A Robust Current Pattern for the Detection of Intraventricular Hemorrhage in Neonates Using Electrical Impedance Tomography

PubMed Central

Tang, T.; Oh, Sungho; Sadleir, R. J.

2010-01-01

We compared two 16-electrode electrical impedance tomography (EIT) current patterns on their ability to reconstruct and quantify small amounts of bleeding inside a neonatal human head using both simulated and phantom data. The current patterns used were an adjacent injection RING pattern (with electrodes located equidistantly on the equator of a sphere) and an EEG current pattern based on the 10–20 EEG electrode layout. Structures mimicking electrically important structures in the infant skull were included in a spherical numerical forward model and their effects on reconstructions were determined. The EEG pattern was found to be a better topology to localize and quantify anomalies within lateral ventricular regions. The RING electrode pattern could not reconstruct anomaly location well, as it could not distinguish different axial positions. The quantification accuracy of the RING pattern was as good as the EEG pattern in noise-free environments. However, the EEG pattern showed better quantification ability than the RING pattern when noise was added. The performance of the EEG pattern improved further with respect to the RING pattern when a fontanel was included in forward models. Significantly better resolution and contrast of reconstructed anomalies was achieved when generated from a model containing such an opening and 50 dB added noise. The EEG method was further applied to reconstruct data from a realistic neonatal head model. Overall, acceptable reconstructions and quantification results were obtained using this model and the homogeneous spherical forward model. PMID:20238166

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

PubMed Central

Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature. PMID:23724108

Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

PubMed

Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature.

The isolation of spatial patterning modes in a mathematical model of juxtacrine cell signalling.

PubMed

O'Dea, R D; King, J R

2013-06-01

Juxtacrine signalling mechanisms are known to be crucial in tissue and organ development, leading to spatial patterns in gene expression. We investigate the patterning behaviour of a discrete model of juxtacrine cell signalling due to Owen & Sherratt (1998, Mathematical modelling of juxtacrine cell signalling. Math. Biosci., 153, 125-150) in which ligand molecules, unoccupied receptors and bound ligand-receptor complexes are modelled. Feedback between the ligand and receptor production and the level of bound receptors is incorporated. By isolating two parameters associated with the feedback strength and employing numerical simulation, linear stability and bifurcation analysis, the pattern-forming behaviour of the model is analysed under regimes corresponding to lateral inhibition and induction. Linear analysis of this model fails to capture the patterning behaviour exhibited in numerical simulations. Via bifurcation analysis, we show that since the majority of periodic patterns fold subcritically from the homogeneous steady state, a wide variety of stable patterns exists at a given parameter set, providing an explanation for this failure. The dominant pattern is isolated via numerical simulation. Additionally, by sampling patterns of non-integer wavelength on a discrete mesh, we highlight a disparity between the continuous and discrete representations of signalling mechanisms: in the continuous case, patterns of arbitrary wavelength are possible, while sampling such patterns on a discrete mesh leads to longer wavelength harmonics being selected where the wavelength is rational; in the irrational case, the resulting aperiodic patterns exhibit 'local periodicity', being constructed from distorted stable shorter wavelength patterns. This feature is consistent with experimentally observed patterns, which typically display approximate short-range periodicity with defects.

Understanding human activity patterns based on space-time-semantics

NASA Astrophysics Data System (ADS)

Huang, Wei; Li, Songnian

2016-11-01

Understanding human activity patterns plays a key role in various applications in an urban environment, such as transportation planning and traffic forecasting, urban planning, public health and safety, and emergency response. Most existing studies in modeling human activity patterns mainly focus on spatiotemporal dimensions, which lacks consideration of underlying semantic context. In fact, what people do and discuss at some places, inferring what is happening at the places, cannot be simple neglected because it is the root of human mobility patterns. We believe that the geo-tagged semantic context, representing what individuals do and discuss at a place and a specific time, drives a formation of specific human activity pattern. In this paper, we aim to model human activity patterns not only based on space and time but also with consideration of associated semantics, and attempt to prove a hypothesis that similar mobility patterns may have different motivations. We develop a spatiotemporal-semantic model to quantitatively express human activity patterns based on topic models, leading to an analysis of space, time and semantics. A case study is conducted using Twitter data in Toronto based on our model. Through computing the similarities between users in terms of spatiotemporal pattern, semantic pattern and spatiotemporal-semantic pattern, we find that only a small number of users (2.72%) have very similar activity patterns, while the majority (87.14%) show different activity patterns (i.e., similar spatiotemporal patterns and different semantic patterns, similar semantic patterns and different spatiotemporal patterns, or different in both). The population of users that has very similar activity patterns is decreased by 56.41% after incorporating semantic information in the corresponding spatiotemporal patterns, which can quantitatively prove the hypothesis.

Patterns of tropical Pacific convection anomalies and associated extratropical wave trains in AMIP5

NASA Astrophysics Data System (ADS)

Ding, Shuoyi; Chen, Wen; Graf, Hans-F.; Guo, Yuanyuan

2018-05-01

In this paper, the performance of 18 Coupled Model Intercomparison Project Phase 5 (CMIP5) models forced by observational SSTs in simulating the tropical Pacific convective variation and the atmospheric responses in the extratropics are assessed. The multi-model ensemble mean results of 18 CMIP5 models show that five major patterns of tropical Pacific convection anomaly in winter can indeed be well reproduced, however, the simulation of the corresponding extratropical responses for each pattern exists some deficiency except for the La Niña pattern compared with observations. We defined an optimized subset of well performing models (ACCESS1.0, CanAM4, CCSM4, CMCC-CM, HadGEM2-A, MPI-ESM-MR) in tropical Pacific deep convection according to the ranking of model skill score. These models exhibit approximately identical convection anomaly patterns in both amplitude and spatial structure to the observation, which potentially might improve the representation of extratropical teleconnections with the tropical Pacific, especially for the CP El Niño (CPEN), EP El Niño (EPEN) and western CP (W-CP) patterns. Both evident atmospheric anomalies of CPEN and EPEN patterns over the NA/E sector and the northeastward propagating wave trains of W-CP pattern can be quite well simulated in the high-skilled models.

Clustering change patterns using Fourier transformation with time-course gene expression data.

PubMed

Kim, Jaehee

2011-01-01

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.

Simulating Spatial Growth Patterns in Developing Countries: A Case of Shama in the Western Region of Ghana.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Nyarko, B. K.

2014-12-01

The integration of geographic information systems (GIS) and agent-based modelling (ABM) can be an efficient tool to improve spatial planning practices. This paper utilizes GIS and ABM approaches to simulate spatial growth patterns of settlement structures in Shama. A preliminary household survey on residential location decision-making choice served as the behavioural rule for household agents in the model. Physical environment properties of the model were extracted from a 2005 image implemented in NetLogo. The resulting growth pattern model was compared with empirical growth patterns to ascertain the model's accuracy. The paper establishes that the development of unplanned structures and its evolving structural pattern are a function of land price, proximity to economic centres, household economic status and location decision-making patterns. The application of the proposed model underlines its potential for integration into urban planning policies and practices, and for understanding residential decision-making processes in emerging cities in developing countries. Key Words: GIS; Agent-based modelling; Growth patterns; NetLogo; Location decision making; Computational Intelligence.

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

How social factors and behavioural strategies affect feeding and social interaction patterns in pigs.

PubMed

Boumans, Iris J M M; de Boer, Imke J M; Hofstede, Gert Jan; Bokkers, Eddie A M

2018-04-26

Animals living in groups compete for food resources and face food conflicts. These conflicts are affected by social factors (e.g. competition level) and behavioural strategies (e.g. avoidance). This study aimed to deepen our understanding of the complex interactions between social factors and behavioural strategies affecting feeding and social interaction patterns in animals. We focused on group-housed growing pigs, Sus scrofa, which typically face conflicts around the feeder, and of which patterns in various competitive environments (i.e. pig:feeder ratio) have been documented soundly. An agent-based model was developed to explore how interactions among social factors and behavioural strategies can affect various feeding and social interaction patterns differently under competitive situations. Model results show that pig and diet characteristics interact with group size and affect daily feeding patterns (e.g. feed intake and feeding time) and conflicts around the feeder. The level of competition can cause a turning point in feeding and social interaction patterns. Beyond a certain point of competition, meal-based (e.g. meal frequency) and social interaction patterns (e.g. displacements) are determined mainly by behavioural strategies. The average daily feeding time can be used to predict the group size at which this turning point occurs. Under the model's assumptions, social facilitation was relatively unimportant in the causation of behavioural patterns in pigs. To validate our model, simulated patterns were compared with empirical patterns in conventionally housed pigs. Similarities between empirical and model patterns support the model results. Our model can be used as a tool in further research for studying the effects of social factors and group dynamics on individual variation in feeding and social interaction patterns in pigs, as well as in other animal species. Copyright © 2018 Elsevier Inc. All rights reserved.

Validating EHR clinical models using ontology patterns.

PubMed

Martínez-Costa, Catalina; Schulz, Stefan

2017-12-01

Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit. This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models. SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of "Shape", a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models. We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation. Copyright © 2017 Elsevier Inc. All rights reserved.

