment of free surface problems in ferrohydrodynamics

NASA Astrophysics Data System (ADS)

Lavrova, O.; Matthies, G.; Mitkova, T.; Polevikov, V.; Tobiska, L.

2006-09-01

The numerical treatment of free surface problems in ferrohydrodynamics is considered. Starting from the general model, special attention is paid to field-surface and flow-surface interactions. Since in some situations these feedback interactions can be partly or even fully neglected, simpler models can be derived. The application of such models to the numerical simulation of dissipative systems, rotary shaft seals, equilibrium shapes of ferrofluid drops, and pattern formation in the normal-field instability of ferrofluid layers is given. Our numerical strategy is able to recover solitary surface patterns which were discovered recently in experiments.

An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

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

Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less

An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

DOE PAGES

Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin; ...

2017-05-15

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less

Numerical modeling tools for chemical vapor deposition

NASA Technical Reports Server (NTRS)

Jasinski, Thomas J.; Childs, Edward P.

1992-01-01

Development of general numerical simulation tools for chemical vapor deposition (CVD) was the objective of this study. Physical models of important CVD phenomena were developed and implemented into the commercial computational fluid dynamics software FLUENT. The resulting software can address general geometries as well as the most important phenomena occurring with CVD reactors: fluid flow patterns, temperature and chemical species distribution, gas phase and surface deposition. The physical models are documented which are available and examples are provided of CVD simulation capabilities.

Mean-field message-passing equations in the Hopfield model and its generalizations

NASA Astrophysics Data System (ADS)

Mézard, Marc

2017-02-01

Motivated by recent progress in using restricted Boltzmann machines as preprocessing algorithms for deep neural network, we revisit the mean-field equations [belief-propagation and Thouless-Anderson Palmer (TAP) equations] in the best understood of such machines, namely the Hopfield model of neural networks, and we explicit how they can be used as iterative message-passing algorithms, providing a fast method to compute the local polarizations of neurons. In the "retrieval phase", where neurons polarize in the direction of one memorized pattern, we point out a major difference between the belief propagation and TAP equations: The set of belief propagation equations depends on the pattern which is retrieved, while one can use a unique set of TAP equations. This makes the latter method much better suited for applications in the learning process of restricted Boltzmann machines. In the case where the patterns memorized in the Hopfield model are not independent, but are correlated through a combinatorial structure, we show that the TAP equations have to be modified. This modification can be seen either as an alteration of the reaction term in TAP equations or, more interestingly, as the consequence of message passing on a graphical model with several hidden layers, where the number of hidden layers depends on the depth of the correlations in the memorized patterns. This layered structure is actually necessary when one deals with more general restricted Boltzmann machines.

A general-purpose framework to simulate musculoskeletal system of human body: using a motion tracking approach.

PubMed

Ehsani, Hossein; Rostami, Mostafa; Gudarzi, Mohammad

2016-02-01

Computation of muscle force patterns that produce specified movements of muscle-actuated dynamic models is an important and challenging problem. This problem is an undetermined one, and then a proper optimization is required to calculate muscle forces. The purpose of this paper is to develop a general model for calculating all muscle activation and force patterns in an arbitrary human body movement. For this aim, the equations of a multibody system forward dynamics, which is considered for skeletal system of the human body model, is derived using Lagrange-Euler formulation. Next, muscle contraction dynamics is added to this model and forward dynamics of an arbitrary musculoskeletal system is obtained. For optimization purpose, the obtained model is used in computed muscle control algorithm, and a closed-loop system for tracking desired motions is derived. Finally, a popular sport exercise, biceps curl, is simulated by using this algorithm and the validity of the obtained results is evaluated via EMG signals.

Nonlinear and Quasi-Simplex Patterns in Latent Growth Models

ERIC Educational Resources Information Center

Bianconcini, Silvia

2012-01-01

In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…

Vegetation pattern formation in a fog-dependent ecosystem.

PubMed

Borthagaray, Ana I; Fuentes, Miguel A; Marquet, Pablo A

2010-07-07

Vegetation pattern formation is a striking characteristic of several water-limited ecosystems around the world. Typically, they have been described on runoff-based ecosystems emphasizing local interactions between water, biomass interception, growth and dispersal. Here, we show that this situation is by no means general, as banded patterns in vegetation can emerge in areas without rainfall and in plants without functional root (the Bromeliad Tillandsia landbeckii) and where fog is the principal source of moisture. We show that a simple model based on the advection of fog-water by wind and its interception by the vegetation can reproduce banded patterns which agree with empirical patterns observed in the Coastal Atacama Desert. Our model predicts how the parameters may affect the conditions to form the banded pattern, showing a transition from a uniform vegetated state, at high water input or terrain slope to a desert state throughout intermediate banded states. Moreover, the model predicts that the pattern wavelength is a decreasing non-linear function of fog-water input and slope, and an increasing function of plant loss and fog-water flow speed. Finally, we show that the vegetation density is increased by the formation of the regular pattern compared to the density expected by the spatially homogeneous model emphasizing the importance of self-organization in arid ecosystems. (c) 2010 Elsevier Ltd. All rights reserved.

Spread of entanglement and causality

NASA Astrophysics Data System (ADS)

Casini, Horacio; Liu, Hong; Mezei, Márk

2016-07-01

We investigate causality constraints on the time evolution of entanglement entropy after a global quench in relativistic theories. We first provide a general proof that the so-called tsunami velocity is bounded by the speed of light. We then generalize the free particle streaming model of [1] to general dimensions and to an arbitrary entanglement pattern of the initial state. In more than two spacetime dimensions the spread of entanglement in these models is highly sensitive to the initial entanglement pattern, but we are able to prove an upper bound on the normalized rate of growth of entanglement entropy, and hence the tsunami velocity. The bound is smaller than what one gets for quenches in holographic theories, which highlights the importance of interactions in the spread of entanglement in many-body systems. We propose an interacting model which we believe provides an upper bound on the spread of entanglement for interacting relativistic theories. In two spacetime dimensions with multiple intervals, this model and its variations are able to reproduce intricate results exhibited by holographic theories for a significant part of the parameter space. For higher dimensions, the model bounds the tsunami velocity at the speed of light. Finally, we construct a geometric model for entanglement propagation based on a tensor network construction for global quenches.

Patterns of sediment dispersion coastwise the State of Bahia - Brazil.

PubMed

Bittencourt; Dominguez; Martin; Silva

2000-06-01

Using the average directions of the main wave-fronts which approach the coast of Bahia State - coinciding with that of the main wind occurring in the area - and of their periods, we define a wave climate model based on the construction of refraction diagrams. The resulting model of sediment transport was able to reproduce, in a general way, the sediment dispersion patterns furnished by geomorphic indicators of the littoral drift. These dispersion patterns control the generation of different types of sediment accumulations and of coastal stretches under erosion. We demonstrate that the presence of the Abrolhos and Corumbaú Point coral reefs is an important factor controlling the sediment dispersion patterns, since them act as a large protection against the waves action.

Square Turing patterns in reaction-diffusion systems with coupled layers

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

Li, Jing; Wang, Hongli, E-mail: hlwang@pku.edu.cn, E-mail: qi@pku.edu.cn; Center for Quantitative Biology, Peking University, Beijing 100871

Square Turing patterns are usually unstable in reaction-diffusion systems and are rarely observed in corresponding experiments and simulations. We report here an example of spontaneous formation of square Turing patterns with the Lengyel-Epstein model of two coupled layers. The squares are found to be a result of the resonance between two supercritical Turing modes with an appropriate ratio. Besides, the spatiotemporal resonance of Turing modes resembles to the mode-locking phenomenon. Analysis of the general amplitude equations for square patterns reveals that the fixed point corresponding to square Turing patterns is stationary when the parameters adopt appropriate values.

How to Make Our Models More Physically-based

NASA Astrophysics Data System (ADS)

Savenije, H. H. G.

2016-12-01

Models that are generally called "physically-based" unfortunately only have a partial view of the physical processes at play in hydrology. Although the coupled partial differential equations in these models reflect the water balance equations and the flow descriptors at laboratory scale, they miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem (and sometimes people). What these agents do is manipulate the substrate in a way that it supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, in agreement with the landscape, and in response to climatic drivers. In brief, our hydrological system is alive and has a strong capacity to adjust to prevailing and changing circumstances. Although most physically based models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian thinking on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. If this active agent is not reflected in our models, then they miss essential physics. Through a Darwinian approach, we can determine the root zone storage capacity of ecosystems, as a crucial component of hydrological models, determining the partitioning of fluxes and the conservation of moisture to bridge periods of drought. Another crucial element of physical systems is the evolution of drainage patterns, both on and below the surface. On the surface, such patterns facilitate infiltration or surface drainage with minimal erosion; in the unsaturated zone, patterns facilitate efficient replenishment of moisture deficits and preferential drainage when there is excess moisture; in the groundwater, patterns facilitate the efficient and gradual drainage of groundwater, resulting in linear reservoir recession. Models that do not incorporate these patterns are not physical. The parameters in the equations may be adjusted to compensate for the lake of patterns, but this involves scale-dependent calibration. In contrast to what is widely believed, relatively simple conceptual models can accommodate these physical processes accurately and very efficiently.

Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model.

PubMed

Lin, Yu-Pin; Lin, Yun-Bin; Wang, Yen-Tan; Hong, Nien-Ming

2008-02-04

Monitoring and simulating urban sprawl and its effects on land-use patterns andhydrological processes in urbanized watersheds are essential in land-use and waterresourceplanning and management. This study applies a novel framework to the urbangrowth model Slope, Land use, Excluded land, Urban extent, Transportation, andHillshading (SLEUTH) and land-use change with the Conversion of Land use and itsEffects (CLUE-s) model using historical SPOT images to predict urban sprawl in thePaochiao watershed in Taipei County, Taiwan. The historical and predicted land-use datawas input into Patch Analyst to obtain landscape metrics. This data was also input to theGeneralized Watershed Loading Function (GWLF) model to analyze the effects of futureurban sprawl on the land-use patterns and watershed hydrology. The landscape metrics ofthe historical SPOT images show that land-use patterns changed between 1990-2000. TheSLEUTH model accurately simulated historical land-use patterns and urban sprawl in thePaochiao watershed, and simulated future clustered land-use patterns (2001-2025). TheCLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTHand CLUE-s models show the significant impact urban sprawl will have on land-usepatterns in the Paochiao watershed. The historical and predicted land-use patterns in thewatershed tended to fragment, had regular shapes and interspersion patterns, but wererelatively less isolated in 2001-2025 and less interspersed from 2005-2025 compared withland-use pattern in 1990. During the study, the variability and magnitude of hydrologicalcomponents based on the historical and predicted land-use patterns were cumulativelyaffected by urban sprawl in the watershed; specifically, surface runoff increasedsignificantly by 22.0% and baseflow decreased by 18.0% during 1990-2025. The proposedapproach is an effective means of enhancing land-use monitoring and management ofurbanized watersheds.

Television Content Viewing Patterns: Some Clues from Societal Norms.

ERIC Educational Resources Information Center

McDonald, Daniel G.; Glynn, Carroll J.

Focusing on how television viewing fits into a general model of consumer consumption patterns, a study examined (1) the extent to which the viewing of certain television content can be considered a "norm" of society, (2) similarities and differences between the norms for adults and those for children, and (3) some of the antecedents of…

Idealized model of polar cap currents, fields, and auroras

NASA Technical Reports Server (NTRS)

Cornwall, J. M.

1985-01-01

During periods of northward Bz, the electric field applied to the magnetosphere is generally opposite to that occurring during southward Bz and complicated patterns of convection result, showing some features reversed in comparison with the southward Bz case. A study is conducted of a simple generalization of early work on idealized convection models, which allows for coexistence of sunward convection over the central polar cap and antisunward convection elsewhere in the cap. The present model, valid for By approximately 0, has a four-cell convection pattern and is based on the combination of ionospheric current conservation with a relation between parallel auroral currents and parallel potential drops. Global magnetospheric issues involving, e.g., reconnection are not considered. The central result of this paper is an expression giving the parallel potential drop for polar cap auroras (with By approximately 0) in terms of the polar cap convection field profile.

Two notions of conspicuity and the classification of phyllotaxis.

PubMed

Reick, Christian H

2002-04-07

Invoking cylindrical Bravais lattices, Adler (1974, 1977) proposed a mathematically precise definition for the botanical classification of phyllotaxis. It is based on opposed pairs of parastichy families, that are conspicuous and visible. Jean (1988) generalized this concept to non-opposed pairs of parastichy families. In the present paper it is shown that this generalization implies a notion of conspicuity different from Adler's. This is made obvious by redefining the key terms of the two approaches. Both classifications are well defined. For Adler's, this is shown by presenting a general proof for his conjecture that conspicuous (in the sense of Adler) opposed pairs of parastichy families are visible. There are indications that in applications to models of phyllotaxis (van Iterson model, inhibitor models) their solutions are better characterized by Jean's classification. The differences between Adler's and Jean's classification show up only in very rare cases, so that the practice of pattern determination is only insignificantly touched by the present results. It turns out that the widely used contact parastichy method to determine phyllotactic patterns gives results according to Jean's classification rather than Adler's. Copyright 2002 Elsevier Science Ltd. All rights reserved.

An open-access CMIP5 pattern library for temperature and precipitation: description and methodology

NASA Astrophysics Data System (ADS)

Lynch, Cary; Hartin, Corinne; Bond-Lamberty, Ben; Kravitz, Ben

2017-05-01

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squares regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90° N/S). Bias and mean errors between modeled and pattern-predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5 °C, but the choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. This paper describes our library of least squares regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns. The dataset and netCDF data generation code are available at doi:10.5281/zenodo.495632.

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

Formal Derivation of Lotka-Volterra-Haken Amplitude Equations of Task-Related Brain Activity in Multiple, Consecutively Performed Tasks

NASA Astrophysics Data System (ADS)

Frank, T. D.

The Lotka-Volterra-Haken equations have been frequently used in ecology and pattern formation. Recently, the equations have been proposed by several research groups as amplitude equations for task-related patterns of brain activity. In this theoretical study, the focus is on the circular causality aspect of pattern formation systems as formulated within the framework of synergetics. Accordingly, the stable modes of a pattern formation system inhibit the unstable modes, whereas the unstable modes excite the stable modes. Using this circular causality principle it is shown that under certain conditions the Lotka-Volterra-Haken amplitude equations can be derived from a general model of brain activity akin to the Wilson-Cowan model. The model captures the amplitude dynamics for brain activity patterns in experiments involving several consecutively performed multiple-choice tasks. This is explicitly demonstrated for two-choice tasks involving grasping and walking. A comment on the relevance of the theoretical framework for clinical psychology and schizophrenia is given as well.

A model-based approach for the scattering-bar printing avoidance

NASA Astrophysics Data System (ADS)

Du, Yaojun; Li, Liang; Zhang, Jingjing; Shao, Feng; Zuniga, Christian; Deng, Yunfei

2018-03-01

As the technology node for the semiconductor manufacturing approaches advanced nodes, the scattering-bars (SBs) are more crucial than ever to ensure a good on-wafer printability of the line space pattern and hole pattern. The main pattern with small pitches requires a very narrow PV (process variation) band. A delicate SB addition scheme is thus needed to maintain a sufficient PW (process window) for the semi-iso- and iso-patterns. In general, the wider, longer, and closer to main feature SBs will be more effective in enhancing the printability; on the other hand, they are also more likely to be printed on the wafer; resulting in undesired defects transferable to subsequent processes. In this work, we have developed a model based approach for the scattering-bar printing avoidance (SPA). A specially designed optical model was tuned based on a broad range of test patterns which contain a variation of CDs and SB placements showing printing and non-printing scattering bars. A printing threshold is then obtained to check the extra-printings of SBs. The accuracy of this threshold is verified by pre-designed test patterns. The printing threshold associated with our novel SPA model allows us to set up a proper SB rule.

An ancient rule for constructing dodecagonal quasiperiodic patterns

NASA Astrophysics Data System (ADS)

Ajlouni, Rima

2017-02-01

The discovery of complex dodecagonal patterns in historical Islamic architecture is generating a renewed interest into understanding the mathematical principles of traditional Islamic geometry. By employing a compass and a straightedge, ancient craftsmen utilized consistent design principles that allowed for diverse geometric expressions to be realized throughout the ancient world. Derived from these principles, a global multi-level structural model is proposed that provides a general guiding principle for constructing a wide variety of infinite dodecagon-based quasiperiodic patterns.

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

PubMed

Vacchiano, Giorgio; Hacket-Pain, Andrew; Turco, Marco; Motta, Renzo; Maringer, Janet; Conedera, Marco; Drobyshev, Igor; Ascoli, Davide

2017-07-01

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

The polarization patterns of skylight reflected off wave water surface.

PubMed

Zhou, Guanhua; Xu, Wujian; Niu, Chunyue; Zhao, Huijie

2013-12-30

In this paper we propose a model to understand the polarization patterns of skylight when reflected off the surface of waves. The semi-empirical Rayleigh model is used to analyze the polarization of scattered skylight; the Harrison and Coombes model is used to analyze light radiance distribution; and the Cox-Munk model and Mueller matrix are used to analyze reflections from wave surface. First, we calculate the polarization patterns and intensity distribution of light reflected off wave surface. Then we investigate their relationship with incident radiation, solar zenith angle, wind speed and wind direction. Our results show that the polarization patterns of reflected skylight from waves and flat water are different, while skylight reflected on both kinds of water is generally highly polarized at the Brewster angle and the polarization direction is approximately parallel to the water's surface. The backward-reflecting Brewster zone has a relatively low reflectance and a high DOP in all observing directions. This can be used to optimally diminish the reflected skylight and avoid sunglint in ocean optics measurements.

SKA aperture array verification system: electromagnetic modeling and beam pattern measurements using a micro UAV

NASA Astrophysics Data System (ADS)

de Lera Acedo, E.; Bolli, P.; Paonessa, F.; Virone, G.; Colin-Beltran, E.; Razavi-Ghods, N.; Aicardi, I.; Lingua, A.; Maschio, P.; Monari, J.; Naldi, G.; Piras, M.; Pupillo, G.

2018-03-01

In this paper we present the electromagnetic modeling and beam pattern measurements of a 16-elements ultra wideband sparse random test array for the low frequency instrument of the Square Kilometer Array telescope. We discuss the importance of a small array test platform for the development of technologies and techniques towards the final telescope, highlighting the most relevant aspects of its design. We also describe the electromagnetic simulations and modeling work as well as the embedded-element and array pattern measurements using an Unmanned Aerial Vehicle system. The latter are helpful both for the validation of the models and the design as well as for the future instrumental calibration of the telescope thanks to the stable, accurate and strong radio frequency signal transmitted by the UAV. At this stage of the design, these measurements have shown a general agreement between experimental results and numerical data and have revealed the localized effect of un-calibrated cable lengths in the inner side-lobes of the array pattern.

Application of reaction-diffusion models to cell patterning in Xenopus retina. Initiation of patterns and their biological stability.

PubMed

Shoaf, S A; Conway, K; Hunt, R K

1984-08-07

We have examined the behavior of two reaction-diffusion models, originally proposed by Gierer & Meinhardt (1972) and by Kauffman, Shymko & Trabert (1978), for biological pattern formation. Calculations are presented for pattern formation on a disc (approximating the geometry of a number of embryonic anlagen including the frog eye rudiment), emphasizing the sensitivity of patterns to changes in initial conditions and to perturbations in the geometry of the morphogen-producing space. Analysis of the linearized equations from the models enabled us to select appropriate parameters and disc size for pattern growth. A computer-implemented finite element method was used to solve the non-linear model equations reiteratively. For the Gierer-Meinhardt model, initial activation (varying in size over two orders of magnitude) of one point on the disc's edge was sufficient to generate the primary gradient. Various parts of the disc were removed (remaining only as diffusible space) from the morphogen-producing cycle to investigate the effects of cells dropping out of the cycle due to cell death or malfunction (single point removed) or differentiation (center removed), as occur in the Xenopus eye rudiment. The resulting patterns had the same general shape and amplitude as normal gradients. Nor did a two-fold increase in disc size affect the pattern-generating ability of the model. Disc fragments bearing their primary gradient patterns were fused (with gradients in opposite directions, but each parallel to the fusion line). The resulting patterns generated by the model showed many similarities to results of "compound eye" experiments in Xenopus. Similar patterns were obtained with the model of Kauffman's group (1978), but we found less stability of the pattern subject to simulations of central differentiation. However, removal of a single point from the morphogen cycle (cell death) did not result in any change. The sensitivity of the Kauffman et al. model to shape perturbations is not surprising since the model was originally designed to use shape and increasing size during growth to generate a sequence of transient patterns. However, the Gierer-Meinhardt model is remarkably stable even when subjected to a wide range of perturbations in the diffusible space, thus allowing it to cope with normal biological variability, and offering an exciting range of possibilities for reaction-diffusion models as mechanisms underlying the spatial patterns of tissue structures.

The amazing evolutionary dynamics of non-linear optical systems with feedback

NASA Astrophysics Data System (ADS)

Yaroslavsky, Leonid

2013-09-01

Optical systems with feedback are, generally, non-linear dynamic systems. As such, they exhibit evolutionary behavior. In the paper we present results of experimental investigation of evolutionary dynamics of several models of such systems. The models are modifications of the famous mathematical "Game of Life". The modifications are two-fold: "Game of Life" rules are made stochastic and mutual influence of cells is made spatially non-uniform. A number of new phenomena in the evolutionary dynamics of the models are revealed: - "Ordering of chaos". Formation, from seed patterns, of stable maze-like patterns with chaotic "dislocations" that resemble natural patterns, such as skin patterns of some animals and fishes, see shell, fingerprints, magnetic domain patterns and alike, which one can frequently find in the nature. These patterns and their fragments exhibit a remarkable capability of unlimited growth. - "Self-controlled growth" of chaotic "live" formations into "communities" bounded, depending on the model, by a square, hexagon or octagon, until they reach a certain critical size, after which the growth stops. - "Eternal life in a bounded space" of "communities" after reaching a certain size and shape. - "Coherent shrinkage" of "mature", after reaching a certain size, "communities" into one of stable or oscillating patterns preserving in this process isomorphism of their bounding shapes until the very end.

Models of clinical reasoning with a focus on general practice: A critical review.

PubMed

Yazdani, Shahram; Hosseinzadeh, Mohammad; Hosseini, Fakhrolsadat

2017-10-01

Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed.

Adapted random sampling patterns for accelerated MRI.

PubMed

Knoll, Florian; Clason, Christian; Diwoky, Clemens; Stollberger, Rudolf

2011-02-01

Variable density random sampling patterns have recently become increasingly popular for accelerated imaging strategies, as they lead to incoherent aliasing artifacts. However, the design of these sampling patterns is still an open problem. Current strategies use model assumptions like polynomials of different order to generate a probability density function that is then used to generate the sampling pattern. This approach relies on the optimization of design parameters which is very time consuming and therefore impractical for daily clinical use. This work presents a new approach that generates sampling patterns by making use of power spectra of existing reference data sets and hence requires neither parameter tuning nor an a priori mathematical model of the density of sampling points. The approach is validated with downsampling experiments, as well as with accelerated in vivo measurements. The proposed approach is compared with established sampling patterns, and the generalization potential is tested by using a range of reference images. Quantitative evaluation is performed for the downsampling experiments using RMS differences to the original, fully sampled data set. Our results demonstrate that the image quality of the method presented in this paper is comparable to that of an established model-based strategy when optimization of the model parameter is carried out and yields superior results to non-optimized model parameters. However, no random sampling pattern showed superior performance when compared to conventional Cartesian subsampling for the considered reconstruction strategy.

Using climate, energy, and spatial-based hypotheses to interpret macroecological patterns of North America chelonians

USGS Publications Warehouse

Ennen, Joshua R.; Agha, Mickey; Matamoros, Wilfredo A.; Hazzard, Sarah C.; Lovich, Jeffrey E.

2016-01-01

Our study investigates how factors, such as latitude, productivity, and several environmental variables, influence contemporary patterns of the species richness in North American turtles. In particular, we test several hypotheses explaining broad-scale species richness patterns on several species richness data sets: (i) total turtles, (ii) freshwater turtles only, (iii) aquatic turtles, (iv) terrestrial turtles only, (v) Emydidae, and (vi) Kinosternidae. In addition to spatial data, we used a combination of 25 abiotic variables in spatial regression models to predict species richness patterns. Our results provide support for multiple hypotheses related to broad-scale patterns of species richness, and in particular, hypotheses related to climate, productivity, water availability, topography, and latitude. In general, species richness patterns were positively associated with temperature, precipitation, diversity of streams, coefficient of variation of elevation, and net primary productivity. We also found that North America turtles follow the general latitudinal diversity gradient pattern (i.e., increasing species richness towards equator) by exhibiting a negative association with latitude. Because of the incongruent results among our six data sets, our study highlights the importance of considering phylogenetic constraints and guilds when interpreting species richness patterns, especially for taxonomic groups that occupy a myriad of habitats.

On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.

PubMed

Tang, Yongqiang

2017-12-01

Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.

Modeling left-turn crash occurrence at signalized intersections by conflicting patterns.

PubMed

Wang, Xuesong; Abdel-Aty, Mohamed

2008-01-01

In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.

Reducing Neuronal Networks to Discrete Dynamics

PubMed Central

Terman, David; Ahn, Sungwoo; Wang, Xueying; Just, Winfried

2008-01-01

We consider a general class of purely inhibitory and excitatory-inhibitory neuronal networks, with a general class of network architectures, and characterize the complex firing patterns that emerge. Our strategy for studying these networks is to first reduce them to a discrete model. In the discrete model, each neuron is represented as a finite number of states and there are rules for how a neuron transitions from one state to another. In this paper, we rigorously demonstrate that the continuous neuronal model can be reduced to the discrete model if the intrinsic and synaptic properties of the cells are chosen appropriately. In a companion paper [1], we analyze the discrete model. PMID:18443649

Modeling of direct wafer bonding: Effect of wafer bow and etch patterns

NASA Astrophysics Data System (ADS)

Turner, K. T.; Spearing, S. M.

2002-12-01

Direct wafer bonding is an important technology for the manufacture of silicon-on-insulator substrates and microelectromechanical systems. As devices become more complex and require the bonding of multiple patterned wafers, there is a need to understand the mechanics of the bonding process. A general bonding criterion based on the competition between the strain energy accumulated in the wafers and the surface energy that is dissipated as the bond front advances is developed. The bonding criterion is used to examine the case of bonding bowed wafers. An analytical expression for the strain energy accumulation rate, which is the quantity that controls bonding, and the final curvature of a bonded stack is developed. It is demonstrated that the thickness of the wafers plays a large role and bonding success is independent of wafer diameter. The analytical results are verified through a finite element model and a general method for implementing the bonding criterion numerically is presented. The bonding criterion developed permits the effect of etched features to be assessed. Shallow etched patterns are shown to make bonding more difficult, while it is demonstrated that deep etched features can facilitate bonding. Model results and their process design implications are discussed in detail.

With the future behind them: convergent evidence from aymara language and gesture in the crosslinguistic comparison of spatial construals of time.

PubMed

Núñez, Rafael E; Sweetser, Eve

2006-05-06

Cognitive research on metaphoric concepts of time has focused on differences between moving Ego and moving time models, but even more basic is the contrast between Ego- and temporal-reference-point models. Dynamic models appear to be quasi-universal cross-culturally, as does the generalization that in Ego-reference-point models, FUTURE IS IN FRONT OF EGO and PAST IS IN BACK OF EGO. The Aymara language instead has a major static model of time wherein FUTURE IS BEHIND EGO and PAST IS IN FRONT OF EGO; linguistic and gestural data give strong confirmation of this unusual culture-specific cognitive pattern. Gestural data provide crucial information unavailable to purely linguistic analysis, suggesting that when investigating conceptual systems both forms of expression should be analyzed complementarily. Important issues in embodied cognition are raised: how fully shared are bodily grounded motivations for universal cognitive patterns, what makes a rare pattern emerge, and what are the cultural entailments of such patterns? 2006 Lawrence Erlbaum Associates, Inc.

A model of growth restraints to explain the development and evolution of tooth shapes in mammals.

PubMed

Osborn, Jeffrey W

2008-12-07

The problem investigated here is control of the development of tooth shape. Cells at the growing soft tissue interface between the ectoderm and mesoderm in a tooth anlage are observed to buckle and fold into a template for the shape of the tooth crown. The final shape is created by enamel secreted onto the folds. The pattern in which the folds develop is generally explained as a response to the pattern in which genes are locally expressed at the interface. This congruence leaves the problem of control unanswered because it does not explain how either pattern is controlled. Obviously, cells are subject to Newton's laws of motion so that mechanical forces and constraints must ultimately cause the movements of cells during tooth morphogenesis. A computer model is used to test the hypothesis that directional resistances to growth of the epithelial part of the interface could account for the shape into which the interface folds. The model starts with a single epithelial cell whose growth is constrained by 4 constant directional resistances (anterior, posterior, medial and lateral). The constraints force the growing epithelium to buckle and fold. By entering into the model different values for these constraints the modeled epithelium is induced to buckle and fold into the different shapes associated with the evolution of a human upper molar from that of a reptilian ancestor. The patterns and sizes of cusps and the sequences in which they develop are all correctly reproduced. The model predicts the changes in the 4 directional constraints necessary to develop and evolve from one tooth shape into another. I conclude more generally expressed genes that control directional resistances to growth, not locally expressed genes, may provide the information for the shape into which a tooth develops.

Correlations between human mobility and social interaction reveal general activity patterns.

PubMed

Mollgaard, Anders; Lehmann, Sune; Mathiesen, Joachim

2017-01-01

A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire population? Here we investigate the interplay between different activity types, namely communication, motion, and physical proximity by analyzing data collected from smartphones distributed among 638 individuals. We explore two central questions: Which underlying principles govern the formation of the activity patterns? Are the patterns specific to each individual or shared across the entire population? We find that statistics of the entire population allows us to successfully predict 71% of the activity and 85% of the inactivity involved in communication, mobility, and physical proximity. Surprisingly, individual level statistics only result in marginally better predictions, indicating that a majority of activity patterns are shared across our sample population. Finally, we predict short-term activity patterns using a generalized linear model, which suggests that a simple linear description might be sufficient to explain a wide range of actions, whether they be of social or of physical character.

Optical Pattern Formation in Spatially Bunched Atoms: A Self-Consistent Model and Experiment

NASA Astrophysics Data System (ADS)

Schmittberger, Bonnie L.; Gauthier, Daniel J.

2014-05-01

The nonlinear optics and optomechanical physics communities use different theoretical models to describe how optical fields interact with a sample of atoms. There does not yet exist a model that is valid for finite atomic temperatures but that also produces the zero temperature results that are generally assumed in optomechanical systems. We present a self-consistent model that is valid for all atomic temperatures and accounts for the back-action of the atoms on the optical fields. Our model provides new insights into the competing effects of the bunching-induced nonlinearity and the saturable nonlinearity. We show that it is crucial to keep the fifth and seventh-order nonlinearities that arise when there exists atomic bunching, even at very low optical field intensities. We go on to apply this model to the results of our experimental system where we observe spontaneous, multimode, transverse optical pattern formation at ultra-low light levels. We show that our model accurately predicts our experimentally observed threshold for optical pattern formation, which is the lowest threshold ever reported for pattern formation. We gratefully acknowledge the financial support of the NSF through Grant #PHY-1206040.

The roles of microclimatic diversity and of behavior in mediating the responses of ectotherms to climate change.

PubMed

Woods, H Arthur; Dillon, Michael E; Pincebourde, Sylvain

2015-12-01

We analyze the effects of changing patterns of thermal availability, in space and time, on the performance of small ectotherms. We approach this problem by breaking it into a series of smaller steps, focusing on: (1) how macroclimates interact with living and nonliving objects in the environment to produce a mosaic of thermal microclimates and (2) how mobile ectotherms filter those microclimates into realized body temperatures by moving around in them. Although the first step (generation of mosaics) is conceptually straightforward, there still exists no general framework for predicting spatial and temporal patterns of microclimatic variation. We organize potential variation along three axes-the nature of the objects producing the microclimates (abiotic versus biotic), how microclimates translate macroclimatic variation (amplify versus buffer), and the temporal and spatial scales over which microclimatic conditions vary (long versus short). From this organization, we propose several general rules about patterns of microclimatic diversity. To examine the second step (behavioral sampling of locally available microclimates), we construct a set of models that simulate ectotherms moving on a thermal landscape according to simple sets of diffusion-based rules. The models explore the effects of both changes in body size (which affect the time scale over which organisms integrate operative body temperatures) and increases in the mean and variance of temperature on the thermal landscape. Collectively, the models indicate that both simple behavioral rules and interactions between body size and spatial patterns of thermal variation can profoundly affect the distribution of realized body temperatures experienced by ectotherms. These analyses emphasize the rich set of problems still to solve before arriving at a general, predictive theory of the biological consequences of climate change. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modelling Vulnerability and Range Shifts in Ant Communities Responding to Future Global Warming in Temperate Forests.

PubMed

Kwon, Tae-Sung; Li, Fengqing; Kim, Sung-Soo; Chun, Jung Hwa; Park, Young-Seuk

2016-01-01

Global warming is likely leading to species' distributional shifts, resulting in changes in local community compositions and diversity patterns. In this study, we applied species distribution models to evaluate the potential impacts of temperature increase on ant communities in Korean temperate forests, by testing hypotheses that 1) the risk of extinction of forest ant species would increase over time, and 2) the changes in species distribution ranges could drive upward movements of ant communities and further alter patterns of species richness. We sampled ant communities at 335 evenly distributed sites across South Korea and modelled the future distribution range for each species using generalized additive models. To account for spatial autocorrelation, autocovariate regressions were conducted prior to generalized additive models. Among 29 common ant species, 12 species were estimated to shrink their suitable geographic areas, whereas five species would benefit from future global warming. Species richness was highest at low altitudes in the current period, and it was projected to be highest at the mid-altitudes in the 2080s, resulting in an upward movement of 4.9 m yr-1. This altered the altitudinal pattern of species richness from a monotonic-decrease curve (common in temperate regions) to a bell-shaped curve (common in tropical regions). Overall, ant communities in temperate forests are vulnerable to the on-going global warming and their altitudinal movements are similar to other faunal communities.

Hydrological hysteresis and its value for assessing process consistency in catchment conceptual models

Treesearch

O. Fovet; L. Ruiz; M. Hrachowitz; M. Faucheux; C. Gascuel-Odoux

2015-01-01

While most hydrological models reproduce the general flow dynamics, they frequently fail to adequately mimic system-internal processes. In particular, the relationship between storage and discharge, which often follows annual hysteretic patterns in shallow hard-rock aquifers, is rarely considered in modelling studies. One main reason is that catchment storage is...

Assessment of Different Turbulence Models for the Motion of Non-metallic Inclusion in Induction Crucible Furnace

NASA Astrophysics Data System (ADS)

Barati, H.; Wu, M.; Kharicha, A.; Ludwig, A.

2016-07-01

Turbulent fluid flow due to the electromagnetic forces in induction crucible furnace (ICF) is modeled using k-ɛ, k-ω SST and Large Eddy Simulation (LES) turbulence models. Fluid flow patterns calculated by different turbulence models and their effects on the motion of non-metallic inclusions (NMI) in the bulk melt have been investigated. Results show that the conventional k-ɛ model cannot solve the transient flow in ICF properly. With k-ω model transient flow and oscillation behavior of the flow pattern can be solved, and the motion of NMI can be tracked fairly well. LES model delivers the best modeling result on both details of the transient flow pattern and motion trajectories of NMI without the limitation of NMI size. The drawback of LES model is the long calculation time. Therefore, for general purpose to estimate the dynamic behavior of NMI in ICF both k-ω SST and LES are recommended. For the precise calculation of the motion of NMI smaller than 10 μm only LES model is appropriate.

Learning abstract visual concepts via probabilistic program induction in a Language of Thought.

PubMed

Overlan, Matthew C; Jacobs, Robert A; Piantadosi, Steven T

2017-11-01

The ability to learn abstract concepts is a powerful component of human cognition. It has been argued that variable binding is the key element enabling this ability, but the computational aspects of variable binding remain poorly understood. Here, we address this shortcoming by formalizing the Hierarchical Language of Thought (HLOT) model of rule learning. Given a set of data items, the model uses Bayesian inference to infer a probability distribution over stochastic programs that implement variable binding. Because the model makes use of symbolic variables as well as Bayesian inference and programs with stochastic primitives, it combines many of the advantages of both symbolic and statistical approaches to cognitive modeling. To evaluate the model, we conducted an experiment in which human subjects viewed training items and then judged which test items belong to the same concept as the training items. We found that the HLOT model provides a close match to human generalization patterns, significantly outperforming two variants of the Generalized Context Model, one variant based on string similarity and the other based on visual similarity using features from a deep convolutional neural network. Additional results suggest that variable binding happens automatically, implying that binding operations do not add complexity to peoples' hypothesized rules. Overall, this work demonstrates that a cognitive model combining symbolic variables with Bayesian inference and stochastic program primitives provides a new perspective for understanding people's patterns of generalization. Copyright © 2017 Elsevier B.V. All rights reserved.

Recurrence Methods for the Identification of Morphogenetic Patterns

PubMed Central

Facchini, Angelo; Mocenni, Chiara

2013-01-01

This paper addresses the problem of identifying the parameters involved in the formation of spatial patterns in nonlinear two dimensional systems. To this aim, we perform numerical experiments on a prototypical model generating morphogenetic Turing patterns, by changing both the spatial frequency and shape of the patterns. The features of the patterns and their relationship with the model parameters are characterized by means of the Generalized Recurrence Quantification measures. We show that the recurrence measures Determinism and Recurrence Entropy, as well as the distribution of the line lengths, allow for a full characterization of the patterns in terms of power law decay with respect to the parameters involved in the determination of their spatial frequency and shape. A comparison with the standard two dimensional Fourier transform is performed and the results show a better performance of the recurrence indicators in identifying a reliable connection with the spatial frequency of the patterns. Finally, in order to evaluate the robustness of the estimation of the power low decay, extensive simulations have been performed by adding different levels of noise to the patterns. PMID:24066062

Temporal pattern processing in songbirds.

PubMed

Comins, Jordan A; Gentner, Timothy Q

2014-10-01

Understanding how the brain perceives, organizes and uses patterned information is directly related to the neurobiology of language. Given the present limitations, such knowledge at the scale of neurons, neural circuits and neural populations can only come from non-human models, focusing on shared capacities that are relevant to language processing. Here we review recent advances in the behavioral and neural basis of temporal pattern processing of natural auditory communication signals in songbirds, focusing on European starlings. We suggest a general inhibitory circuit for contextual modulation that can act to control sensory representations based on patterning rules. Copyright © 2014. Published by Elsevier Ltd.

Major Dietary Patterns in Relation to General and Central Obesity among Chinese Adults.

PubMed

Yu, Canqing; Shi, Zumin; Lv, Jun; Du, Huaidong; Qi, Lu; Guo, Yu; Bian, Zheng; Chang, Liang; Tang, Xuefeng; Jiang, Qilian; Mu, Huaiyi; Pan, Dongxia; Chen, Junshi; Chen, Zhengming; Li, Liming

2015-07-15

Limited evidence exists for the association between diet pattern and obesity phenotypes among Chinese adults. In the present study, we analyzed the cross-sectional data from 474,192 adults aged 30-79 years from the China Kadoorie Biobank baseline survey. Food consumption was collected by an interviewer-administered questionnaire. Three dietary patterns were extracted by factor analysis combined with cluster analysis. After being adjusted for potential confounders, individuals following a traditional southern dietary pattern had the lowest body mass index (BMI) and waist circumference (WC); the Western/new affluence dietary pattern had the highest BMI; and the traditional northern dietary pattern had the highest WC. Compared to the traditional southern dietary pattern in multivariable adjusted logistic models, individuals following a Western/new affluence dietary pattern had a significantly increased risk of general obesity (prevalence ratio (PR): 1.06, 95% confidence interval (CI): 1.03-1.08) and central obesity (PR: 1.07, 95% CI: 1.06-1.08). The corresponding risks for the traditional northern dietary pattern were 1.05 (1.02-1.09) and 1.17 (1.25-1.18), respectively. In addition, the associations were modified by lifestyle behaviors, and the combined effects with alcohol drinking, tobacco smoking, and physical activity were analyzed. Further prospective studies are needed to elucidate the diet-obesity relationships.

Improved Forecasting of Next Day Ozone Concentrations in the Eastern U.S.

EPA Science Inventory

There is an urgent need to provide accurate air quality information and forecasts to the general public. A hierarchical space-time model is used to forecast next day spatial patterns of daily maximum 8-hr ozone concentrations. The model combines ozone monitoring data and gridded...

Modelling the growth of plants with a uniform growth logistics.

PubMed

Kilian, H G; Bartkowiak, D; Kazda, M; Kaufmann, D

2014-05-21

The increment model has previously been used to describe the growth of plants in general. Here, we examine how the same logistics enables the development of different superstructures. Data from the literature are analyzed with the increment model. Increments are growth-invariant molecular clusters, treated as heuristic particles. This approach formulates the law of mass action for multi-component systems, describing the general properties of superstructures which are optimized via relaxation processes. The daily growth patterns of hypocotyls can be reproduced implying predetermined growth invariant model parameters. In various species, the coordinated formation and death of fine roots are modeled successfully. Their biphasic annual growth follows distinct morphological programs but both use the same logistics. In tropical forests, distributions of the diameter in breast height of trees of different species adhere to the same pattern. Beyond structural fluctuations, competition and cooperation within and between the species may drive optimization. All superstructures of plants examined so far could be reproduced with our approach. With genetically encoded growth-invariant model parameters (interaction with the environment included) perfect morphological development runs embedded in the uniform logistics of the increment model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Right-Sizing Statistical Models for Longitudinal Data

PubMed Central

Wood, Phillip K.; Steinley, Douglas; Jackson, Kristina M.

2015-01-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to “right-size” the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting overly parsimonious models to more complex better fitting alternatives, and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically under-identified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A three-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation/covariation patterns. The orthogonal, free-curve slope-intercept (FCSI) growth model is considered as a general model which includes, as special cases, many models including the Factor Mean model (FM, McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, Hierarchical Linear Models (HLM), Repeated Measures MANOVA, and the Linear Slope Intercept (LinearSI) Growth Model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparison of several candidate parametric growth and chronometric models in a Monte Carlo study. PMID:26237507

Right-sizing statistical models for longitudinal data.

PubMed

Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M

2015-12-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).

A USCLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Wang, Hailan; Koster, Randal; Weaver, Scott; Gutzler, David; Dai, Aiguo; Delworth, Tom; Deser, Clara; Findell, Kristen; Fu, Rong;

Mechanochemical pattern formation in simple models of active viscoelastic fluids and solids

NASA Astrophysics Data System (ADS)

Alonso, Sergio; Radszuweit, Markus; Engel, Harald; Bär, Markus

2017-11-01

The cytoskeleton of the organism Physarum polycephalum is a prominent example of a complex active viscoelastic material wherein stresses induce flows along the organism as a result of the action of molecular motors and their regulation by calcium ions. Experiments in Physarum polycephalum have revealed a rich variety of mechanochemical patterns including standing, traveling and rotating waves that arise from instabilities of spatially homogeneous states without gradients in stresses and resulting flows. Herein, we investigate simple models where an active stress induced by molecular motors is coupled to a model describing the passive viscoelastic properties of the cellular material. Specifically, two models for viscoelastic fluids (Maxwell and Jeffrey model) and two models for viscoelastic solids (Kelvin-Voigt and Standard model) are investigated. Our focus is on the analysis of the conditions that cause destabilization of spatially homogeneous states and the related onset of mechano-chemical waves and patterns. We carry out linear stability analyses and numerical simulations in one spatial dimension for different models. In general, sufficiently strong activity leads to waves and patterns. The primary instability is stationary for all active fluids considered, whereas all active solids have an oscillatory primary instability. All instabilities found are of long-wavelength nature reflecting the conservation of the total calcium concentration in the models studied.