ADAM33 polymorphisms are associated with asthma and a distinctive palm dermatoglyphic pattern

PubMed Central

XUE, WEILIN; HAN, WEI; ZHOU, ZHAO-SHAN

2013-01-01

A close correlation between asthma and palm dermatoglyphic patterns has been observed in previous studies, but the underlying genetic mechanisms have not been investigated. A disintegrin and metalloprotein-33 (ADAM33) polymorphisms are important in the development of asthma and other atopic diseases. To investigate the underlying mechanisms of the association between asthma and distinctive palm dermatoglyphic patterns, thirteen ADAM33 single-nucleotide polymorphisms (SNPs) were analyzed for the association between asthma and palm dermatoglyphic patterns in a population of 400 asthmatic patients and 200 healthy controls. Based on the results, five SNPs, rs44707 (codominant model, P=0.031; log-additive model, P=0.0084), rs2787094 (overdominant model, P=0.049), rs678881 (codominant model, P=0.028; overdominant model, P=0.0083), rs677044 (codominant model, P=0.013; log-additive model, P=0.0033) and rs512625 (dominant model, P=0.033), were associated with asthma in this population. Two SNPs, rs44707 (dominant model, P=0.042) and rs2787094 (codominant model, P=0.014; recessive model, P=0.0038), were observed in the asthma patients with the distinctive palm pattern. As rs44707 and rs2787094 are associated with asthma and a distinctive palm pattern, the data suggest that ADAM33 polymorphisms are correlated with asthma and may be the underlying genetic basis of the association between asthma and palm dermatoglyphic patterns. PMID:24141861

Changing clothes easily: connexin41.8 regulates skin pattern variation.

PubMed

Watanabe, Masakatsu; Kondo, Shigeru

2012-05-01

The skin patterns of animals are very important for their survival, yet the mechanisms involved in skin pattern formation remain unresolved. Turing's reaction-diffusion model presents a well-known mathematical explanation of how animal skin patterns are formed, and this model can predict various animal patterns that are observed in nature. In this study, we used transgenic zebrafish to generate various artificial skin patterns including a narrow stripe with a wide interstripe, a narrow stripe with a narrow interstripe, a labyrinth, and a 'leopard' pattern (or donut-like ring pattern). In this process, connexin41.8 (or its mutant form) was ectopically expressed using the mitfa promoter. Specifically, the leopard pattern was generated as predicted by Turing's model. Our results demonstrate that the pigment cells in animal skin have the potential and plasticity to establish various patterns and that the reaction-diffusion principle can predict skin patterns of animals. © 2012 John Wiley & Sons A/S.

Modeling pattern in collections of parameters

USGS Publications Warehouse

Link, W.A.

1999-01-01

Wildlife management is increasingly guided by analyses of large and complex datasets. The description of such datasets often requires a large number of parameters, among which certain patterns might be discernible. For example, one may consider a long-term study producing estimates of annual survival rates; of interest is the question whether these rates have declined through time. Several statistical methods exist for examining pattern in collections of parameters. Here, I argue for the superiority of 'random effects models' in which parameters are regarded as random variables, with distributions governed by 'hyperparameters' describing the patterns of interest. Unfortunately, implementation of random effects models is sometimes difficult. Ultrastructural models, in which the postulated pattern is built into the parameter structure of the original data analysis, are approximations to random effects models. However, this approximation is not completely satisfactory: failure to account for natural variation among parameters can lead to overstatement of the evidence for pattern among parameters. I describe quasi-likelihood methods that can be used to improve the approximation of random effects models by ultrastructural models.

Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

1999-01-01

Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

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.

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

2018-02-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Hierarchical Modeling of Sequential Behavioral Data: Examining Complex Association Patterns in Mediation Models

ERIC Educational Resources Information Center

Dagne, Getachew A.; Brown, C. Hendricks; Howe, George W.

2007-01-01

This article presents new methods for modeling the strength of association between multiple behaviors in a behavioral sequence, particularly those involving substantively important interaction patterns. Modeling and identifying such interaction patterns becomes more complex when behaviors are assigned to more than two categories, as is the case…

The wing pattern of Moerarchis Durrant, 1914 (Lepidoptera: Tineidae) clarifies transitions between predictive models

PubMed Central

2017-01-01

The evolution of wing pattern in Lepidoptera is a popular area of inquiry but few studies have examined microlepidoptera, with fewer still focusing on intraspecific variation. The tineid genus Moerarchis Durrant, 1914 includes two species with high intraspecific variation of wing pattern. A subset of the specimens examined here provide, to my knowledge, the first examples of wing patterns that follow both the ‘alternating wing-margin’ and ‘uniform wing-margin’ models in different regions along the costa. These models can also be evaluated along the dorsum of Moerarchis, where a similar transition between the two models can be seen. Fusion of veins is shown not to effect wing pattern, in agreement with previous inferences that the plesiomorphic location of wing veins constrains the development of colour pattern. The significant correlation between wing length and number of wing pattern elements in Moerarchis australasiella shows that wing size can act as a major determinant of wing pattern complexity. Lastly, some M. australasiella specimens have wing patterns that conform entirely to the ‘uniform wing-margin’ model and contain more than six bands, providing new empirical insight into the century-old question of how wing venation constrains wing patterns with seven or more bands. PMID:28405390

Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-05-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-01-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

PubMed Central

Grimm, Volker; Railsback, Steven F.

2012-01-01

Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392

Patterned corneal collagen crosslinking for astigmatism: Computational modeling study

PubMed Central

Seven, Ibrahim; Roy, Abhijit Sinha; Dupps, William J.

2014-01-01

PURPOSE To test the hypothesis that spatially selective corneal stromal stiffening can alter corneal astigmatism and assess the effects of treatment orientation, pattern, and material model complexity in computational models using patient-specific geometries. SETTING Cornea and Refractive Surgery Service, Academic Eye Institute, Cleveland, Ohio, USA. DESIGN Computational modeling study. METHODS Three-dimensional corneal geometries from 10 patients with corneal astigmatism were exported from a clinical tomography system (Pentacam). Corneoscleral finite element models of each eye were generated. Four candidate treatment patterns were simulated, and the effects of treatment orientation and magnitude of stiffening on anterior curvature and aberrations were studied. The effect of material model complexity on simulated outcomes was also assessed. RESULTS Pretreatment anterior corneal astigmatism ranged from 1.22 to 3.92 diopters (D) in a series that included regular and irregular astigmatic patterns. All simulated treatment patterns oriented on the flat axis resulted in mean reductions in corneal astigmatism and depended on the pattern geometry. The linear bow-tie pattern produced a greater mean reduction in astigmatism (1.08 D ± 0.13 [SD]; range 0.74 to 1.23 D) than other patterns tested under an assumed 2-times increase in corneal stiffness, and it had a nonlinear relationship to the degree of stiffening. The mean astigmatic effect did not change significantly with a fiber- or depth-dependent model, but it did affect the coupling ratio. CONCLUSIONS In silico simulations based on patient-specific geometries suggest that clinically significant reductions in astigmatism are possible with patterned collagen crosslinking. Effect magnitude was dependent on patient-specific geometry, effective stiffening pattern, and treatment orientation. PMID:24767795

Improving the process of process modelling by the use of domain process patterns

NASA Astrophysics Data System (ADS)

Koschmider, Agnes; Reijers, Hajo A.

2015-01-01

The use of business process models has become prevalent in a wide area of enterprise applications. But while their popularity is expanding, concerns are growing with respect to their proper creation and maintenance. An obvious way to boost the efficiency of creating high-quality business process models would be to reuse relevant parts of existing models. At this point, however, limited support exists to guide process modellers towards the usage of appropriate model content. In this paper, a set of content-oriented patterns is presented, which is extracted from a large set of process models from the order management and manufacturing production domains. The patterns are derived using a newly proposed set of algorithms, which are being discussed in this paper. The authors demonstrate how such Domain Process Patterns, in combination with information on their historic usage, can support process modellers in generating new models. To support the wider dissemination and development of Domain Process Patterns within and beyond the studied domains, an accompanying website has been set up.

Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

NASA Astrophysics Data System (ADS)

Yevin, Igor; Koblyakov, Alexander

The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

To evaluate the Models-3/Community Multiscale Air Quality (CMAQ) modeling system in reproducing the spatial patterns of aerosol concentrations over the country on timescales of months and years, the spatial patterns of model output are compared with those derived from observation...

A statistical nanomechanism of biomolecular patterning actuated by surface potential

NASA Astrophysics Data System (ADS)

Lin, Chih-Ting; Lin, Chih-Hao

2011-02-01

Biomolecular patterning on a nanoscale/microscale on chip surfaces is one of the most important techniques used in vitro biochip technologies. Here, we report upon a stochastic mechanics model we have developed for biomolecular patterning controlled by surface potential. The probabilistic biomolecular surface adsorption behavior can be modeled by considering the potential difference between the binding and nonbinding states. To verify our model, we experimentally implemented a method of electroactivated biomolecular patterning technology and the resulting fluorescence intensity matched the prediction of the developed model quite well. Based on this result, we also experimentally demonstrated the creation of a bovine serum albumin pattern with a width of 200 nm in 5 min operations. This submicron noncovalent-binding biomolecular pattern can be maintained for hours after removing the applied electrical voltage. These stochastic understandings and experimental results not only prove the feasibility of submicron biomolecular patterns on chips but also pave the way for nanoscale interfacial-bioelectrical engineering.