Algebraic Reasoning in Solving Mathematical Problem Based on Learning Style

NASA Astrophysics Data System (ADS)

Indraswari, N. F.; Budayasa, I. K.; Ekawati, R.

2018-01-01

This study aimed to describe algebraic reasoning of secondary school’s pupils with different learning styles in solving mathematical problem. This study begins by giving the questionnaire to find out the learning styles and followed by mathematical ability test to get three subjects of 8th-grade whereas the learning styles of each pupil is visual, auditory, kinesthetic and had similar mathematical abilities. Then it continued with given algebraic problems and interviews. The data is validated using triangulation of time. The result showed that in the pattern of seeking indicator, subjects identified the things that were known and asked based on them observations. The visual and kinesthetic learners represented the known information in a chart, whereas the auditory learner in a table. In addition, they found the elements which makes the pattern and made a relationship between two quantities. In the pattern recognition indicator, they created conjectures on the relationship between two quantities and proved it. In the generalization indicator, they were determining the general rule of pattern found on each element of pattern using algebraic symbols and created a mathematical model. Visual and kinesthetic learners determined the general rule of equations which was used to solve problems using algebraic symbols, but auditory learner in a sentence.

Image Understanding and Information Extraction\\

DTIC Science & Technology

1977-11-01

mentation and generalization of DeCarlo’s Nyquist-like stability test [15,161. The last step of the procedure is to check whether this zero ...Several general sta- bility theorems which relate stability to the zero set of B(w,z) have been presented. These theorems led to the conclusion that...Spatial Stochastic Model for Contextual Pattern Recognition . ° . .............. 88 T. S. Yu and K. S. Fu V. PREPROCESSING 1. Stability of General Two

Modelling survival: exposure pattern, species sensitivity and uncertainty.

PubMed

Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

2016-07-06

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Modelling survival: exposure pattern, species sensitivity and uncertainty

NASA Astrophysics Data System (ADS)

Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I.; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B.; van den Brink, Paul J.; Veltman, Karin; Vogel, Sören; Zimmer, Elke I.; Preuss, Thomas G.

2016-07-01

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Classification and Sequential Pattern Analysis for Improving Managerial Efficiency and Providing Better Medical Service in Public Healthcare Centers

PubMed Central

Chung, Sukhoon; Rhee, Hyunsill; Suh, Yongmoo

2010-01-01

Objectives This study sought to find answers to the following questions: 1) Can we predict whether a patient will revisit a healthcare center? 2) Can we anticipate diseases of patients who revisit the center? Methods For the first question, we applied 5 classification algorithms (decision tree, artificial neural network, logistic regression, Bayesian networks, and Naïve Bayes) and the stacking-bagging method for building classification models. To solve the second question, we performed sequential pattern analysis. Results We determined: 1) In general, the most influential variables which impact whether a patient of a public healthcare center will revisit it or not are personal burden, insurance bill, period of prescription, age, systolic pressure, name of disease, and postal code. 2) The best plain classification model is dependent on the dataset. 3) Based on average of classification accuracy, the proposed stacking-bagging method outperformed all traditional classification models and our sequential pattern analysis revealed 16 sequential patterns. Conclusions Classification models and sequential patterns can help public healthcare centers plan and implement healthcare service programs and businesses that are more appropriate to local residents, encouraging them to revisit public health centers. PMID:21818426

Comparing methods of measuring geographic patterns in temporal trends: an application to county-level heart disease mortality in the United States, 1973 to 2010.

PubMed

Vaughan, Adam S; Kramer, Michael R; Waller, Lance A; Schieb, Linda J; Greer, Sophia; Casper, Michele

2015-05-01

To demonstrate the implications of choosing analytical methods for quantifying spatiotemporal trends, we compare the assumptions, implementation, and outcomes of popular methods using county-level heart disease mortality in the United States between 1973 and 2010. We applied four regression-based approaches (joinpoint regression, both aspatial and spatial generalized linear mixed models, and Bayesian space-time model) and compared resulting inferences for geographic patterns of local estimates of annual percent change and associated uncertainty. The average local percent change in heart disease mortality from each method was -4.5%, with the Bayesian model having the smallest range of values. The associated uncertainty in percent change differed markedly across the methods, with the Bayesian space-time model producing the narrowest range of variance (0.0-0.8). The geographic pattern of percent change was consistent across methods with smaller declines in the South Central United States and larger declines in the Northeast and Midwest. However, the geographic patterns of uncertainty differed markedly between methods. The similarity of results, including geographic patterns, for magnitude of percent change across these methods validates the underlying spatial pattern of declines in heart disease mortality. However, marked differences in degree of uncertainty indicate that Bayesian modeling offers substantially more precise estimates. Copyright © 2015 Elsevier Inc. All rights reserved.

Adolescents' eating behaviour in general and in the peer context: testing the prototype-willingness model.

PubMed

Dohnke, Birte; Steinhilber, Amina; Fuchs, Tanja

2015-01-01

To investigate the prototype-willingness model (PWM) for eating behaviour in general and in the peer context in order to gain further evidence on the PWM and social-reactive processes in adolescents' eating behaviour. A longitudinal study was conducted. PWM variables for unhealthy and healthy eating were assessed at baseline in 356 adolescents (mean age 12.61 years). Eating behaviour was measured four weeks after baseline by two indicators: general eating pattern index (self-report) and consumption of unhealthy and healthy snacks in the peer context (behavioural observation). For both, structural equation models were conducted introducing PWM variables for either unhealthy or healthy eating. The PWM was mainly confirmed for the eating pattern index; intention, willingness and prototype perception had direct effects. Differences between unhealthy and healthy eating were found. Moreover, the PWM contributed to the prediction of healthy, but not unhealthy, snack consumption over and above current hunger; willingness had a direct effect. The PWM can be applied to predict and understand adolescents' eating behaviour. Social-reactive processes, namely willingness and prototype perception, are behavioural determinants that should be considered in theory and as novel targets in health promotion interventions.

How consistent are precipitation patterns predicted by GCMs in the absence of cloud radiative effects?

NASA Astrophysics Data System (ADS)

Popke, Dagmar; Bony, Sandrine; Mauritsen, Thorsten; Stevens, Bjorn

2015-04-01

Model simulations with state-of-the-art general circulation models reveal a strong disagreement concerning the simulated regional precipitation patterns and their changes with warming. The deviating precipitation response even persists when reducing the model experiment complexity to aquaplanet simulation with forced sea surface temperatures (Stevens and Bony, 2013). To assess feedbacks between clouds and radiation on precipitation responses we analyze data from 5 models performing the aquaplanet simulations of the Clouds On Off Klima Intercomparison Experiment (COOKIE), where the interaction of clouds and radiation is inhibited. Although cloud radiative effects are then disabled, the precipitation patterns among models are as diverse as with cloud radiative effects switched on. Disentangling differing model responses in such simplified experiments thus appears to be key to better understanding the simulated regional precipitation in more standard configurations. By analyzing the local moisture and moist static energy budgets in the COOKIE experiments we investigate likely causes for the disagreement among models. References Stevens, B. & S. Bony: What Are Climate Models Missing?, Science, 2013, 340, 1053-1054

Hydrology or biology? Modeling simplistic physical constraints on lake carbon biogeochemistry to identify when and where biology is likely to matter

NASA Astrophysics Data System (ADS)

Jones, S.; Zwart, J. A.; Solomon, C.; Kelly, P. T.

2017-12-01

Current efforts to scale lake carbon biogeochemistry rely heavily on empirical observations and rarely consider physical or biological inter-lake heterogeneity that is likely to regulate terrestrial dissolved organic carbon (tDOC) decomposition in lakes. This may in part result from a traditional focus of lake ecologists on in-lake biological processes OR physical-chemical pattern across lake regions, rather than on process AND pattern across scales. To explore the relative importance of local biological processes and physical processes driven by lake hydrologic setting, we created a simple, analytical model of tDOC decomposition in lakes that focuses on the regulating roles of lake size and catchment hydrologic export. Our simplistic model can generally recreate patterns consistent with both local- and regional-scale patterns in tDOC concentration and decomposition. We also see that variation in lake hydrologic setting, including the importance of evaporation as a hydrologic export, generates significant, emergent variation in tDOC decomposition at a given hydrologic residence time, and creates patterns that have been historically attributed to variation in tDOC quality. Comparing predictions of this `biologically null model' to field observations and more biologically complex models could indicate when and where biology is likely to matter most.

Econometrics and data of the 9 sector Dynamic General Equilibrium Model. Volume III. Final report

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

Berndt, E.R.; Fraumeni, B.M.; Hudson, E.A.

1981-03-01

This report presents the econometrics and data of the 9 sector Dynamic General Equilibrium Model. There are two key components of 9DGEM - the model of household behavior and the model of produconcrneer behavior. The household model is concerned with decisions on consumption, saving, labor supply and the composition of consumption. The producer model is concerned with output price formation and determination of input patterns and purchases for each of the nine producing sectors. These components form the behavioral basis of DGEM. The remaining components are concerned with constraints, balance conditions, accounting, and government revenues and expenditures (these elements aremore » developed in the report on the model specification).« less

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

The super-Turing computational power of plastic recurrent neural networks.

PubMed

Cabessa, Jérémie; Siegelmann, Hava T

2014-12-01

We study the computational capabilities of a biologically inspired neural model where the synaptic weights, the connectivity pattern, and the number of neurons can evolve over time rather than stay static. Our study focuses on the mere concept of plasticity of the model so that the nature of the updates is assumed to be not constrained. In this context, we show that the so-called plastic recurrent neural networks (RNNs) are capable of the precise super-Turing computational power--as the static analog neural networks--irrespective of whether their synaptic weights are modeled by rational or real numbers, and moreover, irrespective of whether their patterns of plasticity are restricted to bi-valued updates or expressed by any other more general form of updating. Consequently, the incorporation of only bi-valued plastic capabilities in a basic model of RNNs suffices to break the Turing barrier and achieve the super-Turing level of computation. The consideration of more general mechanisms of architectural plasticity or of real synaptic weights does not further increase the capabilities of the networks. These results support the claim that the general mechanism of plasticity is crucially involved in the computational and dynamical capabilities of biological neural networks. They further show that the super-Turing level of computation reflects in a suitable way the capabilities of brain-like models of computation.

Matching consumer feeding behaviours and resource traits: a fourth-corner problem in food-web theory.

PubMed

Monteiro, Angelo Barbosa; Faria, Lucas Del Bianco

2018-06-06

For decades, food web theory has proposed phenomenological models for the underlying structure of ecological networks. Generally, these models rely on latent niche variables that match the feeding behaviour of consumers with their resource traits. In this paper, we used a comprehensive database to evaluate different hypotheses on the best dependency structure of trait-matching patterns between consumers and resource traits. We found that consumer feeding behaviours had complex interactions with resource traits; however, few dimensions (i.e. latent variables) could reproduce the trait-matching patterns. We discuss our findings in the light of three food web models designed to reproduce the multidimensionality of food web data; additionally, we discuss how using species traits clarify food webs beyond species pairwise interactions and enable studies to infer ecological generality at larger scales, despite potential taxonomic differences, variations in ecological conditions and differences in species abundance between communities. © 2018 John Wiley & Sons Ltd/CNRS.

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

NASA Astrophysics Data System (ADS)

Bianchini, Monica; Scarselli, Franco

In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

Spatial patterns of ecohydrologic properties on a hillslope-alluvial fan transect, central New Mexico

USGS Publications Warehouse

Bedford, D.R.; Small, E.E.

2008-01-01

Spatial patterns of soil properties are linked to patchy vegetation in arid and semi-arid landscapes. The patterns of soil properties are generally assumed to be linked to the ecohydrological functioning of patchy dryland vegetation ecosystems. We studied the effects of vegetation canopy, its spatial pattern, and landforms on soil properties affecting overland flow and infiltration in shrublands at the Sevilleta National Wildlife Refuge/LTER in central New Mexico, USA. We studied the patterns of microtopography and saturated conductivity (Ksat), and generally found it to be affected by vegetation canopy and pattern, as well as landform type. On gently sloping alluvial fans, both microtopography and Ksat are high under vegetation canopy and decay with distance from plant center. On steeper hillslope landforms, only microtopography was significantly higher under vegetation canopy, while there was no significant difference in Ksat between vegetation and interspaces. Using geostatistics, we found that the spatial pattern of soil properties was determined by the spatial pattern of vegetation. Most importantly, the effects of vegetation were present in the unvegetated interspaces 2-4 times the extent of vegetation canopy, on the order of 2-3??m. Our results have implications for the understanding the ecohydrologic function of semi-arid ecosystems as well as the parameterization of hydrologic models. ?? 2007 Elsevier B.V. All rights reserved.

Maximum entropy production allows a simple representation of heterogeneity in semiarid ecosystems.

PubMed

Schymanski, Stanislaus J; Kleidon, Axel; Stieglitz, Marc; Narula, Jatin

2010-05-12

Feedbacks between water use, biomass and infiltration capacity in semiarid ecosystems have been shown to lead to the spontaneous formation of vegetation patterns in a simple model. The formation of patterns permits the maintenance of larger overall biomass at low rainfall rates compared with homogeneous vegetation. This results in a bias of models run at larger scales neglecting subgrid-scale variability. In the present study, we investigate the question whether subgrid-scale heterogeneity can be parameterized as the outcome of optimal partitioning between bare soil and vegetated area. We find that a two-box model reproduces the time-averaged biomass of the patterns emerging in a 100 x 100 grid model if the vegetated fraction is optimized for maximum entropy production (MEP). This suggests that the proposed optimality-based representation of subgrid-scale heterogeneity may be generally applicable to different systems and at different scales. The implications for our understanding of self-organized behaviour and its modelling are discussed.

A discrete model of Drosophila eggshell patterning reveals cell-autonomous and juxtacrine effects.

PubMed

Fauré, Adrien; Vreede, Barbara M I; Sucena, Elio; Chaouiya, Claudine

2014-03-01

The Drosophila eggshell constitutes a remarkable system for the study of epithelial patterning, both experimentally and through computational modeling. Dorsal eggshell appendages arise from specific regions in the anterior follicular epithelium that covers the oocyte: two groups of cells expressing broad (roof cells) bordered by rhomboid expressing cells (floor cells). Despite the large number of genes known to participate in defining these domains and the important modeling efforts put into this developmental system, key patterning events still lack a proper mechanistic understanding and/or genetic basis, and the literature appears to conflict on some crucial points. We tackle these issues with an original, discrete framework that considers single-cell models that are integrated to construct epithelial models. We first build a phenomenological model that reproduces wild type follicular epithelial patterns, confirming EGF and BMP signaling input as sufficient to establish the major features of this patterning system within the anterior domain. Importantly, this simple model predicts an instructive juxtacrine signal linking the roof and floor domains. To explore this prediction, we define a mechanistic model that integrates the combined effects of cellular genetic networks, cell communication and network adjustment through developmental events. Moreover, we focus on the anterior competence region, and postulate that early BMP signaling participates with early EGF signaling in its specification. This model accurately simulates wild type pattern formation and is able to reproduce, with unprecedented level of precision and completeness, various published gain-of-function and loss-of-function experiments, including perturbations of the BMP pathway previously seen as conflicting results. The result is a coherent model built upon rules that may be generalized to other epithelia and developmental systems.

Modeling Agrilus planipennis within-tree colonization patterns and development of a systematic subsampling plan

USDA-ARS?s Scientific Manuscript database

Emerald ash borer, Agrilus planipennis Fairmaire, an insect native to central Asia, was first detected in southeast Michigan in 2002, and has since killed millions of ash trees, Fraxinus spp., throughout eastern North America. Here, we use generalized linear mixed models to predict the presence or a...

Team Design Communication Patterns in e-Learning Design and Development

ERIC Educational Resources Information Center

Rapanta, Chrysi; Maina, Marcelo; Lotz, Nicole; Bacchelli, Alberto

2013-01-01

Prescriptive stage models have been found insufficient to describe the dynamic aspects of designing, especially in interdisciplinary e-learning design teams. There is a growing need for a systematic empirical analysis of team design processes that offer deeper and more detailed insights into instructional design (ID) than general models can offer.…

Feed-forward and generalized regression neural networks in modeling feeding behavior of pigs in the grow-finishing phase

USDA-ARS?s Scientific Manuscript database

Feeding patterns in group-housed grow-finishing pigs have been investigated for use in management decisions, identifying sick animals, and determining genetic differences within a herd. Development of models to predict swine feeding behaviour has been limited due the large number of potential enviro...

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

Models of clinical reasoning with a focus on general practice: A critical review

PubMed Central

YAZDANI, SHAHRAM; HOSSEINZADEH, MOHAMMAD; HOSSEINI, FAKHROLSADAT

2017-01-01

Introduction: Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. Methods: A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Results: Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. Conclusion: A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed. PMID:28979912

Active Curved Polymers Form Vortex Patterns on Membranes.

PubMed

Denk, Jonas; Huber, Lorenz; Reithmann, Emanuel; Frey, Erwin

2016-04-29

Recent in vitro experiments with FtsZ polymers show self-organization into different dynamic patterns, including structures reminiscent of the bacterial Z ring. We model FtsZ polymers as active particles moving along chiral, circular paths by Brownian dynamics simulations and a Boltzmann approach. Our two conceptually different methods point to a generic phase behavior. At intermediate particle densities, we find self-organization into vortex structures including closed rings. Moreover, we show that the dynamics at the onset of pattern formation is described by a generalized complex Ginzburg-Landau equation.

General patterns of niche construction and the management of ‘wild’ plant and animal resources by small-scale pre-industrial societies

PubMed Central

Smith, Bruce D.

2011-01-01

Niche construction efforts by small-scale human societies that involve ‘wild’ species of plants and animals are organized into a set of six general categories based on the shared characteristics of the target species and similar patterns of human management and manipulation: (i) general modification of vegetation communities, (ii) broadcast sowing of wild annuals, (iii) transplantation of perennial fruit-bearing species, (iv) in-place encouragement of economically important perennials, (v) transplantation and in-place encouragement of perennial root crops, and (vi) landscape modification to increase prey abundance in specific locations. Case study examples, mostly drawn from North America, are presented for each of the six general categories of human niche construction. These empirically documented categories of ecosystem engineering form the basis for a predictive model that outlines potential general principles and commonalities in how small-scale human societies worldwide have modified and manipulated their ‘natural’ landscapes throughout the Holocene. PMID:21320898

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

A general framework for predicting delayed responses of ecological communities to habitat loss.

PubMed

Chen, Youhua; Shen, Tsung-Jen

2017-04-20

Although biodiversity crisis at different spatial scales has been well recognised, the phenomena of extinction debt and immigration credit at a crossing-scale context are, at best, unclear. Based on two community patterns, regional species abundance distribution (SAD) and spatial abundance distribution (SAAD), Kitzes and Harte (2015) presented a macroecological framework for predicting post-disturbance delayed extinction patterns in the entire ecological community. In this study, we further expand this basic framework to predict diverse time-lagged effects of habitat destruction on local communities. Specifically, our generalisation of KH's model could address the questions that could not be answered previously: (1) How many species are subjected to delayed extinction in a local community when habitat is destructed in other areas? (2) How do rare or endemic species contribute to extinction debt or immigration credit of the local community? (3) How will species differ between two local areas? From the demonstrations using two SAD models (single-parameter lognormal and logseries), the predicted patterns of the debt, credit, and change in the fraction of unique species can vary, but with consistencies and depending on several factors. The general framework deepens the understanding of the theoretical effects of habitat loss on community dynamic patterns in local samples.

Alcohol use, mental well-being, self-esteem and general self-efficacy among final-year university students.

PubMed

Blank, Mei-Ling; Connor, Jennie; Gray, Andrew; Tustin, Karen

2016-03-01

We aimed to quantify associations between drinking and mental well-being, self-esteem and general self-efficacy among New Zealand university students approaching graduation. A web-based survey was conducted across all eight New Zealand universities in 2011. Participants were enrolled in their final year of a bachelor degree or a higher qualification and were aged 25 years and under (n = 5082, response level 65 %). Measures included the Alcohol Use Disorders Identification Test-Consumption, Warwick-Edinburgh Mental Well-being Scale, and items from the Rosenberg Self-esteem Scale and General Self-efficacy Scale. Linear regression models were used to estimate associations between the psychological measures and (1) drinking patterns for all participants (abstention/moderate/hazardous); and (2) consumption indicators for non-abstaining participants (frequency/quantity/heavy drinking frequency), adjusting for a range of individual, social and personality characteristics, separately for men and women. Lower mental well-being was associated with a moderate or hazardous drinking pattern for men, and a hazardous pattern for women, compared to abstaining participants. Higher self-esteem was associated with any level of heavy drinking frequency for men, while the heaviest drinking women had a pattern of lower self-esteem. There was a general pattern of higher general self-efficacy for men and women who drank alcohol. We observed that higher levels of drinking were associated with small, yet statistically significant, differences in psychological outcomes for men and women. Our findings are of uncertain clinical significance; however, they underscore the importance of investigating a fuller range of social and personality factors that may confound the association of drinking and psychological outcomes.

Comparison between sparsely distributed memory and Hopfield-type neural network models

NASA Technical Reports Server (NTRS)

Keeler, James D.

1986-01-01

The Sparsely Distributed Memory (SDM) model (Kanerva, 1984) is compared to Hopfield-type neural-network models. A mathematical framework for comparing the two is developed, and the capacity of each model is investigated. The capacity of the SDM can be increased independently of the dimension of the stored vectors, whereas the Hopfield capacity is limited to a fraction of this dimension. However, the total number of stored bits per matrix element is the same in the two models, as well as for extended models with higher order interactions. The models are also compared in their ability to store sequences of patterns. The SDM is extended to include time delays so that contextual information can be used to cover sequences. Finally, it is shown how a generalization of the SDM allows storage of correlated input pattern vectors.

A Stochastic-Variational Model for Soft Mumford-Shah Segmentation

PubMed Central

2006-01-01

In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational advantages over Monte Carlo or other stochastic algorithms. In combination, the two can lead to much more powerful novel models and efficient algorithms. In the current work, we propose a stochastic-variational model for soft (or fuzzy) Mumford-Shah segmentation of mixture image patterns. Unlike the classical hard Mumford-Shah segmentation, the new model allows each pixel to belong to each image pattern with some probability. Soft segmentation could lead to hard segmentation, and hence is more general. The modeling procedure, mathematical analysis on the existence of optimal solutions, and computational implementation of the new model are explored in detail, and numerical examples of both synthetic and natural images are presented. PMID:23165059

Stickney-forming impact on PHOBOS - Crater shape and induced stress distribution

NASA Astrophysics Data System (ADS)

Fujiwara, A.

1991-02-01

The results of the present simplified modeling of the size and rim shape of the Phobos crater Stickney, together with the impact-generated stress patterns on the surface of the crater, account for the general features observed and suggest, on the basis of some of the P-waves' surface stress pattern, that a region of higher tensile stress may have occurred in the vicinity of 0 deg latitude and 270 deg W. The correlation of this pattern with the focusing of groove patterns that occurs on the trailing side of Phobos is suggested to demonstrate a connection between these grooves and the Stickney crater-forming impact.

Patterns of human local cerebral glucose metabolism during epileptic seizures

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

Engel, J. Jr.; Kuhl, D.E.; Phelps, M.E.

1982-10-01

Ictal patterns of local cerebral metabolic rate have been studied in epileptic patients by positron computed tomography with /sup 18/F-labeled 2-fluoro-2-deoxy-D-glucose. Partial seizures were associated with activation of anatomic structures unique to each patient studied. Ictal increases and decreases in local cerebral metabolism were observed. Scans performed during generalized convulsions induced by electroshock demonstrated a diffuse ictal increase and postictal decrease in cerebral metabolism. Petit mal absences were associated with a diffuse increase in cerebral metabolic rate. The ictal fluorodeoxyglucose patterns obtained from patients do not resemble autoradiographic patterns obtained from common experimental animal models of epilepsy.

Modelling Vulnerability and Range Shifts in Ant Communities Responding to Future Global Warming in Temperate Forests

PubMed Central

Kim, Sung-Soo; Chun, Jung Hwa; Park, Young-Seuk

2016-01-01

Global warming is likely leading to species’ distributional shifts, resulting in changes in local community compositions and diversity patterns. In this study, we applied species distribution models to evaluate the potential impacts of temperature increase on ant communities in Korean temperate forests, by testing hypotheses that 1) the risk of extinction of forest ant species would increase over time, and 2) the changes in species distribution ranges could drive upward movements of ant communities and further alter patterns of species richness. We sampled ant communities at 335 evenly distributed sites across South Korea and modelled the future distribution range for each species using generalized additive models. To account for spatial autocorrelation, autocovariate regressions were conducted prior to generalized additive models. Among 29 common ant species, 12 species were estimated to shrink their suitable geographic areas, whereas five species would benefit from future global warming. Species richness was highest at low altitudes in the current period, and it was projected to be highest at the mid-altitudes in the 2080s, resulting in an upward movement of 4.9 m yr−1. This altered the altitudinal pattern of species richness from a monotonic-decrease curve (common in temperate regions) to a bell-shaped curve (common in tropical regions). Overall, ant communities in temperate forests are vulnerable to the on-going global warming and their altitudinal movements are similar to other faunal communities. PMID:27504632

Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization

PubMed Central

Peng, Huan-Kai; Lee, Hao-Chih; Pan, Jia-Yu; Marculescu, Radu

2016-01-01

In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications. PMID:26771830

Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization.

PubMed

Peng, Huan-Kai; Lee, Hao-Chih; Pan, Jia-Yu; Marculescu, Radu

2016-01-01

In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications.

Phase diagram of restricted Boltzmann machines and generalized Hopfield networks with arbitrary priors.

PubMed

Barra, Adriano; Genovese, Giuseppe; Sollich, Peter; Tantari, Daniele

2018-02-01

Restricted Boltzmann machines are described by the Gibbs measure of a bipartite spin glass, which in turn can be seen as a generalized Hopfield network. This equivalence allows us to characterize the state of these systems in terms of their retrieval capabilities, both at low and high load, of pure states. We study the paramagnetic-spin glass and the spin glass-retrieval phase transitions, as the pattern (i.e., weight) distribution and spin (i.e., unit) priors vary smoothly from Gaussian real variables to Boolean discrete variables. Our analysis shows that the presence of a retrieval phase is robust and not peculiar to the standard Hopfield model with Boolean patterns. The retrieval region becomes larger when the pattern entries and retrieval units get more peaked and, conversely, when the hidden units acquire a broader prior and therefore have a stronger response to high fields. Moreover, at low load retrieval always exists below some critical temperature, for every pattern distribution ranging from the Boolean to the Gaussian case.

Pseudo-orthogonalization of memory patterns for associative memory.

PubMed

Oku, Makito; Makino, Takaki; Aihara, Kazuyuki

2013-11-01

A new method for improving the storage capacity of associative memory models on a neural network is proposed. The storage capacity of the network increases in proportion to the network size in the case of random patterns, but, in general, the capacity suffers from correlation among memory patterns. Numerous solutions to this problem have been proposed so far, but their high computational cost limits their scalability. In this paper, we propose a novel and simple solution that is locally computable without any iteration. Our method involves XNOR masking of the original memory patterns with random patterns, and the masked patterns and masks are concatenated. The resulting decorrelated patterns allow higher storage capacity at the cost of the pattern length. Furthermore, the increase in the pattern length can be reduced through blockwise masking, which results in a small amount of capacity loss. Movie replay and image recognition are presented as examples to demonstrate the scalability of the proposed method.

The Electrocardiogram as an Example of Electrostatics

ERIC Educational Resources Information Center

Hobbie, Russell K.

1973-01-01

Develops a simplified electrostatic model of the heart with conduction within the torso neglected to relate electrocardiogram patterns to the charge distribution within the myocardium. Suggests its application to explanation of Coulomb's law in general physics. (CC)

Characteristics of atmospheric circulation patterns associated with extreme temperatures over North America in observations and climate models

NASA Astrophysics Data System (ADS)

Loikith, Paul C.

Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. Several novel metrics are used to systematically identify and describe these patterns for the entire continent. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. The influence of the Pacific North American (PNA) pattern, the Northern Annular Mode (NAM), and the El Niño-Southern Oscillation (ENSO) on extreme temperature days and months shows that associations between extreme temperatures and the PNA and NAM are stronger than associations with ENSO. In general, the association with extremes tends to be stronger on monthly than daily time scales. Extreme temperatures are associated with the PNA and NAM in locations typically influenced by these circulation patterns; however many extremes still occur on days when the amplitude and polarity of these patterns do not favor their occurrence. In winter, synoptic-scale, transient weather disturbances are important drivers of extreme temperature days; however these smaller-scale events are often concurrent with amplified PNA or NAM patterns. Associations are weaker in summer when other physical mechanisms affecting the surface energy balance, such as anomalous soil moisture content, are associated with extreme temperatures. Analysis of historical runs from seventeen climate models from the CMIP5 database suggests that most models simulate realistic circulation patterns associated with extreme temperature days in most places. Model-simulated patterns tend to resemble observed patterns better in the winter than the summer and at 500 hPa than at the surface. There is substantial variability among the suite of models analyzed and most models simulate circulation patterns more realistically away from influential features such as large bodies of water and complex topography.

Coupled Particle Transport and Pattern Formation in a Nonlinear Leaky-Box Model

NASA Technical Reports Server (NTRS)

Barghouty, A. F.; El-Nemr, K. W.; Baird, J. K.

2009-01-01

Effects of particle-particle coupling on particle characteristics in nonlinear leaky-box type descriptions of the acceleration and transport of energetic particles in space plasmas are examined in the framework of a simple two-particle model based on the Fokker-Planck equation in momentum space. In this model, the two particles are assumed coupled via a common nonlinear source term. In analogy with a prototypical mathematical system of diffusion-driven instability, this work demonstrates that steady-state patterns with strong dependence on the magnetic turbulence but a rather weak one on the coupled particles attributes can emerge in solutions of a nonlinearly coupled leaky-box model. The insight gained from this simple model may be of wider use and significance to nonlinearly coupled leaky-box type descriptions in general.

Major Dietary Patterns in Relation to General and Central Obesity among Chinese Adults

PubMed Central

Yu, Canqing; Shi, Zumin; Lv, Jun; Du, Huaidong; Qi, Lu; Guo, Yu; Bian, Zheng; Chang, Liang; Tang, Xuefeng; Jiang, Qilian; Mu, Huaiyi; Pan, Dongxia; Chen, Junshi; Chen, Zhengming; Li, Liming

2015-01-01

Limited evidence exists for the association between diet pattern and obesity phenotypes among Chinese adults. In the present study, we analyzed the cross-sectional data from 474,192 adults aged 30–79 years from the China Kadoorie Biobank baseline survey. Food consumption was collected by an interviewer-administered questionnaire. Three dietary patterns were extracted by factor analysis combined with cluster analysis. After being adjusted for potential confounders, individuals following a traditional southern dietary pattern had the lowest body mass index (BMI) and waist circumference (WC); the Western/new affluence dietary pattern had the highest BMI; and the traditional northern dietary pattern had the highest WC. Compared to the traditional southern dietary pattern in multivariable adjusted logistic models, individuals following a Western/new affluence dietary pattern had a significantly increased risk of general obesity (prevalence ratio (PR): 1.06, 95% confidence interval (CI): 1.03–1.08) and central obesity (PR: 1.07, 95% CI: 1.06–1.08). The corresponding risks for the traditional northern dietary pattern were 1.05 (1.02–1.09) and 1.17 (1.25–1.18), respectively. In addition, the associations were modified by lifestyle behaviors, and the combined effects with alcohol drinking, tobacco smoking, and physical activity were analyzed. Further prospective studies are needed to elucidate the diet-obesity relationships. PMID:26184308

Inter-dependent tissue growth and Turing patterning in a model for long bone development

NASA Astrophysics Data System (ADS)

Tanaka, Simon; Iber, Dagmar

2013-10-01

The development of long bones requires a sophisticated spatial organization of cellular signalling, proliferation, and differentiation programs. How such spatial organization emerges on the growing long bone domain is still unresolved. Based on the reported biochemical interactions we developed a regulatory model for the core signalling factors IHH, PTCH1, and PTHrP and included two cell types, proliferating/resting chondrocytes and (pre-)hypertrophic chondrocytes. We show that the reported IHH-PTCH1 interaction gives rise to a Schnakenberg-type Turing kinetics, and that inclusion of PTHrP is important to achieve robust patterning when coupling patterning and tissue dynamics. The model reproduces relevant spatiotemporal gene expression patterns, as well as a number of relevant mutant phenotypes. In summary, we propose that a ligand-receptor based Turing mechanism may control the emergence of patterns during long bone development, with PTHrP as an important mediator to confer patterning robustness when the sensitive Turing system is coupled to the dynamics of a growing and differentiating tissue. We have previously shown that ligand-receptor based Turing mechanisms can also result from BMP-receptor, SHH-receptor, and GDNF-receptor interactions, and that these reproduce the wildtype and mutant patterns during digit formation in limbs and branching morphogenesis in lung and kidneys. Receptor-ligand interactions may thus constitute a general mechanism to generate Turing patterns in nature.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

The modelling of heat, mass and solute transport in solidification systems

NASA Technical Reports Server (NTRS)

Voller, V. R.; Brent, A. D.; Prakash, C.

1989-01-01

The aim of this paper is to explore the range of possible one-phase models of binary alloy solidification. Starting from a general two-phase description, based on the two-fluid model, three limiting cases are identified which result in one-phase models of binary systems. Each of these models can be readily implemented in standard single phase flow numerical codes. Differences between predictions from these models are examined. In particular, the effects of the models on the predicted macro-segregation patterns are evaluated.

Modeling the Underlying Dynamics of the Spread of Crime

PubMed Central

McMillon, David; Simon, Carl P.; Morenoff, Jeffrey

2014-01-01

The spread of crime is a complex, dynamic process that calls for a systems level approach. Here, we build and analyze a series of dynamical systems models of the spread of crime, imprisonment and recidivism, using only abstract transition parameters. To find the general patterns among these parameters—patterns that are independent of the underlying particulars—we compute analytic expressions for the equilibria and for the tipping points between high-crime and low-crime equilibria in these models. We use these expressions to examine, in particular, the effects of longer prison terms and of increased incarceration rates on the prevalence of crime, with a follow-up analysis on the effects of a Three-Strike Policy. PMID:24694545

Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes

DOE PAGES

Cheng, L.; Phillips, T. J.; AghaKouchak, A.

2015-05-01

The objective of this study is to evaluate to what extent the CMIP5 climate model simulations of the climate of the twentieth century can represent observed warm monthly temperature extremes under a changing environment. The biases and spatial patterns of 2-, 10-, 25-, 50- and 100-year return levels of the annual maxima of monthly mean temperature (hereafter, annual temperature maxima) from CMIP5 simulations are compared with those of Climatic Research Unit (CRU) observational data considered under a non-stationary assumption. The results show that CMIP5 climate models collectively underestimate the mean annual maxima over arid and semi-arid regions that are mostmore » subject to severe heat waves and droughts. Furthermore, the results indicate that most climate models tend to underestimate the historical annual temperature maxima over the United States and Greenland, while generally disagreeing in their simulations over cold regions. Return level analysis shows that with respect to the spatial patterns of the annual temperature maxima, there are good agreements between the CRU observations and most CMIP5 simulations. However, the magnitudes of the simulated annual temperature maxima differ substantially across individual models. Discrepancies are generally larger over higher latitudes and cold regions.« less

Classification of NLO operators for composite Higgs models

NASA Astrophysics Data System (ADS)

Alanne, Tommi; Bizot, Nicolas; Cacciapaglia, Giacomo; Sannino, Francesco

2018-04-01

We provide a general classification of template operators, up to next-to-leading order, that appear in chiral perturbation theories based on the two flavor patterns of spontaneous symmetry breaking SU (NF)/Sp (NF) and SU (NF)/SO (NF). All possible explicit-breaking sources parametrized by spurions transforming in the fundamental and in the two-index representations of the flavor symmetry are included. While our general framework can be applied to any model of strong dynamics, we specialize to composite-Higgs models, where the main explicit breaking sources are a current mass, the gauging of flavor symmetries, and the Yukawa couplings (for the top). For the top, we consider both bilinear couplings and linear ones à la partial compositeness. Our templates provide a basis for lattice calculations in specific models. As a special example, we consider the SU (4 )/Sp (4 )≅SO (6 )/SO (5 ) pattern which corresponds to the minimal fundamental composite-Higgs model. We further revisit issues related to the misalignment of the vacuum. In particular, we shed light on the physical properties of the singlet η , showing that it cannot develop a vacuum expectation value without explicit C P violation in the underlying theory.

Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

NASA Astrophysics Data System (ADS)

Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

2015-07-01

Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

The Mean State and Inter-annual Variability of East Asian Summer Monsoon in CMIP5 Coupled Models: Does Air-Sea Coupling Improve the Simulations?

NASA Astrophysics Data System (ADS)

Zhou, T.; Song, F.

2014-12-01

The climatology and inter-annual variability of East Asian summer monsoon (EASM) simulated by 34 Coupled Model Intercomparison Project phase 5 (CMIP5) coupled general circulation models (CGCMs) are evaluated. To estimate the role of air-sea coupling, 17 CGCMs are compared to their corresponding atmospheric general circulation models (AGCMs). The climatological low-level monsoon circulation and mei-yu/changma/baiu rainfall band are improved in CGCMs from AGCMs. The improvement is at the cost of the local cold sea surface temperature (SST) biases in CGCMs, since they decrease the surface evaporation and enhance the circulation. The inter-annual EASM pattern is evaluated by a skill formula and the highest/lowest 8 models are selected to investigate the skill origins. The observed Indian Ocean (IO) warming, tropical eastern Indian Ocean (TEIO) rainfall anomalies and Kelvin wave response are captured well in high-skill models, while these features are not present in low-skill models. Further, the differences in the IO warming between high-skill and low-skill models are rooted in the preceding ENSO simulation. Hence, the IO-WPAC teleconnection is important for CGCMs, similar to AGCMs. However, compared to AGCMs, the easterly anomalies in the southern flank of the WPAC make the TEIO warmer in CGCMs by reducing the climatological monsoon westerlies and decreasing the surface evaporation. The warmer TEIO induces the stronger precipitation anomalies and intensifies the teleconnection. Hence, the inter-annual EASM pattern is better simulated in CGCMs than that in AGCMs. Key words: CMIP5, CGCMs, air-sea coupling, AGCMs, inter-annual EASM pattern, ENSO, IO-WPAC teleconnection

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

PubMed

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

Edge detection and localization with edge pattern analysis and inflection characterization

NASA Astrophysics Data System (ADS)

Jiang, Bo

2012-05-01

In general edges are considered to be abrupt changes or discontinuities in two dimensional image signal intensity distributions. The accuracy of front-end edge detection methods in image processing impacts the eventual success of higher level pattern analysis downstream. To generalize edge detectors designed from a simple ideal step function model to real distortions in natural images, research on one dimensional edge pattern analysis to improve the accuracy of edge detection and localization proposes an edge detection algorithm, which is composed by three basic edge patterns, such as ramp, impulse, and step. After mathematical analysis, general rules for edge representation based upon the classification of edge types into three categories-ramp, impulse, and step (RIS) are developed to reduce detection and localization errors, especially reducing "double edge" effect that is one important drawback to the derivative method. But, when applying one dimensional edge pattern in two dimensional image processing, a new issue is naturally raised that the edge detector should correct marking inflections or junctions of edges. Research on human visual perception of objects and information theory pointed out that a pattern lexicon of "inflection micro-patterns" has larger information than a straight line. Also, research on scene perception gave an idea that contours have larger information are more important factor to determine the success of scene categorization. Therefore, inflections or junctions are extremely useful features, whose accurate description and reconstruction are significant in solving correspondence problems in computer vision. Therefore, aside from adoption of edge pattern analysis, inflection or junction characterization is also utilized to extend traditional derivative edge detection algorithm. Experiments were conducted to test my propositions about edge detection and localization accuracy improvements. The results support the idea that these edge detection method improvements are effective in enhancing the accuracy of edge detection and localization.

Projections of Flood Risk using Credible Climate Signals in the Ohio River Basin

NASA Astrophysics Data System (ADS)

Schlef, K.; Robertson, A. W.; Brown, C.

2017-12-01

Estimating future hydrologic flood risk under non-stationary climate is a key challenge to the design of long-term water resources infrastructure and flood management strategies. In this work, we demonstrate how projections of large-scale climate patterns can be credibly used to create projections of long-term flood risk. Our study area is the northwest region of the Ohio River Basin in the United States Midwest. In the region, three major teleconnections have been previously demonstrated to affect synoptic patterns that influence extreme precipitation and streamflow: the El Nino Southern Oscillation, the Pacific North American pattern, and the Pacific Decadal Oscillation. These teleconnections are strongest during the winter season (January-March), which also experiences the greatest number of peak flow events. For this reason, flood events are defined as the maximum daily streamflow to occur in the winter season. For each gage in the region, the location parameter of a log Pearson type 3 distribution is conditioned on the first principal component of the three teleconnections to create a statistical model of flood events. Future projections of flood risk are created by forcing the statistical model with projections of the teleconnections from general circulation models selected for skill. We compare the results of our method to the results of two other methods: the traditional model chain (i.e., general circulation model projections to downscaling method to hydrologic model to flood frequency analysis) and that of using the historic trend. We also discuss the potential for developing credible projections of flood events for the continental United States.

The use of screening effects in modelling route-based daytime road surface temperature

NASA Astrophysics Data System (ADS)

Hu, Yumei; Almkvist, Esben; Lindberg, Fredrik; Bogren, Jörgen; Gustavsson, Torbjörn

2016-07-01

Winter road maintenance is essential for road safety. Accurate predictions of the road surface temperature (RST) and conditions can enhance the efficiency of winter road maintenance. Screening effects, which encompass shading effects and the influence of the sky-view factor ( ψ s ), influence RST distributions because they affect road surface radiation fluxes. In this work, light detection and ranging (Lidar) data are used to derive shadow patterns and ψ s values, and the resulting shadow patterns are used to model route-based RST distributions along two stretches of road in Sweden. The shading patterns and road surface radiation fluxes calculated from the Lidar data generally agreed well with measured RST values. Variation in land use types and the angle between the road direction and solar azimuth may introduce uncertainties, and accounting for these factors may improve the results obtained in certain cases. A simple shading model that only accounts for the direct radiation at the instant of measurement is often sufficient to provide reasonably accurate RST estimates. However, in certain cases, such as those involving measurements close to sunset, it is important to consider the radiation accumulated over several hours. The inclusion of ψ s improves the model performance even more in such cases. Overall, RST models based on the accumulated direct shortwave radiation offered an optimal balance of simplicity and accuracy. General radiation models were built for country road and highway environments, explaining up to 70 and 65 %, respectively, of the observed variation in RST along the corresponding stretches of road.

Structure of High Latitude Currents in Magnetosphere-Ionosphere Models

NASA Astrophysics Data System (ADS)

Wiltberger, M.; Rigler, E. J.; Merkin, V.; Lyon, J. G.

2017-03-01

Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model we examine the structure of the high latitude field-aligned current patterns. Each resolution was run for the entire Whole Heliosphere Interval which contained two high speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results obtained from the Weimer 2005 computing using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and narrow. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths also results in the cross polar cap potential (CPCP) pattern being concentrated in higher latitudes. Current-voltage relationships between the R1 and CPCP are quite similar at the higher resolution indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.