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.

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

Signal and noise in vegetation patterns in drylands: distinguishing the baby from the bath water

NASA Astrophysics Data System (ADS)

Parsons, Anthony; Wainwright, John; Stewart, Jill; Okin, Gregory

2014-05-01

Patterns, and particularly banded patterns, are widely reported in dryland vegetation, and have been the subject of considerable modelling effort. However, much of this modelling effort is predicated on a mathematical approach that is designed to produce patterns and relies on physical processes that are unreasonable. In consequence, whereas in nature dryland vegetation patterns are irregular, disjointed and discontinuous, those produced by such models tend to be regular, continuous and even. The question, therefore, arises "Is it the irregularity, disjointed and discontinuous character of these patterns that holds the key to their formation rather than any apparent, human-imposed semblance of regularity and continuity?" By focusing on this apparent patterning have such models rejected as noise the key to understanding the signal? Models that produce regular vegetation patterns, typically do so by imposing global rules (largely for the distribution of water). Is it not more likely that vegetation responds to the local supply of water, nutrients and propagules? Here, we present a model for the growth of vegetation in deserts that is predicated on the local conditions of input of water, nutrients and propagules and output, such as loss of biomass by herbivory. The approach represents our best quantitative understanding of how desert ecosystems work. Patterns emerge that show the irregularity and discontinuity seen in nature. By focusing on the process rather than the patterns per se our model has the ability to address specific questions of the role of such patterns in land degradation. Further, it has the potential to provide quantitative estimates of the response of the landscape to specific management strategies, as well as the identification of the key thresholds and tipping points that are so important to the management of drylands. In providing a way to understand and predict the vegetation patterns that may develop during desertification, the approach also represents a crucial potential tool for its management and even reversal.

The Common Patterns of Nature

PubMed Central

Frank, Steven A.

2010-01-01

We typically observe large-scale outcomes that arise from the interactions of many hidden, small-scale processes. Examples include age of disease onset, rates of amino acid substitutions, and composition of ecological communities. The macroscopic patterns in each problem often vary around a characteristic shape that can be generated by neutral processes. A neutral generative model assumes that each microscopic process follows unbiased or random stochastic fluctuations: random connections of network nodes; amino acid substitutions with no effect on fitness; species that arise or disappear from communities randomly. These neutral generative models often match common patterns of nature. In this paper, I present the theoretical background by which we can understand why these neutral generative models are so successful. I show where the classic patterns come from, such as the Poisson pattern, the normal or Gaussian pattern, and many others. Each classic pattern was often discovered by a simple neutral generative model. The neutral patterns share a special characteristic: they describe the patterns of nature that follow from simple constraints on information. For example, any aggregation of processes that preserves information only about the mean and variance attracts to the Gaussian pattern; any aggregation that preserves information only about the mean attracts to the exponential pattern; any aggregation that preserves information only about the geometric mean attracts to the power law pattern. I present a simple and consistent informational framework of the common patterns of nature based on the method of maximum entropy. This framework shows that each neutral generative model is a special case that helps to discover a particular set of informational constraints; those informational constraints define a much wider domain of non-neutral generative processes that attract to the same neutral pattern. PMID:19538344

Clustering of change patterns using Fourier coefficients.

PubMed

Kim, Jaehee; Kim, Haseong

2008-01-15

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a time period because biologically related gene groups can share the same change patterns. Many clustering algorithms have been proposed to group observation data. However, because of the complexity of the underlying functions there have not been many studies on grouping data based on change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. The sample Fourier coefficients not only provide information about the underlying functions, but also reduce the dimension. In addition, as their limiting distribution is a multivariate normal, a model-based clustering method incorporating statistical properties would be appropriate. This work is aimed at discovering gene groups with similar change patterns that share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. The model-based method is advantageous over other methods in our proposed model because the sample Fourier coefficients asymptotically follow the multivariate normal distribution. Change patterns are automatically estimated with the Fourier representation in our model. Our model was tested in simulations and on real gene data sets. The simulation results showed that the model-based clustering method with the sample Fourier coefficients has a lower clustering error rate than K-means clustering. Even when the number of repeated time points was small, the same results were obtained. We also applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns. The R program is available upon the request.

Sparse Matrix Motivated Reconstruction of Far-Field Radiation Patterns

DTIC Science & Technology

2015-03-01

method for base - station antenna radiation patterns. IEEE Antennas Propagation Magazine. 2001;43(2):132. 4. Vasiliadis TG, Dimitriou D, Sergiadis JD...algorithm based on sparse representations of radiation patterns using the inverse Discrete Fourier Transform (DFT) and the inverse Discrete Cosine...patterns using a Model- Based Parameter Estimation (MBPE) technique that reduces the computational time required to model radiation patterns. Another

Consistency functional map propagation for repetitive patterns

NASA Astrophysics Data System (ADS)

Wang, Hao

2017-09-01

Repetitive patterns appear frequently in both man-made and natural environments. Automatically and robustly detecting such patterns from an image is a challenging problem. We study repetitive pattern alignment by embedding segmentation cue with a functional map model. However, this model cannot tackle the repetitive patterns directly due to the large photometric and geometric variations. Thus, a consistency functional map propagation (CFMP) algorithm that extends the functional map with dynamic propagation is proposed to address this issue. This propagation model is acquired in two steps. The first one aligns the patterns from a local region, transferring segmentation functions among patterns. It can be cast as an L norm optimization problem. The latter step updates the template segmentation for the next round of pattern discovery by merging the transferred segmentation functions. Extensive experiments and comparative analyses have demonstrated an encouraging performance of the proposed algorithm in detection and segmentation of repetitive patterns.

Diversity of chimera-like patterns from a model of 2D arrays of neurons with nonlocal coupling

NASA Astrophysics Data System (ADS)

Tian, Chang-Hai; Zhang, Xi-Yun; Wang, Zhen-Hua; Liu, Zong-Hua

2017-06-01

Chimera states have been studied in 1D arrays, and a variety of different chimera states have been found using different models. Research has recently been extended to 2D arrays but only to phase models of them. Here, we extend it to a nonphase model of 2D arrays of neurons and focus on the influence of nonlocal coupling. Using extensive numerical simulations, we find, surprisingly, that this system can show most types of previously observed chimera states, in contrast to previous models, where only one or a few types of chimera states can be observed in each model. We also find that this model can show some special chimera-like patterns such as gridding and multicolumn patterns, which were previously observed only in phase models. Further, we present an effective approach, i.e., removing some of the coupling links, to generate heterogeneous coupling, which results in diverse chimera-like patterns and even induces transformations from one chimera-like pattern to another.

Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

NASA Technical Reports Server (NTRS)

Rohloff, Kurt

2010-01-01

The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

46 CFR 160.052-1 - Incorporation by reference.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., Model AP. Sheet 2—Cutting Pattern and General Arrangement, Model CPM. Sheet 3—Cutting Pattern and General Arrangement, Model CPS. Sheet 4—Insert Patterns. (c) Copies on file. The manufacturer shall keep a... Specifications and Standards may be purchased from the Business Service Center, General Services Administration...

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

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

Kravitz, Ben; Lynch, Cary; Hartin, Corinne

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decomposemore » the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2-/non-CO 2-forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.« less

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

DOE PAGES

Kravitz, Ben; Lynch, Cary; Hartin, Corinne; ...

2017-05-12

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decomposemore » the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2-/non-CO 2-forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.« less

Computer discrimination procedures applicable to aerial and ERTS multispectral data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Torline, R. J.; Allen, W. A.

1970-01-01

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

An innovative professional practice model: adaptation of Carper's patterns of knowing, patterns of research, and Aristotle's intellectual virtues.

PubMed

Jacobs, Barbara Bennett

2013-01-01

Professional practice models have emerged as the way hospital-based nursing expresses its consensus-derived philosophy. Magnet recognition influences this practice, while extant nursing theories continue the quest to bridge scholarship with practice. The innovative model presented in this article is an adaptation of Carper's patterns of knowing into a nursing meta-language of science, ethics, art, and advocacy. In this model, boundaries of the patterns of knowing blur and synchronous movement of values, patterns of research, and Aristotelian intellectual virtues blend. Patient and nurse in an intersubjective relationship share the end of human flourishing as the patient's narrative evolves and shared meaning of the ultimate good is actualized.

A fuzzy logic-based model for noise control at industrial workplaces.

PubMed

Aluclu, I; Dalgic, A; Toprak, Z F

2008-05-01

Ergonomics is a broad science encompassing the wide variety of working conditions that can affect worker comfort and health, including factors such as lighting, noise, temperature, vibration, workstation design, tool design, machine design, etc. This paper describes noise-human response and a fuzzy logic model developed by comprehensive field studies on noise measurements (including atmospheric parameters) and control measures. The model has two subsystems constructed on noise reduction quantity in dB. The first subsystem of the fuzzy model depending on 549 linguistic rules comprises acoustical features of all materials used in any workplace. Totally 984 patterns were used, 503 patterns for model development and the rest 481 patterns for testing the model. The second subsystem deals with atmospheric parameter interactions with noise and has 52 linguistic rules. Similarly, 94 field patterns were obtained; 68 patterns were used for training stage of the model and the rest 26 patterns for testing the model. These rules were determined by taking into consideration formal standards, experiences of specialists and the measurements patterns. The results of the model were compared with various statistics (correlation coefficients, max-min, standard deviation, average and coefficient of skewness) and error modes (root mean square error and relative error). The correlation coefficients were significantly high, error modes were quite low and the other statistics were very close to the data. This statement indicates the validity of the model. Therefore, the model can be used for noise control in any workplace and helpful to the designer in planning stage of a workplace.

Analysis of dynamically stable patterns in a maze-like corridor using the Wasserstein metric.

PubMed

Ishiwata, Ryosuke; Kinukawa, Ryota; Sugiyama, Yuki

2018-04-23

The two-dimensional optimal velocity (2d-OV) model represents a dissipative system with asymmetric interactions, thus being suitable to reproduce behaviours such as pedestrian dynamics and the collective motion of living organisms. In this study, we found that particles in the 2d-OV model form optimal patterns in a maze-like corridor. Then, we estimated the stability of such patterns using the Wasserstein metric. Furthermore, we mapped these patterns into the Wasserstein metric space and represented them as points in a plane. As a result, we discovered that the stability of the dynamical patterns is strongly affected by the model sensitivity, which controls the motion of each particle. In addition, we verified the existence of two stable macroscopic patterns which were cohesive, stable, and appeared regularly over the time evolution of the model.

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.

The Theory of Planned Behavior within the Stages of the Transtheoretical Model: Latent Structural Modeling of Stage-Specific Prediction Patterns in Physical Activity

ERIC Educational Resources Information Center

Lippke, Sonia; Nigg, Claudio R.; Maddock, Jay E.

2007-01-01

This is the first study to test whether the stages of change of the transtheoretical model are qualitatively different through exploring discontinuity patterns in theory of planned behavior (TPB) variables using latent multigroup structural equation modeling (MSEM) with AMOS. Discontinuity patterns in terms of latent means and prediction patterns…

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.

Universal predictability of mobility patterns in cities

PubMed Central

Yan, Xiao-Yong; Zhao, Chen; Fan, Ying; Di, Zengru; Wang, Wen-Xu

2014-01-01

Despite the long history of modelling human mobility, we continue to lack a highly accurate approach with low data requirements for predicting mobility patterns in cities. Here, we present a population-weighted opportunities model without any adjustable parameters to capture the underlying driving force accounting for human mobility patterns at the city scale. We use various mobility data collected from a number of cities with different characteristics to demonstrate the predictive power of our model. We find that insofar as the spatial distribution of population is available, our model offers universal prediction of mobility patterns in good agreement with real observations, including distance distribution, destination travel constraints and flux. By contrast, the models that succeed in modelling mobility patterns in countries are not applicable in cities, which suggests that there is a diversity of human mobility at different spatial scales. Our model has potential applications in many fields relevant to mobility behaviour in cities, without relying on previous mobility measurements. PMID:25232053

Discursive Hierarchical Patterning in Economics Cases

ERIC Educational Resources Information Center

Lung, Jane

2011-01-01

This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…

Neutral model analysis of landscape patterns from mathematical morphology

Treesearch

Kurt H. Riitters; Peter Vogt; Pierre Soille; Jacek Kozak; Christine Estreguil

2007-01-01

Mathematical morphology encompasses methods for characterizing land-cover patterns in ecological research and biodiversity assessments. This paper reports a neutral model analysis of patterns in the absence of a structuring ecological process, to help set standards for comparing and interpreting patterns identified by mathematical morphology on real land-cover maps. We...

On the mechanical theory for biological pattern formation

NASA Astrophysics Data System (ADS)

Bentil, D. E.; Murray, J. D.

1993-02-01

We investigate the pattern-forming potential of mechanical models in embryology proposed by Oster, Murray and their coworkers. We show that the presence of source terms in the tissue extracellular matrix and cell density equations give rise to spatio-temporal oscillations. An extension of one such model to include ‘biologically realistic long range effects induces the formation of stationary spatial patterns. Previous attempts to solve the full system were in one dimension only. We obtain solutions in one dimension and extend our simulations to two dimensions. We show that a single mechanical model alone is capable of generating complex but regular spatial patterns rather than the requirement of model interaction as suggested by Nagorcka et al. and Shaw and Murray. We discuss some biological applications of the models among which are would healing and formation of dermatoglyphic (fingerprint) patterns.

Sensitivity analysis of discharge patterns of subthalamic nucleus in the model of basal ganglia in Parkinson disease.

PubMed

Singh, Jyotsna; Singh, Phool; Malik, Vikas

2017-01-01

Parkinson disease alters the information patterns in movement related pathways in brain. Experimental results performed on rats show that the activity patterns changes from single spike activity to mixed burst mode in Parkinson disease. However the cause of this change in activity pattern is not yet completely understood. Subthalamic nucleus is one of the main nuclei involved in the origin of motor dysfunction in Parkinson disease. In this paper, a single compartment conductance based model is considered which focuses on subthalamic nucleus and synaptic input from globus pallidus (external). This model shows highly nonlinear behavior with respect to various intrinsic parameters. Behavior of model has been presented with the help of activity patterns generated in healthy and Parkinson condition. These patterns have been compared by calculating their correlation coefficient for different values of intrinsic parameters. Results display that the activity patterns are very sensitive to various intrinsic parameters and calcium shows some promising results which provide insights into the motor dysfunction.

Adolescent Psychosocial Development: A Review of Longitudinal Models and Research

ERIC Educational Resources Information Center

Meeus, Wim

2016-01-01

This review used 4 types of longitudinal models (descriptive models, prediction models, developmental sequence models and longitudinal mediation models) to identify regular patterns of psychosocial development in adolescence. Eight patterns of adolescent development were observed across countries: (1) adolescent maturation in multiple…

Understanding eye movements in face recognition using hidden Markov models.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2014-09-16

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

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.

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

Bioconvective patterns, synchrony, and survival. [in light-limited growth model of motile algae culture

NASA Technical Reports Server (NTRS)

Noever, David A.

1990-01-01

With and without bioconvective pattern formation, a theoretical model predicts growth in light-limited cultures of motile algae. At the critical density for pattern formation, the resulting doubly exponential population curves show an inflection. Such growth corresponds quantitatively to experiments in mechanically unstirred cultures. This attaches survival value to synchronized pattern formation.

Landscape patterns from mathematical morphology on maps with contagion

Treesearch

Kurt Riitters; Peter Vogt; Pierre Soille; Christine Estreguil

2009-01-01

The perceived realism of simulated maps with contagion (spatial autocorrelation) has led to their use for comparing landscape pattern metrics and as habitat maps for modeling organism movement across landscapes. The objective of this study was to conduct a neutral model analysis of pattern metrics defined by morphological spatial pattern analysis (MSPA) on maps with...

Heterogeneity and Change in the Patterning of Adolescents' Perceptions of the Legitimacy of Parental Authority: A Latent Transition Model

ERIC Educational Resources Information Center

Cumsille, Patricio; Darling, Nancy; Flaherty, Brian; Martinez, Maria Loreto

2009-01-01

Changes in the patterning of adolescents' beliefs about the legitimate domains of parental authority were modeled in 2,611 Chilean adolescents, 11-16 years old. Transitions in adolescents' belief patterns were studied over 3 years. Latent transition analysis (LTA) revealed 3 distinct patterns of beliefs--"parent control," "shared…

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.

Waves and patterning in developmental biology: vertebrate segmentation and feather bud formation as case studies

PubMed Central

Baker, Ruth E.; Schnell, Santiago; Maini, Philip K.

2014-01-01

In this article we will discuss the integration of developmental patterning mechanisms with waves of competency that control the ability of a homogeneous field of cells to react to pattern forming cues and generate spatially heterogeneous patterns. We base our discussion around two well known patterning events that take place in the early embryo: somitogenesis and feather bud formation. We outline mathematical models to describe each patterning mechanism, present the results of numerical simulations and discuss the validity of each model in relation to our example patterning processes. PMID:19557684

Relationship between dietary pattern and cognitive function in elderly patients with type 2 diabetes mellitus.

PubMed

Enomoto, Mari; Yoshii, Hidenori; Mita, Tomoya; Sanke, Haruna; Yokota, Ayako; Yamashiro, Keiko; Inagaki, Noriko; Gosho, Masahiko; Ohmura, Chie; Kudo, Kayo; Watada, Hirotaka; Onuma, Tomio

2015-08-01

To analyse the relationships between dietary patterns and cognitive function in elderly patients with type 2 diabetes mellitus (T2DM). Patients with T2DM completed a 3-day dietary record and Mini-mental State Examination (MMSE). Dietary patterns were identified by factor analysis. The study included 73 patients and identified five dietary patterns, one of which was characterized by high loading for vegetables and fish. A higher consumption of vegetables and fish was significantly associated with improved MMSE score (unadjusted model, model adjusted for age and sex, and model adjusted for age, sex, education, diabetic nephropathy and alcohol consumption), and decreased prevalence of suspected mild dementia (unadjusted model, model adjusted for age and sex). A high score in the vegetables and fish dietary pattern was associated with high MMSE score and low prevalence of suspected mild dementia in elderly patients with T2DM. © The Author(s) 2015.