Structure of high latitude currents in global magnetospheric-ionospheric models

USGS Publications Warehouse

Wiltberger, M; Rigler, E. J.; Merkin, V; Lyon, J. G

2016-01-01

Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model we examine the structure of the high latitude field-aligned current patterns. Each resolution was run for the entire Whole Heliosphere Interval which contained two high speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results obtained from the Weimer 2005 computing using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and narrow. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths also results in the cross polar cap potential (CPCP) pattern being concentrated in higher latitudes. Current-voltage relationships between the R1 and CPCP are quite similar at the higher resolution indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.

Volumetric pattern analysis of fuselage-mounted airborne antennas. Ph.D. Thesis; [prediction analysis techniques for antenna radiation patterns of microwave antennas on commercial aircraft

NASA Technical Reports Server (NTRS)

Yu, C. L.

1976-01-01

A volumetric pattern analysis of fuselage-mounted airborne antennas at high frequencies was investigated. The primary goal of the investigation was to develop a numerical solution for predicting radiation patterns of airborne antennas in an accurate and efficient manner. An analytical study of airborne antenna pattern problems is presented in which the antenna is mounted on the fuselage near the top or bottom. Since this is a study of general-type commercial aircraft, the aircraft was modeled in its most basic form. The fuselage was assumed to be an infinitely long perfectly conducting elliptic cylinder in its cross-section and a composite elliptic cylinder in its elevation profile. The wing, cockpit, stabilizers (horizontal and vertical) and landing gear are modeled by "N" sided bent or flat plates which can be arbitrarily attached to the fuselage. The volumetric solution developed utilizes two elliptic cylinders, namely, the roll plane and elevation plane models to approximate the principal surface profile (longitudinal and transverse) at the antenna location. With the belt concept and the aid of appropriate coordinate system transformations the solution can be used to predict the volumetric patterns of airborne antennas in an accurate and efficient manner. Applications of this solution to various airborne antenna problems show good agreement with scale model measurements. Extensive data are presented for a microwave landing antenna system.

Pollination Mode and Mating System Explain Patterns in Genetic Differentiation in Neotropical Plants

PubMed Central

Ballesteros-Mejia, Liliana; Lima, Natácia E.; Lima-Ribeiro, Matheus S.

2016-01-01

We studied genetic diversity and differentiation patterns in Neotropical plants to address effects of life history traits (LHT) and ecological attributes based on an exhaustive literature survey. We used generalized linear mixed models (GLMMs) to test the effects as fixed and random factors of growth form, pollination and dispersal modes, mating and breeding systems, geographical range and habitat on patterns of genetic diversity (HS, HeS, π and h), inbreeding coefficient (FIS), allelic richness (AR) and differentiation among populations (FST) for both nuclear and chloroplast genomes. In addition, we used phylogenetic generalized least squares (pGLS) to account for phylogenetic independence on predictor variables and verify the robustness of the results from significant GLMMs. In general, GLMM revealed more significant relationships among LHTs and genetic patterns than pGLS. After accounting for phylogenetic independence (i.e., using pGLS), FST for nuclear microsatellites was significantly related to pollination mode, mating system and habitat. Plants specifically with outcrossing mating system had lower FST. Moreover, AR was significantly related to pollination mode and geographical range and HeS for nuclear dominant markers was significantly related to habitat. Our findings showed that different results might be retrieved when phylogenetic non-independence is taken into account and that LHTs and ecological attributes affect substantially the genetic pattern in Neotropical plants, hence may drive key evolutionary processes in plants. PMID:27472384

Meta-Analytic Methods of Pooling Correlation Matrices for Structural Equation Modeling under Different Patterns of Missing Data

ERIC Educational Resources Information Center

Furlow, Carolyn F.; Beretvas, S. Natasha

2005-01-01

Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for…

Projecting land-use and land cover change in a subtropical urban watershed

Treesearch

John J. Lagrosa IV; Wayne C. Zipperer; Michael G. Andreu

2018-01-01

Urban landscapes are heterogeneous mosaics that develop via significant land-use and land cover (LULC) change. Current LULC models project future landscape patterns, but generally avoid urban landscapes due to heterogeneity. To project LULC change for an urban landscape, we parameterize an established LULC model (Dyna-CLUE) under baseline conditions (continued current...

Transitioning from Software Requirements Models to Design Models

NASA Technical Reports Server (NTRS)

Lowry, Michael (Technical Monitor); Whittle, Jon

2003-01-01

Summary: 1. Proof-of-concept of state machine synthesis from scenarios - CTAS case study. 2. CTAS team wants to use the syntheses algorithm to validate trajectory generation. 3. Extending synthesis algorithm towards requirements validation: (a) scenario relationships' (b) methodology for generalizing/refining scenarios, and (c) interaction patterns to control synthesis. 4. Initial ideas tested on conflict detection scenarios.

Modelling survival: exposure pattern, species sensitivity and uncertainty

PubMed Central

Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I.; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B.; Van den Brink, Paul J.; Veltman, Karin; Vogel, Sören; Zimmer, Elke I.; Preuss, Thomas G.

2016-01-01

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans. PMID:27381500

Using generalized linear models to estimate selectivity from short-term recoveries of tagged red drum Sciaenops ocellatus: Effects of gear, fate, and regulation period

USGS Publications Warehouse

Bacheler, N.M.; Hightower, J.E.; Burdick, S.M.; Paramore, L.M.; Buckel, J.A.; Pollock, K.H.

2010-01-01

Estimating the selectivity patterns of various fishing gears is a critical component of fisheries stock assessment due to the difficulty in obtaining representative samples from most gears. We used short-term recoveries (n = 3587) of tagged red drum Sciaenops ocellatus to directly estimate age- and length-based selectivity patterns using generalized linear models. The most parsimonious models were selected using AIC, and standard deviations were estimated using simulations. Selectivity of red drum was dependent upon the regulation period in which the fish was caught, the gear used to catch the fish (i.e., hook-and-line, gill nets, pound nets), and the fate of the fish upon recovery (i.e., harvested or released); models including all first-order interactions between main effects outperformed models without interactions. Selectivity of harvested fish was generally dome-shaped and shifted toward larger, older fish in response to regulation changes. Selectivity of caught-and-released red drum was highest on the youngest and smallest fish in the early and middle regulation periods, but increased on larger, legal-sized fish in the late regulation period. These results suggest that catch-and-release mortality has consistently been high for small, young red drum, but has recently become more common in larger, older fish. This method of estimating selectivity from short-term tag recoveries is valuable because it is simpler than full tag-return models, and may be more robust because yearly fishing and natural mortality rates do not need to be modeled and estimated. ?? 2009 Elsevier B.V.

Using generalized linear models to estimate selectivity from short-term recoveries of tagged red drum Sciaenops ocellatus: Effects of gear, fate, and regulation period

USGS Publications Warehouse

Burdick, Summer M.; Hightower, Joseph E.; Bacheler, Nathan M.; Paramore, Lee M.; Buckel, Jeffrey A.; Pollock, Kenneth H.

2010-01-01

Estimating the selectivity patterns of various fishing gears is a critical component of fisheries stock assessment due to the difficulty in obtaining representative samples from most gears. We used short-term recoveries (n = 3587) of tagged red drum Sciaenops ocellatus to directly estimate age- and length-based selectivity patterns using generalized linear models. The most parsimonious models were selected using AIC, and standard deviations were estimated using simulations. Selectivity of red drum was dependent upon the regulation period in which the fish was caught, the gear used to catch the fish (i.e., hook-and-line, gill nets, pound nets), and the fate of the fish upon recovery (i.e., harvested or released); models including all first-order interactions between main effects outperformed models without interactions. Selectivity of harvested fish was generally dome-shaped and shifted toward larger, older fish in response to regulation changes. Selectivity of caught-and-released red drum was highest on the youngest and smallest fish in the early and middle regulation periods, but increased on larger, legal-sized fish in the late regulation period. These results suggest that catch-and-release mortality has consistently been high for small, young red drum, but has recently become more common in larger, older fish. This method of estimating selectivity from short-term tag recoveries is valuable because it is simpler than full tag-return models, and may be more robust because yearly fishing and natural mortality rates do not need to be modeled and estimated.

Statistical methods for investigating quiescence and other temporal seismicity patterns

USGS Publications Warehouse

Matthews, M.V.; Reasenberg, P.A.

1988-01-01

We propose a statistical model and a technique for objective recognition of one of the most commonly cited seismicity patterns:microearthquake quiescence. We use a Poisson process model for seismicity and define a process with quiescence as one with a particular type of piece-wise constant intensity function. From this model, we derive a statistic for testing stationarity against a 'quiescence' alternative. The large-sample null distribution of this statistic is approximated from simulated distributions of appropriate functionals applied to Brownian bridge processes. We point out the restrictiveness of the particular model we propose and of the quiescence idea in general. The fact that there are many point processes which have neither constant nor quiescent rate functions underscores the need to test for and describe nonuniformity thoroughly. We advocate the use of the quiescence test in conjunction with various other tests for nonuniformity and with graphical methods such as density estimation. ideally these methods may promote accurate description of temporal seismicity distributions and useful characterizations of interesting patterns. ?? 1988 Birkha??user Verlag.

Mathematical study on robust tissue pattern formation in growing epididymal tubule.

PubMed

Hirashima, Tsuyoshi

2016-10-21

Tissue pattern formation during development is a reproducible morphogenetic process organized by a series of kinetic cellular activities, leading to the building of functional and stable organs. Recent studies focusing on mechanical aspects have revealed physical mechanisms on how the cellular activities contribute to the formation of reproducible tissue patterns; however, the understanding for what factors achieve the reproducibility of such patterning and how it occurs is far from complete. Here, I focus on a tube pattern formation during murine epididymal development, and show that two factors influencing physical design for the patterning, the proliferative zone within the tubule and the viscosity of tissues surrounding to the tubule, control the reproducibility of epididymal tubule pattern, using a mathematical model based on experimental data. Extensive numerical simulation of the simple mathematical model revealed that a spatially localized proliferative zone within the tubule, observed in experiments, results in more reproducible tubule pattern. Moreover, I found that the viscosity of tissues surrounding to the tubule imposes a trade-off regarding pattern reproducibility and spatial accuracy relating to the region where the tubule pattern is formed. This indicates an existence of optimality in material properties of tissues for the robust patterning of epididymal tubule. The results obtained by numerical analysis based on experimental observations provide a general insight on how physical design realizes robust tissue pattern formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model

PubMed Central

Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J.; Scharlemann, Jörn P. W.; Purves, Drew W.

2014-01-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures. PMID:24756001

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.

PubMed

Harfoot, Michael B J; Newbold, Tim; Tittensor, Derek P; Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J; Scharlemann, Jörn P W; Purves, Drew W

2014-04-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Studies of uncontrolled air traffic patterns, phase 1

NASA Technical Reports Server (NTRS)

Baxa, E. G., Jr.; Scharf, L. L.; Ruedger, W. H.; Modi, J. A.; Wheelock, S. L.; Davis, C. M.

1975-01-01

The general aviation air traffic flow patterns at uncontrolled airports are investigated and analyzed and traffic pattern concepts are developed to minimize the midair collision hazard in uncontrolled airspace. An analytical approach to evaluate midair collision hazard probability as a function of traffic densities is established which is basically independent of path structure. Two methods of generating space-time interrelationships between terminal area aircraft are presented; one is a deterministic model to generate pseudorandom aircraft tracks, the other is a statistical model in preliminary form. Some hazard measures are presented for selected traffic densities. It is concluded that the probability of encountering a hazard should be minimized independently of any other considerations and that the number of encounters involving visible-avoidable aircraft should be maximized at the expense of encounters in other categories.

Learning multiple variable-speed sequences in striatum via cortical tutoring.

PubMed

Murray, James M; Escola, G Sean

2017-05-08

Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.

Simulation and analysis of airborne antenna radiation patterns

NASA Technical Reports Server (NTRS)

Kim, J. J.; Burnside, Walter D.

1984-01-01

The objective is to develop an accurate and efficient analytic solution for predicting high frequency radiation patterns of fuselage-mounted airborne antennas. This is an analytic study of airborne antenna patterns using the Uniform Geometrical Theory of Diffraction (UTD). The aircraft is modeled in its most basic form so that the solution is applicable to general-type aircraft. The fuselage is modeled as a perfectly conducting composite ellipsoid; whereas, the wings, stabilizers, nose, fuel tanks, and engines, are simulated as perfectly conducting flat plates that can be attached to the fuselage and/or to each other. The composite-ellipsoid fuselage model is necessary to successfully simulate the wide variety of real world fuselage shapes. Since the antenna is mounted on the fuselage, it has a dominant effect on the resulting radiation pattern so it must be simulated accurately, especially near the antenna. Various radiation patterns are calculated for commercial, private, and military aircraft, and the Space Shuttle Orbiter. The application of this solution to numerous practical airborne antenna problems illustrates its versatility and design capability. In most cases, the solution accuracy is verified by the comparisons between the calculated and measured data.

Impact of the basic state and MJO representation on MJO Pacific teleconnections in GCMs

NASA Astrophysics Data System (ADS)

Henderson, S. A.; Maloney, E. D.; Son, S. W.

2017-12-01

Teleconnection patterns induced by the Madden-Julian Oscillation (MJO) are known to significantly alter extratropical weather and climate patterns. However, accurate MJO representation has been difficult for many General Circulation Models (GCMs). Furthermore, many GCMs contain large basic state biases. These issues present challenges to the simulation of MJO teleconnections and, in turn, their associated extratropical impacts. This study examines the impacts of basic state quality and MJO representation on the quality of MJO teleconnection patterns in GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Results suggest that GCMs assessed to have a good MJO but with large basic state biases have similarly low skill in reproducing MJO teleconnections as GCMs with poor MJO representation. In the good MJO models examined, poor teleconnection quality is associated with large errors in the zonal extent of the Pacific subtropical jet. Whereas the horizontal structure of MJO heating in the Indo-Pacific region is found to have modest impacts on the teleconnection patterns, results suggest that MJO heating east of the dateline can alter the teleconnection pattern characteristics over North America. These findings suggest that in order to accurately simulate the MJO teleconnection patterns and associated extratropical impacts, both the MJO and the basic state must be well represented.

Can preferred atmospheric circulation patterns over the North-Atlantic-Eurasian region be associated with arctic sea ice loss?

NASA Astrophysics Data System (ADS)

Crasemann, Berit; Handorf, Dörthe; Jaiser, Ralf; Dethloff, Klaus; Nakamura, Tetsu; Ukita, Jinro; Yamazaki, Koji

2017-12-01

In the framework of atmospheric circulation regimes, we study whether the recent Arctic sea ice loss and Arctic Amplification are associated with changes in the frequency of occurrence of preferred atmospheric circulation patterns during the extended winter season from December to March. To determine regimes we applied a cluster analysis to sea-level pressure fields from reanalysis data and output from an atmospheric general circulation model. The specific set up of the two analyzed model simulations for low and high ice conditions allows for attributing differences between the simulations to the prescribed sea ice changes only. The reanalysis data revealed two circulation patterns that occur more frequently for low Arctic sea ice conditions: a Scandinavian blocking in December and January and a negative North Atlantic Oscillation pattern in February and March. An analysis of related patterns of synoptic-scale activity and 2 m temperatures provides a synoptic interpretation of the corresponding large-scale regimes. The regimes that occur more frequently for low sea ice conditions are resembled reasonably well by the model simulations. Based on those results we conclude that the detected changes in the frequency of occurrence of large-scale circulation patterns can be associated with changes in Arctic sea ice conditions.

Time-series modeling and prediction of global monthly absolute temperature for environmental decision making

NASA Astrophysics Data System (ADS)

Ye, Liming; Yang, Guixia; Van Ranst, Eric; Tang, Huajun

2013-03-01

A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined (DSC) approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average (SARIMA) models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term (˜10-year) environmental planning and decision making.

The mechanism for migration in Poland.

PubMed

Rykiel, Z

1988-01-01

The author reviews neoclassical theories and models of migration. The mobility theory, which concerns the impact of local labor markets on migration, is discussed in the Polish context. A general model of the regional labor market and a multicausal model are developed to explain the patterns of internal migration. The period of a managed economy (1949-1980) is contrasted with the period since the implementation of a new economic system in 1983.

Are Delinquents Different? Predictive Patterns for Low, Mid and High Delinquency Levels in a General Youth Sample via the HEW Youth Development Model's Impact Scales.

ERIC Educational Resources Information Center

Truckenmiller, James L.

The Health, Education and Welfare (HEW) Office of Youth Development's National Strategy for Youth Development model was promoted as a community-based planning and procedural tool for enhancing positive youth development and reducing delinquency. To test the applicability of the model as a function of delinquency level, the program's Impact Scales…

Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread

PubMed Central

Fumanelli, Laura; Ajelli, Marco; Manfredi, Piero; Vespignani, Alessandro; Merler, Stefano

2012-01-01

Social contact patterns among individuals encode the transmission route of infectious diseases and are a key ingredient in the realistic characterization and modeling of epidemics. Unfortunately, the gathering of high quality experimental data on contact patterns in human populations is a very difficult task even at the coarse level of mixing patterns among age groups. Here we propose an alternative route to the estimation of mixing patterns that relies on the construction of virtual populations parametrized with highly detailed census and demographic data. We present the modeling of the population of 26 European countries and the generation of the corresponding synthetic contact matrices among the population age groups. The method is validated by a detailed comparison with the matrices obtained in six European countries by the most extensive survey study on mixing patterns. The methodology presented here allows a large scale comparison of mixing patterns in Europe, highlighting general common features as well as country-specific differences. We find clear relations between epidemiologically relevant quantities (reproduction number and attack rate) and socio-demographic characteristics of the populations, such as the average age of the population and the duration of primary school cycle. This study provides a numerical approach for the generation of human mixing patterns that can be used to improve the accuracy of mathematical models in the absence of specific experimental data. PMID:23028275

Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

PubMed

Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

2012-02-01

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana.

PubMed

Aspinall, Richard

2004-08-01

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.

Evaluating Treatment and Generalization Patterns of Two Theoretically Motivated Sentence Comprehension Therapies.

PubMed

Des Roches, Carrie A; Vallila-Rohter, Sofia; Villard, Sarah; Tripodis, Yorghos; Caplan, David; Kiran, Swathi

2016-12-01

The current study examined treatment outcomes and generalization patterns following 2 sentence comprehension therapies: object manipulation (OM) and sentence-to-picture matching (SPM). Findings were interpreted within the framework of specific deficit and resource reduction accounts, which were extended in order to examine the nature of generalization following treatment of sentence comprehension deficits in aphasia. Forty-eight individuals with aphasia were enrolled in 1 of 8 potential treatment assignments that varied by task (OM, SPM), complexity of trained sentences (complex, simple), and syntactic movement (noun phrase, wh-movement). Comprehension of trained and untrained sentences was probed before and after treatment using stimuli that differed from the treatment stimuli. Linear mixed-model analyses demonstrated that, although both OM and SPM treatments were effective, OM resulted in greater improvement than SPM. Analyses of covariance revealed main effects of complexity in generalization; generalization from complex to simple linguistically related sentences was observed both across task and across movement. Results are consistent with the complexity account of treatment efficacy, as generalization effects were consistently observed from complex to simpler structures. Furthermore, results provide support for resource reduction accounts that suggest that generalization can extend across linguistic boundaries, such as across movement type.

Oceanic island biogeography through the lens of the general dynamic model: assessment and prospect.

PubMed

Borregaard, Michael K; Amorim, Isabel R; Borges, Paulo A V; Cabral, Juliano S; Fernández-Palacios, José M; Field, Richard; Heaney, Lawrence R; Kreft, Holger; Matthews, Thomas J; Olesen, Jens M; Price, Jonathan; Rigal, Francois; Steinbauer, Manuel J; Triantis, Konstantinos A; Valente, Luis; Weigelt, Patrick; Whittaker, Robert J

2017-05-01

The general dynamic model of oceanic island biogeography (GDM) has added a new dimension to theoretical island biogeography in recognizing that geological processes are key drivers of the evolutionary processes of diversification and extinction within remote islands. It provides a dynamic and essentially non-equilibrium framework generating novel predictions for emergent diversity properties of oceanic islands and archipelagos. Its publication in 2008 coincided with, and spurred on, renewed attention to the dynamics of remote islands. We review progress, both in testing the GDM's predictions and in developing and enhancing ecological-evolutionary understanding of oceanic island systems through the lens of the GDM. In particular, we focus on four main themes: (i) macroecological tests using a space-for-time rationale; (ii) extensions of theory to islands following different patterns of ontogeny; (iii) the implications of GDM dynamics for lineage diversification and trait evolution; and (iv) the potential for downscaling GDM dynamics to local-scale ecological patterns and processes within islands. We also consider the implications of the GDM for understanding patterns of non-native species diversity. We demonstrate the vitality of the field of island biogeography by identifying a range of potentially productive lines for future research. © 2016 Cambridge Philosophical Society.

Nonparametric Hierarchical Bayesian Model for Functional Brain Parcellation

PubMed Central

Lashkari, Danial; Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2011-01-01

We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over the sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to simultaneously learn the patterns of response that are shared across the group, and to estimate the number of these patterns supported by data. Inference based on this model enables automatic discovery and characterization of salient and consistent patterns in functional signals. We apply our method to data from a study that explores the response of the visual cortex to a collection of images. The discovered profiles of activation correspond to selectivity to a number of image categories such as faces, bodies, and scenes. More generally, our results appear superior to the results of alternative data-driven methods in capturing the category structure in the space of stimuli. PMID:21841977

A USCLVAR Multi-Model Assessment of the Impact of SST Anomalies and Land-Atmosphere Feedbacks on Drought

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2009-01-01

The USCLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include, What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCMs), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This talk provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models. It is hoped that these early results will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.

Influence of gender and other factors on medical student specialty interest.

PubMed

Boyle, Veronica; Shulruf, Boaz; Poole, Phillippa

2014-09-12

Medical schools must select and educate to meet anticipated health needs. Factors influencing career choice include those of the student and their background as well as subsequent experience. Women have comprised over 50% of medical classes for over 20 years. This study describes gender patterns of current specialty interest among medical students at the University of Auckland, and models the predictive effect of gender compared to other career influencing factors. The study analysed career intention survey data from 711 graduating medical students (response rate, 79%) from 2006 to 2011. Interest level was highest for medicine, followed by subspecialty surgery, general practice and paediatrics. There were differences by gender for most specialties, but not for general practice. Women were more likely than men to be interested in Obstetrics and Gynaecology, Paediatrics, Geriatrics, Public Health or General Medicine, and less interested in Surgery, Anaesthesia, Emergency Medicine or post graduate study. Each specialty had a different pattern of influencing factors with the most important factor being the experience on a clinical attachment. Factors in career choice are complex and vary by gender and specialty. General practice levels of interest are too low for workforce needs. Predictive models need to be validated in longer term studies but may help guide selection and curriculum design.

Does global warming amplify interannual climate variability?

NASA Astrophysics Data System (ADS)

He, Chao; Li, Tim

2018-06-01

Based on the outputs of 30 models from Coupled Model Intercomparison Project Phase 5 (CMIP5), the fractional changes in the amplitude interannual variability (σ) for precipitation (P') and vertical velocity (ω') are assessed, and simple theoretical models are constructed to quantitatively understand the changes in σ(P') and σ(ω'). Both RCP8.5 and RCP4.5 scenarios show similar results in term of the fractional change per degree of warming, with slightly lower inter-model uncertainty under RCP8.5. Based on the multi-model median, σ(P') generally increases but σ(ω') generally decreases under global warming but both are characterized by non-uniform spatial patterns. The σ(P') decrease over subtropical subsidence regions but increase elsewhere, with a regional averaged value of 1.4% K- 1 over 20°S-50°N under RCP8.5. Diagnoses show that the mechanisms for the change in σ(P') are different for climatological ascending and descending regions. Over ascending regions, the increase of mean state specific humidity contributes to a general increase of σ(P') but the change of σ(ω') dominates its spatial pattern and inter-model uncertainty. But over descending regions, the change of σ(P') and its inter-model uncertainty are constrained by the change of mean state precipitation. The σ(ω') is projected to be weakened almost everywhere except over equatorial Pacific, with a regional averaged fractional change of - 3.4% K- 1 at 500 hPa. The overall reduction of σ(ω') results from the increased mean state static stability, while the substantially increased σ(ω') at the mid-upper troposphere over equatorial Pacific and the inter-model uncertainty of the changes in σ(ω') are dominated by the change in the interannual variability of diabatic heating.

A spatial emergy model for Alachua County, Florida

NASA Astrophysics Data System (ADS)

Lambert, James David

A spatial model of the distribution of energy flows and storages in Alachua County, Florida, was created and used to analyze spatial patterns of energy transformation hierarchy in relation to spatial patterns of human settlement. Emergy, the available energy of one kind previously required directly or indirectly to make a product or service, was used as a measure of the quality of the different forms of energy flows and storages. Emergy provides a common unit of measure for comparing the productive contributions of natural processes with those of economic and social processes---it is an alternative to using money for measuring value. A geographic information system was used to create a spatial model and make maps that show the distribution and magnitude of different types of energy and emergy flows and storages occurring in one-hectare land units. Energy transformities were used to convert individual energy flows and storages into emergy units. Maps of transformities were created that reveal a clear spatial pattern of energy transformation hierarchy. The maps display patterns of widely-dispersed areas with lower transformity energy flows and storages, and smaller, centrally-located areas with higher transformities. Energy signature graphs and spatial unit transformities were used to characterize and compare the types and amounts of energy being consumed and stored according to land use classification, planning unit, and neighborhood categories. Emergy ratio maps and spatial unit ratios were created by dividing the values for specific emergy flows or storages by the values for other emergy flows or storages. Spatial context analysis was used to analyze the spatial distribution patterns of mean and maximum values for emergy flows and storages. The modeling method developed for this study is general and applicable to all types of landscapes and could be applied at any scale. An advantage of this general approach is that the results of other studies using this method will be directly comparable with the results of this study. The results and conclusions of this study reinforce the hypothesis that an urban landscape will develop a predictable spatial pattern that can be described in terms of a universal energy transformation hierarchy.

Quantifying the evolution of flow boiling bubbles by statistical testing and image analysis: toward a general model.

PubMed

Xiao, Qingtai; Xu, Jianxin; Wang, Hua

2016-08-16

A new index, the estimate of the error variance, which can be used to quantify the evolution of the flow patterns when multiphase components or tracers are difficultly distinguishable, was proposed. The homogeneity degree of the luminance space distribution behind the viewing windows in the direct contact boiling heat transfer process was explored. With image analysis and a linear statistical model, the F-test of the statistical analysis was used to test whether the light was uniform, and a non-linear method was used to determine the direction and position of a fixed source light. The experimental results showed that the inflection point of the new index was approximately equal to the mixing time. The new index has been popularized and applied to a multiphase macro mixing process by top blowing in a stirred tank. Moreover, a general quantifying model was introduced for demonstrating the relationship between the flow patterns of the bubble swarms and heat transfer. The results can be applied to investigate other mixing processes that are very difficult to recognize the target.

Optical pattern recognition algorithms on neural-logic equivalent models and demonstration of their prospects and possible implementations

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Zaitsev, Alexandr V.; Voloshin, Victor M.

2001-03-01

Historic information regarding the appearance and creation of fundamentals of algebra-logical apparatus-`equivalental algebra' for description of neuro-nets paradigms and algorithms is considered which is unification of theory of neuron nets (NN), linear algebra and the most generalized neuro-biology extended for matrix case. A survey is given of `equivalental models' of neuron nets and associative memory is suggested new, modified matrix-tenzor neurological equivalental models (MTNLEMS) are offered with double adaptive-equivalental weighing (DAEW) for spatial-non- invariant recognition (SNIR) and space-invariant recognition (SIR) of 2D images (patterns). It is shown, that MTNLEMS DAEW are the most generalized, they can describe the processes in NN both within the frames of known paradigms and within new `equivalental' paradigm of non-interaction type, and the computing process in NN under using the offered MTNLEMs DAEW is reduced to two-step and multi-step algorithms and step-by-step matrix-tenzor procedures (for SNIR) and procedures of defining of space-dependent equivalental functions from two images (for SIR).

Quantifying the evolution of flow boiling bubbles by statistical testing and image analysis: toward a general model

PubMed Central

Xiao, Qingtai; Xu, Jianxin; Wang, Hua

2016-01-01

A new index, the estimate of the error variance, which can be used to quantify the evolution of the flow patterns when multiphase components or tracers are difficultly distinguishable, was proposed. The homogeneity degree of the luminance space distribution behind the viewing windows in the direct contact boiling heat transfer process was explored. With image analysis and a linear statistical model, the F-test of the statistical analysis was used to test whether the light was uniform, and a non-linear method was used to determine the direction and position of a fixed source light. The experimental results showed that the inflection point of the new index was approximately equal to the mixing time. The new index has been popularized and applied to a multiphase macro mixing process by top blowing in a stirred tank. Moreover, a general quantifying model was introduced for demonstrating the relationship between the flow patterns of the bubble swarms and heat transfer. The results can be applied to investigate other mixing processes that are very difficult to recognize the target. PMID:27527065

A review of contrast pattern based data mining

NASA Astrophysics Data System (ADS)

Zhu, Shiwei; Ju, Meilong; Yu, Junfeng; Cai, Binlei; Wang, Aiping

2015-07-01

Contrast pattern based data mining is concerned with the mining of patterns and models that contrast two or more datasets. Contrast patterns can describe similarities or differences between the datasets. They represent strong contrast knowledge and have been shown to be very successful for constructing accurate and robust clusters and classifiers. The increasing use of contrast pattern data mining has initiated a great deal of research and development attempts in the field of data mining. A comprehensive revision on the existing contrast pattern based data mining research is given in this paper. They are generally categorized into background and representation, definitions and mining algorithms, contrast pattern based classification, clustering, and other applications, the research trends in future. The primary of this paper is to server as a glossary for interested researchers to have an overall picture on the current contrast based data mining development and identify their potential research direction to future investigation.

Fractal Measure and Microscopic Modeling of Osseointegration.

PubMed

Santos, Leonardo Cavalcanti Bezerra; Carvalho, Alessandra Albuquerque; Leão, Jair Carneiro; Neto, Paulo Jose; Stosic, Tatijana; Stosic, Borko

2015-01-01

In this study, the process of osseointegration on titanium implant surfaces with different physicochemical treatments subjected to a simulated corporal fluid submersion was evaluated using the concept of fractal dimension. It was found that different treatments led to rather different calcium phosphate crystal growth patterns, with fractal dimension ranging from 1.68 to 1.93. The observed crystal patterns may be explained by a general deposition, diffusion, and aggregation growth mechanism, where diffusing particle sticking probability plays a fundamental role.

Large Structure in the Far Wakes of Two-Dimensional Bluff Bodies,

DTIC Science & Technology

1984-01-01

triggered along with a strobe flash to record the streakline pattern on film . The electronic synchronizing controller for the smoke-wire operation was built...Super 35 mm camera with motor drive was used, along with a General Radio Model 1540 Stroboscope. We had the best success with Kodak Tri-x film pushed one...location being considered, its entire history is contained in the streakline pattern, and may confuse the intepretation . The conclusion from this

Forecasting of hourly load by pattern recognition in a small area power system

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

Dehdashti-Shahrokh, A.

1982-01-01

An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less

Predicting the spread of all invasive forest pests in the United States

Treesearch

Emma J. Hudgins; Andrew M. Liebhold; Brian Leung; Regan Early

2017-01-01

We tested whether a general spread model could capture macroecological patterns across all damaging invasive forest pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all pests, and had 68.00% locational accuracy between predicted and observed...

Basin-scale availability of salmonid spawning gravel as influenced by channel type and hydraulic roughness in mountain catchments.

Treesearch

John M. Buffington; David R. Montgomery; Harvey M. Greenberg

2004-01-01

A general framework is presented for examining the effects of channel type and associated hydraulic roughness on salmonid spawning-gravel availability in mountain catchments. Digital elevation models are coupled with grain-size predictions to provide basin-scale assessments of the potential extent and spatial pattern of spawning gravels. To demonstrate both the model...

Brazil for Sale? Does Sino-Brazilian Trade or Investment Significantly Influence Brazil’s United Nations General Assembly (UNGA) Voting Pattern?

DTIC Science & Technology

2011-12-01

for Trade in Brazil? An Application of the Gravity Model. Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31th Brazilian Economics...FDI Matter for Trade in Brazil? An Application of the Gravity Model. Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31th

Application of Context Input Process and Product Model in Curriculum Evaluation: Case Study of a Call Centre

ERIC Educational Resources Information Center

Kavgaoglu, Derya; Alci, Bülent

2016-01-01

The goal of this research which was carried out in reputable dedicated call centres within the Turkish telecommunication sector aims is to evaluate competence-based curriculums designed by means of internal funding through Stufflebeam's context, input, process, product (CIPP) model. In the research, a general scanning pattern in the scope of…

Investigating the Effects of Grid Resolution of WRF Model for Simulating the Atmosphere for use in the Study of Wake Turbulence

NASA Astrophysics Data System (ADS)

Prince, Alyssa; Trout, Joseph; di Mercurio, Alexis

2017-01-01

The Weather Research and Forecasting (WRF) Model is a nested-grid, mesoscale numerical weather prediction system maintained by the Developmental Testbed Center. The model simulates the atmosphere by integrating partial differential equations, which use the conservation of horizontal momentum, conservation of thermal energy, and conservation of mass along with the ideal gas law. This research investigated the possible use of WRF in investigating the effects of weather on wing tip wake turbulence. This poster shows the results of an investigation into the accuracy of WRF using different grid resolutions. Several atmospheric conditions were modeled using different grid resolutions. In general, the higher the grid resolution, the better the simulation, but the longer the model run time. This research was supported by Dr. Manuel A. Rios, Ph.D. (FAA) and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA'' (13-G-006). Dr. Manuel A. Rios, Ph.D. (FAA), and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''

The ontogeny of phonological categories and the primacy of lexical learning in linguistic development.

PubMed

Beckman, M E; Edwards, J

2000-01-01

In this paper, we draw on recent developments in several areas of cognitive science that suggest that the lexicon is at the core of grammatical generalizations at several different levels of representation. Evidence comes from many sources, including recent studies on language processing in adults and on language acquisition in children. Phonological behavior is influenced very early by pattern frequency in the lexicon of the ambient language, and we propose that phonological acquisition might provide the initial bootstrapping into grammatical generalization in general. The phonological categories over which pattern frequencies are calculated, however, are neither transparently available in the audiovisual signal nor deterministically fixed by the physiological and perceptual capacities of the species. Therefore, we need several age-appropriate models of how the lexicon can influence a child's interactions with the ambient language over the course of phonological acquisition.

Mechanical constraint from growing jaw facilitates mammalian dental diversity

PubMed Central

Renvoisé, Elodie; Kavanagh, Kathryn D.; Lazzari, Vincent; Häkkinen, Teemu J.; Rice, Ritva; Pantalacci, Sophie; Salazar-Ciudad, Isaac; Jernvall, Jukka

2017-01-01

Much of the basic information about individual organ development comes from studies using model species. Whereas conservation of gene regulatory networks across higher taxa supports generalizations made from a limited number of species, generality of mechanistic inferences remains to be tested in tissue culture systems. Here, using mammalian tooth explants cultured in isolation, we investigate self-regulation of patterning by comparing developing molars of the mouse, the model species of mammalian research, and the bank vole. A distinct patterning difference between the vole and the mouse molars is the alternate cusp offset present in the vole. Analyses of both species using 3D reconstructions of developing molars and jaws, computational modeling of cusp patterning, and tooth explants cultured with small braces show that correct cusp offset requires constraints on the lateral expansion of the developing tooth. Vole molars cultured without the braces lose their cusp offset, and mouse molars cultured with the braces develop a cusp offset. Our results suggest that cusp offset, which changes frequently in mammalian evolution, is more dependent on the 3D support of the developing jaw than other aspects of tooth shape. This jaw–tooth integration of a specific aspect of the tooth phenotype indicates that organs may outsource specific aspects of their morphology to be regulated by adjacent body parts or organs. Comparative studies of morphologically different species are needed to infer the principles of organogenesis. PMID:28808032

Estimation and mapping of wet and dry mercury deposition across northeastern North America

USGS Publications Warehouse

Miller, E.K.; Vanarsdale, A.; Keeler, G.J.; Chalmers, A.; Poissant, L.; Kamman, N.C.; Brulotte, R.

2005-01-01

Whereas many ecosystem characteristics and processes influence mercury accumulation in higher trophic-level organisms, the mercury flux from the atmosphere to a lake and its watershed is a likely factor in potential risk to biota. Atmospheric deposition clearly affects mercury accumulation in soils and lake sediments. Thus, knowledge of spatial patterns in atmospheric deposition may provide information for assessing the relative risk for ecosystems to exhibit excessive biotic mercury contamination. Atmospheric mercury concentrations in aerosol, vapor, and liquid phases from four observation networks were used to estimate regional surface concentration fields. Statistical models were developed to relate sparsely measured mercury vapor and aerosol concentrations to the more commonly measured mercury concentration in precipitation. High spatial resolution deposition velocities for different phases (precipitation, cloud droplets, aerosols, and reactive gaseous mercury (RGM)) were computed using inferential models. An empirical model was developed to estimate gaseous elemental mercury (GEM) deposition. Spatial patterns of estimated total mercury deposition were complex. Generally, deposition was higher in the southwest and lower in the northeast. Elevation, land cover, and proximity to urban areas modified the general pattern. The estimated net GEM and RGM fluxes were each greater than or equal to wet deposition in many areas. Mercury assimilation by plant foliage may provide a substantial input of methyl-mercury (MeHg) to ecosystems. ?? 2005 Springer Science+Business Media, Inc.

Design pattern mining using distributed learning automata and DNA sequence alignment.

PubMed

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

Citizen science: A new perspective to evaluate spatial patterns in hydrology.

NASA Astrophysics Data System (ADS)

Koch, J.; Stisen, S.

2016-12-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning make humans often more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which is inevitable giving benefits such as speed and the possibility to automatize processes. This study highlights the integration of the generally underused human resource into hydrology. We established a citizen science project on the zooniverse platform entitled Pattern Perception. The aim is to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of a hydrological catchment model. In total, the turnout counts more than 2,800 users that provided over 46,000 classifications of 1,095 individual subjects within 64 days after the launch. Each subject displays simulated spatial patterns of land-surface variables of a baseline model and six modelling scenarios. The citizen science data discloses a numeric pattern similarity score for each of the scenarios with respect to the reference. We investigate the capability of a set of innovative statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide flexibility and auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric.

A selection criterion for patterns in reaction–diffusion systems

PubMed Central

2014-01-01

Background Alan Turing’s work in Morphogenesis has received wide attention during the past 60 years. The central idea behind his theory is that two chemically interacting diffusible substances are able to generate stable spatial patterns, provided certain conditions are met. Ever since, extensive work on several kinds of pattern-generating reaction diffusion systems has been done. Nevertheless, prediction of specific patterns is far from being straightforward, and a great deal of interest in deciphering how to generate specific patterns under controlled conditions prevails. Results Techniques allowing one to predict what kind of spatial structure will emerge from reaction–diffusion systems remain unknown. In response to this need, we consider a generalized reaction diffusion system on a planar domain and provide an analytic criterion to determine whether spots or stripes will be formed. Our criterion is motivated by the existence of an associated energy function that allows bringing in the intuition provided by phase transitions phenomena. Conclusions Our criterion is proved rigorously in some situations, generalizing well-known results for the scalar equation where the pattern selection process can be understood in terms of a potential. In more complex settings it is investigated numerically. Our work constitutes a first step towards rigorous pattern prediction in arbitrary geometries/conditions. Advances in this direction are highly applicable to the efficient design of Biotechnology and Developmental Biology experiments, as well as in simplifying the analysis of morphogenetic models. PMID:24476200

Adressing optimality principles in DGVMs: Dynamics of Carbon allocation changes

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

DGVMs are designed to reproduce and quantify ecosystem processes. Based on plant functions or species specific parameter sets, the energy, carbon, nitrogen and water cycles of different ecosystems are assessed. These models have been proven to be important tools to investigate ecosystem fluxes as they are derived by plant, site and environmental factors. The general model approach assumes steady state conditions and constant model parameters. Both assumptions, however, are wrong, since: (i) No given ecosystem ever is at steady state! (ii) Ecosystems have the capability to adapt to changes in growth conditions, e.g. via changes in allocation patterns! This presentation will give examples how these general failures within current DGVMs may be addressed.

Adressing optimality principles in DGVMs: Dynamics of Carbon allocation changes.

NASA Astrophysics Data System (ADS)

Pietsch, S.

2016-12-01

DGVMs are designed to reproduce and quantify ecosystem processes. Based on plant functions or species specific parameter sets, the energy, carbon, nitrogen and water cycles of different ecosystems are assessed. These models have been proven to be important tools to investigate ecosystem fluxes as they are derived by plant, site and environmental factors. The general model approach assumes steady state conditions and constant model parameters. Both assumptions, however, are wrong. Any given ecosystem never is at steady state! Ecosystems have the capability to adapt to changes in growth conditions, e.g. via changes in allocation patterns! This presentation will give examples how these general failures within current DGVMs may be addressed.

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

Strons, Philip; Bailey, James L.

Anemometer readings alone cannot provide a complete picture of air flow patterns at an open gloveport. Having a means to visualize air flow for field tests in general provides greater insight by indicating direction in addition to the magnitude of the air flow velocities in the region of interest. Furthermore, flow visualization is essential for Computational Fluid Dynamics (CFD) verification, where important modeling assumptions play a significant role in analyzing the chaotic nature of low-velocity air flow. A good example is shown Figure 1, where an unexpected vortex pattern occurred during a field test that could not have been measuredmore » relying only on anemometer readings. Here by, observing and measuring the patterns of the smoke flowing into the gloveport allowed the CFD model to be appropriately updated to match the actual flow velocities in both magnitude and direction.« less

Generalized reproduction numbers and the prediction of patterns in waterborne disease

PubMed Central

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-01-01

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix , explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number (the dominant eigenvalue of ) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of . Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections. PMID:23150538

Structure of high latitude currents in magnetosphere-ionosphere models

NASA Astrophysics Data System (ADS)

Wiltberger, M. J.; Lyon, J.; Merkin, V. G.; Rigler, E. J.

2016-12-01

Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model the structure of the high latitude field-aligned current patterns is examined. Each LFM resolution was run for the entire Whole Heliosphere Interval (WHI), which contained two high-speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results from the Weimer 2005 computed using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and confined. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths in the model also results in a better shielding of mid- and low-latitude ionosphere from the polar cap convection, also in agreement with observations. Current-voltage relationships between the R1 strength and the cross-polar cap potential (CPCP) are quite similar at the higher resolutions indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.

Modelling spatial patterns of urban growth in Africa

PubMed Central

Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius

2013-01-01

The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers. PMID:25152552

On universal procrastination

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-09-01

This paper presents a general stochastic model for procrastination with respect to a deadline. The model establishes a universal procrastination pattern that follows an inverse power-law: if the time remaining to the deadline is r then the response is 1/rε , where ɛ is a positive exponent. The model further establishes that the exponent value ε =1 , which yields the harmonic response 1/r , stands out as special and distinguishable. The theoretical results of the model are shown to be in perfect accord with recent empirical findings.

Differential effects of adding and removing components of a context on the generalization of conditional freezing.

PubMed

González, Felisa; Quinn, Jennifer J; Fanselow, Michael S

2003-01-01

Rats were conditioned across 2 consecutive days where a single unsignaled footshock was presented in the presence of specific contextual cues. Rats were tested with contexts that had additional stimulus components either added or subtracted. Using freezing as a measure of conditioning, removal but not addition of a cue from the training context produced significant generalization decrement. The results are discussed in relation to the R. A. Rescorla and A. R. Wagner (1972), J. M. Pearce (1994), and A. R. Wagner and S. E. Brandon (2001) accounts of generalization. Although the present data are most consistent with elemental models such as Rescorla and Wagner, a slight modification of the Wagner-Brandon replaced-elements model that can account for differences in the pattern of generalization obtained with contexts and discrete conditional stimuli is proposed.

Linear hypergeneralization of learned dynamics across movement speeds reveals anisotropic, gain-encoding primitives for motor adaptation.

PubMed

Joiner, Wilsaan M; Ajayi, Obafunso; Sing, Gary C; Smith, Maurice A

2011-01-01

The ability to generalize learned motor actions to new contexts is a key feature of the motor system. For example, the ability to ride a bicycle or swing a racket is often first developed at lower speeds and later applied to faster velocities. A number of previous studies have examined the generalization of motor adaptation across movement directions and found that the learned adaptation decays in a pattern consistent with the existence of motor primitives that display narrow Gaussian tuning. However, few studies have examined the generalization of motor adaptation across movement speeds. Following adaptation to linear velocity-dependent dynamics during point-to-point reaching arm movements at one speed, we tested the ability of subjects to transfer this adaptation to short-duration higher-speed movements aimed at the same target. We found near-perfect linear extrapolation of the trained adaptation with respect to both the magnitude and the time course of the velocity profiles associated with the high-speed movements: a 69% increase in movement speed corresponded to a 74% extrapolation of the trained adaptation. The close match between the increase in movement speed and the corresponding increase in adaptation beyond what was trained indicates linear hypergeneralization. Computational modeling shows that this pattern of linear hypergeneralization across movement speeds is not compatible with previous models of adaptation in which motor primitives display isotropic Gaussian tuning of motor output around their preferred velocities. Instead, we show that this generalization pattern indicates that the primitives involved in the adaptation to viscous dynamics display anisotropic tuning in velocity space and encode the gain between motor output and motion state rather than motor output itself.

General aviation air traffic pattern safety analysis

NASA Technical Reports Server (NTRS)

Parker, L. C.

1973-01-01

A concept is described for evaluating the general aviation mid-air collision hazard in uncontrolled terminal airspace. Three-dimensional traffic pattern measurements were conducted at uncontrolled and controlled airports. Computer programs for data reduction, storage retrieval and statistical analysis have been developed. Initial general aviation air traffic pattern characteristics are presented. These preliminary results indicate that patterns are highly divergent from the expected standard pattern, and that pattern procedures observed can affect the ability of pilots to see and avoid each other.

Modeling Creep Processes in Aging Polymers

NASA Astrophysics Data System (ADS)

Olali, N. V.; Voitovich, L. V.; Zazimko, N. N.; Malezhik, M. P.

2016-03-01

The photoelastic method is generalized to creep in hereditary aging materials. Optical-creep curves and mechanical-creep or optical-relaxation curves are used to interpret fringe patterns. For materials with constant Poisson's ratio, it is sufficient to use mechanical- or optical-creep curves for this purpose

Master stability functions reveal diffusion-driven pattern formation in networks

NASA Astrophysics Data System (ADS)

Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

2018-03-01

We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni

2015-09-01

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.

Constructing increment-decrement life tables.

PubMed

Schoen, R

1975-05-01

A life table model which can recognize increments (or entrants) as well as decrements has proven to be of considerable value in the analysis of marital status patterns, labor force participation patterns, and other areas of substantive interest. Nonetheless, relatively little work has been done on the methodology of increment-decrement (or combined) life tables. The present paper reviews the general, recursive solution of Schoen and Nelson (1974), develops explicit solutions for three cases of particular interest, and compares alternative approaches to the construction of increment-decrement tables.

Storage Capacity of Generalized Palimpsests

NASA Astrophysics Data System (ADS)

Bonnaz, D.

1997-12-01

A simple analytical study of a short term memory model is performed. This model consists of a symmetric p-neuron interaction between N neurons. Learning is achieved by a generalized Hebb rule. Saturation is prevented by the introduction of a bound A to the couplings. At each time step, an input pattern is drawn at random, independently of the previous ones. The determination of the life time T of a memorized pattern viewed as a function of A and N is accomplished by a statistical study of the dynamic of the learning process which has been made possible under the assumption that the couplings evolve independently. This simplification reduces the determination of T to a one-dimensional problem, by considering energies rather than couplings. The choice of the optimal value A_opt of A is a compromise between the success of the learning process and the maximization of T. The essential results are expressed by the formulae Tpropto A^2 and A_optpropto N^{frac{p-1}{2}}.

An efficient Cellular Potts Model algorithm that forbids cell fragmentation

NASA Astrophysics Data System (ADS)

Durand, Marc; Guesnet, Etienne

2016-11-01

The Cellular Potts Model (CPM) is a lattice based modeling technique which is widely used for simulating cellular patterns such as foams or biological tissues. Despite its realism and generality, the standard Monte Carlo algorithm used in the scientific literature to evolve this model preserves connectivity of cells on a limited range of simulation temperature only. We present a new algorithm in which cell fragmentation is forbidden for all simulation temperatures. This allows to significantly enhance realism of the simulated patterns. It also increases the computational efficiency compared with the standard CPM algorithm even at same simulation temperature, thanks to the time spared in not doing unrealistic moves. Moreover, our algorithm restores the detailed balance equation, ensuring that the long-term stage is independent of the chosen acceptance rate and chosen path in the temperature space.

Statistical ecology comes of age.

PubMed

Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-12-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Statistical ecology comes of age

PubMed Central

Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-01-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

SSME seal test program: Test results for smooth, hole-pattern and helically-grooved stators

NASA Technical Reports Server (NTRS)

Childs, Dara W.

1987-01-01

All of the listed seals were tested in a liquid Halon test facility at high Reynolds numbers. In addition, a helically-grooved-stator seal was tested in an air seal facility. An analysis of the test results with comparisons to theoretical predictions supports the following conclusions: (1) For small seals, the Hirs' friction-factor model is more restricted than had been thought; (2) For smooth seals, predictions of stiffness and damping improve markedly as the radical clearance is reduced; (3) Friction-factor data for hole-pattern-seal stators frequently deviates from the Hirs model; (4) Predictions of stiffness and damping coefficients for hole-pattern-stator seals is generally reasonable; (5) Tests for the hole-pattern stators at reduced clearances show no clear optimum for hole-pattern seals with respect to either hole-area ratio or hole depth to minimum clearance ratios; (6) Tests of these hole-pattern stators show no significant advantage in net damping over smooth seals; (7) Tests of helically-grooved seal stators in Halon show reasonable agreement between theory and prediction for leakage and direct stiffness but poor agreement for the net damping coefficient.

Network architectures and circuit function: testing alternative hypotheses in multifunctional networks.

PubMed

Leonard, J L

2000-05-01

Understanding how species-typical movement patterns are organized in the nervous system is a central question in neurobiology. The current explanations involve 'alphabet' models in which an individual neuron may participate in the circuit for several behaviors but each behavior is specified by a specific neural circuit. However, not all of the well-studied model systems fit the 'alphabet' model. The 'equation' model provides an alternative possibility, whereby a system of parallel motor neurons, each with a unique (but overlapping) field of innervation, can account for the production of stereotyped behavior patterns by variable circuits. That is, it is possible for such patterns to arise as emergent properties of a generalized neural network in the absence of feedback, a simple version of a 'self-organizing' behavioral system. Comparison of systems of identified neurons suggest that the 'alphabet' model may account for most observations where CPGs act to organize motor patterns. Other well-known model systems, involving architectures corresponding to feed-forward neural networks with a hidden layer, may organize patterned behavior in a manner consistent with the 'equation' model. Such architectures are found in the Mauthner and reticulospinal circuits, 'escape' locomotion in cockroaches, CNS control of Aplysia gill, and may also be important in the coordination of sensory information and motor systems in insect mushroom bodies and the vertebrate hippocampus. The hidden layer of such networks may serve as an 'internal representation' of the behavioral state and/or body position of the animal, allowing the animal to fine-tune oriented, or particularly context-sensitive, movements to the prevalent conditions. Experiments designed to distinguish between the two models in cases where they make mutually exclusive predictions provide an opportunity to elucidate the neural mechanisms by which behavior is organized in vivo and in vitro. Copyright 2000 S. Karger AG, Basel

A proposed mathematical model for sleep patterning.

PubMed

Lawder, R E

1984-01-01

The simple model of a ramp, intersecting a triangular waveform, yields results which conform with seven generalized observations of sleep patterning; including the progressive lengthening of 'rapid-eye-movement' (REM) sleep periods within near-constant REM/nonREM cycle periods. Predicted values of REM sleep time, and of Stage 3/4 nonREM sleep time, can be computed using the observed values of other parameters. The distributions of the actual REM and Stage 3/4 times relative to the predicted values were closer to normal than the distributions relative to simple 'best line' fits. It was found that sleep onset tends to occur at a particular moment in the individual subject's '90-min cycle' (the use of a solar time-scale masks this effect), which could account for a subject with a naturally short sleep/wake cycle synchronizing to a 24-h rhythm. A combined 'sleep control system' model offers quantitative simulation of the sleep patterning of endogenous depressives and, with a different perturbation, qualitative simulation of the symptoms of narcolepsy.

Modeling Effects of Local Extinctions on Culture Change and Diversity in the Paleolithic

PubMed Central

Premo, L. S.; Kuhn, Steven L.

2010-01-01

The persistence of early stone tool technologies has puzzled archaeologists for decades. Cognitively based explanations, which presume either lack of ability to innovate or extreme conformism, do not account for the totality of the empirical patterns. Following recent research, this study explores the effects of demographic factors on rates of culture change and diversification. We investigate whether the appearance of stability in early Paleolithic technologies could result from frequent extinctions of local subpopulations within a persistent metapopulation. A spatially explicit agent-based model was constructed to test the influence of local extinction rate on three general cultural patterns that archaeologists might observe in the material record: total diversity, differentiation among spatially defined groups, and the rate of cumulative change. The model shows that diversity, differentiation, and the rate of cumulative cultural change would be strongly affected by local extinction rates, in some cases mimicking the results of conformist cultural transmission. The results have implications for understanding spatial and temporal patterning in ancient material culture. PMID:21179418

Local orientation and the evolution of foraging: changes in decision making can eliminate evolutionary trade-offs.

PubMed

van der Post, Daniel J; Semmann, Dirk

2011-10-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or "recognize patterns" in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is "staying in patches". In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape.

Historical droughts in Mediterranean regions during the last 500 years: a data/model approach

NASA Astrophysics Data System (ADS)

Brewer, S.; Alleaume, S.; Guiot, J.; Nicault, A.

2007-06-01

We present here a new method for comparing the output of General Circulation Models (GCMs) with proxy-based reconstructions, using time series of reconstructed and simulated climate parameters. The method uses k-means clustering to allow comparison between different periods that have similar spatial patterns, and a fuzzy logic-based distance measure in order to take reconstruction errors into account. The method has been used to test two coupled ocean-atmosphere GCMs over the Mediterranean region for the last 500 years, using an index of drought stress, the Palmer Drought Severity Index. The results showed that, whilst no model exactly simulated the reconstructed changes, all simulations were an improvement over using the mean climate, and a good match was found after 1650 with a model run that took into account changes in volcanic forcing, solar irradiance, and greenhouse gases. A more detailed investigation of the output of this model showed the existence of a set of atmospheric circulation patterns linked to the patterns of drought stress: 1) a blocking pattern over northern Europe linked to dry conditions in the south prior to the Little Ice Age (LIA) and during the 20th century; 2) a NAO-positive like pattern with increased westerlies during the LIA; 3) a NAO-negative like period shown in the model prior to the LIA, but that occurs most frequently in the data during the LIA. The results of the comparison show the improvement in simulated climate as various forcings are included and help to understand the atmospheric changes that are linked to the observed reconstructed climate changes.

Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

PubMed Central

Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

2015-01-01

Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

Hydrodynamical simulations of the barred spiral galaxy NGC 1300. Dynamical interpretation of observations

NASA Astrophysics Data System (ADS)

Lindblad, P. A. B.; Kristen, H.

1996-09-01

We perform two-dimensional time dependent hydrodynamical simulations of the barred spiral galaxy NGC 1300. The input potential is divided into an axisymmetric part mainly derived from the observed rotation curve, and a perturbing part obtained from near infrared surface photometry of the bar and spiral structure. Self-gravitation of the gas is not taken into account in our modeling. A pure bar perturbed model is unable to reproduce the observations. It was found necessary to add a weak spiral potential to the perturbation, thus suggesting the presence of massive spiral arms in NGC 1300. We find two models, differing mainly in pattern speed, which are able to reproduce the essentials of NGC 1300. The high pattern speed model has {OMEGA}_p_=20km/s/kpc, corresponding to a corotation radius at R_CR_~104"=1.3R_bar_. Furthermore, the adopted rotation curve for this model supports one ILR at R_ILR_~26" and an OLR at R_OLR_~188". The low pattern speed model has {OMEGA}_p_=12km/s/kpc, corresponding to a corotation radius at R_ CR_~190"=2.4R_bar_. The adopted rotation curve for this model, which differs from the fast pattern speed model, supports one ILR at R_ILR_~25" and an OLR at R_OLR_~305". Morphological features, like spiral arms and offset dust lanes, are basically reproduced by both models. They are driven by orbit crowding effects across various resonances, leading to density enhancements. The general velocity structure, as described by HI data and optical long slit measurements, is fairly consistent with the model velocities.

Behavioral pattern separation and its link to the neural mechanisms of fear generalization.

PubMed

Lange, Iris; Goossens, Liesbet; Michielse, Stijn; Bakker, Jindra; Lissek, Shmuel; Papalini, Silvia; Verhagen, Simone; Leibold, Nicole; Marcelis, Machteld; Wichers, Marieke; Lieverse, Ritsaert; van Os, Jim; van Amelsvoort, Therese; Schruers, Koen

2017-11-01

Fear generalization is a prominent feature of anxiety disorders and post-traumatic stress disorder (PTSD). It is defined as enhanced fear responding to a stimulus that bears similarities, but is not identical to a threatening stimulus. Pattern separation, a hippocampal-dependent process, is critical for stimulus discrimination; it transforms similar experiences or events into non-overlapping representations. This study is the first in humans to investigate the extent to which fear generalization relies on behavioral pattern separation abilities. Participants (N = 46) completed a behavioral task taxing pattern separation, and a neuroimaging fear conditioning and generalization paradigm. Results show an association between lower behavioral pattern separation performance and increased generalization in shock expectancy scores, but not in fear ratings. Furthermore, lower behavioral pattern separation was associated with diminished recruitment of the subcallosal cortex during presentation of generalization stimuli. This region showed functional connectivity with the orbitofrontal cortex and ventromedial prefrontal cortex. Together, the data provide novel experimental evidence that pattern separation is related to generalization of threat expectancies, and reduced fear inhibition processes in frontal regions. Deficient pattern separation may be critical in overgeneralization and therefore may contribute to the pathophysiology of anxiety disorders and PTSD. © The Author (2017). Published by Oxford University Press.

Information processing in dendrites I. Input pattern generalisation.

PubMed

Gurney, K N

2001-10-01

In this paper and its companion, we address the question as to whether there are any general principles underlying information processing in the dendritic trees of biological neurons. In order to address this question, we make two assumptions. First, the key architectural feature of dendrites responsible for many of their information processing abilities is the existence of independent sub-units performing local non-linear processing. Second, any general functional principles operate at a level of abstraction in which neurons are modelled by Boolean functions. To accommodate these assumptions, we therefore define a Boolean model neuron-the multi-cube unit (MCU)-which instantiates the notion of the discrete functional sub-unit. We then use this model unit to explore two aspects of neural functionality: generalisation (in this paper) and processing complexity (in its companion). Generalisation is dealt with from a geometric viewpoint and is quantified using a new metric-the set of order parameters. These parameters are computed for threshold logic units (TLUs), a class of random Boolean functions, and MCUs. Our interpretation of the order parameters is consistent with our knowledge of generalisation in TLUs and with the lack of generalisation in randomly chosen functions. Crucially, the order parameters for MCUs imply that these functions possess a range of generalisation behaviour. We argue that this supports the general thesis that dendrites facilitate input pattern generalisation despite any local non-linear processing within functionally isolated sub-units.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Caenorhabditis elegans vulval cell fate patterning

NASA Astrophysics Data System (ADS)

Félix, Marie-Anne

2012-08-01

The spatial patterning of three cell fates in a row of competent cells is exemplified by vulva development in the nematode Caenorhabditis elegans. The intercellular signaling network that underlies fate specification is well understood, yet quantitative aspects remain to be elucidated. Quantitative models of the network allow us to test the effect of parameter variation on the cell fate pattern output. Among the parameter sets that allow us to reach the wild-type pattern, two general developmental patterning mechanisms of the three fates can be found: sequential inductions and morphogen-based induction, the former being more robust to parameter variation. Experimentally, the vulval cell fate pattern is robust to stochastic and environmental challenges, and minor variants can be detected. The exception is the fate of the anterior cell, P3.p, which is sensitive to stochastic variation and spontaneous mutation, and is also evolving the fastest. Other vulval precursor cell fates can be affected by mutation, yet little natural variation can be found, suggesting stabilizing selection. Despite this fate pattern conservation, different Caenorhabditis species respond differently to perturbations of the system. In the quantitative models, different parameter sets can reconstitute their response to perturbation, suggesting that network variation among Caenorhabditis species may be quantitative. Network rewiring likely occurred at longer evolutionary scales.

Mimoza: web-based semantic zooming and navigation in metabolic networks.

PubMed

Zhukova, Anna; Sherman, David J

2015-02-26

The complexity of genome-scale metabolic models makes them quite difficult for human users to read, since they contain thousands of reactions that must be included for accurate computer simulation. Interestingly, hidden similarities between groups of reactions can be discovered, and generalized to reveal higher-level patterns. The web-based navigation system Mimoza allows a human expert to explore metabolic network models in a semantically zoomable manner: The most general view represents the compartments of the model; the next view shows the generalized versions of reactions and metabolites in each compartment; and the most detailed view represents the initial network with the generalization-based layout (where similar metabolites and reactions are placed next to each other). It allows a human expert to grasp the general structure of the network and analyze it in a top-down manner Mimoza can be installed standalone, or used on-line at http://mimoza.bordeaux.inria.fr/ , or installed in a Galaxy server for use in workflows. Mimoza views can be embedded in web pages, or downloaded as COMBINE archives.

Temporal consistency of spatial pattern in growth of the mussel, Mytilus edulis: Implications for predictive modelling

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats

2013-10-01

Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.

The Rising Landscape: A Visual Exploration of Superstring Revolutions in Physics.

ERIC Educational Resources Information Center

Chen, Chaomei; Kuljis, Jasna

2003-01-01

Discussion of knowledge domain visualization focuses on practical issues concerning modeling and visualizing scientific revolutions. Studies growth patterns of specialties derived from citation and cocitation data on string theory in physics, using the general framework of Thomas Kuhn's structure of scientific revolutions. (Author/LRW)

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

1999-01-01

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Variation in Strategy Use across Grade Level by Pattern Generalization Types

ERIC Educational Resources Information Center

El Mouhayar, Rabih; Jurdak, Murad

2015-01-01

This paper explored variation of strategy use in pattern generalization across different generalization types and across grade level. A test was designed to assess students' strategy use in pattern generalization tasks. The test was given to a sample of 1232 students from grades 4 to 11 from five schools in Lebanon. The findings of this study…

Similarity of Cortical Activity Patterns Predicts generalization Behavior

PubMed Central

Engineer, Crystal T.; Perez, Claudia A.; Carraway, Ryan S.; Chang, Kevin Q.; Roland, Jarod L.; Sloan, Andrew M.; Kilgard, Michael P.

2013-01-01

Humans and animals readily generalize previously learned knowledge to new situations. Determining similarity is critical for assigning category membership to a novel stimulus. We tested the hypothesis that category membership is initially encoded by the similarity of the activity pattern evoked by a novel stimulus to the patterns from known categories. We provide behavioral and neurophysiological evidence that activity patterns in primary auditory cortex contain sufficient information to explain behavioral categorization of novel speech sounds by rats. Our results suggest that category membership might be encoded by the similarity of the activity pattern evoked by a novel speech sound to the patterns evoked by known sounds. Categorization based on featureless pattern matching may represent a general neural mechanism for ensuring accurate generalization across sensory and cognitive systems. PMID:24147140

Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus

PubMed Central

Jehee, Janneke F. M.; Ballard, Dana H.

2009-01-01

Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain. PMID:19412529

Numerical Estimation of the Outer Bank Resistance Characteristics in AN Evolving Meandering River

NASA Astrophysics Data System (ADS)

Wang, D.; Konsoer, K. M.; Rhoads, B. L.; Garcia, M. H.; Best, J.

2017-12-01

Few studies have examined the three-dimensional flow structure and its interaction with bed morphology within elongate loops of large meandering rivers. The present study uses a numerical model to simulate the flow pattern and sediment transport, especially the flow close to the outer-bank, at two elongate meandering loops in Wabash River, USA. The numerical grid for the model is based on a combination of airborne LIDAR data on floodplains and the multibeam data within the river channel. A Finite Element Method (FEM) is used to solve the non-hydrostatic RANS equation using a K-epsilon turbulence closure scheme. High-resolution topographic data allows detailed numerical simulation of flow patterns along the outer bank and model calibration involves comparing simulated velocities to ADCP measurements at 41 cross sections near this bank. Results indicate that flow along the outer bank is strongly influenced by large resistance elements, including woody debris, large erosional scallops within the bank face, and outcropping bedrock. In general, patterns of bank migration conform with zones of high near-bank velocity and shear stress. Using the existing model, different virtual events can be simulated to explore the impacts of different resistance characteristics on patterns of flow, sediment transport, and bank erosion.

Epithelial Patterning, Morphogenesis, and Evolution: Drosophila Eggshell as a Model.

PubMed

Osterfield, Miriam; Berg, Celeste A; Shvartsman, Stanislav Y

2017-05-22

Understanding the mechanisms driving tissue and organ formation requires knowledge across scales. How do signaling pathways specify distinct tissue types? How does the patterning system control morphogenesis? How do these processes evolve? The Drosophila egg chamber, where EGF and BMP signaling intersect to specify unique cell types that construct epithelial tubes for specialized eggshell structures, has provided a tractable system to ask these questions. Work there has elucidated connections between scales of development, including across evolutionary scales, and fostered the development of quantitative modeling tools. These tools and general principles can be applied to the understanding of other developmental processes across organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluating Treatment and Generalization Patterns of Two Theoretically Motivated Sentence Comprehension Therapies

PubMed Central

Des Roches, Carrie A.; Vallila-Rohter, Sofia; Villard, Sarah; Tripodis, Yorghos; Caplan, David

2016-01-01

Purpose The current study examined treatment outcomes and generalization patterns following 2 sentence comprehension therapies: object manipulation (OM) and sentence-to-picture matching (SPM). Findings were interpreted within the framework of specific deficit and resource reduction accounts, which were extended in order to examine the nature of generalization following treatment of sentence comprehension deficits in aphasia. Method Forty-eight individuals with aphasia were enrolled in 1 of 8 potential treatment assignments that varied by task (OM, SPM), complexity of trained sentences (complex, simple), and syntactic movement (noun phrase, wh-movement). Comprehension of trained and untrained sentences was probed before and after treatment using stimuli that differed from the treatment stimuli. Results Linear mixed-model analyses demonstrated that, although both OM and SPM treatments were effective, OM resulted in greater improvement than SPM. Analyses of covariance revealed main effects of complexity in generalization; generalization from complex to simple linguistically related sentences was observed both across task and across movement. Conclusions Results are consistent with the complexity account of treatment efficacy, as generalization effects were consistently observed from complex to simpler structures. Furthermore, results provide support for resource reduction accounts that suggest that generalization can extend across linguistic boundaries, such as across movement type. PMID:27997950

Archaeology in the Kilauea East Rift Zone: Part 1, Land-use model and research design, Kapoho, Kamaili and Kilauea Geothermal Subzones, Puna District, Hawaii Island

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

Burtchard, G.C.; Moblo, P.

1994-07-01

The Puna Geothermal Resource Subzones (GRS) project area encompasses approximately 22,000 acres centered on the Kilauea East Rift Zone in Puna District, Hawaii Island. The area is divided into three subzones proposed for geothermal power development -- Kilauea Middle East Rift, Kamaili and Kapoho GRS. Throughout the time of human occupation, eruptive episodes along the rift have maintained a dynamic landscape. Periodic volcanic events, for example, have changed the coastline configuration, altered patterns of agriculturally suitable sediments, and created an assortment of periodically active, periodically quiescent, volcanic hazards. Because of the active character of the rift zone, then, the area`smore » occupants have always been obliged to organize their use of the landscape to accommodate a dynamic mosaic of lava flow types and ages. While the specific configuration of settlements and agricultural areas necessarily changed in response to volcanic events, it is possible to anticipate general patterns in the manner in which populations used the landscape through time. This research design offers a model that predicts the spatial results of long-term land-use patterns and relates them to the character of the archaeological record of that use. In essence, the environmental/land-use model developed here predicts that highest population levels, and hence the greatest abundance and complexity of identifiable prehistoric remains, tended to cluster near the coast at places that maximized access to productive fisheries and agricultural soils. With the possible exception of a few inland settlements, the density of archaeological remains expected to decrease with distance from the coastline. The pattern is generally supported in the regions existing ethnohistoric and archaeological record.« less

A haptic model of vibration modes in spherical geometry and its application in atomic physics, nuclear physics and beyond

NASA Astrophysics Data System (ADS)

Ubben, Malte; Heusler, Stefan

2018-07-01

Vibration modes in spherical geometry can be classified based on the number and position of nodal planes. However, the geometry of these planes is non-trivial and cannot be easily displayed in two dimensions. We present 3D-printed models of those vibration modes, enabling a haptic approach for understanding essential features of bound states in quantum physics and beyond. In particular, when applied to atomic physics, atomic orbitals are obtained in a natural manner. Applied to nuclear physics, the same patterns of vibration modes emerge as cornerstone for the nuclear shell model. These applications of the very same model in a range of more than 5 orders of magnitude in length scales leads to a general discussion of the applicability and limits of validity of physical models in general.

Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone

PubMed Central

Gerhard, Felipe; Kispersky, Tilman; Gutierrez, Gabrielle J.; Marder, Eve; Kramer, Mark; Eden, Uri

2013-01-01

Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have been proposed to deduce connectivity directly from electrophysiological signals, such as extracellularly recorded spiking activity. Usually, these algorithms have not been validated on a neurophysiological data set for which the actual circuitry is known. Recent work has shown that traditional network inference algorithms based on linear models typically fail to identify the correct coupling of a small central pattern generating circuit in the stomatogastric ganglion of the crab Cancer borealis. In this work, we show that point process models of observed spike trains can guide inference of relative connectivity estimates that match the known physiological connectivity of the central pattern generator up to a choice of threshold. We elucidate the necessary steps to derive faithful connectivity estimates from a model that incorporates the spike train nature of the data. We then apply the model to measure changes in the effective connectivity pattern in response to two pharmacological interventions, which affect both intrinsic neural dynamics and synaptic transmission. Our results provide the first successful application of a network inference algorithm to a circuit for which the actual physiological synapses between neurons are known. The point process methodology presented here generalizes well to larger networks and can describe the statistics of neural populations. In general we show that advanced statistical models allow for the characterization of effective network structure, deciphering underlying network dynamics and estimating information-processing capabilities. PMID:23874181

An Oceanic General Circulation Model (OGCM) investigation of the Red Sea circulation, 1. Exchange between the Red Sea and the Indian Ocean

NASA Astrophysics Data System (ADS)

Sofianos, Sarantis S.; Johns, William E.

2002-11-01

The mechanisms involved in the seasonal exchange between the Red Sea and the Indian Ocean are studied using an Oceanic General Circulation Model (OGCM), namely the Miami Isopycnic Coordinate Ocean Model (MICOM). The model reproduces the basic characteristics of the seasonal circulation observed in the area of the strait of Bab el Mandeb. There is good agreement between model results and available observations on the strength of the exchange and the characteristics of the water masses involved, as well as the seasonal flow pattern. During winter, this flow consists of a typical inverse estuarine circulation, while during summer, the surface flow reverses, there is an intermediate inflow of relatively cold and fresh water, and the hypersaline outflow at the bottom of the strait is significantly reduced. Additional experiments with different atmospheric forcing (seasonal winds, seasonal thermohaline air-sea fluxes, or combinations) were performed in order to assess the role of the atmospheric forcing fields in the exchange flow at Bab el Mandeb. The results of both the wind- and thermohaline-driven experiments exhibit a strong seasonality at the area of the strait, which is in phase with the observations. However, it is the combination of both the seasonal pattern of the wind stress and the seasonal thermohaline forcing that can reproduce the observed seasonal variability at the strait. The importance of the seasonal cycle of the thermohaline forcing on the exchange flow pattern is also emphasized by these results. In the experiment where the thermohaline forcing is represented by its annual mean, the strength of the exchange is reduced almost by half.

Emergent Verbal Behavior and Analogy: Skinnerian and Linguistic Approaches

PubMed Central

Matos, Maria Amelia; de Lourdes Passos, Maria

2010-01-01

The production of verbal operants not previously taught is an important aspect of language productivity. For Skinner, new mands, tacts, and autoclitics result from the recombination of verbal operants. The relation between these mands, tacts, and autoclitics is what linguists call analogy, a grammatical pattern that serves as a foundation on which a speaker might emit new linguistic forms. Analogy appears in linguistics as a regularity principle that characterizes language and has been related to how languages change and also to creativity. The approaches of neogrammarians like Hermann Paul, as well as those of Jespersen and Bloomfield, appear to have influenced Skinner's understanding of verbal creativity. Generalization and stimulus equivalence are behavioral processes related to the generative grammatical behavior described in the analogy model. Linguistic forms and grammatical patterns described in analogy are part of the contingencies of reinforcement that produce generalization and stimulus equivalence. The analysis of verbal behavior needs linguistic analyses of the constituents of linguistic forms and their combination patterns. PMID:22479127

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks

PubMed Central

2018-01-01

Much of the information the brain processes and stores is temporal in nature—a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds—we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. PMID:29537963

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

PubMed

Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

Integrating the philosophy and psychology of aesthetic experience: development of the aesthetic experience scale.

PubMed

Stamatopoulou, Despina

2004-10-01

This study assessed the dynamic relationship between person and object in aesthetic experience. Patterns of the structure of aesthetic experience were derived from a conceptual model based on philosophical and psychological ideas. These patterns were further informed by interviewing individuals with extensive involvement in aesthetic activities and 25 secondary students. Accordingly, patterns were tested by developing a large pool of items attempting to identify measurable structural components of aesthetic experience. Refined first in a pilot study, the 36-item questionnaire was administered to 652 Greek students, aged from 13 to 15 years. Correlation matrices and exploratory factor analyses on principal components were used to examine internal structural relationships. The obliquely rotated five-factor solution of the refined instrument accounted for the 44.1% of the total variance and was combatible with the conceptual model of aesthetic experience, indicating the plausibility of both. The internal consistency of the items was adequate and external correlational analysis offered preliminary support for subsequent development of a self-report measure that serves to operationalize the major constructs of aesthetic experience in the general adolescent population. The results also raise theoretical issues for those interested in empirical aesthetics, suggesting that in experiential functioning, expressive perception and affect may play a more constructive role in cognitive processes than is generally acknowledged.

Dietary Pattern Trajectories from 6 to 12 Months of Age in a Multi-Ethnic Asian Cohort

PubMed Central

Lim, Geraldine Huini; Toh, Jia Ying; Aris, Izzuddin M.; Chia, Ai-Ru; Han, Wee Meng; Saw, Seang Mei; Godfrey, Keith M.; Gluckman, Peter D.; Chong, Yap-Seng; Yap, Fabian; Lee, Yung Seng; Kramer, Michael S.; Chong, Mary Foong-Fong

2016-01-01

Little is known about the dietary patterns of Asian infants in the first year of life, nor of their associations with maternal socio-demographic factors. Based on the Growing Up in Singapore towards healthy Outcomes (GUSTO) mother-offspring cohort, cross-sectional dietary patterns were derived by factor analysis using 24-h recalls and food diaries of infants at 6-, 9- and 12-months of age. Dietary pattern trajectories were modeled by mapping similar dietary patterns across each age using multilevel mixed models. Associations with maternal socio-demographic variables, collected through questionnaires during pregnancy, were assessed using general linear models. In n = 486 infants, four dietary pattern trajectories were established from 6- to 12-months. Predominantly breastmilk: mainly breastmilk and less formula milk, Guidelines: rice porridge, vegetables, fruits and low-fat fish and meat, Easy-to-prepare foods: infant cereals, juices, cakes and biscuits and Noodles (in soup) and seafood: noodle and common accompaniments. In adjusted models, higher maternal education attainment was correlated with higher start scores on Predominantly breastmilk, but lowest education attainment increased its adherence over time. Older mothers had higher start scores on Easy-to-prepare foods, but younger mothers had increased adherence over time. Chinese mothers had higher start scores on Predominantly breastmilk but greater adherence to Guidelines over time, while Indian mothers had higher start scores on Easy-to-prepare foods but greater adherence to Predominantly breastmilk with time (p < 0.05 for all). Changes in trajectories over time were small. Hence, dietary patterns established during weaning are strongly influenced by maternal socio-demographic factors and remain stable over the first year of life. PMID:27314387

Dietary Pattern Trajectories from 6 to 12 Months of Age in a Multi-Ethnic Asian Cohort.

PubMed

Lim, Geraldine Huini; Toh, Jia Ying; Aris, Izzuddin M; Chia, Ai-Ru; Han, Wee Meng; Saw, Seang Mei; Godfrey, Keith M; Gluckman, Peter D; Chong, Yap-Seng; Yap, Fabian; Lee, Yung Seng; Kramer, Michael S; Chong, Mary Foong-Fong

2016-06-15

Little is known about the dietary patterns of Asian infants in the first year of life, nor of their associations with maternal socio-demographic factors. Based on the Growing Up in Singapore towards healthy Outcomes (GUSTO) mother-offspring cohort, cross-sectional dietary patterns were derived by factor analysis using 24-h recalls and food diaries of infants at 6-, 9- and 12-months of age. Dietary pattern trajectories were modeled by mapping similar dietary patterns across each age using multilevel mixed models. Associations with maternal socio-demographic variables, collected through questionnaires during pregnancy, were assessed using general linear models. In n = 486 infants, four dietary pattern trajectories were established from 6- to 12-months. Predominantly breastmilk: mainly breastmilk and less formula milk, rice porridge, vegetables, fruits and low-fat fish and meat, Easy-to-prepare foods: infant cereals, juices, cakes and biscuits and Noodles (in soup) and seafood: noodle and common accompaniments. In adjusted models, higher maternal education attainment was correlated with higher start scores on Predominantly breastmilk, but lowest education attainment increased its adherence over time. Older mothers had higher start scores on Easy-to-prepare foods, but younger mothers had increased adherence over time. Chinese mothers had higher start scores on Predominantly breastmilk but greater adherence to GUIDELINES over time, while Indian mothers had higher start scores on Easy-to-prepare foods but greater adherence to Predominantly breastmilk with time (p < 0.05 for all). Changes in trajectories over time were small. Hence, dietary patterns established during weaning are strongly influenced by maternal socio-demographic factors and remain stable over the first year of life.

Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

PubMed

Galleske, I; Castellanos, J

2002-05-01

This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

Flow visualization methods for field test verification of CFD analysis of an open gloveport

DOE PAGES

Strons, Philip; Bailey, James L.

2017-01-01

Anemometer readings alone cannot provide a complete picture of air flow patterns at an open gloveport. Having a means to visualize air flow for field tests in general provides greater insight by indicating direction in addition to the magnitude of the air flow velocities in the region of interest. Furthermore, flow visualization is essential for Computational Fluid Dynamics (CFD) verification, where important modeling assumptions play a significant role in analyzing the chaotic nature of low-velocity air flow. A good example is shown Figure 1, where an unexpected vortex pattern occurred during a field test that could not have been measuredmore » relying only on anemometer readings. Here by, observing and measuring the patterns of the smoke flowing into the gloveport allowed the CFD model to be appropriately updated to match the actual flow velocities in both magnitude and direction.« less

A unifying framework for quantifying the nature of animal interactions.

PubMed

Potts, Jonathan R; Mokross, Karl; Lewis, Mark A

2014-07-06

Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Thundercloud electrification models in atmospheric electricity and meteorology

NASA Technical Reports Server (NTRS)

Parker, L. W.

1980-01-01

A survey is presented of presently-available theoretical models. The models are classified into three main groups: (1) convection models, (2) precipitation models, and (3) general models. The strengths and weaknesses of the models, their dimensionalities and degrees of sophistication, the nature of their inputs and outputs, and the various specific charging mechanisms treated by them, are considered. In results obtained to date, the convection models predict no significant electrification enhancement based on conductivity gradients and convection alone, with the assumed air circulation patterns. Results of the precipitation models show that the initial electrification can occur rapidly and stably through noninductive collision mechanisms involving ice, and breakdown-strength electric fields can relatively easily be achieved subsequently through the collisional-inductive mechanism. A critical difficulty of the collision mechanisms is imprecise knowledge of relaxation times versus contact times, which can easily lead to overestimates of electrification. The general model results tend to support those of the precipitation models in emphasizing the high potential effectiveness of the collisional-inductive mechanism.

Toward the quantification of a conceptual framework for movement ecology using circular statistical modeling.

PubMed

Shimatani, Ichiro Ken; Yoda, Ken; Katsumata, Nobuhiro; Sato, Katsufumi

2012-01-01

To analyze an animal's movement trajectory, a basic model is required that satisfies the following conditions: the model must have an ecological basis and the parameters used in the model must have ecological interpretations, a broad range of movement patterns can be explained by that model, and equations and probability distributions in the model should be mathematically tractable. Random walk models used in previous studies do not necessarily satisfy these requirements, partly because movement trajectories are often more oriented or tortuous than expected from the models. By improving the modeling for turning angles, this study aims to propose a basic movement model. On the basis of the recently developed circular auto-regressive model, we introduced a new movement model and extended its applicability to capture the asymmetric effects of external factors such as wind. The model was applied to GPS trajectories of a seabird (Calonectris leucomelas) to demonstrate its applicability to various movement patterns and to explain how the model parameters are ecologically interpreted under a general conceptual framework for movement ecology. Although it is based on a simple extension of a generalized linear model to circular variables, the proposed model enables us to evaluate the effects of external factors on movement separately from the animal's internal state. For example, maximum likelihood estimates and model selection suggested that in one homing flight section, the seabird intended to fly toward the island, but misjudged its navigation and was driven off-course by strong winds, while in the subsequent flight section, the seabird reset the focal direction, navigated the flight under strong wind conditions, and succeeded in approaching the island.

The social distribution of dietary patterns. Traditional, modern and healthy eating among women in a Latin American city.

PubMed

Bojorquez, Ietza; Unikel, Claudia; Cortez, Irene; Cerecero, Diego

2015-09-01

Popkin's nutrition transition model proposes that after the change from the traditional to the modern dietary pattern, another change toward "healthy eating" could occur. As health-related practices are associated with social position, with higher socioeconomic groups generally being the first to adopt public health recommendations, a gradient of traditional-modern-healthy dietary patterns should be observed between groups. The objectives of this article were: 1) to describe the dietary patterns of a representative sample of adult women; 2) to assess whether dietary patterns differentiate in traditional, modern and healthy; and 3) to evaluate the association of social position and dietary patterns. We conducted a survey in Tijuana, a Mexican city at the Mexico-United States (US) border. Women 18-65 years old (n = 2345) responded to a food frequency questionnaire, and questions about socioeconomic and demographic factors. We extracted dietary patterns through factor analysis, and employed indicators of economic and cultural capital, life course stage and migration to define social position. We evaluated the association of social position and dietary patterns with linear regression models. Three patterns were identified: "tortillas," "hamburgers" and "vegetables." Women in a middle position of economic and cultural capital scored higher in the "hamburgers" pattern, and women in upper positions scored higher in the "vegetables" pattern. Economic and cultural capitals and migration interacted, so that for women lower in economic capital, having lived in the US was associated with higher scores in the "hamburgers" pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling Menstrual Cycle Length and Variability at the Approach of Menopause Using Hierarchical Change Point Models

PubMed Central

Huang, Xiaobi; Elliott, Michael R.; Harlow, Siobán D.

2013-01-01

SUMMARY As women approach menopause, the patterns of their menstrual cycle lengths change. To study these changes, we need to jointly model both the mean and variability of cycle length. Our proposed model incorporates separate mean and variance change points for each woman and a hierarchical model to link them together, along with regression components to include predictors of menopausal onset such as age at menarche and parity. Additional complexity arises from the fact that the calendar data have substantial missingness due to hormone use, surgery, and failure to report. We integrate multiple imputation and time-to event modeling in a Bayesian estimation framework to deal with different forms of the missingness. Posterior predictive model checks are applied to evaluate the model fit. Our method successfully models patterns of women’s menstrual cycle trajectories throughout their late reproductive life and identifies change points for mean and variability of segment length, providing insight into the menopausal process. More generally, our model points the way toward increasing use of joint mean-variance models to predict health outcomes and better understand disease processes. PMID:24729638

The Laborers-AGC Construction Skills Training Program. Final Performance Report.

ERIC Educational Resources Information Center

Tippie, John L.; Rice, Eric

Patterned after a previously successful Laborers-Associated General Contractors model named the Construction Skills Training Program, a demonstration project was implemented at five regional training centers. At least eight courses were created, combined, or revised. Four full-length audiovisual support pieces were completed. Three courses were…

Religious Attendance and Loneliness in Later Life

ERIC Educational Resources Information Center

Rote, Sunshine; Hill, Terrence D.; Ellison, Christopher G.

2013-01-01

Purpose of the Study: Studies show that loneliness is a major risk factor for health issues in later life. Although research suggests that religious involvement can protect against loneliness, explanations for this general pattern are underdeveloped and undertested. In this paper, we propose and test a theoretical model, which suggests that social…

Apprenticeships Should Work for Women Too!

ERIC Educational Resources Information Center

Simon, Linda; Clarke, Kira

2016-01-01

Purpose: The purpose of this paper is to explore some of the issues affecting successful employment outcomes for young women in male-dominated careers, focusing on those generally accessed via a traditional Australian apprenticeship model. Current patterns of participation in trades-based fields of education and training reinforce the highly…

Reshaping the Enterprise through an Information Architecture and Process Reengineering.

ERIC Educational Resources Information Center

Laudato, Nicholas C.; DeSantis, Dennis J.

1995-01-01

The approach used by the University of Pittsburgh (Pennsylvania) in designing a campus-wide information architecture and a framework for reengineering the business process included building consensus on a general philosophy for information systems, using pattern-based abstraction techniques, applying data modeling and application prototyping, and…

Post-OPC verification using a full-chip pattern-based simulation verification method

NASA Astrophysics Data System (ADS)

Hung, Chi-Yuan; Wang, Ching-Heng; Ma, Cliff; Zhang, Gary

2005-11-01

In this paper, we evaluated and investigated techniques for performing fast full-chip post-OPC verification using a commercial product platform. A number of databases from several technology nodes, i.e. 0.13um, 0.11um and 90nm are used in the investigation. Although it has proven that for most cases, our OPC technology is robust in general, due to the variety of tape-outs with complicated design styles and technologies, it is difficult to develop a "complete or bullet-proof" OPC algorithm that would cover every possible layout patterns. In the evaluation, among dozens of databases, some OPC databases were found errors by Model-based post-OPC checking, which could cost significantly in manufacturing - reticle, wafer process, and more importantly the production delay. From such a full-chip OPC database verification, we have learned that optimizing OPC models and recipes on a limited set of test chip designs may not provide sufficient coverage across the range of designs to be produced in the process. And, fatal errors (such as pinch or bridge) or poor CD distribution and process-sensitive patterns may still occur. As a result, more than one reticle tape-out cycle is not uncommon to prove models and recipes that approach the center of process for a range of designs. So, we will describe a full-chip pattern-based simulation verification flow serves both OPC model and recipe development as well as post OPC verification after production release of the OPC. Lastly, we will discuss the differentiation of the new pattern-based and conventional edge-based verification tools and summarize the advantages of our new tool and methodology: 1). Accuracy: Superior inspection algorithms, down to 1nm accuracy with the new "pattern based" approach 2). High speed performance: Pattern-centric algorithms to give best full-chip inspection efficiency 3). Powerful analysis capability: Flexible error distribution, grouping, interactive viewing and hierarchical pattern extraction to narrow down to unique patterns/cells.