Style consistent classification of isogenous patterns.

PubMed

Sarkar, Prateek; Nagy, George

2005-01-01

In many applications of pattern recognition, patterns appear together in groups (fields) that have a common origin. For example, a printed word is usually a field of character patterns printed in the same font. A common origin induces consistency of style in features measured on patterns. The features of patterns co-occurring in a field are statistically dependent because they share the same, albeit unknown, style. Style constrained classifiers achieve higher classification accuracy by modeling such dependence among patterns in a field. Effects of style consistency on the distributions of field-features (concatenation of pattern features) can be modeled by hierarchical mixtures. Each field derives from a mixture of styles, while, within a field, a pattern derives from a class-style conditional mixture of Gaussians. Based on this model, an optimal style constrained classifier processes entire fields of patterns rendered in a consistent but unknown style. In a laboratory experiment, style constrained classification reduced errors on fields of printed digits by nearly 25 percent over singlet classifiers. Longer fields favor our classification method because they furnish more information about the underlying style.

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

2017-11-01

Understanding the dynamic processes of a real game system requires an appropriate dynamics model, and rigorously testing a dynamics model is nontrivial. In our methodological research, we develop an approach to testing the validity of game dynamics models that considers the dynamic patterns of angular momentum and speed as measurement variables. Using Rock-Paper-Scissors (RPS) games as an example, we illustrate the geometric patterns in the experiment data. We then derive the related theoretical patterns from a series of typical dynamics models. By testing the goodness-of-fit between the experimental and theoretical patterns, we show that the validity of these models can be evaluated quantitatively. Our approach establishes a link between dynamics models and experimental systems, which is, to the best of our knowledge, the most effective and rigorous strategy for ascertaining the testability of evolutionary game dynamics models.

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.

Numerical approaches to model perturbation fire in turing pattern formations

NASA Astrophysics Data System (ADS)

Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.

2017-11-01

Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.

Simulation of South-Asian Summer Monsoon in a GCM

NASA Astrophysics Data System (ADS)

Ajayamohan, R. S.

2007-10-01

Major characteristics of Indian summer monsoon climate are analyzed using simulations from the upgraded version of Florida State University Global Spectral Model (FSUGSM). The Indian monsoon has been studied in terms of mean precipitation and low-level and upper-level circulation patterns and compared with observations. In addition, the model's fidelity in simulating observed monsoon intraseasonal variability, interannual variability and teleconnection patterns is examined. The model is successful in simulating the major rainbelts over the Indian monsoon region. However, the model exhibits bias in simulating the precipitation bands over the South China Sea and the West Pacific region. Seasonal mean circulation patterns of low-level and upper-level winds are consistent with the model's precipitation pattern. Basic features like onset and peak phase of monsoon are realistically simulated. However, model simulation indicates an early withdrawal of monsoon. Northward propagation of rainbelts over the Indian continent is simulated fairly well, but the propagation is weak over the ocean. The model simulates the meridional dipole structure associated with the monsoon intraseasonal variability realistically. The model is unable to capture the observed interannual variability of monsoon and its teleconnection patterns. Estimate of potential predictability of the model reveals the dominating influence of internal variability over the Indian monsoon region.

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

In order to better understand the dynamic processes of a real game system, we need an appropriate dynamics model, so to evaluate the validity of a model is not a trivial task. Here, we demonstrate an approach, considering the dynamical macroscope patterns of angular momentum and speed as the measurement variables, to evaluate the validity of various dynamics models. Using the data in real time Rock-Paper-Scissors (RPS) games experiments, we obtain the experimental dynamic patterns, and then derive the related theoretical dynamic patterns from a series of typical dynamics models respectively. By testing the goodness-of-fit between the experimental and theoretical patterns, the validity of the models can be evaluated. One of the results in our study case is that, among all the nonparametric models tested, the best-known Replicator dynamics model performs almost worst, while the Projection dynamics model performs best. Besides providing new empirical macroscope patterns of social dynamics, we demonstrate that the approach can be an effective and rigorous tool to test game dynamics models. Fundamental Research Funds for the Central Universities (SSEYI2014Z) and the National Natural Science Foundation of China (Grants No. 61503062).

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.

Automation for pattern library creation and in-design optimization

NASA Astrophysics Data System (ADS)

Deng, Rock; Zou, Elain; Hong, Sid; Wang, Jinyan; Zhang, Yifan; Sweis, Jason; Lai, Ya-Chieh; Ding, Hua; Huang, Jason

2015-03-01

Semiconductor manufacturing technologies are becoming increasingly complex with every passing node. Newer technology nodes are pushing the limits of optical lithography and requiring multiple exposures with exotic material stacks for each critical layer. All of this added complexity usually amounts to further restrictions in what can be designed. Furthermore, the designs must be checked against all these restrictions in verification and sign-off stages. Design rules are intended to capture all the manufacturing limitations such that yield can be maximized for any given design adhering to all the rules. Most manufacturing steps employ some sort of model based simulation which characterizes the behavior of each step. The lithography models play a very big part of the overall yield and design restrictions in patterning. However, lithography models are not practical to run during design creation due to their slow and prohibitive run times. Furthermore, the models are not usually given to foundry customers because of the confidential and sensitive nature of every foundry's processes. The design layout locations where a model flags unacceptable simulated results can be used to define pattern rules which can be shared with customers. With advanced technology nodes we see a large growth of pattern based rules. This is due to the fact that pattern matching is very fast and the rules themselves can be very complex to describe in a standard DRC language. Therefore, the patterns are left as either pattern layout clips or abstracted into pattern-like syntax which a pattern matcher can use directly. The patterns themselves can be multi-layered with "fuzzy" designations such that groups of similar patterns can be found using one description. The pattern matcher is often integrated with a DRC tool such that verification and signoff can be done in one step. The patterns can be layout constructs that are "forbidden", "waived", or simply low-yielding in nature. The patterns can also contain remedies built in so that fixing happens either automatically or in a guided manner. Building a comprehensive library of patterns is a very difficult task especially when a new technology node is being developed or the process keeps changing. The main dilemma is not having enough representative layouts to use for model simulation where pattern locations can be marked and extracted. This paper will present an automatic pattern library creation flow by using a few known yield detractor patterns to systematically expand the pattern library and generate optimized patterns. We will also look at the specific fixing hints in terms of edge movements, additive, or subtractive changes needed during optimization. Optimization will be shown for both the digital physical implementation and custom design methods.

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

NASA Technical Reports Server (NTRS)

Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco;

Optical Pattern Formation in Cold Atoms: Explaining the Red-Blue Asymmetry

NASA Astrophysics Data System (ADS)

Schmittberger, Bonnie; Gauthier, Daniel

2013-05-01

The study of pattern formation in atomic systems has provided new insight into fundamental many-body physics and low-light-level nonlinear optics. Pattern formation in cold atoms in particular is of great interest in condensed matter physics and quantum information science because atoms undergo self-organization at ultralow input powers. We recently reported the first observation of pattern formation in cold atoms but found that our results were not accurately described by any existing theoretical model of pattern formation. Previous models describing pattern formation in cold atoms predict that pattern formation should occur using both red and blue-detuned pump beams, favoring a lower threshold for blue detunings. This disagrees with our recent work, in which we only observed pattern formation with red-detuned pump beams. Previous models also assume a two-level atom, which cannot account for the cooling processes that arise when beams counterpropagate through a cold atomic vapor. We describe a new model for pattern formation that accounts for Sisyphus cooling in multi-level atoms, which gives rise to a new nonlinearity via spatial organization of the atoms. This spatial organization causes a sharp red-blue detuning asymmetry, which agrees well with our experimental observations. We gratefully acknowledge the financial support of the NSF through Grant #PHY-1206040.

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation

PubMed Central

Thompson, David W. J.; van den Broeke, Michiel R.

2017-01-01

Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735

A model for optimizing file access patterns using spatio-temporal parallelism

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

Boonthanome, Nouanesengsy; Patchett, John; Geveci, Berk

2013-01-01

For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible filemore » access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.« less

Implementation of pattern generation algorithm in forming Gilmore and Gomory model for two dimensional cutting stock problem

NASA Astrophysics Data System (ADS)

Octarina, Sisca; Radiana, Mutia; Bangun, Putra B. J.

2018-01-01

Two dimensional cutting stock problem (CSP) is a problem in determining the cutting pattern from a set of stock with standard length and width to fulfill the demand of items. Cutting patterns were determined in order to minimize the usage of stock. This research implemented pattern generation algorithm to formulate Gilmore and Gomory model of two dimensional CSP. The constraints of Gilmore and Gomory model was performed to assure the strips which cut in the first stage will be used in the second stage. Branch and Cut method was used to obtain the optimal solution. Based on the results, it found many patterns combination, if the optimal cutting patterns which correspond to the first stage were combined with the second stage.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Leveraging workflow control patterns in the domain of clinical practice guidelines.