2D-pattern matching image and video compression: theory, algorithms, and experiments.

PubMed

Alzina, Marc; Szpankowski, Wojciech; Grama, Ananth

2002-01-01

In this paper, we propose a lossy data compression framework based on an approximate two-dimensional (2D) pattern matching (2D-PMC) extension of the Lempel-Ziv (1977, 1978) lossless scheme. This framework forms the basis upon which higher level schemes relying on differential coding, frequency domain techniques, prediction, and other methods can be built. We apply our pattern matching framework to image and video compression and report on theoretical and experimental results. Theoretically, we show that the fixed database model used for video compression leads to suboptimal but computationally efficient performance. The compression ratio of this model is shown to tend to the generalized entropy. For image compression, we use a growing database model for which we provide an approximate analysis. The implementation of 2D-PMC is a challenging problem from the algorithmic point of view. We use a range of techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.5 Mbps for a baseline video compression scheme that does not use any prediction or interpolation. We also demonstrate that this asymmetric compression scheme is capable of extremely fast decompression making it particularly suitable for networked multimedia applications.

Development of compositional and contextual communicable congruence in robots by using dynamic neural network models.

PubMed

Park, Gibeom; Tani, Jun

2015-12-01

The current study presents neurorobotics experiments on acquisition of skills for "communicable congruence" with human via learning. A dynamic neural network model which is characterized by its multiple timescale dynamics property was utilized as a neuromorphic model for controlling a humanoid robot. In the experimental task, the humanoid robot was trained to generate specific sequential movement patterns as responding to various sequences of imperative gesture patterns demonstrated by the human subjects by following predefined compositional semantic rules. The experimental results showed that (1) the adopted MTRNN can achieve generalization by learning in the lower feature perception level by using a limited set of tutoring patterns, (2) the MTRNN can learn to extract compositional semantic rules with generalization in its higher level characterized by slow timescale dynamics, (3) the MTRNN can develop another type of cognitive capability for controlling the internal contextual processes as situated to on-going task sequences without being provided with cues for explicitly indicating task segmentation points. The analysis on the dynamic property developed in the MTRNN via learning indicated that the aforementioned cognitive mechanisms were achieved by self-organization of adequate functional hierarchy by utilizing the constraint of the multiple timescale property and the topological connectivity imposed on the network configuration. These results of the current research could contribute to developments of socially intelligent robots endowed with cognitive communicative competency similar to that of human. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using Visualization to Generalize on Quadratic Patterning Tasks

ERIC Educational Resources Information Center

Kirwan, J. Vince

2017-01-01

Patterning tasks engage students in a core aspect of algebraic thinking-generalization (Kaput 2008). The National Council of Teachers of Mathematics (NCTM) Algebra Standard states that students in grades 9-12 should "generalize patterns using explicitly defined and recursively defined functions" (NCTM 2000, p. 296). Although educators…

QuEST for malware type-classification

NASA Astrophysics Data System (ADS)

Vaughan, Sandra L.; Mills, Robert F.; Grimaila, Michael R.; Peterson, Gilbert L.; Oxley, Mark E.; Dube, Thomas E.; Rogers, Steven K.

2015-05-01

Current cyber-related security and safety risks are unprecedented, due in no small part to information overload and skilled cyber-analyst shortages. Advances in decision support and Situation Awareness (SA) tools are required to support analysts in risk mitigation. Inspired by human intelligence, research in Artificial Intelligence (AI) and Computational Intelligence (CI) have provided successful engineering solutions in complex domains including cyber. Current AI approaches aggregate large volumes of data to infer the general from the particular, i.e. inductive reasoning (pattern-matching) and generally cannot infer answers not previously programmed. Whereas humans, rarely able to reason over large volumes of data, have successfully reached the top of the food chain by inferring situations from partial or even partially incorrect information, i.e. abductive reasoning (pattern-completion); generating a hypothetical explanation of observations. In order to achieve an engineering advantage in computational decision support and SA we leverage recent research in human consciousness, the role consciousness plays in decision making, modeling the units of subjective experience which generate consciousness, qualia. This paper introduces a novel computational implementation of a Cognitive Modeling Architecture (CMA) which incorporates concepts of consciousness. We apply our model to the malware type-classification task. The underlying methodology and theories are generalizable to many domains.

The General Circulation Model Response to a North Pacific SST Anomaly: Dependence on Time Scale and Pattern Polarity.

NASA Astrophysics Data System (ADS)

Kushnir, Yochanan; Lau, Ngar-Cheung

1992-04-01

A general circulation model was integrated with perpetual January conditions and prescribed sea surface temperature (SST) anomalies in the North Pacific. A characteristic pattern with a warm region centered northeast of Hawaii and a cold region along the western seaboard of North America was alternately added to and subtracted from the climatological SST field. Long 1350-day runs, as well as short 180-day runs, each starting from different initial conditions, were performed. The results were compared to a control integration with climatological SSTs.The model's quasi-stationary response does not exhibit a simple linear relationship with the polarity of the prescribed SST anomaly. In the short runs with a negative SST anomaly over the central ocean, a large negative height anomaly, with an equivalent barotropic vertical structure, occurs over the Gulf of Alaska. For the same SST forcing, the long run yields a different response pattern in which an anomalous high prevails over northern Canada and the Alaskan Peninsula. A significant reduction in the northward heat flux associated with baroclinic eddies and a concomitant reduction in convective heating occur along the model's Pacific storm track. In the runs with a positive SST anomaly over the central ocean, the average height response during the first 90-day period of the short runs is too weak to be significant. In the subsequent 90-day period and in the long run an equivalent barotropic low occurs downstream from the warm SST anomaly. All positive anomaly runs exhibit little change in baroclinic eddy activity or in the patterns of latent heat release. Horizontal momentum transports by baroclinic eddies appear to help sustain the quasi-stationary response in the height field regardless of the polarity of the SST anomaly. These results emphasize the important role played by baroclinic eddies in determining the quasi-stationary response to midlatitude SST anomalies. Differences between the response patterns of the short and long integrations may be relevant to future experimental design for studying air-sea interactions in the extratropies.

Patterns of impaired oral health-related quality of life dimensions.

PubMed

John, M T; Rener-Sitar, K; Baba, K; Čelebić, A; Larsson, P; Szabo, G; Norton, W E; Reissmann, D R

2016-07-01

How dental patients are affected by oral conditions can be described with the concept of oral health-related quality of life (OHRQoL). This concept intends to make the patient experience measurable. OHRQoL is multidimensional, and Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact were suggested as its four dimensions and consequently four scores are needed for comprehensive OHRQoL assessment. When only the presence of dimensional impact is measured, a pattern of affected OHRQoL dimensions would describe in a simple way how oral conditions influence the individual. By determining which patterns of impact on OHRQoL dimensions exist in prosthodontic patients and general population subjects, we aimed to identify in which combinations oral conditions' functional, painful, aesthetical and psychosocial impact occurs. Data came from the Dimensions of OHRQoL Project with Oral Health Impact Profile (OHIP)-49 data from 6349 general population subjects and 2999 prosthodontic patients in the Learning Sample (N = 5173) and the Validation Sample (N = 5022). We hypothesised that all 16 patterns of OHRQoL dimensions should occur in these individuals who suffered mainly from tooth loss, its causes and consequences. A dimension was considered impaired when at least one item in the dimension was affected frequently. The 16 possible patterns of impaired OHRQoL dimensions were found in patients and general population subjects in both Learning and Validation Samples. In a four-dimensional OHRQoL model consisting Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact, oral conditions' impact can occur in any combination of the OHRQoL dimensions. © 2016 John Wiley & Sons Ltd.

The Bayesian reader: explaining word recognition as an optimal Bayesian decision process.

PubMed

Norris, Dennis

2006-04-01

This article presents a theory of visual word recognition that assumes that, in the tasks of word identification, lexical decision, and semantic categorization, human readers behave as optimal Bayesian decision makers. This leads to the development of a computational model of word recognition, the Bayesian reader. The Bayesian reader successfully simulates some of the most significant data on human reading. The model accounts for the nature of the function relating word frequency to reaction time and identification threshold, the effects of neighborhood density and its interaction with frequency, and the variation in the pattern of neighborhood density effects seen in different experimental tasks. Both the general behavior of the model and the way the model predicts different patterns of results in different tasks follow entirely from the assumption that human readers approximate optimal Bayesian decision makers. ((c) 2006 APA, all rights reserved).

Improved computer simulation of the TCAS 3 circular array mounted on an aircraft

NASA Astrophysics Data System (ADS)

Rojas, R. G.; Chen, Y. C.; Burnside, Walter D.

1989-03-01

The Traffic advisory and Collision Avoidance System (TCAS) is being developed by the Federal Aviation Administration (FAA) to assist aircraft pilots in mid-air collision avoidance. This report concentrates on the computer simulation of the enchanced TCAS 2 systems mounted on a Boeing 727. First, the moment method is used to obtain an accurate model for the enhanced TCAS 2 antenna array. Then, the OSU Aircraft Code is used to generate theoretical radiation patterns of this model mounted on a simulated Boeing 727 model. Scattering error curves obtained from these patterns can be used to evaluate the performance of this system in determining the angular position of another aircraft with respect to the TCAS-equipped aircraft. Finally, the tracking of another aircraft is simulated when the TCAS-equipped aircraft follows a prescribed escape curve. In short, the computer models developed in this report have generality, completeness and yield reasonable results.

A Formal Investigation of Human Spatial Control Skills: Mathematical Formalization, Skill Development, and Skill Assessment

NASA Astrophysics Data System (ADS)

Li, Bin

Spatial control behaviors account for a large proportion of human everyday activities from normal daily tasks, such as reaching for objects, to specialized tasks, such as driving, surgery, or operating equipment. These behaviors involve intensive interactions within internal processes (i.e. cognitive, perceptual, and motor control) and with the physical world. This dissertation builds on a concept of interaction pattern and a hierarchical functional model. Interaction pattern represents a type of behavior synergy that humans coordinates cognitive, perceptual, and motor control processes. It contributes to the construction of the hierarchical functional model that delineates humans spatial control behaviors as the coordination of three functional subsystems: planning, guidance, and tracking/pursuit. This dissertation formalizes and validates these two theories and extends them for the investigation of human spatial control skills encompassing development and assessment. Specifically, this dissertation first presents an overview of studies in human spatial control skills encompassing definition, characteristic, development, and assessment, to provide theoretical evidence for the concept of interaction pattern and the hierarchical functional model. The following, the human experiments for collecting motion and gaze data and techniques to register and classify gaze data, are described. This dissertation then elaborates and mathematically formalizes the hierarchical functional model and the concept of interaction pattern. These theories then enables the construction of a succinct simulation model that can reproduce a variety of human performance with a minimal set of hypotheses. This validates the hierarchical functional model as a normative framework for interpreting human spatial control behaviors. The dissertation then investigates human skill development and captures the emergence of interaction pattern. The final part of the dissertation applies the hierarchical functional model for skill assessment and introduces techniques to capture interaction patterns both from the top down using their geometric features and from the bottom up using their dynamical characteristics. The validity and generality of the skill assessment is illustrated using two the remote-control flight and laparoscopic surgical training experiments.

Prediction of PM 10 concentrations at urban traffic intersections using semi-empirical box modelling with instantaneous velocity and acceleration

NASA Astrophysics Data System (ADS)

He, Hong-di; Lu, Wei-Zhen; Xue, Yu

2009-12-01

At urban traffic intersections, vehicles frequently stop with idling engines during the red-light period and speed up rapidly during the green-light period. The changes of driving patterns (i.e., idle, acceleration, deceleration and cruising patterns) generally produce uncertain emission. Additionally, the movement of pedestrians and the influence of wind further result in the random dispersion of pollutants. It is, therefore, too complex to simulate the effects of such dynamics on the resulting emission using conventional deterministic causal models. For this reason, a modified semi-empirical box model for predicting the PM 10 concentrations on roadsides is proposed in this paper. The model constitutes three parts, i.e., traffic, emission and dispersion components. The traffic component is developed using a generalized force traffic model to obtain the instantaneous velocity and acceleration when vehicles move through intersections. Hence the distribution of vehicle emission in street canyon during the green-light period is calculated. Then the dispersion component is investigated using a semi-empirical box model combining average wind speed, box height and background concentrations. With these considerations, the proposed model is applied and evaluated using measured data at a busy traffic intersection in Mong Kok, Hong Kong. In order to test the performance of the model, two situations, i.e., the data sets within a sunny day and between two sunny days, were selected to examine the model performance. The predicted values are generally well coincident with the observed data during different time slots except several values are overestimated or underestimated. Moreover, two types of vehicles, i.e., buses and petrol cars, are separately taken into account in the study. Buses are verified to contribute most to the emission in street canyons, which may be useful in evaluating the impact of vehicle emissions on the ambient air quality when there is a significant change in a specific vehicular population.

Dictionary Indexing of Electron Channeling Patterns.

PubMed

Singh, Saransh; De Graef, Marc

2017-02-01

The dictionary-based approach to the indexing of diffraction patterns is applied to electron channeling patterns (ECPs). The main ingredients of the dictionary method are introduced, including the generalized forward projector (GFP), the relevant detector model, and a scheme to uniformly sample orientation space using the "cubochoric" representation. The GFP is used to compute an ECP "master" pattern. Derivative free optimization algorithms, including the Nelder-Mead simplex and the bound optimization by quadratic approximation are used to determine the correct detector parameters and to refine the orientation obtained from the dictionary approach. The indexing method is applied to poly-silicon and shows excellent agreement with the calibrated values. Finally, it is shown that the method results in a mean disorientation error of 1.0° with 0.5° SD for a range of detector parameters.

MOAB: a spatially explicit, individual-based expert system for creating animal foraging models

USGS Publications Warehouse

Carter, J.; Finn, John T.

1999-01-01

We describe the development, structure, and corroboration process of a simulation model of animal behavior (MOAB). MOAB can create spatially explicit, individual-based animal foraging models. Users can create or replicate heterogeneous landscape patterns, and place resources and individual animals of a goven species on that landscape to simultaneously simulate the foraging behavior of multiple species. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. MOAB can be used to explore hypotheses concerning the influence of landscape patttern on animal movement and foraging behavior. A red fox (Vulpes vulpes L.) foraging and nest predation model was created to test MOAB's capabilities. Foxes were simulated for 30-day periods using both expert system and random movement rules. Home range size, territory formation and other available simulation studies. A striped skunk (Mephitis mephitis L.) model also was developed. The expert system model proved superior to stochastic in respect to territory formation, general movement patterns and home range size.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework.

PubMed

Namboodiri, Vijay Mohan K; Levy, Joshua M; Mihalas, Stefan; Sims, David W; Hussain Shuler, Marshall G

2016-08-02

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

Forced decadal changes in the East Asian summer monsoon: the roles of greenhouse gases and anthropogenic aerosols

NASA Astrophysics Data System (ADS)

Tian, Fangxing; Dong, Buwen; Robson, Jon; Sutton, Rowan

2018-02-01

Since the mid-1990s precipitation trends over eastern China display a dipole pattern, characterized by positive anomalies in the south and negative anomalies in the north, named as the Southern-Flood-Northern-Drought (SFND) pattern. This work investigates the drivers of decadal changes of the East Asian summer monsoon (EASM), and the dynamical mechanisms involved, by using a coupled climate model (specifically an atmospheric general circulation model coupled to an ocean mixed layer model) forced by changes in (1) anthropogenic greenhouse gases (GHG), (2) anthropogenic aerosol (AA) and (3) the combined effects of both GHG and AA (All Forcing) between two periods across the mid-1990s. The model experiment forced by changes in All Forcing shows a dipole pattern of response in precipitation over China that is similar to the observed SFND pattern across the mid-1990s, which suggests that anthropogenic forcing changes played an important role in the observed decadal changes. Furthermore, the experiments with separate forcings indicate that GHG and AA forcing dominate different parts of the SFND pattern. In particular, changes in GHG increase precipitation over southern China, whilst changes in AA dominate in the drought conditions over northern China. Increases in GHG cause increased moisture transport convergence over eastern China, which leads to increased precipitation. The AA forcing changes weaken the EASM, which lead to divergent wind anomalies over northern China and reduced precipitation.

Evaluation of two models for predicting elemental accumulation by arthropods

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

Webster, J.R.; Crossley, D.A. Jr.

1978-06-15

Two different models have been proposed for predicting elemental accumulation by arthropods. Parameters of both models can be quantified from radioisotope elimination experiments. Our analysis of the 2 models shows that both predict identical elemental accumulation for a whole organism, though differing in the accumulation in body and gut. We quantified both models with experimental data from /sup 134/Cs and /sup 85/Sr elimination by crickets. Computer simulations of radioisotope accumulation were then compared with actual accumulation experiments. Neither model showed exact fit to the experimental data, though both showed the general pattern of elemental accumulation.

Hydrological Validation of The Lpj Dynamic Global Vegetation Model - First Results and Required Actions

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Gerten, D.; Schaphoff, S.; Lucht, W.

Dynamic global vegetation models are developed with the main purpose to describe the spatio-temporal dynamics of vegetation at the global scale. Increasing concern about climate change impacts has put the focus of recent applications on the sim- ulation of the global carbon cycle. Water is a prime driver of biogeochemical and biophysical processes, thus an appropriate representation of the water cycle is crucial for their proper simulation. However, these models usually lack thorough validation of the water balance they produce. Here we present a hydrological validation of the current version of the LPJ (Lund- Potsdam-Jena) model, a dynamic global vegetation model operating at daily time steps. Long-term simulated runoff and evapotranspiration are compared to literature values, results from three global hydrological models, and discharge observations from various macroscale river basins. It was found that the seasonal and spatial patterns of the LPJ-simulated average values correspond well both with the measurements and the results from the stand-alone hy- drological models. However, a general underestimation of runoff occurs, which may be attributable to the low input dynamics of precipitation (equal distribution within a month), to the simulated vegetation pattern (potential vegetation without anthro- pogenic influence), and to some generalizations of the hydrological components in LPJ. Future research will focus on a better representation of the temporal variability of climate forcing, improved description of hydrological processes, and on the consider- ation of anthropogenic land use.

Food web complexity and stability across habitat connectivity gradients.

PubMed

LeCraw, Robin M; Kratina, Pavel; Srivastava, Diane S

2014-12-01

The effects of habitat connectivity on food webs have been studied both empirically and theoretically, yet the question of whether empirical results support theoretical predictions for any food web metric other than species richness has received little attention. Our synthesis brings together theory and empirical evidence for how habitat connectivity affects both food web stability and complexity. Food web stability is often predicted to be greatest at intermediate levels of connectivity, representing a compromise between the stabilizing effects of dispersal via rescue effects and prey switching, and the destabilizing effects of dispersal via regional synchronization of population dynamics. Empirical studies of food web stability generally support both this pattern and underlying mechanisms. Food chain length has been predicted to have both increasing and unimodal relationships with connectivity as a result of predators being constrained by the patch occupancy of their prey. Although both patterns have been documented empirically, the underlying mechanisms may differ from those predicted by models. In terms of other measures of food web complexity, habitat connectivity has been empirically found to generally increase link density but either reduce or have no effect on connectance, whereas a unimodal relationship is expected. In general, there is growing concordance between empirical patterns and theoretical predictions for some effects of habitat connectivity on food webs, but many predictions remain to be tested over a full connectivity gradient, and empirical metrics of complexity are rarely modeled. Closing these gaps will allow a deeper understanding of how natural and anthropogenic changes in connectivity can affect real food webs.

Generalized reproduction numbers and the prediction of patterns in waterborne disease.

PubMed

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-11-27

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0, explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Genomic signal processing: from matrix algebra to genetic networks.

PubMed

Alter, Orly

2007-01-01

DNA microarrays make it possible, for the first time, to record the complete genomic signals that guide the progression of cellular processes. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment, and drug development. This chapter reviews the first data-driven models that were created from these genome-scale data, through adaptations and generalizations of mathematical frameworks from matrix algebra that have proven successful in describing the physical world, in such diverse areas as mechanics and perception: the singular value decomposition model, the generalized singular value decomposition model comparative model, and the pseudoinverse projection integrative model. These models provide mathematical descriptions of the genetic networks that generate and sense the measured data, where the mathematical variables and operations represent biological reality. The variables, patterns uncovered in the data, correlate with activities of cellular elements such as regulators or transcription factors that drive the measured signals and cellular states where these elements are active. The operations, such as data reconstruction, rotation, and classification in subspaces of selected patterns, simulate experimental observation of only the cellular programs that these patterns represent. These models are illustrated in the analyses of RNA expression data from yeast and human during their cell cycle programs and DNA-binding data from yeast cell cycle transcription factors and replication initiation proteins. Two alternative pictures of RNA expression oscillations during the cell cycle that emerge from these analyses, which parallel well-known designs of physical oscillators, convey the capacity of the models to elucidate the design principles of cellular systems, as well as guide the design of synthetic ones. In these analyses, the power of the models to predict previously unknown biological principles is demonstrated with a prediction of a novel mechanism of regulation that correlates DNA replication initiation with cell cycle-regulated RNA transcription in yeast. These models may become the foundation of a future in which biological systems are modeled as physical systems are today.

Few-cycle optical rogue waves: complex modified Korteweg-de Vries equation.

PubMed

He, Jingsong; Wang, Lihong; Li, Linjing; Porsezian, K; Erdélyi, R

2014-06-01

In this paper, we consider the complex modified Korteweg-de Vries (mKdV) equation as a model of few-cycle optical pulses. Using the Lax pair, we construct a generalized Darboux transformation and systematically generate the first-, second-, and third-order rogue wave solutions and analyze the nature of evolution of higher-order rogue waves in detail. Based on detailed numerical and analytical investigations, we classify the higher-order rogue waves with respect to their intrinsic structure, namely, fundamental pattern, triangular pattern, and ring pattern. We also present several new patterns of the rogue wave according to the standard and nonstandard decomposition. The results of this paper explain the generalization of higher-order rogue waves in terms of rational solutions. We apply the contour line method to obtain the analytical formulas of the length and width of the first-order rogue wave of the complex mKdV and the nonlinear Schrödinger equations. In nonlinear optics, the higher-order rogue wave solutions found here will be very useful to generate high-power few-cycle optical pulses which will be applicable in the area of ultrashort pulse technology.

Decoding negative affect personality trait from patterns of brain activation to threat stimuli.

PubMed

Fernandes, Orlando; Portugal, Liana C L; Alves, Rita de Cássia S; Arruda-Sanchez, Tiago; Rao, Anil; Volchan, Eliane; Pereira, Mirtes; Oliveira, Letícia; Mourao-Miranda, Janaina

2017-01-15

Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875).

PubMed

Hugall, Andrew; Moritz, Craig; Moussalli, Adnan; Stanisic, John

2002-04-30

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them.

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875)

PubMed Central

Hugall, Andrew; Moritz, Craig; Moussalli, Adnan; Stanisic, John

2002-01-01

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them. PMID:11972064

Investigation of Skylab imagery for regional planning. [New York, New Jersey, and Connecticut

NASA Technical Reports Server (NTRS)

Harting, W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. It is feasible to use earth terrain camera imagery to detect four land uses (vacant land, developed land, streets, and water) for general regional planning purposes. Multispectral imagery is suitable for detecting, mapping, and measuring water bodies as small as two acres. Sufficient information can be extracted to prepare graphic and pictorial representations of the general growth and development patterns, but cannot be incorporated into an inventory file for predictive models.

Random Boolean networks for autoassociative memory: Optimization and sequential learning

NASA Astrophysics Data System (ADS)

Sherrington, D.; Wong, K. Y. M.

Conventional neural networks are based on synaptic storage of information, even when the neural states are discrete and bounded. In general, the set of potential local operations is much greater. Here we discuss some aspects of the properties of networks of binary neurons with more general Boolean functions controlling the local dynamics. Two specific aspects are emphasised; (i) optimization in the presence of noise and (ii) a simple model for short-term memory exhibiting primacy and recency in the recall of sequentially taught patterns.

Benzene patterns in different urban environments and a prediction model for benzene rates based on NOx values

NASA Astrophysics Data System (ADS)

Paz, Shlomit; Goldstein, Pavel; Kordova-Biezuner, Levana; Adler, Lea

2017-04-01

Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. The aims of the study were to compare benzene rates in different urban environments (region with heavy traffic and industrial region), to analyse the relationship between benzene and meteorological parameters in a Mediterranean climate type, to estimate the linkages between benzene and NOx and to suggest a prediction model for benzene rates based on NOx levels in order contribute to a better estimation of benzene. Data were used from two different monitoring stations, located on the eastern Mediterranean coast: 1) a traffic monitoring station in Tel Aviv, Israel (TLV) located in an urban region with heavy traffic; 2) a general air quality monitoring station in Haifa Bay (HIB), located in Israel's main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NOx, mean temperature, relative humidity, inversion level, and temperature gradient were analysed over three years: 2008, 2009, and 2010. A prediction model for benzene rates based on NOx levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station (TLV) than at the general air quality station (HIB), despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NOx and benzene allowed the development of a prediction model for benzene rates, based on NOx, the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year (except for September). The severity of benzene pollution was found to be considerably higher at the traffic station (TLV) than at the general air quality station (HIB), despite being located in an industrial area. Hourly, daily, seasonal, and annual patterns of benzene rates have been shown to coincide with anthropogenic activities (traffic), day of the week, and atmospheric conditions. A prediction model for benzene rates was developed, based on NOx, the day of the week, and the month. The model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.

Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

NASA Astrophysics Data System (ADS)

White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

Oscillations and patterns in a model of simultaneous CO and C2H2 oxidation and NO(x) reduction in a cross-flow reactor.

PubMed

Hadač, Otto; Kohout, Martin; Havlica, Jaromír; Schreiber, Igor

2015-03-07

A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.

Intelligent-based Structural Damage Detection Model

NASA Astrophysics Data System (ADS)

Lee, Eric Wai Ming; Yu, Kin Fung

2010-05-01

This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

Advancing the Assessment of Personality Pathology With the Cognitive-Affective Processing System.

PubMed

Huprich, Steven K; Nelson, Sharon M

2015-01-01

The Cognitive-Affective Processing System (CAPS) is a dynamic and expansive model of personality proposed by Mischel and Shoda (1995) that incorporates dispositional and processing frameworks by considering the interaction of the individual and the situation, and the patterns of variation that result. These patterns of cognition, affect, and behavior are generally defined through the use of if … then statements, and provide a rich understanding of the individual across varying levels of assessment. In this article, we describe the CAPS model and articulate ways in which it can be applied to conceptualizing and assessing personality pathology. We suggest that the CAPS model is an ideal framework that integrates a number of current theories of personality pathology, and simultaneously overcomes a number of limits that have been empirically identified in the past.

Forging patterns and making waves from biology to geology: a commentary on Turing (1952) 'The chemical basis of morphogenesis'.

PubMed

Ball, Philip

2015-04-19

Alan Turing was neither a biologist nor a chemist, and yet the paper he published in 1952, 'The chemical basis of morphogenesis', on the spontaneous formation of patterns in systems undergoing reaction and diffusion of their ingredients has had a substantial impact on both fields, as well as in other areas as disparate as geomorphology and criminology. Motivated by the question of how a spherical embryo becomes a decidedly non-spherical organism such as a human being, Turing devised a mathematical model that explained how random fluctuations can drive the emergence of pattern and structure from initial uniformity. The spontaneous appearance of pattern and form in a system far away from its equilibrium state occurs in many types of natural process, and in some artificial ones too. It is often driven by very general mechanisms, of which Turing's model supplies one of the most versatile. For that reason, these patterns show striking similarities in systems that seem superficially to share nothing in common, such as the stripes of sand ripples and of pigmentation on a zebra skin. New examples of 'Turing patterns' in biology and beyond are still being discovered today. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

Unimodal Latitudinal Pattern of Land-Snail Species Richness across Northern Eurasian Lowlands

PubMed Central

Horsák, Michal; Chytrý, Milan

2014-01-01

Large-scale patterns of species richness and their causes are still poorly understood for most terrestrial invertebrates, although invertebrates can add important insights into the mechanisms that generate regional and global biodiversity patterns. Here we explore the general plausibility of the climate-based “water-energy dynamics” hypothesis using the latitudinal pattern of land-snail species richness across extensive topographically homogeneous lowlands of northern Eurasia. We established a 1480-km long latitudinal transect across the Western Siberian Plain (Russia) from the Russia-Kazakhstan border (54.5°N) to the Arctic Ocean (67.5°N), crossing eight latitudinal vegetation zones: steppe, forest-steppe, subtaiga, southern, middle and northern taiga, forest-tundra, and tundra. We sampled snails in forests and open habitats each half-degree of latitude and used generalized linear models to relate snail species richness to climatic variables and soil calcium content measured in situ. Contrary to the classical prediction of latitudinal biodiversity decrease, we found a striking unimodal pattern of snail species richness peaking in the subtaiga and southern-taiga zones between 57 and 59°N. The main south-to-north interchange of the two principal diversity constraints, i.e. drought stress vs. cold stress, explained most of the variance in the latitudinal diversity pattern. Water balance, calculated as annual precipitation minus potential evapotranspiration, was a single variable that could explain 81.7% of the variance in species richness. Our data suggest that the “water-energy dynamics” hypothesis can apply not only at the global scale but also at subcontinental scales of higher latitudes, as water availability was found to be the primary limiting factor also in this extratropical region with summer-warm and dry climate. A narrow zone with a sharp south-to-north switch in the two main diversity constraints seems to constitute the dominant and general pattern of terrestrial diversity across a large part of northern Eurasia, resulting in a subcontinental diversity hotspot of various taxa in this zone. PMID:25090628

Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.

PubMed

Bakal, Gokhan; Talari, Preetham; Kakani, Elijah V; Kavuluru, Ramakanth

2018-06-01

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying different causal relations between biomedical entities is also critical to understand biomedical processes. Generally, natural language processing (NLP) and machine learning are used to predict specific relations between any given pair of entities using the distant supervision approach. To build high accuracy supervised predictive models to predict previously unknown treatment and causative relations between biomedical entities based only on semantic graph pattern features extracted from biomedical knowledge graphs. We used 7000 treats and 2918 causes hand-curated relations from the UMLS Metathesaurus to train and test our models. Our graph pattern features are extracted from simple paths connecting biomedical entities in the SemMedDB graph (based on the well-known SemMedDB database made available by the U.S. National Library of Medicine). Using these graph patterns connecting biomedical entities as features of logistic regression and decision tree models, we computed mean performance measures (precision, recall, F-score) over 100 distinct 80-20% train-test splits of the datasets. For all experiments, we used a positive:negative class imbalance of 1:10 in the test set to model relatively more realistic scenarios. Our models predict treats and causes relations with high F-scores of 99% and 90% respectively. Logistic regression model coefficients also help us identify highly discriminative patterns that have an intuitive interpretation. We are also able to predict some new plausible relations based on false positives that our models scored highly based on our collaborations with two physician co-authors. Finally, our decision tree models are able to retrieve over 50% of treatment relations from a recently created external dataset. We employed semantic graph patterns connecting pairs of candidate biomedical entities in a knowledge graph as features to predict treatment/causative relations between them. We provide what we believe is the first evidence in direct prediction of biomedical relations based on graph features. Our work complements lexical pattern based approaches in that the graph patterns can be used as additional features for weakly supervised relation prediction. Copyright © 2018 Elsevier Inc. All rights reserved.

A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies

PubMed Central

Tompkins, Adrian Mark; Caporaso, Luca; Biondi, Riccardo; Bell, Jean Pierre

2015-01-01

A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001–2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified. PMID:26394392

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

PubMed Central

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Context Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. Objective This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. Method The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. Results The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. Conclusion The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns. PMID:25243670

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex.

PubMed

Tong, Frank; Harrison, Stephenie A; Dewey, John A; Kamitani, Yukiyasu

2012-11-15

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. Copyright © 2012 Elsevier Inc. All rights reserved.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

PubMed Central

Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

2012-01-01

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

Plate Like Convection with Viscous Strain Weakening and Corresponding Surface Deformation Pattern

NASA Astrophysics Data System (ADS)

Fuchs, L.; Becker, T. W.

2017-12-01

How plate tectonic surface motions are generated by mantle convection on Earth and possibly other terrestrial type planets has recently become more readily accessible with fully dynamic convection computations. However, it remains debated how plate-like the behavior in such models truly is, and in particular how the well plate boundary dynamics are captured in models which typically exclude the effects of deformation history and memory. Here, we analyze some of the effects of viscous strain weakening on plate behavior and the interactions between interior convection dynamics and surface deformation patterns. We use the finite element code CitcomCU to model convection in a 3D Cartesian model setup. The models are internally heated, with an Arrhenius-type temperature dependent viscosity including plastic yielding and viscous strain weakening (VSW) and healing (VSWH). VSW can mimic first order features of more complex damage mechanisms such as grain-size dependent rheology. Besides plate diagnostic parameters (Plateness, Mobility, and Toroidal: Poloidal ratio) to analyze the tectonic behavior our models, we also explore how "plate boundaries" link to convective patterns. In a first model series, we analyze general surface deformation patterns without VSW. In the early stages, deformation patterns are clearly co-located with up- and downwelling limbs of convection. Along downwellings strain-rates are high and localized, whereas upwellings tend to lead to broad zones of high deformation. At a more advanced stage, however, the plates' interior is highly deformed due to continuous strain accumulation and resurfaced inherited strain. Including only VSW leads to more localized deformation along downwellings. However, at a more advanced stage plate-like convection fails due an overall weakening of the material. This is prevented including strain healing. Deformation pattern at the surface more closely coincide with the internal convection patterns. The average surface deformation is reduced significantly and mainly governed by the location of the up- and downwellings. VSWH thereby affects plate dynamics due to two main properties: the intensity of weakening with increasing strain and the strain healing rate. As both increase, mobility increases as well and strain becomes more localized at the downwellings.

Fundamental trade-offs generating the worldwide leaf economics spectrum.

PubMed

Shipley, Bill; Lechowicz, Martin J; Wright, Ian; Reich, Peter B

2006-03-01

Recent work has identified a worldwide "economic" spectrum of correlated leaf traits that affects global patterns of nutrient cycling and primary productivity and that is used to calibrate vegetation-climate models. The correlation patterns are displayed by species from the arctic to the tropics and are largely independent of growth form or phylogeny. This generality suggests that unidentified fundamental constraints control the return of photosynthates on investments of nutrients and dry mass in leaves. Using novel graph theoretic methods and structural equation modeling, we show that the relationships among these variables can best be explained by assuming (1) a necessary trade-off between allocation to structural tissues versus liquid phase processes and (2) an evolutionary tradeoff between leaf photosynthetic rates, construction costs, and leaf longevity.

Association of Major Dietary Patterns with General and Abdominal Obesity in Iranian Patients with Type 2 Diabetes Mellitus.

PubMed

Ghane Basiri, Marjan; Sotoudeh, Gity; Djalali, Mahmood; Reza Eshraghian, Mohammad; Noorshahi, Neda; Rafiee, Masoumeh; Nikbazm, Ronak; Karimi, Zeinab; Koohdani, Fariba

2015-01-01

The aim of this study was to identify dietary patterns associated with general and abdominal obesity in type 2 diabetic patients. We included 728 patients (35 - 65 years) with type 2 diabetes mellitus in this cross-sectional study. The usual dietary intake of individuals over 1 year was collected using a validated semi-quantitative food frequency questionnaire. Weight, height, and waist circumference were measured according to standard protocol. The two major dietary patterns identified by factor analysis were healthy and unhealthy dietary patterns. After adjustment for potential confounders, subjects in the highest quintile of the healthy dietary pattern scores had a lower odds ratio for the general obesity when compared to the lowest quintile (OR = 0.45, 95 % CI = 0.26 - 0.79, P for trend = 0.02), while patients in the highest quintile of the unhealthy dietary pattern scores had greater odds for the general obesity (OR = 3.2, 95 % CI = 1.8 - 5.9, P for trend < 0.001). There were no significant associations between major dietary patterns and abdominal obesity, even after adjusting for confounding factors. This study shows that in patients with type 2 diabetes mellitus, a healthy dietary pattern is inversely associated and an unhealthy dietary pattern is directly associated with general obesity.

The advantage of flexible neuronal tunings in neural network models for motor learning

PubMed Central

Marongelli, Ellisha N.; Thoroughman, Kurt A.

2013-01-01

Human motor adaptation to novel environments is often modeled by a basis function network that transforms desired movement properties into estimated forces. This network employs a layer of nodes that have fixed broad tunings that generalize across the input domain. Learning is achieved by updating the weights of these nodes in response to training experience. This conventional model is unable to account for rapid flexibility observed in human spatial generalization during motor adaptation. However, added plasticity in the widths of the basis function tunings can achieve this flexibility, and several neurophysiological experiments have revealed flexibility in tunings of sensorimotor neurons. We found a model, Locally Weighted Projection Regression (LWPR), which uniquely possesses the structure of a basis function network in which both the weights and tuning widths of the nodes are updated incrementally during adaptation. We presented this LWPR model with training functions of different spatial complexities and monitored incremental updates to receptive field widths. An inverse pattern of dependence of receptive field adaptation on experienced error became evident, underlying both a relationship between generalization and complexity, and a unique behavior in which generalization always narrows after a sudden switch in environmental complexity. These results implicate a model that is flexible in both basis function widths and weights, like LWPR, as a viable alternative model for human motor adaptation that can account for previously observed plasticity in spatial generalization. This theory can be tested by using the behaviors observed in our experiments as novel hypotheses in human studies. PMID:23888141

Modeling of Waves, Hydrodynamics and Sediment Transport for Protection of Wetlands at Braddock Bay, New York

DTIC Science & Technology

2015-03-01

entrance were evaluated on their ability to reduce potential impacts of waves and currents on wet- lands. Study results indicated all three proposed...transport de- veloped were used in the evaluation of proposed solutions. The prelimi- nary modeling results helped to assess general sediment pattern...Corps of Engineers (USACE), Buffalo Dis- trict, is conducting a study to evaluate shoreline protection measures for coastal wetlands at Braddock Bay

Allele-sharing models: LOD scores and accurate linkage tests.

PubMed

Kong, A; Cox, N J

1997-11-01

Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested.

Allele-sharing models: LOD scores and accurate linkage tests.

PubMed Central

Kong, A; Cox, N J

1997-01-01

Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested. PMID:9345087

40 CFR 158.1100 - Spray drift data requirements table.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the general use patterns of terrestrial food crop and terrestrial nonfood crop. The aquatic use pattern includes products classified under the general use patterns of aquatic food crop and aquatic... Pattern Terrestrial Food Crop Nonfood Crop Aquatic Food Nonfood Greenhouse Food Crop Nonfood Crop Forestry...

40 CFR 158.1100 - Spray drift data requirements table.

Code of Federal Regulations, 2011 CFR

2011-07-01

... the general use patterns of terrestrial food crop and terrestrial nonfood crop. The aquatic use pattern includes products classified under the general use patterns of aquatic food crop and aquatic... Pattern Terrestrial Food Crop Nonfood Crop Aquatic Food Nonfood Greenhouse Food Crop Nonfood Crop Forestry...

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

PubMed Central

Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

2010-01-01

Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927

Discretization-dependent model for weakly connected excitable media

NASA Astrophysics Data System (ADS)

Arroyo, Pedro André; Alonso, Sergio; Weber dos Santos, Rodrigo

2018-03-01

Pattern formation has been widely observed in extended chemical and biological processes. Although the biochemical systems are highly heterogeneous, homogenized continuum approaches formed by partial differential equations have been employed frequently. Such approaches are usually justified by the difference of scales between the heterogeneities and the characteristic spatial size of the patterns. Under different conditions, for example, under weak coupling, discrete models are more adequate. However, discrete models may be less manageable, for instance, in terms of numerical implementation and mesh generation, than the associated continuum models. Here we study a model to approach discreteness which permits the computer implementation on general unstructured meshes. The model is cast as a partial differential equation but with a parameter that depends not only on heterogeneities sizes, as in the case of quasicontinuum models, but also on the discretization mesh. Therefore, we refer to it as a discretization-dependent model. We validate the approach in a generic excitable media that simulates three different phenomena: the propagation of action membrane potential in cardiac tissue, in myelinated axons of neurons, and concentration waves in chemical microemulsions.

Building functional groups of marine benthic macroinvertebrates on the basis of general community assembly mechanisms

NASA Astrophysics Data System (ADS)

Alexandridis, Nikolaos; Bacher, Cédric; Desroy, Nicolas; Jean, Fred

2017-03-01

The accurate reproduction of the spatial and temporal dynamics of marine benthic biodiversity requires the development of mechanistic models, based on the processes that shape macroinvertebrate communities. The modelled entities should, accordingly, be able to adequately represent the many functional roles that are performed by benthic organisms. With this goal in mind, we applied the emergent group hypothesis (EGH), which assumes functional equivalence within and functional divergence between groups of species. The first step of the grouping involved the selection of 14 biological traits that describe the role of benthic macroinvertebrates in 7 important community assembly mechanisms. A matrix of trait values for the 240 species that occurred in the Rance estuary (Brittany, France) in 1995 formed the basis for a hierarchical classification that generated 20 functional groups, each with its own trait values. The functional groups were first evaluated based on their ability to represent observed patterns of biodiversity. The two main assumptions of the EGH were then tested, by assessing the preservation of niche attributes among the groups and the neutrality of functional differences within them. The generally positive results give us confidence in the ability of the grouping to recreate functional diversity in the Rance estuary. A first look at the emergent groups provides insights into the potential role of community assembly mechanisms in shaping biodiversity patterns. Our next steps include the derivation of general rules of interaction and their incorporation, along with the functional groups, into mechanistic models of benthic biodiversity.

Number-specific and general cognitive markers of preschoolers' math ability profiles.

PubMed

Gray, Sarah A; Reeve, Robert A

2016-07-01

Different number-specific and general cognitive markers have been claimed to underlie preschoolers' math ability. It is unclear, however, whether similar/different cognitive markers, or combinations of them, are associated with different patterns of emerging math abilities (i.e., different patterns of strength and weakness). To examine this question, 103 preschoolers (40-60 months of age) completed six math tasks (count sequence, object counting, give a number, naming numbers, ordinal relations, and arithmetic), three number-specific markers of math ability (dot enumeration, magnitude comparison, and spontaneous focusing on numerosity), and four general markers (working memory, response inhibition, attention, and vocabulary). A three-step latent profile modeling procedure identified five math ability profiles that differed in their patterns of math strengths and weaknesses; specifically, the profiles were characterized by (a) excellent math ability on all math tasks, (b) good arithmetic ability, (c) good math ability but relatively poor count sequence recitation ability, (d) average ability on all math tasks, and (e) poor ability on all math tasks. After controlling for age, only dot enumeration and spontaneous focusing on numerosity were associated with the math ability profiles, whereas vocabulary was also marginally significant, and these markers were differentially associated with different profiles; that is, different cognitive markers were associated with different patterns of strengths and weaknesses in math abilities. Findings are discussed in terms of their implications for the development of math cognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Reaction-diffusion systems and external morphogen gradients: the two-dimensional case, with an application to skeletal pattern formation.

PubMed

Glimm, Tilmann; Zhang, Jianying; Shen, Yun-Qiu; Newman, Stuart A

2012-03-01

We investigate a reaction-diffusion system consisting of an activator and an inhibitor in a two-dimensional domain. There is a morphogen gradient in the domain. The production of the activator depends on the concentration of the morphogen. Mathematically, this leads to reaction-diffusion equations with explicitly space-dependent terms. It is well known that in the absence of an external morphogen, the system can produce either spots or stripes via the Turing bifurcation. We derive first-order expansions for the possible patterns in the presence of an external morphogen and show how both stripes and spots are affected. This work generalizes previous one-dimensional results to two dimensions. Specifically, we consider the quasi-one-dimensional case of a thin rectangular domain and the case of a square domain. We apply the results to a model of skeletal pattern formation in vertebrate limbs. In the framework of reaction-diffusion models, our results suggest a simple explanation for some recent experimental findings in the mouse limb which are much harder to explain in positional-information-type models.

A new way of thinking about complications of prematurity.

PubMed

Moore, Tiffany A; Berger, Ann M; Wilson, Margaret E

2014-01-01

The morbidity and mortality of preterm infants are impacted by their ability to maintain physiologic homeostasis using metabolic, endocrine, and immunologic mechanisms independent of the mother's placenta. Exploring McEwen's allostatic load model in preterm infants provides a new way to understand the altered physiologic processes associated with frequently occurring complications of prematurity such as bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, and retinopathy of prematurity. The purpose of this article is to present a new model to enhance understanding of the altered physiologic processes associated with complications of prematurity. The model of allostatic load and complications of prematurity was derived to explore the relationship between general stress of prematurity and complications of prematurity. The proposed model uses the concepts of general stress of prematurity, allostasis, physiologic response patterns (adaptive-maladaptive), allostatic load, and complications of prematurity. These concepts are defined and theoretical relationships in the proposed model are interpreted using the four maladaptive response patterns of repeated hits, lack of adaptation, prolonged response, and inadequate response. Empirical evidence for cortisol, inflammation, and oxidative stress responses are used to support the theoretical relationships. The proposed model provides a new way of thinking about physiologic dysregulation in preterm infants. The ability to describe and understand complex physiologic mechanisms involved in complications of prematurity is essential for research. Advancing the knowledge of complications of prematurity will advance clinical practice and research and lead to testing of interventions to reduce negative outcomes in preterm infants.

Exclusionary Discipline of Students with Disabilities: Student and School Characteristics Predicting Suspension

ERIC Educational Resources Information Center

Sullivan, Amanda L.; Van Norman, Ethan R.; Klingbeil, David A.

2014-01-01

Given the negative outcomes associated with suspension, scholars and practitioners are concerned with discipline disparities. This study explored patterns and predictors of suspension in a sample of 2,750 students with disabilities in 39 schools in a Midwestern district. Hierarchical generalized linear modeling demonstrated that disability type,…

The Physics of a Gymnastics Flight Element

ERIC Educational Resources Information Center

Contakos, Jonas; Carlton, Les G.; Thompson, Bruce; Suddaby, Rick

2009-01-01

From its inception, performance in the sport of gymnastics has relied on the laws of physics to create movement patterns and static postures that appear almost impossible. In general, gymnastics is physics in motion and can provide an ideal framework for studying basic human modeling techniques and physical principles. Using low-end technology and…

Collaboration as School Reform: Are There Patterns in the Chaos of Planning with Teachers?

ERIC Educational Resources Information Center

Kimmel, Sue C.

2012-01-01

Emphasis on collaboration is a significant thrust in both current school reform and school librarianship. Planning for instruction is generally included in various definitions and models of collaboration. Some research exists about individual planning done in isolation (Warren 2000), but little is known about teachers' planning with other…

Delivery of Education and Training in Oregon's Adult Corrections Institutions. An Analysis of Present and Future Directions.

ERIC Educational Resources Information Center

Northwest Regional Educational Lab., Portland, OR. Education and Work Program.

This report on education and training in Oregon corrections institutions begins with a brief discussion of trends in correctional education and funding patterns. It then examines three general models of corrections education service delivery: educational programming under institutional superintendents, statewide programming facilitated by a state…

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

ERIC Educational Resources Information Center

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

Mining and Modeling Real-World Networks: Patterns, Anomalies, and Tools

ERIC Educational Resources Information Center

Akoglu, Leman

2012-01-01

Large real-world graph (a.k.a network, relational) data are omnipresent, in online media, businesses, science, and the government. Analysis of these massive graphs is crucial, in order to extract descriptive and predictive knowledge with many commercial, medical, and environmental applications. In addition to its general structure, knowing what…

How well does the Rayleigh model describe the E-vector distribution of skylight in clear and cloudy conditions? A full-sky polarimetric study.

PubMed

Suhai, Bence; Horváth, Gábor

2004-09-01

We present the first high-resolution maps of Rayleigh behavior in clear and cloudy sky conditions measured by full-sky imaging polarimetry at the wavelengths of 650 nm (red), 550 nm (green), and 450 nm (blue) versus the solar elevation angle thetas. Our maps display those celestial areas at which the deviation deltaalpha = /alphameas - alphaRyleigh/ is below the threshold alphathres = 5 degrees, where alphameas is the angle of polarization of skylight measured by full-sky imaging polarimetry, and alphaRayleigh is the celestial angle of polarization calculated on the basis of the single-scattering Rayleigh model. From these maps we derived the proportion r of the full sky for which the single-scattering Rayleigh model describes well (with an accuracy of deltaalpha = 5 degrees) the E-vector alignment of skylight. Depending on thetas, r is high for clear skies, especially for low solar elevations (40% < r < 70% for thetas < or = 13 degrees). Depending on the cloud cover and the solar illumination, r decreases more or less under cloudy conditions, but sometimes its value remains remarkably high, especially at low solar elevations (rmax = 69% for thetas = 0 degrees). The proportion r of the sky that follows the Rayleigh model is usually higher for shorter wavelengths under clear as well as cloudy sky conditions. This partly explains why the shorter wavelengths are generally preferred by animals navigating by means of the celestial polarization. We found that the celestial E-vector pattern generally follows the Rayleigh pattern well, which is a fundamental hypothesis in the studies of animal orientation and human navigation (e.g., in aircraft flying near the geomagnetic poles and using a polarization sky compass) with the use of the celestial alpha pattern.

Spin textures on general surfaces of the correlated topological insulator SmB6

NASA Astrophysics Data System (ADS)

Baruselli, Pier Paolo; Vojta, Matthias

2016-05-01

Employing the k .p expansion for a family of tight-binding models for SmB6, we analytically compute topological surface states on a generic (l m n ) surface. We show how the Dirac-cone spin structure depends on model ingredients and on the angle θ between the surface normal and the main crystal axes. We apply the general theory to (001), (110), (111), and (210) surfaces, for which we provide concrete predictions for the spin pattern of surface states which we also compare with tight-binding results. As shown in previous work, the spin pattern on a (001 ) surface can be related to the value of mirror Chern numbers, and we explore the possibility of topological phase transitions between states with different mirror Chern numbers and the associated change of the spin structure of surface states. Such transitions may be accessed by varying either the hybridization between conduction and f electrons or the crystal-field splitting of the low-energy f multiplets, and we compute corresponding phase diagrams. Experimentally, chemical doping is a promising route to realize such transitions.

Generalized run-and-turn motions: From bacteria to Lévy walks

NASA Astrophysics Data System (ADS)

Detcheverry, François

2017-07-01

Swimming bacteria exhibit a repertoire of motility patterns, in which persistent motion is interrupted by turning events. What are the statistical properties of such random walks? If some particular instances have long been studied, the general case where turning times do not follow a Poisson process has remained unsolved. We present a generic extension of the continuous time random walks formalism relying on operators and noncommutative calculus. The approach is first applied to a unimodal model of bacterial motion. We examine the existence of a minimum in velocity correlation function and discuss the maximum of diffusivity at an optimal value of rotational diffusion. The model is then extended to bimodal patterns and includes as particular cases all swimming strategies: run-and-tumble, run-stop, run-reverse and run-reverse-flick. We characterize their velocity correlation functions and investigate how bimodality affects diffusivity. Finally, the wider applicability of the method is illustrated by considering curved trajectories and Lévy walks. Our results are relevant for intermittent motion of living beings, be they swimming micro-organisms or crawling cells.

EXAMINING TATOOINE: ATMOSPHERIC MODELS OF NEPTUNE-LIKE CIRCUMBINARY PLANETS

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

May, E. M.; Rauscher, E.

2016-08-01

Circumbinary planets experience a time-varying irradiation pattern as they orbit their two host stars. In this work, we present the first detailed study of the atmospheric effects of this irradiation pattern on known and hypothetical gaseous circumbinary planets. Using both a one-dimensional energy balance model (EBM) and a three-dimensional general circulation model (GCM), we look at the temperature differences between circumbinary planets and their equivalent single-star cases in order to determine the nature of the atmospheres of these planets. We find that for circumbinary planets on stable orbits around their host stars, temperature differences are on average no more thanmore » 1.0% in the most extreme cases. Based on detailed modeling with the GCM, we find that these temperature differences are not large enough to excite circulation differences between the two cases. We conclude that gaseous circumbinary planets can be treated as their equivalent single-star case in future atmospheric modeling efforts.« less

Bioconvection in spatially extended domains

NASA Astrophysics Data System (ADS)

Karimi, A.; Paul, M. R.

2013-05-01

We numerically explore gyrotactic bioconvection in large spatially extended domains of finite depth using parameter values from available experiments with the unicellular alga Chlamydomonas nivalis. We numerically integrate the three-dimensional, time-dependent continuum model of Pedley [J. Fluid Mech.10.1017/S0022112088002393 195, 223 (1988)] using a high-order, parallel, spectral-element approach. We explore the long-time nonlinear patterns and dynamics found for layers with an aspect ratio of 10 over a range of Rayleigh numbers. Our results yield the pattern wavelength and pattern dynamics which we compare with available theory and experimental measurement. There is good agreement for the pattern wavelength at short times between numerics, experiment, and a linear stability analysis. At long times we find that the general sequence of patterns given by the nonlinear evolution of the governing equations correspond qualitatively to what has been described experimentally. However, at long times the patterns in numerics grow to larger wavelengths, in contrast to what is observed in experiment where the wavelength is found to decrease with time.

The fin-to-limb transition as the re-organization of a Turing pattern

PubMed Central

Onimaru, Koh; Marcon, Luciano; Musy, Marco; Tanaka, Mikiko; Sharpe, James

2016-01-01

A Turing mechanism implemented by BMP, SOX9 and WNT has been proposed to control mouse digit patterning. However, its generality and contribution to the morphological diversity of fins and limbs has not been explored. Here we provide evidence that the skeletal patterning of the catshark Scyliorhinus canicula pectoral fin is likely driven by a deeply conserved Bmp–Sox9–Wnt Turing network. In catshark fins, the distal nodular elements arise from a periodic spot pattern of Sox9 expression, in contrast to the stripe pattern in mouse digit patterning. However, our computer model shows that the Bmp–Sox9–Wnt network with altered spatial modulation can explain the Sox9 expression in catshark fins. Finally, experimental perturbation of Bmp or Wnt signalling in catshark embryos produces skeletal alterations which match in silico predictions. Together, our results suggest that the broad morphological diversity of the distal fin and limb elements arose from the spatial re-organization of a deeply conserved Turing mechanism. PMID:27211489

Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

PubMed Central

Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay

2012-01-01

The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833

Poverty trap formed by the ecology of infectious diseases

PubMed Central

Bonds, Matthew H.; Keenan, Donald C.; Rohani, Pejman; Sachs, Jeffrey D.

2010-01-01

While most of the world has enjoyed exponential economic growth, more than one-sixth of the world is today roughly as poor as their ancestors were many generations ago. Widely accepted general explanations for the persistence of such poverty have been elusive and are needed by the international development community. Building on a well-established model of human infectious diseases, we show how formally integrating simple economic and disease ecology models can naturally give rise to poverty traps, where initial economic and epidemiological conditions determine the long-term trajectory of the health and economic development of a society. This poverty trap may therefore be broken by improving health conditions of the population. More generally, we demonstrate that simple human ecological models can help explain broad patterns of modern economic organization. PMID:20007179

Two-Phase Contiguous Supported Lipid Bilayer Model for Membrane Rafts via Polymer Blotting and Stenciling.

PubMed

Richards, Mark J; Daniel, Susan

2017-02-07

The supported lipid bilayer has been portrayed as a useful model of the cell membrane compatible with many biophysical tools and techniques that demonstrate its appeal in learning about the basic features of the plasma membrane. However, some of its potential has yet to be realized, particularly in the area of bilayer patterning and phase/composition heterogeneity. In this work, we generate contiguous bilayer patterns as a model system that captures the general features of membrane domains and lipid rafts. Micropatterned polymer templates of two types are investigated for generating patterned bilayer formation: polymer blotting and polymer lift-off stenciling. While these approaches have been used previously to create bilayer arrays by corralling bilayers patches with various types of boundaries impenetrable to bilayer diffusion, unique to the methods presented here, there are no physical barriers to diffusion. In this work, interfaces between contiguous lipid phases define the pattern shapes, with continuity between them allowing transfer of membrane-bound biomolecules between the phases. We examine effectors of membrane domain stability including temperature and cholesterol content to investigate domain dynamics. Contiguous patterning of supported bilayers as a model of lipid rafts expands the application of the SLB to an area with current appeal and brings with it a useful toolset for characterization and analysis. These combined tools should be helpful to researchers investigating lipid raft dynamics and function and biomolecule partitioning studies. Additionally, this patterning technique may be useful for applications such as bioseparations that exploit differences in lipid phase partitioning or creation of membranes that bind species like viruses preferentially at lipid phase boundaries, to name a few.

A Novel Modeling Approach for Estimating Patterns of Migration into and out of San Francisco by HIV Status and Race among Men Who Have Sex with Men.

PubMed

Hughes, Alison J; Chen, Yea-Hung; Scheer, Susan; Raymond, H Fisher

2017-06-01

In the early 1980s, men who have sex with men (MSM) in San Francisco were one of the first populations to be affected by the human immunodeficiency virus (HIV) epidemic, and they continue to bear a heavy HIV burden. Once a rapidly fatal disease, survival with HIV improved drastically following the introduction of combination antiretroviral therapy in 1996. As a result, the ability of HIV-positive persons to move into and out of San Francisco has increased due to lengthened survival. Although there is a high level of migration among the general US population and among HIV-positive persons in San Francisco, in- and out-migration patterns of MSM in San Francisco have, to our knowledge, never been described. Understanding migration patterns by HIV serostatus is crucial in determining how migration could influence both HIV transmission dynamics and estimates of the HIV prevalence and incidence. In this article, we describe methods, results, and implications of a novel approach for indirect estimation of in- and out-migration patterns, and consequently population size, of MSM by HIV serostatus and race in San Francisco. The results suggest that the overall MSM population and all the MSM subpopulations studied decreased in size from 2006 to 2014. Further, there were differences in migration patterns by race and by HIV serostatus. The modeling methods outlined can be applied by others to determine how migration patterns contribute to HIV-positive population size and output from these models can be used in a transmission model to better understand how migration can impact HIV transmission.

Local Conjecturing Process in the Solving of Pattern Generalization Problem

ERIC Educational Resources Information Center

Sutarto; Nusantara, Toto; Subanji; Sisworo

2016-01-01

This aim of this study is to describe the process of local conjecturing in generalizing patterns based on Action, Process, Object, Schema (APOS) theory. The subjects were 16 grade 8 students from a junior high school. Data collection used Pattern Generalization Problem (PGP) and interviews. In the first stage, students completed PGP; in the second…

Dietary patterns and cognitive ability among 12- to 13 year-old adolescents in Selangor, Malaysia.

PubMed

Nurliyana, Abdul Razak; Mohd Nasir, Mohd Taib; Zalilah, Mohd Shariff; Rohani, Abdullah

2015-02-01

The present study aimed to identify dietary patterns and determine the relationship between dietary patterns and cognitive ability among 12- to 13 year-old Malay adolescents in the urban areas of Gombak district in Selangor, Malaysia. Data on sociodemographic background were obtained from parents. Height and weight were measured and BMI-for-age was determined. Adolescents were interviewed on their habitual dietary intakes using a semi-quantitative FFQ. Cognitive ability was assessed using the Wechsler Nonverbal Scale of Ability in a one-to-one manner. Dietary patterns were constructed using principal component analysis based on thirty-eight food groups of the semi-quantitative FFQ. Urban secondary public schools in the district of Gombak in Selangor, Malaysia. Malay adolescents aged 12 to 13 years (n 416). The mean general cognitive ability score was 101·8 (sd 12·4). Four major dietary patterns were identified and labelled as 'refined-grain pattern', 'snack-food pattern', 'plant-based food pattern' and 'high-energy food pattern'. These dietary patterns explained 39·1 % of the variance in the habitual dietary intakes of the adolescents. The refined-grain pattern was negatively associated with processing speed, which is a construct of general cognitive ability. The high-energy food pattern was negatively associated with general cognitive ability, perceptual reasoning and processing speed. Monthly household income and parents' educational attainment were positively associated with all of the cognitive measures. In multivariate analysis, only the high-energy food pattern was found to contribute significantly towards general cognitive ability after controlling for socio-economic status. Consumption of foods in the high-energy food pattern contributed towards general cognitive ability after controlling for socio-economic status. However, the contribution was small.

Self-organization principles of intracellular pattern formation.

PubMed

Halatek, J; Brauns, F; Frey, E

2018-05-26

Dynamic patterning of specific proteins is essential for the spatio-temporal regulation of many important intracellular processes in prokaryotes, eukaryotes and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article, we review quantitative models for intracellular Min protein patterns in Escherichia coli , Cdc42 polarization in Saccharomyces cerevisiae and the bipolar PAR protein patterns found in Caenorhabditis elegans By analysing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as 'activators', 'inhibitors' or 'substrate depletion'. Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction-diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Authors.

A general scaling law reveals why the largest animals are not the fastest.

PubMed

Hirt, Myriam R; Jetz, Walter; Rall, Björn C; Brose, Ulrich

2017-08-01

Speed is the fundamental constraint on animal movement, yet there is no general consensus on the determinants of maximum speed itself. Here, we provide a general scaling model of maximum speed with body mass, which holds across locomotion modes, ecosystem types and taxonomic groups. In contrast to traditional power-law scaling, we predict a hump-shaped relationship resulting from a finite acceleration time for animals, which explains why the largest animals are not the fastest. This model is strongly supported by extensive empirical data (474 species, with body masses ranging from 30 μg to 100 tonnes) from terrestrial as well as aquatic ecosystems. Our approach unravels a fundamental constraint on the upper limit of animal movement, thus enabling a better understanding of realized movement patterns in nature and their multifold ecological consequences.

Patterns of Activity in A Global Model of A Solar Active Region

NASA Technical Reports Server (NTRS)

Bradshaw, S. J.; Viall, N. M.

2016-01-01

In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (1) Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. (2) Shorter coronal loops in the core cool more quickly than longer loops at the periphery. (3) All channel pairs show zero time lag when the line of sight passes through coronal loop footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating across active regions. (5) Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.

Is prostate cancer different in black men? Answers from three natural history models

PubMed Central

Tsodikov, Alex; Gulati, Roman; de Carvalho, Tiago M.; Heijnsdijk, Eveline A. M.; Hunter-Merrill, Rachel A.; Mariotto, Angela B.; de Koning, Harry J.; Etzioni, Ruth

2017-01-01

Background Black men in the US have substantially higher prostate cancer incidence rates than the general population. The extent to which the incidence disparity is due to prostate cancer being more prevalent, more aggressive, and/or more frequently diagnosed in black men is unknown. Methods We estimated three independently developed models of prostate cancer natural history in black men and in the general population using an updated reconstruction of PSA screening, based on the National Health Interview Survey in 2005, and prostate cancer incidence from the Surveillance, Epidemiology, and End Results program in 1975–2000. Using the estimated models, we compared prostate cancer natural history in black men and in the general population. Results The models projected that 30–43% (range across models) of black men develop preclinical prostate cancer by age 85 years, a risk that is (relatively) 28–56% higher than in the general population. Among men who have had preclinical disease onset, black men have a similar risk of diagnosis (35–49%) compared with the general population (32–44%), but their risk of progression to metastatic disease by the time of diagnosis is 44–75% higher than in the general population. Conclusions Prostate cancer incidence patterns implicate higher incidence of preclinical disease and higher risk of metastatic progression among black men. The findings suggest screening black men earlier than white men and support further research into the benefit-harm tradeoffs of more aggressive screening policies for black men. PMID:28436011

Trend surface models in the representation and analysis of time factors in cancer mortality.

PubMed

Cislaghi, C; Negri, E; La Vecchia, C; Levi, F

1990-01-01

A method of graphic representation of time factors in cancer mortality is presented, based on different tonalities of grey applied to the surface of the matrix defined by various age-specific rates. It is illustrated using mortality data from cancers of the mouth or pharynx, oesophagus, larynx and lung in Italian and Swiss males. Progressively more complex regression surface equations are defined, on the basis of two independent variables (age and cohort) and a dependent one (each age-specific rate). General patterns of trends were thus identified, showing important similarities in cohort and period effects, but also noticeable differences in time-related factors in mortality from various neoplasms of the upper digestive and respiratory tract. For instance, there were declines in mortality from cancers of the mouth or pharynx in the oldest age groups, whereas rates were appreciably upwards at younger and middle age, particularly in Italy. Likewise, cancers of the oesophagus and, chiefly, of the larynx were substantially increasing, on a cohort basis, in oldest Italian males. Temporal pattern for laryngeal cancer in Italy was similar to that of lung cancer, thus suggesting that (cigarette) smoking has a greater impact on this cancer site as compared with alcohol. However, it is difficult to explain, on this basis alone, the totally diverging pattern for cancer of the larynx (downwards) and of the lung (upwards) observed among older Swiss males. These examples indicate that trend surface models are a useful summary guide to illustrate and understand the general patterns of age, period and cohort effects in cancer mortality.

[Spatial-temporal pattern and obstacle factors of cultivated land ecological security in major grain producing areas of northeast China: a case study in Jilin Province].

PubMed

Zhao, Hong-Bo; Ma, Yan-Ji

2014-02-01

According to the cultivated land ecological security in major grain production areas of Northeast China, this paper selected 48 counties of Jilin Province as the research object. Based on the PSR-EES conceptual framework model, an evaluation index system of cultivated land ecological security was built. By using the improved TOPSIS, Markov chains, GIS spatial analysis and obstacle degree models, the spatial-temporal pattern of cultivated land ecological security and the obstacle factors were analyzed from 1995 to 2011 in Jilin Province. The results indicated that, the composite index of cultivated land ecological security appeared in a rising trend in Jilin Province from 1995 to 2011, and the cultivated land ecological security level changed from being sensitive to being general. There was a pattern of 'Club Convergence' in cultivated land ecological security level in each county and the spatial discrepancy tended to become larger. The 'Polarization' trend of cultivated land ecological security level was obvious. The distributions of sensitive level and critical security level with ribbon patterns tended to be dispersed, the general security level and relative security levels concentrated, and the distributions of security level scattered. The unstable trend of cultivated land ecological security level was more and more obvious. The main obstacle factors that affected the cultivated land ecological security level in Jilin Province were rural net income per capita, economic density, the proportion of environmental protection investment in GDP, degree of machinery cultivation and the comprehensive utilization rate of industrial solid wastes.

Robust hierarchical state-space models reveal diel variation in travel rates of migrating leatherback turtles.

PubMed

Jonsen, Ian D; Myers, Ransom A; James, Michael C

2006-09-01

1. Biological and statistical complexity are features common to most ecological data that hinder our ability to extract meaningful patterns using conventional tools. Recent work on implementing modern statistical methods for analysis of such ecological data has focused primarily on population dynamics but other types of data, such as animal movement pathways obtained from satellite telemetry, can also benefit from the application of modern statistical tools. 2. We develop a robust hierarchical state-space approach for analysis of multiple satellite telemetry pathways obtained via the Argos system. State-space models are time-series methods that allow unobserved states and biological parameters to be estimated from data observed with error. We show that the approach can reveal important patterns in complex, noisy data where conventional methods cannot. 3. Using the largest Atlantic satellite telemetry data set for critically endangered leatherback turtles, we show that the diel pattern in travel rates of these turtles changes over different phases of their migratory cycle. While foraging in northern waters the turtles show similar travel rates during day and night, but on their southward migration to tropical waters travel rates are markedly faster during the day. These patterns are generally consistent with diving data, and may be related to changes in foraging behaviour. Interestingly, individuals that migrate southward to breed generally show higher daytime travel rates than individuals that migrate southward in a non-breeding year. 4. Our approach is extremely flexible and can be applied to many ecological analyses that use complex, sequential data.

Cell-fate specification in the epidermis: a common patterning mechanism in the root and shoot.

PubMed

Schiefelbein, John

2003-02-01

The specification of epidermal hairs in Arabidopsis provides a useful model for the study of pattern formation in plants. Although the distributions of hair cells in the root and shoot appear quite different, recent studies show that pattern formation in each relies on a common cassette of transcriptional regulators. During development in each organ, neighboring cells compete to express regulators that specify the primary cell fate (including WEREWOLF [WER]/GLABRA1 [GL1], GL3/bHLH, TRANSPARENT TESTA GLABRA [TTG], and GL2), as well as those that prevent their neighbors from adopting this fate (including CAPRICE [CPC] and TRIPTYCHON [TRY]). The basic mechanism of lateral inhibition with feedback that has been uncovered by recent studies provides a conceptual framework for understanding how patterns of cell fate in general may be specified during plant development.

Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

NASA Astrophysics Data System (ADS)

Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

2015-03-01

Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

A mathematical model of the chevron-like wave pattern on a weld piece

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

Dowden, J.; Kapadia, P.

1996-12-31

In welding processes in general the surface of a metallic weld displays a chevron-like pattern. Such a pattern is also clearly seen to be present if welding is carried out using a laser beam. In the welding process a laser beam is directed normally on the metal undergoing translation and usually penetrates it to form a keyhole. The keyhole is surrounded by a molten region, the weld pool. Even if a CO{sub 2} laser is used, there are numerous fluctuations and instabilities that occur, so that the keyhole imposes forcing frequencies on the molten weld pool, additional to vibrations attendantmore » on the process of translation. The weld pool in turn responds by supporting a spectrum of waves of different frequencies involving the natural frequency of the weld pool as well as various forcing frequencies. These waves are surface tension-type capillary waves and previous publications have attempted to model their behavior mathematically, although not all aspects of the problem have always been included. The wave pattern that is manifested in the chevron-like pattern seen on the weld piece is, however, not necessarily identical to the wave pattern present in the weld pool. This is because the chevron-like wave pattern forms as a result of several complicating effects that arise as the weld specimen cools on its surface immediately after the weld has been formed. This process involves the waves on the surface of the weld pool freezing to form the chevron-like wave pattern. A feature that is often ignored is the fact that the waves on the weld pool can only be regarded as irrotational if the translation speed is sufficiently low. This paper describes mathematically the formation of the chevron-like wave pattern based on suitable simplifying assumptions to model the process. The mathematical description of the way in which this chevron-like pattern forms is a step toward a more comprehensive understanding of this process.« less

Hydroclimatology of Dual-Peak Annual Cholera Incidence: Insights from a Spatially Explicit Model

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

Cholera incidence in some regions of the Indian subcontinent may exhibit two annual peaks although the main environmental drivers that have been linked to the disease (e.g. sea surface temperature, zooplankton abundance, river discharge) peak once per year during the summer. An empirical hydroclimatological explanation relating cholera transmission to river flows and to the disease spatial spreading has been recently proposed. We specifically support and substantiate mechanistically such hypothesis by means of a spatially explicit model of cholera transmission. Our framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for spatial and temporal annual fluctuations of precipitation and river flows. To single out the single out the hydroclimatologic controls on the prevalence patterns in a non-specific geographical context, we first apply the model to Optimal Channel Networks as a general model of hydrological networks. Moreover, we impose a uniform distribution of population. The model is forced by seasonal environmental drivers, namely precipitation, temperature and chlorophyll concentration in the coastal environment, a proxy for Vibrio cholerae concentration. Our results show that these drivers may suffice to generate dual-peak cholera prevalence patterns for proper combinations of timescales involved in pathogen transport, hydrologic variability and disease unfolding. The model explains the possible occurrence of spatial patterns of cholera incidence characterized by a spring peak confined to coastal areas and a fall peak involving inland regions. We then proceed applying the model to the specific settings of Bay of Bengal accounting for the actual river networks (derived from digital terrain map manipulations), the proper distribution of population (estimated from downscaling of census data based on remotely sensed features) and precipitation patterns. Overall our modeling framework suggests insights on how environmental drivers concert the generation of complex spatiotemporal infections and proposes an explanation for the different cholera patterns (dual or single annual peaks) exhibited by regions that share similar hydroclimatological forcings.

Patterns of impaired oral health-related quality of life dimensions

PubMed Central

John, Mike T.; Rener-Sitar, Ksenija; Baba, Kazuyoshi; Čelebić, Asja; Larsson, Pernilla; Szabo, Gyula; Norton, Wynne E.; Reissmann, Daniel R.

2016-01-01

Background How dental patients are affected by oral conditions can be described with the concept of oral health-related quality of life (OHRQoL). This concept intends to make the patient experience measurable. OHRQoL is multidimensional and Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact were suggested as its four dimensions and consequently four scores are needed for comprehensive OHRQoL assessment. When only the presence of dimensional impact is measured, a pattern of affected OHRQoL dimensions would describe in a simple way how oral conditions’ influence the individual. Objective By determining which patterns of impact on OHRQoL dimensions (Oral Function-Orofacial Pain-Orofacial Appearance-Psychosocial Impact) exist in prosthodontic patients and general population subjects, we aimed to identify in which combinations oral conditions’ functional, painful, aesthetical, and psychosocial impact occurs. Methods Data came from the Dimensions of OHRQoL Project with OHIP-49 data from 6,349 general population subjects and 2,999 prosthodontic patients in the Learning Sample (N=5,173) and the Validation Sample (N=5,022). We hypothesized that all 16 patterns of OHRQoL dimensions should occur in these individuals who suffered mainly from tooth loss, its causes and consequences. A dimension was considered impaired when at least one item in the dimension was affected frequently. Results The 16 possible patterns of impaired OHRQoL dimensions were found in patients and general population subjects in both Learning and Validation Samples. Conclusions In a four-dimensional OHRQoL model consisting of Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact, oral conditions’ impact can occur in any combination of the OHRQoL dimensions. PMID:27027734

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

PubMed Central

Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.

2011-01-01

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710

Mechanisms of macroevolution: polyphagous plasticity in butterfly larvae revealed by RNA-Seq.

PubMed

de la Paz Celorio-Mancera, Maria; Wheat, Christopher W; Vogel, Heiko; Söderlind, Lina; Janz, Niklas; Nylin, Sören

2013-10-01

Transcriptome studies of insect herbivory are still rare, yet studies in model systems have uncovered patterns of transcript regulation that appear to provide insights into how insect herbivores attain polyphagy, such as a general increase in expression breadth and regulation of ribosomal, digestion- and detoxification-related genes. We investigated the potential generality of these emerging patterns, in the Swedish comma, Polygonia c-album, which is a polyphagous, widely-distributed butterfly. Urtica dioica and Ribes uva-crispa are hosts of P. c-album, but Ribes represents a recent evolutionary shift onto a very divergent host. Utilizing the assembled transcriptome for read mapping, we assessed gene expression finding that caterpillar life-history (i.e. 2nd vs. 4th-instar regulation) had a limited influence on gene expression plasticity. In contrast, differential expression in response to host-plant identified genes encoding serine-type endopeptidases, membrane-associated proteins and transporters. Differential regulation of genes involved in nucleic acid binding was also observed suggesting that polyphagy involves large scale transcriptional changes. Additionally, transcripts coding for structural constituents of the cuticle were differentially expressed in caterpillars in response to their diet indicating that the insect cuticle may be a target for plant defence. Our results state that emerging patterns of transcript regulation from model species appear relevant in species when placed in an evolutionary context. © 2013 John Wiley & Sons Ltd.

Using remote sensing environmental data to forecast malaria incidence at a rural district hospital in Western Kenya.

PubMed

Sewe, Maquins Odhiambo; Tozan, Yesim; Ahlm, Clas; Rocklöv, Joacim

2017-06-01

Malaria surveillance data provide opportunity to develop forecasting models. Seasonal variability in environmental factors correlate with malaria transmission, thus the identification of transmission patterns is useful in developing prediction models. However, with changing seasonal transmission patterns, either due to interventions or shifting weather seasons, traditional modelling approaches may not yield adequate predictive skill. Two statistical models,a general additive model (GAM) and GAMBOOST model with boosted regression were contrasted by assessing their predictive accuracy in forecasting malaria admissions at lead times of one to three months. Monthly admission data for children under five years with confirmed malaria at the Siaya district hospital in Western Kenya for the period 2003 to 2013 were used together with satellite derived data on rainfall, average temperature and evapotranspiration(ET). There was a total of 8,476 confirmed malaria admissions. The peak of malaria season changed and malaria admissions reduced overtime. The GAMBOOST model at 1-month lead time had the highest predictive skill during both the training and test periods and thus can be utilized in a malaria early warning system.

“Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data

PubMed Central

Zhang, Min; Davidian, Marie

2008-01-01

Summary A general framework for regression analysis of time-to-event data subject to arbitrary patterns of censoring is proposed. The approach is relevant when the analyst is willing to assume that distributions governing model components that are ordinarily left unspecified in popular semiparametric regression models, such as the baseline hazard function in the proportional hazards model, have densities satisfying mild “smoothness” conditions. Densities are approximated by a truncated series expansion that, for fixed degree of truncation, results in a “parametric” representation, which makes likelihood-based inference coupled with adaptive choice of the degree of truncation, and hence flexibility of the model, computationally and conceptually straightforward with data subject to any pattern of censoring. The formulation allows popular models, such as the proportional hazards, proportional odds, and accelerated failure time models, to be placed in a common framework; provides a principled basis for choosing among them; and renders useful extensions of the models straightforward. The utility and performance of the methods are demonstrated via simulations and by application to data from time-to-event studies. PMID:17970813

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2013-10-01

Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater level dynamics were not adequately reproduced and the predicted spatial patterns of soil saturation did not correspond to the patterns estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a more complex model. Especially high spatial resolution and very detailed process representations at the boundary between the unsaturated and the saturated zone are expected to be crucial. The data needed for such a detailed model are not generally available. The high computational demand and the complex model setup would require more resources than the direct identification of saturated areas in the field. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

How to Compress Sequential Memory Patterns into Periodic Oscillations: General Reduction Rules

PubMed Central

Zhang, Kechen

2017-01-01

A neural network with symmetric reciprocal connections always admits a Lyapunov function, whose minima correspond to the memory states stored in the network. Networks with suitable asymmetric connections can store and retrieve a sequence of memory patterns, but the dynamics of these networks cannot be characterized as readily as that of the symmetric networks due to the lack of established general methods. Here, a reduction method is developed for a class of asymmetric attractor networks that store sequences of activity patterns as associative memories, as in a Hopfield network. The method projects the original activity pattern of the network to a low-dimensional space such that sequential memory retrievals in the original network correspond to periodic oscillations in the reduced system. The reduced system is self-contained and provides quantitative information about the stability and speed of sequential memory retrievals in the original network. The time evolution of the overlaps between the network state and the stored memory patterns can also be determined from extended reduced systems. The reduction procedure can be summarized by a few reduction rules, which are applied to several network models, including coupled networks and networks with time-delayed connections, and the analytical solutions of the reduced systems are confirmed by numerical simulations of the original networks. Finally, a local learning rule that provides an approximation to the connection weights involving the pseudoinverse is also presented. PMID:24877729

How General are Risk Preferences? Choices under Uncertainty in Different Domains*

PubMed Central

Einav, Liran; Finkelstein, Amy; Pascu, Iuliana; Cullen, Mark R.

2011-01-01

We analyze the extent to which individuals’ choices over five employer-provided insurance coverage decisions and one 401(k) investment decision exhibit systematic patterns, as would be implied by a general utility component of risk preferences. We provide evidence consistent with an important domain-general component that operates across all insurance choices. We find a considerably weaker relationship between one's insurance decisions and 401(k) asset allocation, although this relationship appears larger for more “financially sophisticated” individuals. Estimates from a stylized coverage choice model suggest that up to thirty percent of our sample makes choices that may be consistent across all six domains. PMID:24634517

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

PubMed Central

van der Post, Daniel J.; Semmann, Dirk

2011-01-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

PubMed Central

Namboodiri, Vijay Mohan K.; Levy, Joshua M.; Mihalas, Stefan; Sims, David W.; Hussain Shuler, Marshall G.

2016-01-01

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers. PMID:27385831

Tuning a climate model using nudging to reanalysis.

NASA Astrophysics Data System (ADS)

Cheedela, S. K.; Mapes, B. E.

2014-12-01

Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.

Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar, Antelope Valley, Mojave Desert, California

USGS Publications Warehouse

Galloway, D.L.; Hudnut, K.W.; Ingebritsen, S.E.; Phillips, S.P.; Peltzer, G.; Rogez, F.; Rosen, P.A.

1998-01-01

Interferometric synthetic aperture radar (InSAR) has great potential to detect and quantify land subsidence caused by aquifer system compaction. InSAR maps with high spatial detail and resolution of range displacement (±10 mm in change of land surface elevation) were developed for a groundwater basin (∼103 km2) in Antelope Valley, California, using radar data collected from the ERS-1 satellite. These data allow comprehensive comparison between recent (1993–1995) subsidence patterns and those detected historically (1926–1992) by more traditional methods. The changed subsidence patterns are generally compatible with recent shifts in land and water use. The InSAR-detected patterns are generally consistent with predictions based on a coupled model of groundwater flow and aquifer system compaction. The minor inconsistencies may reflect our imperfect knowledge of the distribution and properties of compressible sediments. When used in conjunction with coincident measurements of groundwater levels and other geologic information, InSAR data may be useful for constraining parameter estimates in simulations of aquifer system compaction.

Activities, self-referent memory beliefs, and cognitive performance: evidence for direct and mediated relations.

PubMed

Jopp, Daniela; Hertzog, Christopher

2007-12-01

In this study, the authors investigated the role of activities and self-referent memory beliefs for cognitive performance in a life-span sample. A factor analysis identified 8 activity factors, including Developmental Activities, Experiential Activities, Social Activities, Physical Activities, Technology Use, Watching Television, Games, and Crafts. A second-order general activity factor was significantly related to a general factor of cognitive function as defined by ability tests. Structural regression models suggested that prediction of cognition by activity level was partially mediated by memory beliefs, controlling for age, education, health, and depressive affect. Models adding paths from general and specific activities to aspects of crystallized intelligence suggested additional unique predictive effects for some activities. In alternative models, nonsignificant effects of beliefs on activities were detected when cognition predicted both variables, consistent with the hypothesis that beliefs derive from monitoring cognition and have no influence on activity patterns. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2014-09-01

Spatially distributed models are popular tools in hydrology claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for inputs of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography and artificial drainage. We translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to observed groundwater levels and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the the groundwater level predictions were not accurate enough to be used for the prediction of saturated areas. Groundwater level dynamics were not adequately reproduced and the predicted spatial saturation patterns did not correspond to those estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a model that better represents processes at the boundary between the unsaturated and the saturated zone. However, data needed for such a more detailed model are not generally available. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

A new computational growth model for sea urchin skeletons.

PubMed

Zachos, Louis G

2009-08-07

A new computational model has been developed to simulate growth of regular sea urchin skeletons. The model incorporates the processes of plate addition and individual plate growth into a composite model of whole-body (somatic) growth. A simple developmental model based on hypothetical morphogens underlies the assumptions used to define the simulated growth processes. The data model is based on a Delaunay triangulation of plate growth center points, using the dual Voronoi polygons to define plate topologies. A spherical frame of reference is used for growth calculations, with affine deformation of the sphere (based on a Young-Laplace membrane model) to result in an urchin-like three-dimensional form. The model verifies that the patterns of coronal plates in general meet the criteria of Voronoi polygonalization, that a morphogen/threshold inhibition model for plate addition results in the alternating plate addition pattern characteristic of sea urchins, and that application of the Bertalanffy growth model to individual plates results in simulated somatic growth that approximates that seen in living urchins. The model suggests avenues of research that could explain some of the distinctions between modern sea urchins and the much more disparate groups of forms that characterized the Paleozoic Era.

Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila, Philippines.

PubMed

Carvajal, Thaddeus M; Viacrusis, Katherine M; Hernandez, Lara Fides T; Ho, Howell T; Amalin, Divina M; Watanabe, Kozo

2018-04-17

Several studies have applied ecological factors such as meteorological variables to develop models and accurately predict the temporal pattern of dengue incidence or occurrence. With the vast amount of studies that investigated this premise, the modeling approaches differ from each study and only use a single statistical technique. It raises the question of whether which technique would be robust and reliable. Hence, our study aims to compare the predictive accuracy of the temporal pattern of Dengue incidence in Metropolitan Manila as influenced by meteorological factors from four modeling techniques, (a) General Additive Modeling, (b) Seasonal Autoregressive Integrated Moving Average with exogenous variables (c) Random Forest and (d) Gradient Boosting. Dengue incidence and meteorological data (flood, precipitation, temperature, southern oscillation index, relative humidity, wind speed and direction) of Metropolitan Manila from January 1, 2009 - December 31, 2013 were obtained from respective government agencies. Two types of datasets were used in the analysis; observed meteorological factors (MF) and its corresponding delayed or lagged effect (LG). After which, these datasets were subjected to the four modeling techniques. The predictive accuracy and variable importance of each modeling technique were calculated and evaluated. Among the statistical modeling techniques, Random Forest showed the best predictive accuracy. Moreover, the delayed or lag effects of the meteorological variables was shown to be the best dataset to use for such purpose. Thus, the model of Random Forest with delayed meteorological effects (RF-LG) was deemed the best among all assessed models. Relative humidity was shown to be the top-most important meteorological factor in the best model. The study exhibited that there are indeed different predictive outcomes generated from each statistical modeling technique and it further revealed that the Random forest model with delayed meteorological effects to be the best in predicting the temporal pattern of Dengue incidence in Metropolitan Manila. It is also noteworthy that the study also identified relative humidity as an important meteorological factor along with rainfall and temperature that can influence this temporal pattern.

Contemporary Model Fidelity over the Maritime Continent: Examination of the Diurnal Cycle, Synoptic, Intraseasonal and Seasonal Variability

NASA Astrophysics Data System (ADS)

Baranowski, D.; Waliser, D. E.; Jiang, X.

2016-12-01

One of the key challenges in subseasonal weather forecasting is the fidelity in representing the propagation of the Madden-Julian Oscillation (MJO) across the Maritime Continent (MC). In reality both propagating and non-propagating MJO events are observed, but in numerical forecast the latter group largely dominates. For this study, comprehensive model performances are evaluated using metrics that utilize the mean precipitation pattern and the amplitude and phase of the diurnal cycle, with a particular focus on the linkage between a model's local MC variability and its fidelity in representing propagation of the MJO and equatorial Kelvin waves across the MC. Subseasonal to seasonal variability of mean precipitation and its diurnal cycle in 20 year long climate simulations from over 20 general circulation models (GCMs) is examined to benchmark model performance. Our results show that many models struggle to represent the precipitation pattern over complex Maritime Continent terrain. Many models show negative biases of mean precipitation and amplitude of its diurnal cycle; these biases are often larger over land than over ocean. Furthermore, only a handful of models realistically represent the spatial variability of the phase of the diurnal cycle of precipitation. Models tend to correctly simulate the timing of the diurnal maximum of precipitation over ocean during local solar time morning, but fail to acknowledge influence of the land, with the timing of the maximum of precipitation there occurring, unrealistically, at the same time as over ocean. The day-to-day and seasonal variability of the mean precipitation follows observed patterns, but is often unrealistic for the diurnal cycle amplitude. The intraseasonal variability of the amplitude of the diurnal cycle of precipitation is mainly driven by model's ability (or lack of) to produce eastward propagating MJO-like signal. Our results show that many models tend to decrease apparent air-sea contrast in the mean precipitation and diurnal cycle of precipitation patterns over the Maritime Continent. As a result, the complexity of those patterns is heavily smoothed, to such an extent in some models that the Maritime Continent features and imprint is almost unrecognizable relative to the eastern Indian Ocean or Western Pacific.