PubMed

Kaiser, Katharina; Marcos, Mar

2016-02-10

Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Even with tool assistance, authoring of CPG models is a labor-intensive task. We aim at facilitating the early stages of CPG modeling task. In this context, we propose to support the authoring of CPG models based on a set of suitable procedural patterns described in an implementation-independent notation that can be then semi-automatically transformed into one of the alternative executable CPG languages. We have started with the workflow control patterns which have been identified in the fields of workflow systems and business process management. We have analyzed the suitability of these patterns by means of a qualitative analysis of CPG texts. Following our analysis we have implemented a selection of workflow patterns in the Asbru and PROforma CPG languages. As implementation-independent notation for the description of patterns we have chosen BPMN 2.0. Finally, we have developed XSLT transformations to convert the BPMN 2.0 version of the patterns into the Asbru and PROforma languages. We showed that although a significant number of workflow control patterns are suitable to describe CPG procedural knowledge, not all of them are applicable in the context of CPGs due to their focus on single-patient care. Moreover, CPGs may require additional patterns not included in the set of workflow control patterns. We also showed that nearly all the CPG-suitable patterns can be conveniently implemented in the Asbru and PROforma languages. Finally, we demonstrated that individual patterns can be semi-automatically transformed from a process specification in BPMN 2.0 to executable implementations in these languages. We propose a pattern and transformation-based approach for the development of CPG models. Such an approach can form the basis of a valid framework for the authoring of CPG models. The identification of adequate patterns and the implementation of transformations to convert patterns from a process specification into different executable implementations are the first necessary steps for our approach.

Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth.

PubMed

Huang, Tousheng; Zhang, Huayong; Dai, Liming; Cong, Xuebing; Ma, Shengnan

2018-03-01

This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution. Copyright © 2018. Published by Elsevier Masson SAS.

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.

Neural activity in the hippocampus during conflict resolution.

PubMed

Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo

2013-01-15

This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Soft tissue modelling with conical springs.

PubMed

Omar, Nadzeri; Zhong, Yongmin; Jazar, Reza N; Subic, Aleksandar; Smith, Julian; Shirinzadeh, Bijan

2015-01-01

This paper presents a new method for real-time modelling soft tissue deformation. It improves the traditional mass-spring model with conical springs to deal with nonlinear mechanical behaviours of soft tissues. A conical spring model is developed to predict soft tissue deformation with reference to deformation patterns. The model parameters are formulated according to tissue deformation patterns and the nonlinear behaviours of soft tissues are modelled with the stiffness variation of conical spring. Experimental results show that the proposed method can describe different tissue deformation patterns using one single equation and also exhibit the typical mechanical behaviours of soft tissues.

Location contexts of user check-ins to model urban geo life-style patterns.

PubMed

Hasan, Samiul; Ukkusuri, Satish V

2015-01-01

Geo-location data from social media offers us information, in new ways, to understand people's attitudes and interests through their activity choices. In this paper, we explore the idea of inferring individual life-style patterns from activity-location choices revealed in social media. We present a model to understand life-style patterns using the contextual information (e. g. location categories) of user check-ins. Probabilistic topic models are developed to infer individual geo life-style patterns from two perspectives: i) to characterize the patterns of user interests to different types of places and ii) to characterize the patterns of user visits to different neighborhoods. The method is applied to a dataset of Foursquare check-ins of the users from New York City. The co-existence of several location contexts and the corresponding probabilities in a given pattern provide useful information about user interests and choices. It is found that geo life-style patterns have similar items-either nearby neighborhoods or similar location categories. The semantic and geographic proximity of the items in a pattern reflects the hidden regularity in user preferences and location choice behavior.

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

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

Chimera patterns in two-dimensional networks of coupled neurons.

PubMed

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

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.

Chimera patterns in two-dimensional networks of coupled neurons

NASA Astrophysics Data System (ADS)

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

Algorithms for Hidden Markov Models Restricted to Occurrences of Regular Expressions

PubMed Central

Tataru, Paula; Sand, Andreas; Hobolth, Asger; Mailund, Thomas; Pedersen, Christian N. S.

2013-01-01

Hidden Markov Models (HMMs) are widely used probabilistic models, particularly for annotating sequential data with an underlying hidden structure. Patterns in the annotation are often more relevant to study than the hidden structure itself. A typical HMM analysis consists of annotating the observed data using a decoding algorithm and analyzing the annotation to study patterns of interest. For example, given an HMM modeling genes in DNA sequences, the focus is on occurrences of genes in the annotation. In this paper, we define a pattern through a regular expression and present a restriction of three classical algorithms to take the number of occurrences of the pattern in the hidden sequence into account. We present a new algorithm to compute the distribution of the number of pattern occurrences, and we extend the two most widely used existing decoding algorithms to employ information from this distribution. We show experimentally that the expectation of the distribution of the number of pattern occurrences gives a highly accurate estimate, while the typical procedure can be biased in the sense that the identified number of pattern occurrences does not correspond to the true number. We furthermore show that using this distribution in the decoding algorithms improves the predictive power of the model. PMID:24833225

Modeling and analyzing stripe patterns in fish skin

NASA Astrophysics Data System (ADS)

Zheng, Yibo; Zhang, Lei; Wang, Yuan; Liang, Ping; Kang, Junjian

2009-11-01

The formation mechanism of stripe patterns in the skin of tropical fishes has been investigated by a coupled two variable reaction diffusion model. Two types of spatial inhomogeneities have been introduced into a homogenous system. Several Turing modes pumped by the Turing instability give rise to a simple stripe pattern. It is found that the Turing mechanism can only determine the wavelength of stripe pattern. The orientation of stripe pattern is determined by the spatial inhomogeneity. Our numerical results suggest that it may be the most possible mechanism for the forming process of fish skin patterns.

MODELING SCALE-DEPENDENT LANDSCAPE PATTERN, DISPERSAL, AND CONNECTIVITY FROM THE PERSPECTIVE OF THE ORGANISM

EPA Science Inventory

Effects of fine- to broad-scale patterns of landscape heterogeneity on dispersal success were examined for organisms varying in life history traits. To systematically control spatial pattern, a landscape model was created by merging physiographically-based maps of simulated land...

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Evaluation of the effect scan pattern has on the trueness and precision of six intraoral digital impression systems.

PubMed

Mennito, Anthony S; Evans, Zachary P; Lauer, Abigail W; Patel, Ravi B; Ludlow, Mark E; Renne, Walter G

2018-03-01

Clinicians have been slow to adopt digital impression technologies due possibly to perceived technique sensitivities involved in data acquisition. This research has two aims: determine whether scan pattern and sequence affects the accuracy of the three-dimensional (3D) model created from this digital impression and to compare the 5 imaging systems with regards to their scanning accuracy for sextant impressions. Six digital intraoral impression systems were used to scan a typodont sextant with optical properties similar to natural teeth. The impressions were taken using five different scan patterns and the resulting digital models were overlayed on a master digital model to determine the accuracy of each scanner performing each scan pattern. Furthermore, regardless of scan pattern, each digital impression system was evaluated for accuracy to the other systems in this same manner. No differences of significance were noted in the accuracy of 3D models created using six distinct scan patterns with one exception involving the CEREC Omnicam. Planmeca Planscan was determined to be the truest scanner while 3Shape Trios was determined to be the most precise for sextant impression making. Scan pattern does not significantly affect the accuracy of the resulting digital model for sextant scanning. Companies who make digital impression systems often recommend a scan pattern specific for their system. However, every clinical scanning scenario is different and may require a different approach. Knowing how important scan pattern is with regards to accuracy would be helpful for guiding a growing number of practitioners who are utilizing this technology. © 2018 Wiley Periodicals, Inc.

Neuronal pattern separation of motion-relevant input in LIP activity

PubMed Central

Berberian, Nareg; MacPherson, Amanda; Giraud, Eloïse; Richardson, Lydia

2016-01-01

In various regions of the brain, neurons discriminate sensory stimuli by decreasing the similarity between ambiguous input patterns. Here, we examine whether this process of pattern separation may drive the rapid discrimination of visual motion stimuli in the lateral intraparietal area (LIP). Starting with a simple mean-rate population model that captures neuronal activity in LIP, we show that overlapping input patterns can be reformatted dynamically to give rise to separated patterns of neuronal activity. The population model predicts that a key ingredient of pattern separation is the presence of heterogeneity in the response of individual units. Furthermore, the model proposes that pattern separation relies on heterogeneity in the temporal dynamics of neural activity and not merely in the mean firing rates of individual neurons over time. We confirm these predictions in recordings of macaque LIP neurons and show that the accuracy of pattern separation is a strong predictor of behavioral performance. Overall, results propose that LIP relies on neuronal pattern separation to facilitate decision-relevant discrimination of sensory stimuli. NEW & NOTEWORTHY A new hypothesis is proposed on the role of the lateral intraparietal (LIP) region of cortex during rapid decision making. This hypothesis suggests that LIP alters the representation of ambiguous inputs to reduce their overlap, thus improving sensory discrimination. A combination of computational modeling, theoretical analysis, and electrophysiological data shows that the pattern separation hypothesis links neural activity to behavior and offers novel predictions on the role of LIP during sensory discrimination. PMID:27881719

Inputs and spatial distribution patterns of Cr in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

2018-03-01

Cr pollution in marine bays has been one of the critical environmental issues, and understanding the input and spatial distribution patterns is essential to pollution control. In according to the source strengths of the major pollution sources, the input patterns of pollutants to marine bay include slight, moderate and heavy, and the spatial distribution are corresponding to three block models respectively. This paper analyzed input patterns and distributions of Cr in Jiaozhou Bay, eastern China based on investigation on Cr in surface waters during 1979-1983. Results showed that the input strengths of Cr in Jiaozhou Bay could be classified as moderate input and slight input, and the input strengths were 32.32-112.30 μg L-1 and 4.17-19.76 μg L-1, respectively. The input patterns of Cr included two patterns of moderate input and slight input, and the horizontal distributions could be defined by means of Block Model 2 and Block Model 3, respectively. In case of moderate input pattern via overland runoff, Cr contents were decreasing from the estuaries to the bay mouth, and the distribution pattern was parallel. In case of moderate input pattern via marine current, Cr contents were decreasing from the bay mouth to the bay, and the distribution pattern was parallel to circular. The Block Models were able to reveal the transferring process of various pollutants, and were helpful to understand the distributions of pollutants in marine bay.

The flow patterning capability of localized natural convection.

PubMed

Huang, Ling-Ting; Chao, Ling

2016-09-14

Controlling flow patterns to align materials can have various applications in optics, electronics, and biosciences. In this study, we developed a natural-convection-based method to create desirable spatial flow patterns by controlling the locations of heat sources. Fluid motion in natural convection is induced by the spatial fluid density gradient that is caused by the established spatial temperature gradient. To analyze the patterning resolution capability of this method, we used a mathematical model combined with nondimensionalization to correlate the flow patterning resolution with experimental operating conditions. The nondimensionalized model suggests that the flow pattern and resolution is only influenced by two dimensionless parameters, and , where Gr is the Grashof number, representing the ratio of buoyancy to the viscous force acting on a fluid, and Pr is the Prandtl number, representing the ratio of momentum diffusivity to thermal diffusivity. We used the model to examine all of the flow behaviors in a wide range of the two dimensionless parameter group and proposed a flow pattern state diagram which suggests a suitable range of operating conditions for flow patterning. In addition, we developed a heating wire with an angular configuration, which enabled us to efficiently examine the pattern resolution capability numerically and experimentally. Consistent resolutions were obtained between the experimental results and model predictions, suggesting that the state diagram and the identified operating range can be used for further application.

Modeling of Diffusion Based Correlations Between Heart Rate Modulations and Respiration Pattern

DTIC Science & Technology

2001-10-25

1 of 4 MODELING OF DIFFUSION BASED CORRELATIONS BETWEEN HEART RATE MODULATIONS AND RESPIRATION PATTERN R.Langer,(1) Y.Smorzik,(2) S.Akselrod,(1...generations of the bronchial tree. The second stage describes the oxygen diffusion process from the pulmonary gas in the alveoli into the pulmonary...patterns (FRC, TV, rate). Keywords – Modeling, Diffusion , Heart Rate fluctuations I. INTRODUCTION Under a whole-body management perception, the

A perturbation analysis of a mechanical model for stable spatial patterning in embryology

NASA Astrophysics Data System (ADS)

Bentil, D. E.; Murray, J. D.

1992-12-01

We investigate a mechanical cell-traction mechanism that generates stationary spatial patterns. A linear analysis highlights the model's potential for these heterogeneous solutions. We use multiple-scale perturbation techniques to study the evolution of these solutions and compare our solutions with numerical simulations of the model system. We discuss some potential biological applications among which are the formation of ridge patterns, dermatoglyphs, and wound healing.

Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.

PubMed

Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei

2015-02-01

This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.

Generation of fluoroscopic 3D images with a respiratory motion model based on an external surrogate signal

NASA Astrophysics Data System (ADS)

Hurwitz, Martina; Williams, Christopher L.; Mishra, Pankaj; Rottmann, Joerg; Dhou, Salam; Wagar, Matthew; Mannarino, Edward G.; Mak, Raymond H.; Lewis, John H.

2015-01-01

Respiratory motion during radiotherapy can cause uncertainties in definition of the target volume and in estimation of the dose delivered to the target and healthy tissue. In this paper, we generate volumetric images of the internal patient anatomy during treatment using only the motion of a surrogate signal. Pre-treatment four-dimensional CT imaging is used to create a patient-specific model correlating internal respiratory motion with the trajectory of an external surrogate placed on the chest. The performance of this model is assessed with digital and physical phantoms reproducing measured irregular patient breathing patterns. Ten patient breathing patterns are incorporated in a digital phantom. For each patient breathing pattern, the model is used to generate images over the course of thirty seconds. The tumor position predicted by the model is compared to ground truth information from the digital phantom. Over the ten patient breathing patterns, the average absolute error in the tumor centroid position predicted by the motion model is 1.4 mm. The corresponding error for one patient breathing pattern implemented in an anthropomorphic physical phantom was 0.6 mm. The global voxel intensity error was used to compare the full image to the ground truth and demonstrates good agreement between predicted and true images. The model also generates accurate predictions for breathing patterns with irregular phases or amplitudes.

Influence of modified muscle morphology and activity pattern on the results of musculoskeletal system modelling in cerebral palsy patient.

PubMed

Ogrodnik, Justyna; Piszczatowski, Szczepan

2017-01-01

The aim of the present study was to evaluate the influence of modified morphological parameters of the muscle model and excitation pattern on the results of musculoskeletal system numerical simulation in a cerebral palsy patient. The modelling of the musculoskeletal system was performed in the AnyBody Modelling System. The standard model (MoCap) was subjected to modifications consisting of changes in morphological parameters and excitation patterns of selected muscles. The research was conducted with the use of data of a 14-year-old cerebral palsy patient. A reduction of morphological parameters (variant MI) caused a decrease in the value of active force generated by the muscle with changed geometry, and as a consequence the changes in active force generated by other muscles. A simulation of the abnormal excitation pattern (variant MII) resulted in the muscle's additional activity during its lengthening. The simultaneous modification of the muscle morphology and excitation pattern (variant MIII) points to the interdependence of both types of muscle model changes. A significant increase in the value of the reaction force in the hip joint was observed as a consequence of modification of the hip abductor activity. The morphological parameters and the excitation pattern of modelled muscles have a significant influence on the results of numerical simulation of the musculoskeletal system functioning.

Simulation of Cell Patterning Triggered by Cell Death and Differential Adhesion in Drosophila Wing.

PubMed

Nagai, Tatsuzo; Honda, Hisao; Takemura, Masahiko

2018-02-27

The Drosophila wing exhibits a well-ordered cell pattern, especially along the posterior margin, where hair cells are arranged in a zigzag pattern in the lateral view. Based on an experimental result observed during metamorphosis of Drosophila, we considered that a pattern of initial cells autonomously develops to the zigzag pattern through cell differentiation, intercellular communication, and cell death (apoptosis) and performed computer simulations of a cell-based model of vertex dynamics for tissues. The model describes the epithelial tissue as a monolayer cell sheet of polyhedral cells. Their vertices move according to equations of motion, minimizing the sum total of the interfacial and elastic energies of cells. The interfacial energy densities between cells are introduced consistently with an ideal zigzag cell pattern, extracted from the experimental result. The apoptosis of cells is modeled by gradually reducing their equilibrium volume to zero and by assuming that the hair cells prohibit neighboring cells from undergoing apoptosis. Based on experimental observations, we also assumed wing elongation along the proximal-distal axis. Starting with an initial cell pattern similar to the micrograph experimentally obtained just before apoptosis, we carried out the simulations according to the model mentioned above and successfully reproduced the ideal zigzag cell pattern. This elucidates a physical mechanism of patterning triggered by cell apoptosis theoretically and exemplifies, to our knowledge, a new framework to study apoptosis-induced patterning. We conclude that the zigzag cell pattern is formed by an autonomous communicative process among the participant cells. Copyright © 2018 Biophysical Society. All rights reserved.

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.

Dietary patterns and chronic kidney disease: a cross-sectional association in the Irish Nun Eye Study.

PubMed

Paterson, Euan N; Neville, Charlotte E; Silvestri, Giuliana; Montgomery, Shannon; Moore, Evelyn; Silvestri, Vittorio; Cardwell, Christopher R; MacGillivray, Tom J; Maxwell, Alexander P; Woodside, Jayne V; McKay, Gareth J

2018-04-27

Associations between dietary patterns and chronic kidney disease are not well established, especially in European populations. We conducted a cross-sectional study of 1033 older Irish women (age range 56-100 years) with a restricted lifestyle. Dietary intake was assessed using a food frequency questionnaire. Renal function was determined by estimated glomerular filtration rate. Two dietary patterns were identified within the study population using factor analysis. A significant negative association was found between unhealthy dietary pattern adherence and renal function in both unadjusted and adjusted models controlling for potential confounding variables (p for trend <0.001), with a mean difference in estimated glomerular filtration rate of -6 ml/min/1.73 m 2 between those in the highest fifth of adherence to the unhealthy dietary pattern compared to the lowest, in the fully adjusted model. Chronic kidney disease risk was significantly greater for the highest fifth, compared to the lowest fifth of unhealthy dietary pattern adherence in adjusted models (adjusted odds ratio = 2.62, p < 0.001). Adherence to the healthy dietary pattern was not associated with renal function or chronic kidney disease in adjusted models. In this cohort, an unhealthy dietary pattern was associated with lower renal function and greater prevalence of chronic kidney disease.