Settlement patterns, GIS, remote sensing, and the late prehistory of the Black Prairie in east central Mississippi

NASA Technical Reports Server (NTRS)

Johnson, Jay K.

1991-01-01

Data recovered as the result of a recent field project designed to test a model of the distribution of protohistoric settlement in an unusual physiographic zone in eastern Mississippi are examined using GIS based techniques to manipulate soil and stream distance information. Significant patterning is derived. The generally thin soils and uniform substratum of the Black Prairie in combination with a distinctive settlement pattern offer a promising opportunity for the search for site specific characteristics within airborne imagery. Landsat TM data provide information on modern ground cover which is used as a mask to select areas in which a multivariate search for archaeological site signatures within a TIMS image is most likely to prove fruitful.

Effect of triangular element orientation on finite element solutions of the Helmholtz equation

NASA Technical Reports Server (NTRS)

Baumeister, K. J.

1986-01-01

The Galerkin finite element solutions for the scalar homogeneous Helmholtz equation are presented for no reflection, hard wall, and potential relief exit terminations with a variety of triangular element orientations. For this group of problems, the correlation between the accuracy of the solution and the orientation of the linear triangle is examined. Nonsymmetric element patterns are found to give generally poor results in the model problems investigated, particularly for cases where standing waves exist. For a fixed number of vertical elements, the results showed that symmetric element patterns give much better agreement with corresponding exact analytical results. In laminated wave guide application, the symmetric pyramid pattern is convenient to use and is shown to give excellent results.

Naval Health Research Center (NHRC) Report for the Calendar Year 1981.

DTIC Science & Technology

1981-01-01

r, liminary study on growth patterns of Shigella. The Abbott MS-2 Research Model %%as used to show that of 35 cultures studied 5 distinctive growth...vaccination system may provide a suitabl( model for control of ceretrospinal meningitis epidemics in the rural areas of many countries. 81-5 KOILB, D F...rates among Marine Corps basic training platoons suggested that a general factor such as emergent social climate within the platoons might affect

Reactive solute transport in acidic streams

USGS Publications Warehouse

Broshears, R.E.

1996-01-01

Spatial and temporal profiles of Ph and concentrations of toxic metals in streams affected by acid mine drainage are the result of the interplay of physical and biogeochemical processes. This paper describes a reactive solute transport model that provides a physically and thermodynamically quantitative interpretation of these profiles. The model combines a transport module that includes advection-dispersion and transient storage with a geochemical speciation module based on MINTEQA2. Input to the model includes stream hydrologic properties derived from tracer-dilution experiments, headwater and lateral inflow concentrations analyzed in field samples, and a thermodynamic database. Simulations reproduced the general features of steady-state patterns of observed pH and concentrations of aluminum and sulfate in St. Kevin Gulch, an acid mine drainage stream near Leadville, Colorado. These patterns were altered temporarily by injection of sodium carbonate into the stream. A transient simulation reproduced the observed effects of the base injection.

Improved GART neural network model for pattern classification and rule extraction with application to power systems.

PubMed

Yap, Keem Siah; Lim, Chee Peng; Au, Mau Teng

2011-12-01

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

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

Wang, Jiali; Han, Yuefeng; Stein, Michael L.

2016-02-10

The Weather Research and Forecast (WRF) model downscaling skill in extreme maximum daily temperature is evaluated by using the generalized extreme value (GEV) distribution. While the GEV distribution has been used extensively in climatology and meteorology for estimating probabilities of extreme events, accurately estimating GEV parameters based on data from a single pixel can be difficult, even with fairly long data records. This work proposes a simple method assuming that the shape parameter, the most difficult of the three parameters to estimate, does not vary over a relatively large region. This approach is applied to evaluate 31-year WRF-downscaled extreme maximummore » temperature through comparison with North American Regional Reanalysis (NARR) data. Uncertainty in GEV parameter estimates and the statistical significance in the differences of estimates between WRF and NARR are accounted for by conducting bootstrap resampling. Despite certain biases over parts of the United States, overall, WRF shows good agreement with NARR in the spatial pattern and magnitudes of GEV parameter estimates. Both WRF and NARR show a significant increase in extreme maximum temperature over the southern Great Plains and southeastern United States in January and over the western United States in July. The GEV model shows clear benefits from the regionally constant shape parameter assumption, for example, leading to estimates of the location and scale parameters of the model that show coherent spatial patterns.« less

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

Characteristics of Quasi-Biennial Oscillation simulation in the Meteorological Research Institute earth system model

NASA Astrophysics Data System (ADS)

Yoshida, K.; Naoe, H.

2016-12-01

Whether climate models drive Quasi-Biennial Oscillation (QBO) appropriately is important to assess QBO impact on climate change such as global warming and solar related variation. However, there were few models generating QBO in the Coupled Model Intercomparison Project Phase 5 (CMIP5). This study focuses on dynamical structure of the QBO and its sensitivity to background wind pattern and model configuration. We present preliminary results of experiments designed by "Towards Improving the QBO in Global Climate Models (QBOi)", which is derived from the Stratosphere-troposphere processes and their role in climate (SPARC), in the Meteorological Research Institute earth system model, MRI-ESM2. The simulations were performed in present-day climate condition, repeated annual cycle condition with various CO2 level and sea surface temperatures, and QBO hindcast. In the present climate simulation, zonal wind in the equatorial stratosphere generally exhibits realistic behavior of the QBO. Equatorial zonal wind variability associated with QBO is overestimated in upper stratosphere and underestimated in lower stratosphere. In the MRI-ESM2, the QBO behavior is mainly driven by gravity wave drag parametrization (GWDP) introduced in Hines (1997). Comparing to reanalyses, shortage of resolved wave forcing is found especially in equatorial lower stratosphere. These discrepancies can be attributed to difference in wave forcing, background wind pattern and model configuration. We intend to show results of additional sensitivity experiments to examine how model configuration and background wind pattern affect resolved wave source, wave propagation characteristics, and QBO behavior.

Stochastic and deterministic model of microbial heat inactivation.

PubMed

Corradini, Maria G; Normand, Mark D; Peleg, Micha

2010-03-01

Microbial inactivation is described by a model based on the changing survival probabilities of individual cells or spores. It is presented in a stochastic and discrete form for small groups, and as a continuous deterministic model for larger populations. If the underlying mortality probability function remains constant throughout the treatment, the model generates first-order ("log-linear") inactivation kinetics. Otherwise, it produces survival patterns that include Weibullian ("power-law") with upward or downward concavity, tailing with a residual survival level, complete elimination, flat "shoulder" with linear or curvilinear continuation, and sigmoid curves. In both forms, the same algorithm or model equation applies to isothermal and dynamic heat treatments alike. Constructing the model does not require assuming a kinetic order or knowledge of the inactivation mechanism. The general features of its underlying mortality probability function can be deduced from the experimental survival curve's shape. Once identified, the function's coefficients, the survival parameters, can be estimated directly from the experimental survival ratios by regression. The model is testable in principle but matching the estimated mortality or inactivation probabilities with those of the actual cells or spores can be a technical challenge. The model is not intended to replace current models to calculate sterility. Its main value, apart from connecting the various inactivation patterns to underlying probabilities at the cellular level, might be in simulating the irregular survival patterns of small groups of cells and spores. In principle, it can also be used for nonthermal methods of microbial inactivation and their combination with heat.

Patient communication pattern scale: psychometric characteristics.

PubMed

Ilan, Sara; Carmel, Sara

2016-08-01

In western societies, a shared decision-making model for doctor-patient relationships calling for open and collaborative communication is recommended. Research focuses mainly on the doctor's communication patterns, while research on patient communication patterns is rare. The purpose of this study was to develop a tool for evaluating patient's communication patterns - the Patient Communication Pattern Scale (PCPS). Interviews based on structured questionnaires were conducted with 251 cancer patients. In addition to the 14-item PCPS, the questionnaire included questions regarding education, religiosity and desirability of control in general and over one's own health in particular, for validating the scale. The PCPS was found to be a valid and reliable tool for evaluating patients' communication patterns. Confirmatory factor analysis supported the PCPS designed structure of five facets: (1) Information, (2) Clarification, (3) Initiation, (4) Preferences and (5) Emotions. The PCPS is a reliable scale for evaluating patient communication patterns. The use of this scale can assist in promoting related research and in developing interventions for enhancing open and collaborative doctor-patient communication. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Emergence of a complex and stable network in a model ecosystem with extinction and mutation.

PubMed

Tokita, Kei; Yasutomi, Ayumu

2003-03-01

We propose a minimal model of the dynamics of diversity-replicator equations with extinction, invasion and mutation. We numerically study the behavior of this simple model and show that it displays completely different behavior from the conventional replicator equation and the generalized Lotka-Volterra equation. We reach several significant conclusions as follows: (1) a complex ecosystem can emerge when mutants with respect to species-specific interaction are introduced; (2) such an ecosystem possesses strong resistance to invasion; (3) a typical fixation process of mutants is realized through the rapid growth of a group of mutualistic mutants with higher fitness than majority species; (4) a hierarchical taxonomic structure (like family-genus-species) emerges; and (5) the relative abundance of species exhibits a typical pattern widely observed in nature. Several implications of these results are discussed in connection with the relationship of the present model to the generalized Lotka-Volterra equation.

The "bear" essentials: actualistic research on Ursus arctos arctos in the Spanish Pyrenees and its implications for paleontology and archaeology.

PubMed

Arilla, Maite; Rosell, Jordi; Blasco, Ruth; Domínguez-Rodrigo, Manuel; Pickering, Travis Rayne

2014-01-01

Neotaphonomic studies of large carnivores are used to create models in order to explain the formation of terrestrial vertebrate fossil faunas. The research reported here adds to the growing body of knowledge on the taphonomic consequences of large carnivore behavior in temperate habitats and has important implications for paleontology and archaeology. Using photo- and videotrap data, we were able to describe the consumption of 17 ungulate carcasses by wild brown bears (Ursus arctos arctos) ranging the Spanish Pyrenees. Further, we analyzed the taphonomic impact of these feeding bouts on the bones recovered from those carcasses. The general sequence of consumption that we charted starts with separation of a carcass's trunk; viscera are generally eaten first, followed by musculature of the humerus and femur. Long limb bones are not broken open for marrow extraction. Bears did not transport carcasses or carcass parts from points of feeding and did not disperse bones appreciably (if at all) from their anatomical positions. The general pattern of damage that resulted from bear feeding includes fracturing, peeling, crenulation, tooth pitting and scoring of axial and girdle elements and furrowing of the upper long limb bones. As predicted from observational data, the taphonomic consequences of bear feeding resemble those of other non-durophagus carnivores, such as felids, and are distinct from those of durophagus carnivores, such as hyenids. Our results have paleontological and archaeological relevance. Specifically, they may prove useful in building analogical models for interpreting the formation of fossil faunas for which bears are suspected bone accumulators and/or modifiers. More generally, our comparative statistical analyses draw precise quantitative distinctions between bone damage patterns imparted respectively by durophagus (modelled here primarily by spotted hyenas [Crocuta crocuta] and wolves [Canis lupus]) and non-durophagus (modelled here by brown bears and lions [Panthera leo]) carnivorans.

The “Bear” Essentials: Actualistic Research on Ursus arctos arctos in the Spanish Pyrenees and Its Implications for Paleontology and Archaeology

PubMed Central

Arilla, Maite; Rosell, Jordi; Blasco, Ruth; Domínguez-Rodrigo, Manuel; Pickering, Travis Rayne

2014-01-01

Neotaphonomic studies of large carnivores are used to create models in order to explain the formation of terrestrial vertebrate fossil faunas. The research reported here adds to the growing body of knowledge on the taphonomic consequences of large carnivore behavior in temperate habitats and has important implications for paleontology and archaeology. Using photo- and videotrap data, we were able to describe the consumption of 17 ungulate carcasses by wild brown bears (Ursus arctos arctos) ranging the Spanish Pyrenees. Further, we analyzed the taphonomic impact of these feeding bouts on the bones recovered from those carcasses. The general sequence of consumption that we charted starts with separation of a carcass’s trunk; viscera are generally eaten first, followed by musculature of the humerus and femur. Long limb bones are not broken open for marrow extraction. Bears did not transport carcasses or carcass parts from points of feeding and did not disperse bones appreciably (if at all) from their anatomical positions. The general pattern of damage that resulted from bear feeding includes fracturing, peeling, crenulation, tooth pitting and scoring of axial and girdle elements and furrowing of the upper long limb bones. As predicted from observational data, the taphonomic consequences of bear feeding resemble those of other non-durophagus carnivores, such as felids, and are distinct from those of durophagus carnivores, such as hyenids. Our results have paleontological and archaeological relevance. Specifically, they may prove useful in building analogical models for interpreting the formation of fossil faunas for which bears are suspected bone accumulators and/or modifiers. More generally, our comparative statistical analyses draw precise quantitative distinctions between bone damage patterns imparted respectively by durophagus (modelled here primarily by spotted hyenas [Crocuta crocuta] and wolves [Canis lupus]) and non-durophagus (modelled here by brown bears and lions [Panthera leo]) carnivorans. PMID:25029167

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

The El Nino-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with Coupled General Circulation Models (CGCMs) to investigate how regional precipitation in the 21st century may be affected by changes in both ENSO-driven precipitation variability and slowly-evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of 20th century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in 21st century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with 20th century observations and more stationary during the 21st century. Finally, the model-predicted 21st century rainfall response to cENSO is decomposed into the sum of three terms: 1) the 21st century change in the mean state of precipitation; 2) the historical precipitation response to the cENSO pattern; and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Developmental stage related patterns of codon usage and genomic GC content: searching for evolutionary fingerprints with models of stem cell differentiation

PubMed Central

2007-01-01

Background The usage of synonymous codons shows considerable variation among mammalian genes. How and why this usage is non-random are fundamental biological questions and remain controversial. It is also important to explore whether mammalian genes that are selectively expressed at different developmental stages bear different molecular features. Results In two models of mouse stem cell differentiation, we established correlations between codon usage and the patterns of gene expression. We found that the optimal codons exhibited variation (AT- or GC-ending codons) in different cell types within the developmental hierarchy. We also found that genes that were enriched (developmental-pivotal genes) or specifically expressed (developmental-specific genes) at different developmental stages had different patterns of codon usage and local genomic GC (GCg) content. Moreover, at the same developmental stage, developmental-specific genes generally used more GC-ending codons and had higher GCg content compared with developmental-pivotal genes. Further analyses suggest that the model of translational selection might be consistent with the developmental stage-related patterns of codon usage, especially for the AT-ending optimal codons. In addition, our data show that after human-mouse divergence, the influence of selective constraints is still detectable. Conclusion Our findings suggest that developmental stage-related patterns of gene expression are correlated with codon usage (GC3) and GCg content in stem cell hierarchies. Moreover, this paper provides evidence for the influence of natural selection at synonymous sites in the mouse genome and novel clues for linking the molecular features of genes to their patterns of expression during mammalian ontogenesis. PMID:17349061

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Clustering of health behaviours in adult survivors of childhood cancer and the general population.

PubMed

Rebholz, C E; Rueegg, C S; Michel, G; Ammann, R A; von der Weid, N X; Kuehni, C E; Spycher, B D

2012-07-10

Little is known about engagement in multiple health behaviours in childhood cancer survivors. Using latent class analysis, we identified health behaviour patterns in 835 adult survivors of childhood cancer (age 20-35 years) and 1670 age- and sex-matched controls from the general population. Behaviour groups were determined from replies to questions on smoking, drinking, cannabis use, sporting activities, diet, sun protection and skin examination. The model identified four health behaviour patterns: 'risk-avoidance', with a generally healthy behaviour; 'moderate drinking', with higher levels of sporting activities, but moderate alcohol-consumption; 'risk-taking', engaging in several risk behaviours; and 'smoking', smoking but not drinking. Similar proportions of survivors and controls fell into the 'risk-avoiding' (42% vs 44%) and the 'risk-taking' cluster (14% vs 12%), but more survivors were in the 'moderate drinking' (39% vs 28%) and fewer in the 'smoking' cluster (5% vs 16%). Determinants of health behaviour clusters were gender, migration background, income and therapy. A comparable proportion of childhood cancer survivors as in the general population engage in multiple health-compromising behaviours. Because of increased vulnerability of survivors, multiple risk behaviours should be addressed in targeted health interventions.

Generalized Feature Extraction for Wrist Pulse Analysis: From 1-D Time Series to 2-D Matrix.

PubMed

Dimin Wang; Zhang, David; Guangming Lu

2017-07-01

Traditional Chinese pulse diagnosis, known as an empirical science, depends on the subjective experience. Inconsistent diagnostic results may be obtained among different practitioners. A scientific way of studying the pulse should be to analyze the objectified wrist pulse waveforms. In recent years, many pulse acquisition platforms have been developed with the advances in sensor and computer technology. And the pulse diagnosis using pattern recognition theories is also increasingly attracting attentions. Though many literatures on pulse feature extraction have been published, they just handle the pulse signals as simple 1-D time series and ignore the information within the class. This paper presents a generalized method of pulse feature extraction, extending the feature dimension from 1-D time series to 2-D matrix. The conventional wrist pulse features correspond to a particular case of the generalized models. The proposed method is validated through pattern classification on actual pulse records. Both quantitative and qualitative results relative to the 1-D pulse features are given through diabetes diagnosis. The experimental results show that the generalized 2-D matrix feature is effective in extracting both the periodic and nonperiodic information. And it is practical for wrist pulse analysis.

Complexity in language learning and treatment.

PubMed

Thompson, Cynthia K

2007-02-01

To introduce a Clinical Forum focused on the Complexity Account of Treatment Efficacy (C. K. Thompson, L. P. Shapiro, S. Kiran, & J. Sobecks, 2003), a counterintuitive but effective approach for treating language disorders. This approach espouses training complex structures to promote generalized improvement of simpler, linguistically related structures. Three articles are included, addressing complexity in treatment of phonology, lexical-semantics, and syntax. Complexity hierarchies based on models of normal language representation and processing are discussed in each language domain. In addition, each article presents single-subject controlled experimental studies examining the complexity effect. By counterbalancing treatment of complex and simple structures across participants, acquisition and generalization patterns are examined as they emerge. In all language domains, cascading generalization occurs from more to less complex structures; however, the opposite pattern is rarely seen. The results are robust, with replication within and across participants. The construct of complexity appears to be a general principle that is relevant to treating a range of language disorders in both children and adults. While challenging the long-standing clinical notion that treatment should begin with simple structures, mounting evidence points toward the facilitative effects of using more complex structures as a starting point for treatment.

Failure to recall.

PubMed

Laming, Donald

2009-01-01

Mathematical analysis shows that if the pattern of rehearsal in free-recall experiments (of necessity, the pattern observed when participants rehearse aloud) be continued without any further interruption by stimuli (as happens during recall), it terminates with the retrieval of the same 1 word over and over again. Such a terminal state is commonly reached before some of the words in the list have been retrieved even once; those words are not recalled. The 1 minute frequently allowed for recall in free-recall experiments is ample time for retrieval to seize up in this way. The author proposes a model that represents the essential features of the pattern of rehearsal; validates that model by reference to the overt rehearsal data from B. B. Murdock, Jr., and J. Metcalfe (1978) and the recall data from B. B. Murdock, Jr., and R. Okada (1970); demonstrates the long-term properties of continued sequences of retrievals and, also, a fundamental relation linking recall to the total time of presentation; and, finally, compares failure to recall in free-recall experiments with forgetting in general.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Modeling epigenome folding: formation and dynamics of topologically associated chromatin domains

PubMed Central

Jost, Daniel; Carrivain, Pascal; Cavalli, Giacomo; Vaillant, Cédric

2014-01-01

Genomes of eukaryotes are partitioned into domains of functionally distinct chromatin states. These domains are stably inherited across many cell generations and can be remodeled in response to developmental and external cues, hence contributing to the robustness and plasticity of expression patterns and cell phenotypes. Remarkably, recent studies indicate that these 1D epigenomic domains tend to fold into 3D topologically associated domains forming specialized nuclear chromatin compartments. However, the general mechanisms behind such compartmentalization including the contribution of epigenetic regulation remain unclear. Here, we address the question of the coupling between chromatin folding and epigenome. Using polymer physics, we analyze the properties of a block copolymer model that accounts for local epigenomic information. Considering copolymers build from the epigenomic landscape of Drosophila, we observe a very good agreement with the folding patterns observed in chromosome conformation capture experiments. Moreover, this model provides a physical basis for the existence of multistability in epigenome folding at sub-chromosomal scale. We show how experiments are fully consistent with multistable conformations where topologically associated domains of the same epigenomic state interact dynamically with each other. Our approach provides a general framework to improve our understanding of chromatin folding during cell cycle and differentiation and its relation to epigenetics. PMID:25092923

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

NASA Astrophysics Data System (ADS)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Applying the Technology Acceptance Model and flow theory to Cyworld user behavior: implication of the Web2.0 user acceptance.

PubMed

Shin, Dong-Hee; Kim, Won-Yong; Kim, Won-Young

2008-06-01

This study explores attitudinal and behavioral patterns when using Cyworld by adopting an expanded Technology Acceptance Model (TAM). A model for Cyworld acceptance is used to examine how various factors modified from the TAM influence acceptance and its antecedents. This model is examined through an empirical study involving Cyworld users using structural equation modeling techniques. The model shows reasonably good measurement properties and the constructs are validated. The results not only confirm the model but also reveal general factors applicable to Web2.0. A set of constructs in the model can be the Web2.0-specific factors, playing as enhancing factor to attitudes and intention.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Zonal flow as pattern formation

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

Parker, Jeffrey B.; Krommes, John A.

2013-10-15

Zonal flows are well known to arise spontaneously out of turbulence. We show that for statistically averaged equations of the stochastically forced generalized Hasegawa-Mima model, steady-state zonal flows, and inhomogeneous turbulence fit into the framework of pattern formation. There are many implications. First, the wavelength of the zonal flows is not unique. Indeed, in an idealized, infinite system, any wavelength within a certain continuous band corresponds to a solution. Second, of these wavelengths, only those within a smaller subband are linearly stable. Unstable wavelengths must evolve to reach a stable wavelength; this process manifests as merging jets.

A comprehensive model of food addiction in patients with binge-eating symptomatology: The essential role of negative urgency.

PubMed

Wolz, Ines; Granero, Roser; Fernández-Aranda, Fernando

2017-04-01

Food addiction has been widely researched in past years. However, there is a debate on the mechanisms underlying addictive eating and a better understanding of the processes associated to these behaviors is needed. Previous studies have found characteristic psychological correlates of food addiction, such as high negative urgency, emotion regulation difficulties and low self-directedness, in different samples of adults with addictive eating patterns. Still, it seems difficult to disentangle effects independent from general eating disorder psychopathology. Therefore, this study aimed to test a comprehensive model under control of eating disorder severity, in order to find independent predictors of food addiction. 315 patients with eating disorder diagnoses on the binge-eating spectrum were assessed in personality, emotion regulation, negative urgency, eating disorder symptomatology, and food addiction by self-report. Hypothesis-driven structural equation modeling was conducted to test the comprehensive model. The only independent predictor found for food addiction was negative urgency, while self-directedness and emotion regulation predicted negative urgency and were highly related to eating disorder symptomatology, but not to food addiction. Altogether the model suggests that low self-directedness and difficulties in emotion regulation are related to higher eating disorder symptomatology in general. Those patients who, in addition to these traits, tend to act impulsively when in negative mood states, are at risk for developing addictive eating patterns. Urgency-based treatments are therefore recommended for this subgroup of patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Contingency planning for a deliberate release of smallpox in Great Britain--the role of geographical scale and contact structure.

PubMed

House, Thomas; Hall, Ian; Danon, Leon; Keeling, Matt J

2010-02-14

In the event of a release of a pathogen such as smallpox, which is human-to-human transmissible and has high associated mortality, a key question is how best to deploy containment and control strategies. Given the general uncertainty surrounding this issue, mathematical modelling has played an important role in informing the likely optimal response, in particular defining the conditions under which mass-vaccination would be appropriate. In this paper, we consider two key questions currently unanswered in the literature: firstly, what is the optimal spatial scale for intervention; and secondly, how sensitive are results to the modelling assumptions made about the pattern of human contacts? Here we develop a novel mathematical model for smallpox that incorporates both information on individual contact structure (which is important if the effects of contact tracing are to be captured accurately) and large-scale patterns of movement across a range of spatial scales in Great Britain. Analysis of this model confirms previous work suggesting that a locally targeted 'ring' vaccination strategy is optimal, and that this conclusion is actually quite robust for different socio-demographic and epidemiological assumptions. Our method allows for intuitive understanding of the reasons why national mass vaccination is typically predicted to be suboptimal. As such, we present a general framework for fast calculation of expected outcomes during the attempted control of diverse emerging infections; this is particularly important given that parameters would need to be interactively estimated and modelled in any release scenario.

Risk assessment of precipitation extremes in northern Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng

2018-05-01

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity-humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity-humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites' 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.

Instructional Model of Critical Literacy in an EFL Context: Balancing Conventional and Critical Literacy

ERIC Educational Resources Information Center

Huh, Seonmin

2016-01-01

This article explores the general patterns of interactions between the teacher and students during the different instructional steps when the teacher attempted to incorporate both conventional skill-based reading and critical literacy in an English as a foreign language (EFL) literacy class in a Korean university. There has been a paucity of EFL…

Modelling near field regional uplift patterns in West Greenland/Disko Bay with plane-Earth finite element models.

NASA Astrophysics Data System (ADS)

Meldgaard, Asger; Nielsen, Lars; Iaffaldano, Giampiero

2017-04-01

Relative sea level data, primarily obtained through isolation basin analysis in western Greenland and on Disko Island, indicates asynchronous rates of uplift during the Early Holocene with larger rates of uplift in southern Disko Bay compared to the northern part of the bay. Similar short-wavelength variations can be inferred from the Holocene marine limit as observations on the north and south side of Disko Island differ by as much as 60 m. While global isostatic adjustment models are needed to account for far field contributions to the relative sea level and for the calculation of accurate ocean functions, they are generally not suited for a detailed analysis of the short-wavelength uplift patterns observed close to present ice margins. This is in part due to the excessive computational cost required for sufficient resolution, and because these models generally ignore regional lateral heterogeneities in mantle and lithosphere rheology. To mitigate this problem, we perform sensitivity tests to investigate the effects of near field loading on a regional plane-Earth finite element model of the lithosphere and mantle of the Disko Bay area, where the global isostatic uplift chronology is well documented. By loading the model area through detailed regional ocean function and ice models, and by including a high resolution topography model of the area, we seek to assess the isostatic rebound generated by surface processes with wavelengths similar to those of the observed rebound signal. We also investigate possible effects of varying lithosphere and mantle rheology, which may play an important role in explaining the rebound signal. We use the abundance of relative sea level curves obtained in the region primarily through isolation basin analysis on Disko Island to constrain the parameters of the Earth model.

Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities

PubMed Central

2017-01-01

The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons’ outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several–but not all–types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees' antennal lobes with their behavioural performances over the course of their life. PMID:28640825

Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change

USGS Publications Warehouse

Reese, Gordon; Skagen, Susan K.

2017-01-01

To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.

Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities.

PubMed

MaBouDi, HaDi; Shimazaki, Hideaki; Giurfa, Martin; Chittka, Lars

2017-06-01

The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons' outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several-but not all-types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees' antennal lobes with their behavioural performances over the course of their life.

Commensurate comparisons of models with energy budget observations reveal consistent climate sensitivities

NASA Astrophysics Data System (ADS)

Armour, K.

2017-12-01

Global energy budget observations have been widely used to constrain the effective, or instantaneous climate sensitivity (ICS), producing median estimates around 2°C (Otto et al. 2013; Lewis & Curry 2015). A key question is whether the comprehensive climate models used to project future warming are consistent with these energy budget estimates of ICS. Yet, performing such comparisons has proven challenging. Within models, values of ICS robustly vary over time, as surface temperature patterns evolve with transient warming, and are generally smaller than the values of equilibrium climate sensitivity (ECS). Naively comparing values of ECS in CMIP5 models (median of about 3.4°C) to observation-based values of ICS has led to the suggestion that models are overly sensitive. This apparent discrepancy can partially be resolved by (i) comparing observation-based values of ICS to model values of ICS relevant for historical warming (Armour 2017; Proistosescu & Huybers 2017); (ii) taking into account the "efficacies" of non-CO2 radiative forcing agents (Marvel et al. 2015); and (iii) accounting for the sparseness of historical temperature observations and differences in sea-surface temperature and near-surface air temperature over the oceans (Richardson et al. 2016). Another potential source of discrepancy is a mismatch between observed and simulated surface temperature patterns over recent decades, due to either natural variability or model deficiencies in simulating historical warming patterns. The nature of the mismatch is such that simulated patterns can lead to more positive radiative feedbacks (higher ICS) relative to those engendered by observed patterns. The magnitude of this effect has not yet been addressed. Here we outline an approach to perform fully commensurate comparisons of climate models with global energy budget observations that take all of the above effects into account. We find that when apples-to-apples comparisons are made, values of ICS in models are consistently in good agreement with values of ICS inferred from global energy budget constraints. This suggests that the current generation of coupled climate models are not overly sensitive. However, since global energy budget observations do not constrain ECS, it is less certain whether model ECS values are realistic.

Alignment-free sequence comparison (II): theoretical power of comparison statistics.

PubMed

Wan, Lin; Reinert, Gesine; Sun, Fengzhu; Waterman, Michael S

2010-11-01

Rapid methods for alignment-free sequence comparison make large-scale comparisons between sequences increasingly feasible. Here we study the power of the statistic D2, which counts the number of matching k-tuples between two sequences, as well as D2*, which uses centralized counts, and D2S, which is a self-standardized version, both from a theoretical viewpoint and numerically, providing an easy to use program. The power is assessed under two alternative hidden Markov models; the first one assumes that the two sequences share a common motif, whereas the second model is a pattern transfer model; the null model is that the two sequences are composed of independent and identically distributed letters and they are independent. Under the first alternative model, the means of the tuple counts in the individual sequences change, whereas under the second alternative model, the marginal means are the same as under the null model. Using the limit distributions of the count statistics under the null and the alternative models, we find that generally, asymptotically D2S has the largest power, followed by D2*, whereas the power of D2 can even be zero in some cases. In contrast, even for sequences of length 140,000 bp, in simulations D2* generally has the largest power. Under the first alternative model of a shared motif, the power of D2*approaches 100% when sufficiently many motifs are shared, and we recommend the use of D2* for such practical applications. Under the second alternative model of pattern transfer,the power for all three count statistics does not increase with sequence length when the sequence is sufficiently long, and hence none of the three statistics under consideration canbe recommended in such a situation. We illustrate the approach on 323 transcription factor binding motifs with length at most 10 from JASPAR CORE (October 12, 2009 version),verifying that D2* is generally more powerful than D2. The program to calculate the power of D2, D2* and D2S can be downloaded from http://meta.cmb.usc.edu/d2. Supplementary Material is available at www.liebertonline.com/cmb.

Disturbance History,Spatial Variability, and Patterns of Biodiversity

NASA Astrophysics Data System (ADS)

Bendix, J.; Wiley, J. J.; Commons, M.

2012-12-01

The intermediate disturbance hypothesis predicts that species diversity will be maximized in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting combined impact of the magnitude of disturbance and the time since it occurred. We modeled the changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance. Model outputs show that individual landscape patches have highly variable species richness through time, with the details reflecting the timing, intensity and sequence of their disturbance history. When the results are mapped across the landscape, the resulting temporal and spatial complexity illustrates both the contingent nature of diversity and the danger of generalizing about the impacts of disturbance.

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Effect of various classes of pesticides on expression of stress genes in transgenic C. elegans model of Parkinson's disease.

PubMed

Jadiya, Pooja; Mir, Snober S; Nazir, Aamir

2012-12-01

Neurodegenerative diseases are known to be associated with genetic and environmental factors. The multifactorial Parkinson's disease (PD) is triggered and/or further worsened by exposure to certain pesticides. Existing literature suggests a link between pesticide exposure and increased incidence of PD. We carried out the present study to look into the stress gene expression pattern of transgenic Caenorhabditis elegans (C. elegans) model of PD after exposure to pesticides from different classes. Expression level of sod-1, sod-2, sod-3, hsp-70, hsp-60, and hsp-16.2 stress responsive genes was determined using qPCR. Our findings demonstrate that the expression of stress related genes does not follow a generalized pattern to different toxicants; rather each pesticide class has a specific expression signature.

APPLIED ORIGAMI. Origami of thick panels.

PubMed

Chen, Yan; Peng, Rui; You, Zhong

2015-07-24

Origami patterns, including the rigid origami patterns in which flat inflexible sheets are joined by creases, are primarily created for zero-thickness sheets. In order to apply them to fold structures such as roofs, solar panels, and space mirrors, for which thickness cannot be disregarded, various methods have been suggested. However, they generally involve adding materials to or offsetting panels away from the idealized sheet without altering the kinematic model used to simulate folding. We develop a comprehensive kinematic synthesis for rigid origami of thick panels that differs from the existing kinematic model but is capable of reproducing motions identical to that of zero-thickness origami. The approach, proven to be effective for typical origami, can be readily applied to fold real engineering structures. Copyright © 2015, American Association for the Advancement of Science.

From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

USGS Publications Warehouse

Eisenhauer, Nico; Powell, Jeff R; Grace, James B.; Bowker, Matthew A.

2015-01-01

In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

Island biogeography: Taking the long view of nature's laboratories.

PubMed

Whittaker, Robert J; Fernández-Palacios, José María; Matthews, Thomas J; Borregaard, Michael K; Triantis, Kostas A

2017-09-01

Islands provide classic model biological systems. We review how growing appreciation of geoenvironmental dynamics of marine islands has led to advances in island biogeographic theory accommodating both evolutionary and ecological phenomena. Recognition of distinct island geodynamics permits general models to be developed and modified to account for patterns of diversity, diversification, lineage development, and trait evolution within and across island archipelagos. Emergent patterns of diversity include predictable variation in island species-area relationships, progression rule colonization from older to younger land masses, and syndromes including loss of dispersability and secondary woodiness in herbaceous plant lineages. Further developments in Earth system science, molecular biology, and trait data for islands hold continued promise for unlocking many of the unresolved questions in evolutionary biology and biogeography. Copyright © 2017, American Association for the Advancement of Science.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Projected distributions and diversity of flightless ground beetles within the Australian Wet Tropics and their environmental correlates.

PubMed

Staunton, Kyran M; Robson, Simon K A; Burwell, Chris J; Reside, April E; Williams, Stephen E

2014-01-01

With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group's primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region.

Projected Distributions and Diversity of Flightless Ground Beetles within the Australian Wet Tropics and Their Environmental Correlates

PubMed Central

Staunton, Kyran M.; Robson, Simon K. A.; Burwell, Chris J.; Reside, April E.; Williams, Stephen E.

2014-01-01

With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group’s primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region. PMID:24586362

A null model for microbial diversification

PubMed Central

Straub, Timothy J.

2017-01-01

Whether prokaryotes (Bacteria and Archaea) are naturally organized into phenotypically and genetically cohesive units comparable to animal or plant species remains contested, frustrating attempts to estimate how many such units there might be, or to identify the ecological roles they play. Analyses of gene sequences in various closely related prokaryotic groups reveal that sequence diversity is typically organized into distinct clusters, and processes such as periodic selection and extensive recombination are understood to be drivers of cluster formation (“speciation”). However, observed patterns are rarely compared with those obtainable with simple null models of diversification under stochastic lineage birth and death and random genetic drift. Via a combination of simulations and analyses of core and phylogenetic marker genes, we show that patterns of diversity for the genera Escherichia, Neisseria, and Borrelia are generally indistinguishable from patterns arising under a null model. We suggest that caution should thus be taken in interpreting observed clustering as a result of selective evolutionary forces. Unknown forces do, however, appear to play a role in Helicobacter pylori, and some individual genes in all groups fail to conform to the null model. Taken together, we recommend the presented birth−death model as a null hypothesis in prokaryotic speciation studies. It is only when the real data are statistically different from the expectations under the null model that some speciation process should be invoked. PMID:28630293

Optimal management strategies in variable environments: Stochastic optimal control methods

USGS Publications Warehouse

Williams, B.K.

1985-01-01

Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both the discount rate and the climatic patterns on optimal harvest strategics. In general, decreases in either the discount rate or in the frequency of favorable weather patterns lcd to a more conservative defoliation policy. This did not hold, however, for plants in states of low vigor. Optimal control for shadscale and winterfat tended to stabilize on a policy of heavy defoliation stress, followed by one or more seasons of rest. Big sagebrush required a policy of heavy summer defoliation when sufficient active shoot material is present at the beginning of the growing season. The comparison of fixed and optimal strategies indicated considerable improvement in defoliation yields when optimal strategies are followed. The superior performance was attributable to increased defoliation of plants in states of high vigor. Improvements were found for both discounted and undiscounted yields.

The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

PubMed

Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

2011-06-01

The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

The Role of River Morphodynamic Disturbance and Groundwater Hydrology As Driving Factors of Riparian Landscape Patterns in Mediterranean Rivers.

PubMed

Rivaes, Rui; Pinheiro, António N; Egger, Gregory; Ferreira, Teresa

2017-01-01

Fluvial disturbances, especially floods and droughts, are the main drivers of the successional patterns of riparian vegetation. Those disturbances control the riparian landscape dynamics through the direct interaction between flow and vegetation. The main aim of this work is to investigate the specific paths by which fluvial disturbances, distributed by its components of groundwater hydrology (grndh) and morphodynamic disturbance (mrphd), drive riparian landscape patterns as characterized by the location (position in the river corridor) and shape (physical form of the patch) of vegetation patches in Mediterranean rivers. Specifically, this work assesses how the different components of fluvial disturbances affect these features in general and particularly in each succession phase of riparian vegetation. grndh and mrphd were defined by time and intensity weighted indexes calculated, respectively, from the mean annual water table elevations and the annual maximum instantaneous discharge shear stresses of the previous decade. The interactions between riparian landscape features and fluvial disturbances were assessed by confirmatory factor analysis using structural equation modeling. Two hypothetical models for patch location and shape were conceptualized and tested against empirical data collected from 220 patches at four different study sites. Both models were successfully fitted, meaning that they adequately depicted the relationships between the variables. Furthermore, the models achieved a good adjustment for the observed data, based on the evaluation of several approximate fit indexes. The patch location model explained approximately 80% of the patch location variability, demonstrating that the location of the riparian patches is primarily driven by grndh, while the mrphd had very little effect on this feature. In a multigroup analysis regarding the succession phases of riparian vegetation, the fitted model explained more than 68% of the variance of the data, confirming the results of the general model. The patch shape model explained nearly 13% of the patch shape variability, in which the disturbances came to have less influence on driving this feature. However, grndh continues to be the primary driver of riparian vegetation between the two disturbance factors, despite the proportional increase of the mrphd effect to approximately a third of the grndh effect.

The Role of River Morphodynamic Disturbance and Groundwater Hydrology As Driving Factors of Riparian Landscape Patterns in Mediterranean Rivers

PubMed Central

Rivaes, Rui; Pinheiro, António N.; Egger, Gregory; Ferreira, Teresa

2017-01-01

Fluvial disturbances, especially floods and droughts, are the main drivers of the successional patterns of riparian vegetation. Those disturbances control the riparian landscape dynamics through the direct interaction between flow and vegetation. The main aim of this work is to investigate the specific paths by which fluvial disturbances, distributed by its components of groundwater hydrology (grndh) and morphodynamic disturbance (mrphd), drive riparian landscape patterns as characterized by the location (position in the river corridor) and shape (physical form of the patch) of vegetation patches in Mediterranean rivers. Specifically, this work assesses how the different components of fluvial disturbances affect these features in general and particularly in each succession phase of riparian vegetation. grndh and mrphd were defined by time and intensity weighted indexes calculated, respectively, from the mean annual water table elevations and the annual maximum instantaneous discharge shear stresses of the previous decade. The interactions between riparian landscape features and fluvial disturbances were assessed by confirmatory factor analysis using structural equation modeling. Two hypothetical models for patch location and shape were conceptualized and tested against empirical data collected from 220 patches at four different study sites. Both models were successfully fitted, meaning that they adequately depicted the relationships between the variables. Furthermore, the models achieved a good adjustment for the observed data, based on the evaluation of several approximate fit indexes. The patch location model explained approximately 80% of the patch location variability, demonstrating that the location of the riparian patches is primarily driven by grndh, while the mrphd had very little effect on this feature. In a multigroup analysis regarding the succession phases of riparian vegetation, the fitted model explained more than 68% of the variance of the data, confirming the results of the general model. The patch shape model explained nearly 13% of the patch shape variability, in which the disturbances came to have less influence on driving this feature. However, grndh continues to be the primary driver of riparian vegetation between the two disturbance factors, despite the proportional increase of the mrphd effect to approximately a third of the grndh effect. PMID:28979278

Patterns and drivers of daily bed-level dynamics on two tidal flats with contrasting wave exposure.

PubMed

Hu, Zhan; Yao, Peng; van der Wal, Daphne; Bouma, Tjeerd J

2017-08-02

Short-term bed-level dynamics has been identified as one of the main factors affecting biota establishment or retreat on tidal flats. However, due to a lack of proper instruments and intensive labour involved, the pattern and drivers of daily bed-level dynamics are largely unexplored in a spatiotemporal context. In this study, 12 newly-developed automatic bed-level sensors were deployed for nearly 15 months on two tidal flats with contrasting wave exposure, proving an unique dataset of daily bed-level changes and hydrodynamic forcing. By analysing the data, we show that (1) a general steepening trend exists on both tidal flats, even with contrasting wave exposure and different bed sediment grain size; (2) daily morphodynamics level increases towards the sea; (3) tidal forcing sets the general morphological evolution pattern at both sites; (4) wave forcing induces short-term bed-level fluctuations at the wave-exposed site, but similar effect is not seen at the sheltered site with smaller waves; (5) storms provoke aggravated erosion, but the impact is conditioned by tidal levels. This study provides insights in the pattern and drivers of daily intertidal bed-level dynamics, thereby setting a template for future high-resolution field monitoring programmes and inviting in-depth morphodynamic modelling for improved understanding and predictive capability.

Valuing options in shot noise market

NASA Astrophysics Data System (ADS)

Laskin, Nick

2018-07-01

A new exactly solvable option pricing model has been introduced and elaborated. It is assumed that a stock price follows a Geometric shot noise process. An arbitrage-free integro-differential option pricing equation has been obtained and solved. The new Greeks have been analytically calculated. It has been shown that in diffusion approximation the developed option pricing model incorporates the well-known Black-Scholes equation and its solution. The stochastic dynamic origin of the Black-Scholes volatility has been uncovered. To model the observed market stock price patterns consisting of high frequency small magnitude and low frequency large magnitude jumps, the superposition of two Geometric shot noises has been implemented. A new generalized option pricing equation has been obtained and its exact solution was found. Merton's jump-diffusion formula for option price was recovered in diffusion approximation. Despite the non-Gaussian nature of probability distributions involved, the new option pricing model has the same degree of analytical tractability as the Black-Scholes model and the Merton jump-diffusion model. This attractive feature allows one to derive exact formulas to value options and option related instruments in the market with jump-like price patterns.

Birth order in small multihospital systems.

PubMed

Luke, R D; Ozcan, Y A; Begun, J W

1990-06-01

The strategic behaviors of small multihospital systems have received little attention in the literature despite the fact that small systems are the predominant scale among multihospital systems. This study examines one important aspect of small-system strategic behaviors: the birth-order or evolutionary patterns of hospital acquisition. The evolutionary patterns of acquisition are compared across three strategic model types studied elsewhere: local market, investment, and historical. Using data obtained from a variety of sources, local market model systems are found, in the sequence of acquisition, to be significantly different from the other two model types in terms of relative distances of acquisitions from the initiating or parent hospital, the sizes of acquisition hospitals, the complexity of those hospitals, and the likelihood that the acquisitions are located in rural areas. Differences between parents and acquisitions are also significant, as hypothesized, for the market model system types, although they are not generally significant for the other two model types. The findings suggest that the market model represents an important strategic form that may have important implications for the restructuring of hospital markets.

Factor demand in Swedish manufacturing industry with special reference to the demand for energy. Instantaneous adjustment models; some results

NASA Astrophysics Data System (ADS)

Sjoeholm, K. R.

1981-02-01

The dual approach to the theory of production is used to estimate factor demand functions of the Swedish manufacturing industry. Two approximations of the cost function, the translog and the generalized Leontief models, are used. The price elasticities of the factor demand do not seem to depend on the choice of model. This is at least true as to the sign pattern and as to the inputs capital, labor, total energy and other materials. Total energy is separated into solid fuels, gasoline, fuel oil, electricity and a residual. Fuel oil and electricity are found to be substitutes by both models. Capital and energy are shown to be substitutes. This implies that Swedish industry will save more energy if the capital cost can be reduced. Both models are, in the best versions, able to detect an inappropriate variable. The assumption of perfect competition on the product market, is shown to be inadequate by both models. When this assumption is relaxed, the normal substitution pattern among the inputs is resumed.

Forging patterns and making waves from biology to geology: a commentary on Turing (1952) ‘The chemical basis of morphogenesis’

PubMed Central

Ball, Philip

2015-01-01

Alan Turing was neither a biologist nor a chemist, and yet the paper he published in 1952, ‘The chemical basis of morphogenesis’, on the spontaneous formation of patterns in systems undergoing reaction and diffusion of their ingredients has had a substantial impact on both fields, as well as in other areas as disparate as geomorphology and criminology. Motivated by the question of how a spherical embryo becomes a decidedly non-spherical organism such as a human being, Turing devised a mathematical model that explained how random fluctuations can drive the emergence of pattern and structure from initial uniformity. The spontaneous appearance of pattern and form in a system far away from its equilibrium state occurs in many types of natural process, and in some artificial ones too. It is often driven by very general mechanisms, of which Turing's model supplies one of the most versatile. For that reason, these patterns show striking similarities in systems that seem superficially to share nothing in common, such as the stripes of sand ripples and of pigmentation on a zebra skin. New examples of ‘Turing patterns' in biology and beyond are still being discovered today. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society. PMID:25750229

Association between dietary patterns and mental disorders in pregnant women in Southern Brazil.

PubMed

Paskulin, Jéssica T A; Drehmer, Michele; Olinto, Maria T; Hoffmann, Juliana F; Pinheiro, Andréa P; Schmidt, Maria I; Nunes, Maria A

2017-01-01

To evaluate the association between dietary patterns and mental disorders among pregnant women in southern Brazil. Cross-sectional study with 712 pregnant women recruited from the Study of Food Intake and Eating Behaviors in Pregnancy (ECCAGe). Food intake assessment was performed using the Food Frequency Questionnaire. Dietary patterns were identified by cluster analysis. The Primary Care Evaluation of Mental Disorders (PRIME-MD) was used to evaluate participants' mental health. Poisson regression models with robust variance were fitted to estimate prevalence ratios (PR). In the adjusted models, there was a high prevalence of major depressive disorder among women with low fruit intake (43%, PR 1.43, 95%CI 1.04-1.95) and high sweets and sugars intake (91%, PR 1.91, 95%CI 1.19-3.07). Women with a common-Brazilian dietary pattern had higher prevalence of major depressive disorder compared to those with a varied consumption pattern (PR 1.43, 95%CI 1.01-2.02). Low intake of beans was significantly associated with generalized anxiety disorder (PR 1.40, 95%CI 1.01-1.93). Low consumption of fruits and beans and intake of the common-Brazilian dietary pattern during pregnancy were associated with higher prevalence of mental disorders. These results reinforce the importance of an adequate dietary intake to ensure better mental health in pregnancy.

Computational modelling of mesoscale dislocation patterning and plastic deformation of single crystals

NASA Astrophysics Data System (ADS)

Xia, Shengxu; El-Azab, Anter

2015-07-01

We present a continuum dislocation dynamics model that predicts the formation of dislocation cell structure in single crystals at low strains. The model features a set of kinetic equations of the curl type that govern the space and time evolution of the dislocation density in the crystal. These kinetic equations are coupled to stress equilibrium and deformation kinematics using the eigenstrain approach. A custom finite element method has been developed to solve the coupled system of equations of dislocation kinetics and crystal mechanics. The results show that, in general, dislocations self-organize in patterns under their mutual interactions. However, the famous dislocation cell structure has been found to form only when cross slip is implemented in the model. Cross slip is also found to lower the yield point, increase the hardening rate, and sustain an increase in the dislocation density over the hardening regime. Analysis of the cell structure evolution reveals that the average cell size decreases with the applied stress, which is consistent with the similitude principle.

Common ecology quantifies human insurgency.

PubMed

Bohorquez, Juan Camilo; Gourley, Sean; Dixon, Alexander R; Spagat, Michael; Johnson, Neil F

2009-12-17

Many collective human activities, including violence, have been shown to exhibit universal patterns. The size distributions of casualties both in whole wars from 1816 to 1980 and terrorist attacks have separately been shown to follow approximate power-law distributions. However, the possibility of universal patterns ranging across wars in the size distribution or timing of within-conflict events has barely been explored. Here we show that the sizes and timing of violent events within different insurgent conflicts exhibit remarkable similarities. We propose a unified model of human insurgency that reproduces these commonalities, and explains conflict-specific variations quantitatively in terms of underlying rules of engagement. Our model treats each insurgent population as an ecology of dynamically evolving, self-organized groups following common decision-making processes. Our model is consistent with several recent hypotheses about modern insurgency, is robust to many generalizations, and establishes a quantitative connection between human insurgency, global terrorism and ecology. Its similarity to financial market models provides a surprising link between violent and non-violent forms of human behaviour.

The (Conditional) Resource Dilution Model: State- and Community-Level Modifications.

PubMed

Gibbs, Benjamin G; Workman, Joseph; Downey, Douglas B

2016-06-01

One of the most consistent patterns in the social sciences is the relationship between sibship size and educational outcomes: those with fewer siblings outperform those with many. The resource dilution (RD) model emphasizes the increasing division of parental resources within the nuclear family as the number of children grows, yet it fails to account for instances when the relationship between sibship size and education is often weak or even positive. To reconcile, we introduce a conditional resource dilution (CRD) model to acknowledge that nonparental investments might aid in children's development and condition the effect of siblings. We revisit the General Social Surveys (1972-2010) and find support for a CRD approach: the relationship between sibship size and educational attainment has declined during the first half of the twentieth century, and this relationship varies across religious groups. Findings suggest that state and community resources can offset the impact of resource dilution-a more sociological interpretation of sibship size patterns than that of the traditional RD model.

Proposal of diagnostic process model for computer based diagnosis.

PubMed

Matsumura, Yasushi; Takeda, Toshihiro; Manabe, Shiro; Saito, Hirokazu; Teramoto, Kei; Kuwata, Shigeki; Mihara, Naoki

2012-01-01

We aim at making a diagnosis support system that can be put to practical use. We proposed a diagnostic process model based on simple knowledge which can be gleaned from textbooks. We defined clinical finding (CF) as a general concept for patient's symptom or findings etc., whose value is expressed by Boolean. We call the combination of several CFs a "CF pattern", and a set of CF patterns with concomitant diseases "case base". We consider diagnosis as a process of searching an instance from the case base whose CF pattern is concomitant with that of a patient. The diseases which have the same CF pattern are candidates for diagnosis. Then we select a CF which is present in part of the candidates and check whether it is present or absent in the patient in order to narrow down the candidates. Because the case base does not exist in reality, the probability of CF pattern is calculated by the product of CF occurrence rate assuming that occurrence of CF is independent. Therefore the knowledge required for diagnosis is frequency of disease under sex and age group and CF-disease relation (CF and its occurrence rate in the disease). By processing these two types of knowledge, diagnosis can be made.

NAO and its relationship with the Northern Hemisphere mean surface temperature in CMIP5 simulations

NASA Astrophysics Data System (ADS)

Wang, Xiaofan; Li, Jianping; Sun, Cheng; Liu, Ting

2017-04-01

The North Atlantic Oscillation (NAO) is one of the most prominent teleconnection patterns in the Northern Hemisphere and has recently been found to be both an internal source and useful predictor of the multidecadal variability of the Northern Hemisphere mean surface temperature (NHT). In this study, we examine how well the variability of the NAO and NHT are reproduced in historical simulations generated by the 40 models that constitute Phase 5 of the Coupled Model Intercomparison Project (CMIP5). All of the models are able to capture the basic characteristics of the interannual NAO pattern reasonably well, whereas the simulated decadal NAO patterns show less consistency with the observations. The NAO fluctuations over multidecadal time scales are underestimated by almost all models. Regarding the NHT multidecadal variability, the models generally represent the externally forced variations well but tend to underestimate the internal NHT. With respect to the performance of the models in reproducing the NAO-NHT relationship, 14 models capture the observed decadal lead of the NAO, and model discrepancies in the representation of this linkage are derived mainly from their different interpretation of the underlying physical processes associated with the Atlantic Multidecadal Oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC). This study suggests that one way to improve the simulation of the multidecadal variability of the internal NHT lies in better simulation of the multidecadal variability of the NAO and its delayed effect on the NHT variability via slow ocean processes.

Enhanced anger superiority effect in generalized anxiety disorder and panic disorder

PubMed Central

Ashwin, Chris; Holas, Pawel; Broadhurst, Shanna; Kokoszka, Andrzej; Georgiou, George A.; Fox, Elaine

2012-01-01

People are typically faster and more accurate to detect angry compared to happy faces, which is known as the anger superiority effect. Many cognitive models of anxiety suggest anxiety disorders involve attentional biases towards threat, although the nature of these biases remains unclear. The present study used a Face-in-the-Crowd task to investigate the anger superiority effect in a control group and patients diagnosed with either generalized anxiety disorder (GAD) or panic disorder (PD). The main finding was that both anxiety groups showed an enhanced anger superiority effect compared to controls, which is consistent with key theories of anxiety. Furthermore, both anxiety groups showed a differential pattern of enhanced bias towards threat depending on the crowd in the displays. The different attentional bias patterns between the GAD and PD groups may be related to the diverse symptoms in these disorders. These findings have implications for the diagnosis and treatment of anxiety. PMID:22196167

The mode branching route to localization of the finite-length floating elastica

NASA Astrophysics Data System (ADS)

Rivetti, Marco; Neukirch, Sébastien

2014-09-01

The beam on elastic foundation is a general model used in physical, biological, and technological problems to study delamination, wrinkling, or pattern formation. Recent focus has been given to the buckling of beams deposited on liquid baths, and in the regime where the beam is soft compared to hydrostatic forces the wrinkling pattern observed at buckling has been shown to lead to localization of the deformation when the confinement is increased. Here we perform a global study of the general case where the intensity of the liquid foundation and the confinement are both varied. We compute equilibrium and stability of the solutions and unravel secondary bifurcations that play a major role in the route to localization. Moreover we classify the post-buckling solutions and shed light on the mechanism leading to localization. Finally, using an asymptotic technique imported from fluid mechanics, we derive an approximated analytical solution to the problem.

Final Technical Report for DE-SC0005467

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

Broccoli, Anthony J.

2014-09-14

The objective of this project is to gain a comprehensive understanding of the key atmospheric mechanisms and physical processes associated with temperature extremes in order to better interpret and constrain uncertainty in climate model simulations of future extreme temperatures. To achieve this objective, we first used climate observations and a reanalysis product to identify the key atmospheric circulation patterns associated with extreme temperature days over North America during the late twentieth century. We found that temperature extremes were associated with distinctive signatures in near-surface and mid-tropospheric circulation. The orientations and spatial scales of these circulation anomalies vary with latitude, season,more » and proximity to important geographic features such as mountains and coastlines. We next examined the associations between daily and monthly temperature extremes and large-scale, recurrent modes of climate variability, including the Pacific-North American (PNA) pattern, the northern annular mode (NAM), and the El Niño-Southern Oscillation (ENSO). The strength of the associations are strongest with the PNA and NAM and weaker for ENSO, and also depend upon season, time scale, and location. The associations are stronger in winter than summer, stronger for monthly than daily extremes, and stronger in the vicinity of the centers of action of the PNA and NAM patterns. In the final stage of this project, we compared climate model simulations of the circulation patterns associated with extreme temperature days over North America with those obtained from observations. Using a variety of metrics and self-organizing maps, we found the multi-model ensemble and the majority of individual models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) generally capture the observed patterns well, including their strength and as well as variations with latitude and season. The results from this project indicate that current models are capable of simulating the large-scale meteorological patterns associated with daily temperature extremes and they suggest that such models can be used to evaluate the extent to which changes in atmospheric circulation will influence future changes in temperature extremes.« less

Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream

NASA Astrophysics Data System (ADS)

Ding, Yulin; Lin, Hui; Li, Rongrong

2016-06-01

Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led to large estimation error. In order to achieve the best generalization error, it is an important challenge for the data cleaning methodology to be able to characterize the behavior of data stream distributions and adaptively update a model to include new information and remove old information. However, the complicated data changing property invalidates traditional data cleaning methods, which rely on the assumption of a stationary data distribution, and drives the need for more dynamic and adaptive online data cleaning methods. To overcome these shortcomings, this paper presents a change semantics constrained online filtering method for real-time observational data. Based on the principle that the filter parameter should vary in accordance to the data change patterns, this paper embeds semantic description, which quantitatively depicts the change patterns in the data distribution to self-adapt the filter parameter automatically. Real-time observational water level data streams of different precipitation scenarios are selected for testing. Experimental results prove that by means of this method, more accurate and reliable water level information can be available, which is prior to scientific and prompt flood assessment and decision-making.

A Healthy Dietary Pattern Reduces Lung Cancer Risk: A Systematic Review and Meta-Analysis.

PubMed

Sun, Yanlai; Li, Zhenxiang; Li, Jianning; Li, Zengjun; Han, Jianjun

2016-03-04

Diet and nutrients play an important role in cancer development and progress; a healthy dietary pattern has been found to be associated with several types of cancer. However, the association between a healthy eating pattern and lung cancer risk is still unclear. Therefore, we conducted a systematic review with meta-analysis to evaluate whether a healthy eating pattern might reduce lung cancer risk. We identified relevant studies from the PubMed and Embase databases up to October 2015, and the relative risks were extracted and combined by the fixed-effects model when no substantial heterogeneity was observed; otherwise, the random-effects model was employed. Subgroup and publication bias analyses were also performed. Finally, eight observational studies were included in the meta-analysis. The pooled relative risk of lung cancer for the highest vs. lowest category of healthy dietary pattern was 0.81 (95% confidence interval, CI: 0.75-0.86), and no significant heterogeneity was detected. The relative risks (RRs) for non-smokers, former smokers and current smokers were 0.89 (95% CI: 0.63-1.27), 0.74 (95% CI: 0.62-0.89) and 0.86 (95% CI: 0.79-0.93), respectively. The results remained stable in subgroup analyses by other confounders and sensitivity analysis. The results of our meta-analysis suggest that a healthy dietary pattern is associated with a lower lung cancer risk, and they provide more beneficial evidence for changing the diet pattern in the general population.

Interannual tropical Pacific sea surface temperature anomalies teleconnection to Northern Hemisphere atmosphere in November

NASA Astrophysics Data System (ADS)

King, Martin P.; Herceg-Bulić, Ivana; Kucharski, Fred; Keenlyside, Noel

2018-03-01

We investigate the Northern Hemisphere atmospheric circulation anomalies associated to the sea surface temperature (SST) anomalies that are related to the eastern-Pacific and central-Pacific El Nino-Southern Oscillations in the late autumn (November). This research is motivated by the need for improving understanding of the autumn climate conditions which can impact on winter climate, as well as the relative lack of study on the boreal autumn climate processes compared to winter. Using reanalysis and SST datasets available from the late nineteenth century through the recent years, we found that there are two major atmospheric responses; one is a hemispheric-wide wave number-4 pattern, another has a more annular pattern. Both of these project on the East Atlantic pattern (southward-shifted North Atlantic Oscillation) in the Atlantic sector. Which of the patterns is active is suggested to depend on the background mean flow, with the annular anomaly active in the most recent decades, while the wave-4 pattern in the decades before. This switch is associated with a change of correlation sign in the North Pacific. We discuss the robustness of this finding. The ability of two atmospheric general circulation models (ICTP-AGCM and ECHAM-AGCM) to reproduce the teleconnections is also examined. Evidence provided shows that the wave-4 pattern and the East Atlantic pattern signals can be reproduced by the models, while the shift from this to an annular response for the recent years is not found conclusively.

An application of a Hill-based response surface model for a drug combination experiment on lung cancer.

PubMed

Ning, Shaoyang; Xu, Hongquan; Al-Shyoukh, Ibrahim; Feng, Jiaying; Sun, Ren

2014-10-30

Combination chemotherapy with multiple drugs has been widely applied to cancer treatment owing to enhanced efficacy and reduced drug resistance. For drug combination experiment analysis, response surface modeling has been commonly adopted. In this paper, we introduce a Hill-based global response surface model and provide an application of the model to a 512-run drug combination experiment with three chemicals, namely AG490, U0126, and indirubin-3  ' -monoxime (I-3-M), on lung cancer cells. The results demonstrate generally improved goodness of fit of our model from the traditional polynomial model, as well as the original Hill model on the basis of fixed-ratio drug combinations. We identify different dose-effect patterns between normal and cancer cells on the basis of our model, which indicates the potential effectiveness of the drug combination in cancer treatment. Meanwhile, drug interactions are analyzed both qualitatively and quantitatively. The distinct interaction patterns between U0126 and I-3-M on two types of cells uncovered by the model could be a further indicator of the efficacy of the drug combination. Copyright © 2014 John Wiley & Sons, Ltd.

A flexible motif search technique based on generalized profiles.

PubMed

Bucher, P; Karplus, K; Moeri, N; Hofmann, K

1996-03-01

A flexible motif search technique is presented which has two major components: (1) a generalized profile syntax serving as a motif definition language; and (2) a motif search method specifically adapted to the problem of finding multiple instances of a motif in the same sequence. The new profile structure, which is the core of the generalized profile syntax, combines the functions of a variety of motif descriptors implemented in other methods, including regular expression-like patterns, weight matrices, previously used profiles, and certain types of hidden Markov models (HMMs). The relationship between generalized profiles and other biomolecular motif descriptors is analyzed in detail, with special attention to HMMs. Generalized profiles are shown to be equivalent to a particular class of HMMs, and conversion procedures in both directions are given. The conversion procedures provide an interpretation for local alignment in the framework of stochastic models, allowing for clear, simple significance tests. A mathematical statement of the motif search problem defines the new method exactly without linking it to a specific algorithmic solution. Part of the definition includes a new definition of disjointness of alignments.

Gravity versus radiation models: on the importance of scale and heterogeneity in commuting flows.

PubMed

Masucci, A Paolo; Serras, Joan; Johansson, Anders; Batty, Michael

2013-08-01

We test the recently introduced radiation model against the gravity model for the system composed of England and Wales, both for commuting patterns and for public transportation flows. The analysis is performed both at macroscopic scales, i.e., at the national scale, and at microscopic scales, i.e., at the city level. It is shown that the thermodynamic limit assumption for the original radiation model significantly underestimates the commuting flows for large cities. We then generalize the radiation model, introducing the correct normalization factor for finite systems. We show that even if the gravity model has a better overall performance the parameter-free radiation model gives competitive results, especially for large scales.

Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

USGS Publications Warehouse

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.

Statistical Patterns in Movie Rating Behavior

PubMed Central

2015-01-01

Currently, users and consumers can review and rate products through online services, which provide huge databases that can be used to explore people’s preferences and unveil behavioral patterns. In this work, we investigate patterns in movie ratings, considering IMDb (the Internet Movie Database), a highly visited site worldwide, as a source. We find that the distribution of votes presents scale-free behavior over several orders of magnitude, with an exponent very close to 3/2, with exponential cutoff. It is remarkable that this pattern emerges independently of movie attributes such as average rating, age and genre, with the exception of a few genres and of high-budget films. These results point to a very general underlying mechanism for the propagation of adoption across potential audiences that is independent of the intrinsic features of a movie and that can be understood through a simple spreading model with mean-field avalanche dynamics. PMID:26322899

Statistical Patterns in Movie Rating Behavior.

PubMed

Ramos, Marlon; Calvão, Angelo M; Anteneodo, Celia

2015-01-01

Currently, users and consumers can review and rate products through online services, which provide huge databases that can be used to explore people's preferences and unveil behavioral patterns. In this work, we investigate patterns in movie ratings, considering IMDb (the Internet Movie Database), a highly visited site worldwide, as a source. We find that the distribution of votes presents scale-free behavior over several orders of magnitude, with an exponent very close to 3/2, with exponential cutoff. It is remarkable that this pattern emerges independently of movie attributes such as average rating, age and genre, with the exception of a few genres and of high-budget films. These results point to a very general underlying mechanism for the propagation of adoption across potential audiences that is independent of the intrinsic features of a movie and that can be understood through a simple spreading model with mean-field avalanche dynamics.

Utilization of Norway’s Emergency Wards: The Second 5 Years after the Introduction of the Patient List System

PubMed Central

Goth, Ursula S.; Hammer, Hugo L.; Claussen, Bjørgulf

2014-01-01

Utilization of services is an important indicator for estimating access to healthcare. In Norway, the General Practitioner Scheme, a patient list system, was established in 2001 to enable a stable doctor-patient relationship. Although satisfaction with the system is generally high, people often choose a more accessible but inferior solution for routine care: emergency wards. The aim of the article is to investigate contact patterns in primary health care situations for the total population in urban and remote areas of Norway and for major immigrant groups in Oslo. The primary regression model had a cross-sectional study design analyzing 2,609,107 consultations in representative municipalities across Norway, estimating the probability of choosing the emergency ward in substitution to a general practitioner. In a second regression model comprising 625,590 consultations in Oslo, we calculated this likelihood for immigrants from the 14 largest groups. We noted substantial differences in emergency ward utilization between ethnic Norwegians both in rural and remote areas and among the various immigrant groups residing in Oslo. Oslo utilization of emergency ward services for the whole population declined, and so did this use among all immigrant groups after 2009. Other municipalities, while overwhelmingly ethnically Norwegian, showed diverse patterns including an increase in some and a decrease in others, results which we were unable to explain. PMID:24662997

Dietary patterns and their associations with general obesity and abdominal obesity among young Chinese women.

PubMed

Zhang, J G; Wang, Z H; Wang, H J; Du, W W; Su, C; Zhang, J; Jiang, H R; Zhai, F Y; Zhang, B

2015-09-01

Dietary patterns represent the combined effects of foods and efficaciously illustrate the impact of diet on health outcomes. This study identified the dietary patterns and determined their relationships with obesity among young Chinese women. In 2011, the China Health and Nutrition Survey included 2363 young women aged 18-44 years. Factor analysis of data from three consecutive 24-h dietary recalls identified the dietary patterns. Weight, height and waist circumstance (WC) were measured, and body mass index (BMI) was calculated. General obesity was defined as BMI ⩾28 kg/m(2) and abdominal obesity as WC ⩾85 cm. Four dietary patterns were identified: traditional south; traditional north; snack; and high protein. After adjusting for confounders and energy intake, women in the highest-score quintiles of the traditional south pattern were less likely to have general obesity (odds ratio (OR)=0.48; 95% confidence interval (CI) 0.29-0.78) and abdominal obesity (OR=0.64; 95% CI 0.46-0.90). Subjects in the highest-score quintiles of the traditional north pattern had significantly greater risk of general obesity (OR=2.28; 95% CI 1.38-3.74) and of abdominal obesity (OR=2.32; 95% CI 1.66-3.24). The traditional south pattern of rice as the major staple food with pork and vegetable dishes is associated with lower risk of general and abdominal obesity. The traditional north pattern of high intake of wheat, other cereals and tubers is positively associated with general and abdominal obesity. This provides important information for interventions and policies addressing obesity prevention among young Chinese women.

Oscillations, neural computations and learning during wake and sleep.

PubMed

Penagos, Hector; Varela, Carmen; Wilson, Matthew A

2017-06-01

Learning and memory theories consider sleep and the reactivation of waking hippocampal neural patterns to be crucial for the long-term consolidation of memories. Here we propose that precisely coordinated representations across brain regions allow the inference and evaluation of causal relationships to train an internal generative model of the world. This training starts during wakefulness and strongly benefits from sleep because its recurring nested oscillations may reflect compositional operations that facilitate a hierarchical processing of information, potentially including behavioral policy evaluations. This suggests that an important function of sleep activity is to provide conditions conducive to general inference, prediction and insight, which contribute to a more robust internal model that underlies generalization and adaptive behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relations between winter precipitation and atmospheric circulation simulated by the Geophysical Fluid Dynamics Laboratory general circulation model

USGS Publications Warehouse

McCabe, G.J.; Dettinger, M.D.

1995-01-01

General circulation model (GCM) simulations of atmospheric circulation are more reliable than GCM simulations of temperature and precipitation. In this study, temporal correlations between 700 hPa height anomalies simulated winter precipitation at eight locations in the conterminous United States are compared with corresponding correlations in observations. The objectives are to 1) characterize the relations between atmospheric circulation and winter precipitation simulated by the GFDL, GCM for selected locations in the conterminous USA, ii) determine whether these relations are similar to those found in observations of the actual climate system, and iii) determine if GFDL-simulated precipitation is forced by the same circulation patterns as in the real atmosphere. -from Authors

Modelling information dissemination under privacy concerns in social media

NASA Astrophysics Data System (ADS)

Zhu, Hui; Huang, Cheng; Lu, Rongxing; Li, Hui

2016-05-01

Social media has recently become an important platform for users to share news, express views, and post messages. However, due to user privacy preservation in social media, many privacy setting tools are employed, which inevitably change the patterns and dynamics of information dissemination. In this study, a general stochastic model using dynamic evolution equations was introduced to illustrate how privacy concerns impact the process of information dissemination. Extensive simulations and analyzes involving the privacy settings of general users, privileged users, and pure observers were conducted on real-world networks, and the results demonstrated that user privacy settings affect information differently. Finally, we also studied the process of information diffusion analytically and numerically with different privacy settings using two classic networks.

Assessment of local variability by high-throughput e-beam metrology for prediction of patterning defect probabilities

NASA Astrophysics Data System (ADS)

Wang, Fuming; Hunsche, Stefan; Anunciado, Roy; Corradi, Antonio; Tien, Hung Yu; Tang, Peng; Wei, Junwei; Wang, Yongjun; Fang, Wei; Wong, Patrick; van Oosten, Anton; van Ingen Schenau, Koen; Slachter, Bram

2018-03-01

We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from an HMI high-throughput e-beam tool. The test case is a 10nm node SRAM via array patterned with a DUV immersion LELE process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to a seemingly qualitative differences in defectivity. The large available data volume enables further analysis to reliably distinguish global and local CDU variations, including a breakdown into local systematics and stochastics. A closer inspection of the tail end of the distributions and estimation of defect probabilities concludes that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. We expect that the analysis methodology can be applied for defect probability modeling as well as general process qualification in the future.

Predicting the temporal and spatial probability of orographic cloud cover in the Luquillo Experimental Forest in Puerto Rico using generalized linear (mixed) models.

Treesearch

Wei Wu; Charlesb Hall; Lianjun Zhang

2006-01-01

We predicted the spatial pattern of hourly probability of cloud cover in the Luquillo Experimental Forest (LEF) in North-Eastern Puerto Rico using four different models. The probability of cloud cover (defined as “the percentage of the area covered by clouds in each pixel on the map” in this paper) at any hour and any place is a function of three topographic variables...

Melatonin Production, Sleep Patterns and Modeled Performance Effectiveness in Subjects in the High Arctic

DTIC Science & Technology

2014-05-01

measure ambient light as well as motion. Sleep data obtained from the Actigraphs was used to model the cognitive effectiveness of each subject...Furthermore, saliva was collected at regular intervals to measure melatonin and assess DLMO. Results. In general, sleep duration was found to be...Repeated measures ANOVA with ‘month’ as a between factor and ‘days’ as the repeated measure , indicates a significant main effect of ‘month’ F(1, 23) = 4.98

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

PubMed

Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

2015-12-01

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. © 2015 John Wiley & Sons Ltd.

A stochastic dynamic model for human error analysis in nuclear power plants

NASA Astrophysics Data System (ADS)

Delgado-Loperena, Dharma

Nuclear disasters like Three Mile Island and Chernobyl indicate that human performance is a critical safety issue, sending a clear message about the need to include environmental press and competence aspects in research. This investigation was undertaken to serve as a roadmap for studying human behavior through the formulation of a general solution equation. The theoretical model integrates models from two heretofore-disassociated disciplines (behavior specialists and technical specialists), that historically have independently studied the nature of error and human behavior; including concepts derived from fractal and chaos theory; and suggests re-evaluation of base theory regarding human error. The results of this research were based on comprehensive analysis of patterns of error, with the omnipresent underlying structure of chaotic systems. The study of patterns lead to a dynamic formulation, serving for any other formula used to study human error consequences. The search for literature regarding error yielded insight for the need to include concepts rooted in chaos theory and strange attractors---heretofore unconsidered by mainstream researchers who investigated human error in nuclear power plants or those who employed the ecological model in their work. The study of patterns obtained from the rupture of a steam generator tube (SGTR) event simulation, provided a direct application to aspects of control room operations in nuclear power plant operations. In doing so, the conceptual foundation based in the understanding of the patterns of human error analysis can be gleaned, resulting in reduced and prevent undesirable events.

Characterization, scaling, and partial representation of diffuse and discrete input junctions to CA3 hippocampus.

PubMed

Ascarrunz, F G; Kisley, M A; Flach, K A; Hamilton, R W; MacGregor, R J

1995-07-01

This paper applies a general mathematical system for characterizing and scaling functional connectivity and information flow across the diffuse (EC) and discrete (DG) input junctions to the CA3 hippocampus. Both gross connectivity and coordinated multiunit informational firing patterns are quantitatively characterized in terms of 32 defining parameters interrelated by 17 equations, and then scaled down according to rules for uniformly proportional scaling and for partial representation. The diffuse EC-CA3 junction is shown to be uniformly scalable with realistic representation of both essential spatiotemporal cooperativity and coordinated firing patterns down to populations of a few hundred neurons. Scaling of the discrete DG-CA3 junction can be effected with a two-step process, which necessarily deviates from uniform proportionality but nonetheless produces a valuable and readily interpretable reduced model, also utilizing a few hundred neurons in the receiving population. Partial representation produces a reduced model of only a portion of the full network where each model neuron corresponds directly to a biological neuron. The mathematical analysis illustrated here shows that although omissions and distortions are inescapable in such an application, satisfactorily complete and accurate models the size of pattern modules are possible. Finally, the mathematical characterization of these junctions generates a theory which sees the DG as a definer of the fine structure of embedded traces in the hippocampus and entire coordinated patterns of sequences of 14-cell links in CA3 as triggered by the firing of sequences of individual neurons in DG.

Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

PubMed Central

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-01-01

Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

Complex Degradation Processes Lead to Non-Exponential Decay Patterns and Age-Dependent Decay Rates of Messenger RNA

PubMed Central

Deneke, Carlus; Lipowsky, Reinhard; Valleriani, Angelo

2013-01-01

Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data. PMID:23408982

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

PubMed Central

Bennett, James E. M.; Bair, Wyeth

2015-01-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity.

PubMed

Bennett, James E M; Bair, Wyeth

2015-08-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.

On optimal current patterns for electrical impedance tomography.

PubMed

Demidenko, Eugene; Hartov, Alex; Soni, Nirmal; Paulsen, Keith D

2005-02-01

We develop a statistical criterion for optimal patterns in planar circular electrical impedance tomography. These patterns minimize the total variance of the estimation for the resistance or conductance matrix. It is shown that trigonometric patterns (Isaacson, 1986), originally derived from the concept of distinguishability, are a special case of our optimal statistical patterns. New optimal random patterns are introduced. Recovering the electrical properties of the measured body is greatly simplified when optimal patterns are used. The Neumann-to-Dirichlet map and the optimal patterns are derived for a homogeneous medium with an arbitrary distribution of the electrodes on the periphery. As a special case, optimal patterns are developed for a practical EIT system with a finite number of electrodes. For a general nonhomogeneous medium, with no a priori restriction, the optimal patterns for the resistance and conductance matrix are the same. However, for a homogeneous medium, the best current pattern is the worst voltage pattern and vice versa. We study the effect of the number and the width of the electrodes on the estimate of resistivity and conductivity in a homogeneous medium. We confirm experimentally that the optimal patterns produce minimum conductivity variance in a homogeneous medium. Our statistical model is able to discriminate between a homogenous agar phantom and one with a 2 mm air hole with error probability (p-value) 1/1000.

Modelling plume dispersion pattern from a point source using spatial auto-correlational analysis

NASA Astrophysics Data System (ADS)

Ujoh, F.; Kwabe, D.

2014-02-01

The main objective of the study is to estimate the rate and model the pattern of plume rise from Dangote Cement Plc. A handheld Garmin GPS was employed for collection of coordinates at a single kilometre graduation from the centre of the factory to 10 kilometres. Plume rate was estimated using the Gaussian model while Kriging, using ArcGIS, was adopted for modelling the pattern of plume dispersion over a 10 kilometre radius around the factory. ANOVA test was applied for statistical analysis of the plume coefficients. The results indicate that plume dispersion is generally high with highest values recorded for the atmospheric stability classes A and B, while the least values are recorded for the atmospheric stability classes F and E. The variograms derived from the Kriging reveal that the pattern of plume dispersion is outwardly radial and omni-directional. With the exception of 3 stability sub-classes (DH, EH and FH) out of a total of 12, the 24-hour average of particulate matters (PM10 and PM2.5) within the study area is outrageously higher (highest value at 21392.3) than the average safety limit of 150 ug/m3 - 230 ug/m3 prescribed by the 2006 WHO guidelines. This indicates the presence of respirable and non-respirable pollutants that create poor ambient air quality. The study concludes that the use of geospatial technology can be adopted in modelling dispersion of pollutants from a point source. The study recommends ameliorative measures to reduce the rate of plume emission at the factory.

Clines in quantitative traits: The role of migration patterns and selection scenarios

PubMed Central

Geroldinger, Ludwig; Bürger, Reinhard

2015-01-01

The existence, uniqueness, and shape of clines in a quantitative trait under selection toward a spatially varying optimum is studied. The focus is on deterministic diploid two-locus n-deme models subject to various migration patterns and selection scenarios. Migration patterns may exhibit isolation by distance, as in the stepping-stone model, or random dispersal, as in the island model. The phenotypic optimum may change abruptly in a single environmental step, more gradually, or not at all. Symmetry assumptions are imposed on phenotypic optima and migration rates. We study clines in the mean, variance, and linkage disequilibrium (LD). Clines result from polymorphic equilibria. The possible equilibrium configurations are determined as functions of the migration rate. Whereas for weak migration, many polymorphic equilibria may be simultaneously stable, their number decreases with increasing migration rate. Also for intermediate migration rates polymorphic equilibria are in general not unique, however, for loci of equal effects the corresponding clines in the mean, variance, and LD are unique. For sufficiently strong migration, no polymorphism is maintained. Both migration pattern and selection scenario exert strong influence on the existence and shape of clines. The results for discrete demes are compared with those from models in which space varies continuously and dispersal is modeled by diffusion. Comparisons with previous studies, which investigated clines under neutrality or under linkage equilibrium, are performed. If there is no long-distance migration, the environment does not change abruptly, and linkage is not very tight, populations are almost everywhere close to linkage equilibrium. PMID:25446959

More than one way to see it: Individual heuristics in avian visual computation

PubMed Central

Ravignani, Andrea; Westphal-Fitch, Gesche; Aust, Ulrike; Schlumpp, Martin M.; Fitch, W. Tecumseh

2015-01-01

Comparative pattern learning experiments investigate how different species find regularities in sensory input, providing insights into cognitive processing in humans and other animals. Past research has focused either on one species’ ability to process pattern classes or different species’ performance in recognizing the same pattern, with little attention to individual and species-specific heuristics and decision strategies. We trained and tested two bird species, pigeons (Columba livia) and kea (Nestor notabilis, a parrot species), on visual patterns using touch-screen technology. Patterns were composed of several abstract elements and had varying degrees of structural complexity. We developed a model selection paradigm, based on regular expressions, that allowed us to reconstruct the specific decision strategies and cognitive heuristics adopted by a given individual in our task. Individual birds showed considerable differences in the number, type and heterogeneity of heuristic strategies adopted. Birds’ choices also exhibited consistent species-level differences. Kea adopted effective heuristic strategies, based on matching learned bigrams to stimulus edges. Individual pigeons, in contrast, adopted an idiosyncratic mix of strategies that included local transition probabilities and global string similarity. Although performance was above chance and quite high for kea, no individual of either species provided clear evidence of learning exactly the rule used to generate the training stimuli. Our results show that similar behavioral outcomes can be achieved using dramatically different strategies and highlight the dangers of combining multiple individuals in a group analysis. These findings, and our general approach, have implications for the design of future pattern learning experiments, and the interpretation of comparative cognition research more generally. PMID:26113444

Methylmercury bioaccumulation in an urban estuary: Delaware River USA.

PubMed

Buckman, Kate; Taylor, Vivien; Broadley, Hannah; Hocking, Daniel; Balcom, Prentiss; Mason, Rob; Nislow, Keith; Chen, Celia

2017-09-01

Spatial variation in mercury (Hg) and methylmercury (MeHg) bioaccumulation in urban coastal watersheds reflects complex interactions between Hg sources, land use, and environmental gradients. We examined MeHg concentrations in fauna from the Delaware River estuary, and related these measurements to environmental parameters and human impacts on the waterway. The sampling sites followed a north to south gradient of increasing salinity, decreasing urban influence, and increasing marsh cover. Although mean total Hg in surface sediments (top 4cm) peaked in the urban estuarine turbidity maximum and generally decreased downstream, surface sediment MeHg concentrations showed no spatial patterns consistent with the examined environmental gradients, indicating urban influence on Hg loading to the sediment but not subsequent methylation. Surface water particulate MeHg concentration showed a positive correlation with marsh cover whereas dissolved MeHg concentrations were slightly elevated in the estuarine turbidity maximum region. Spatial patterns of MeHg bioaccumulation in resident fauna varied across taxa. Small fish showed increased MeHg concentrations in the more urban/industrial sites upstream, with concentrations generally decreasing farther downstream. Invertebrates either showed no clear spatial patterns in MeHg concentrations (blue crabs, fiddler crabs) or increasing concentrations further downstream (grass shrimp). Best-supported linear mixed models relating tissue concentration to environmental variables reflected these complex patterns, with species specific model results dominated by random site effects with a combination of particulate MeHg and landscape variables influencing bioaccumulation in some species. The data strengthen accumulating evidence that bioaccumulation in estuaries can be decoupled from sediment MeHg concentration, and that drivers of MeHg production and fate may vary within a small region.

Patterns of New Physics in b → sℓ+ℓ- transitions in the light of recent data

NASA Astrophysics Data System (ADS)

Capdevila, Bernat; Crivellin, Andreas; Descotes-Genon, Sébastien; Matias, Joaquim; Virto, Javier

2018-01-01

In the Standard Model (SM), the rare transitions where a bottom quark decays into a strange quark and a pair of light leptons exhibit a potential sensitivity to physics beyond the SM. In addition, the SM embeds Lepton Flavour Universality (LFU), leading to almost identical probabilities for muon and electron modes. The LHCb collaboration discovered a set of deviations from the SM expectations in decays to muons and also in ratios assessing LFU. Other experiments (Belle, ATLAS, CMS) found consistent measurements, albeit with large error bars. We perform a global fit to all available b → sℓ+ℓ- data (ℓ = e, μ) in a model-independent way allowing for different patterns of New Physics. For the first time, the NP hypothesis is preferred over the SM by 5 σ in a general case when NP can enter SM-like operators and their chirally-flipped partners. LFU violation is favoured with respect to LFU at the 3-4 σ level. We discuss the impact of LFU-violating New Physics on the observable P 5 ' from B → K ∗ μ + μ - and we compare our estimate for long-distance charm contributions with an empirical model recently proposed by a group of LHCb experimentalists. Finally, we discuss NP models able to describe this consistent pattern of deviations.

Modeling methylene chloride exposure-reduction options for home paint-stripper users.

PubMed

Riley, D M; Small, M J; Fischhoff, B

2000-01-01

Home improvement is a popular activity, but one that can also involve exposure to hazardous substances. Paint stripping is of particular concern because of the high potential exposures to methylene chloride, a solvent that is a potential human carcinogen and neurotoxicant. This article presents a general methodology for evaluating the effectiveness of behavioral interventions for reducing these risks. It doubles as a model that assesses exposure patterns, incorporating user time-activity patterns and risk-mitigation strategies. The model draws upon recent innovations in indoor air-quality modeling to estimate exposure through inhalation and dermal pathways to paint-stripper users. It is designed to use data gathered from home paint-stripper users about room characteristics, amount of stripper used, time-activity patterns and exposure-reduction strategies (e.g., increased ventilation and modification in the timing of stripper application, scraping, and breaks). Results indicate that the effectiveness of behavioral interventions depends strongly on characteristics of the room (e.g., size, number and size of doors and windows, base air-exchange rates). The greatest simple reduction in exposure is achieved by using an exhaust fan in addition to opening windows and doors. These results can help identify the most important information for product labels and other risk-communication materials.

The temporal representation of speech in a nonlinear model of the guinea pig cochlea

NASA Astrophysics Data System (ADS)

Holmes, Stephen D.; Sumner, Christian J.; O'Mard, Lowel P.; Meddis, Ray

2004-12-01

The temporal representation of speechlike stimuli in the auditory-nerve output of a guinea pig cochlea model is described. The model consists of a bank of dual resonance nonlinear filters that simulate the vibratory response of the basilar membrane followed by a model of the inner hair cell/auditory nerve complex. The model is evaluated by comparing its output with published physiological auditory nerve data in response to single and double vowels. The evaluation includes analyses of individual fibers, as well as ensemble responses over a wide range of best frequencies. In all cases the model response closely follows the patterns in the physiological data, particularly the tendency for the temporal firing pattern of each fiber to represent the frequency of a nearby formant of the speech sound. In the model this behavior is largely a consequence of filter shapes; nonlinear filtering has only a small contribution at low frequencies. The guinea pig cochlear model produces a useful simulation of the measured physiological response to simple speech sounds and is therefore suitable for use in more advanced applications including attempts to generalize these principles to the response of human auditory system, both normal and impaired. .