Modeling of the Effect of Path Planning on Thermokinetic Evolutions in Laser Powder Deposition Process

NASA Astrophysics Data System (ADS)

Foroozmehr, Ehsan; Kovacevic, Radovan

2011-07-01

A thermokinetic model coupling finite-element heat transfer with transformation kinetics is developed to determine the effect of deposition patterns on the phase-transformation kinetics of laser powder deposition (LPD) process of a hot-work tool steel. The finite-element model is used to define the temperature history of the process used in an empirical-based kinetic model to analyze the tempering effect of the heating and cooling cycles of the deposition process. An area is defined to be covered by AISI H13 on a substrate of AISI 1018 with three different deposition patterns: one section, two section, and three section. The two-section pattern divides the area of the one-section pattern into two sections, and the three-section pattern divides that area into three sections. The results show that dividing the area under deposition into smaller areas can influence the phase transformation kinetics of the process and, consequently, change the final hardness of the deposited material. The two-section pattern shows a higher average hardness than the one-section pattern, and the three-section pattern shows a fully hardened surface without significant tempered zones of low hardness. To verify the results, a microhardness test and scanning electron microscope were used.

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.

PubMed

Martínez-Costa, Catalina; Cornet, Ronald; Karlsson, Daniel; Schulz, Stefan; Kalra, Dipak

2015-05-01

To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Testing a Conceptual Model of Working through Self-Defeating Patterns

ERIC Educational Resources Information Center

Wei, Meifen; Ku, Tsun-Yao

2007-01-01

The present study developed and examined a conceptual model of working through self-defeating patterns. Participants were 390 college students at a large midwestern university. Results indicated that self-defeating patterns mediated the relations between attachment and distress. Also, self-esteem mediated the link between self-defeating patterns…

Power Law Patch Scaling and Lack of Characteristic Wavelength Suggest "Scale-Free" Processes Drive Pattern Formation in the Florida Everglades

NASA Astrophysics Data System (ADS)

Kaplan, D. A.; Casey, S. T.; Cohen, M. J.; Acharya, S.; Jawitz, J. W.

2016-12-01

A century of hydrologic modification has altered the physical and biological drivers of landscape processes in the Everglades (Florida, USA). Restoring the ridge-slough patterned landscape, a dominant feature of the historical system, is a priority, but requires an understanding of pattern genesis and degradation mechanisms. Physical experiments to evaluate alternative pattern formation mechanisms are limited by the long time scales of peat accumulation and loss, necessitating model-based comparisons, where support for a particular mechanism is based on model replication of extant patterning and trajectories of degradation. However, multiple mechanisms yield patch elongation in the direction of historical flow (a central feature of ridge-slough patterning), limiting the utility of that characteristic for discriminating among alternatives. Using data from vegetation maps, we investigated the statistical features of ridge-slough spatial patterning (ridge density, patch perimeter, elongation, patch-size distributions, and spatial periodicity) to establish more rigorous criteria for evaluating model performance and to inform controls on pattern variation across the contemporary system. Two independent analyses (2-D periodograms and patch size distributions) provide strong evidence against regular patterning, with the landscape exhibiting neither a characteristic wavelength nor a characteristic patch size, both of which are expected under conditions that produce regular patterns. Rather, landscape properties suggest robust scale-free patterning, indicating genesis from the coupled effects of local facilitation and a global negative feedback operating uniformly at the landscape-scale. This finding challenges widespread invocation of scale-dependent negative feedbacks for explaining ridge-slough pattern origins. These results help discern among genesis mechanisms and provide an improved statistical description of the landscape that can be used to compare among model outputs, as well as to assess the success of future restoration projects.

Modeling Child-Nature Interaction in a Nature Preschool: A Proof of Concept.

PubMed

Kahn, Peter H; Weiss, Thea; Harrington, Kit

2018-01-01

This article provides a proof of concept for an approach to modeling child-nature interaction based on the idea of interaction patterns : characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur - in more domestic or wild forms - given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one's body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal , and being outside in weather . These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model.

Modeling Real-Time Applications with Reusable Design Patterns

NASA Astrophysics Data System (ADS)

Rekhis, Saoussen; Bouassida, Nadia; Bouaziz, Rafik

Real-Time (RT) applications, which manipulate important volumes of data, need to be managed with RT databases that deal with time-constrained data and time-constrained transactions. In spite of their numerous advantages, RT databases development remains a complex task, since developers must study many design issues related to the RT domain. In this paper, we tackle this problem by proposing RT design patterns that allow the modeling of structural and behavioral aspects of RT databases. We show how RT design patterns can provide design assistance through architecture reuse of reoccurring design problems. In addition, we present an UML profile that represents patterns and facilitates further their reuse. This profile proposes, on one hand, UML extensions allowing to model the variability of patterns in the RT context and, on another hand, extensions inspired from the MARTE (Modeling and Analysis of Real-Time Embedded systems) profile.

Crossover Patterning by the Beam-Film Model: Analysis and Implications

PubMed Central

Zhang, Liangran; Liang, Zhangyi; Hutchinson, John; Kleckner, Nancy

2014-01-01

Crossing-over is a central feature of meiosis. Meiotic crossover (CO) sites are spatially patterned along chromosomes. CO-designation at one position disfavors subsequent CO-designation(s) nearby, as described by the classical phenomenon of CO interference. If multiple designations occur, COs tend to be evenly spaced. We have previously proposed a mechanical model by which CO patterning could occur. The central feature of a mechanical mechanism is that communication along the chromosomes, as required for CO interference, can occur by redistribution of mechanical stress. Here we further explore the nature of the beam-film model, its ability to quantitatively explain CO patterns in detail in several organisms, and its implications for three important patterning-related phenomena: CO homeostasis, the fact that the level of zero-CO bivalents can be low (the “obligatory CO”), and the occurrence of non-interfering COs. Relationships to other models are discussed. PMID:24497834

The Role of Different Plant Soil-Water Feedbacks in Models of Dryland Vegetation Patterns

NASA Astrophysics Data System (ADS)

Silber, M.; Bonetti, S.; Gandhi, P.; Gowda, K.; Iams, S.; Porporato, A. M.

2017-12-01

Understanding the processes underlying the formation of regular vegetation patterns in arid and semi-arid regions is important to assessing desertification risk under increasing anthropogenic pressure. Various modeling frameworks have been proposed, which are all capable of generating similar patterns through self-organizing mechanisms that stem from assumptions about plant feedbacks on surface/subsurface water transport. We critically discuss a hierarchy of hydrology-vegetation models for the coupled dynamics of surface water, soil moisture, and vegetation biomass on a hillslope. We identify distinguishing features and trends for the periodic traveling wave solutions when there is an imposed idealized topography and make some comparisons to satellite images of large-scale banded vegetation patterns in drylands of Africa, Australia and North America. This work highlights the potential for constraining models by considerations of where the patterns may lie on a landscape, such as whether on a ridge or in a valley.

Pattern formation in three-dimensional reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Callahan, T. K.; Knobloch, E.

1999-08-01

Existing group theoretic analysis of pattern formation in three dimensions [T.K. Callahan, E. Knobloch, Symmetry-breaking bifurcations on cubic lattices, Nonlinearity 10 (1997) 1179-1216] is used to make specific predictions about the formation of three-dimensional patterns in two models of the Turing instability, the Brusselator model and the Lengyel-Epstein model. Spatially periodic patterns having the periodicity of the simple cubic (SC), face-centered cubic (FCC) or body-centered cubic (BCC) lattices are considered. An efficient center manifold reduction is described and used to identify parameter regimes permitting stable lamellæ, SC, FCC, double-diamond, hexagonal prism, BCC and BCCI states. Both models possess a special wavenumber k* at which the normal form coefficients take on fixed model-independent ratios and both are described by identical bifurcation diagrams. This property is generic for two-species chemical reaction-diffusion models with a single activator and inhibitor.

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations.

PubMed

van Strien, Maarten J; Slager, Cornelis T J; de Vries, Bauke; Grêt-Regamey, Adrienne

2016-06-01

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer-generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape-level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class- and patch-level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user-defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online.

Digital Elevation Models of Patterned Ground in the Canadian Arctic and Implications for the Study of Mars

NASA Astrophysics Data System (ADS)

Knightly, P.; Murakami, Y.; Clarke, J.; Sizemore, H.; Siegler, M.; Rupert, S.; Chevrier, V.

2017-12-01

Patterned ground forms in periglacial zones from both expansion and contraction of permafrost by freeze-thaw and sub-freezing temperature changes and has been observed on both Earth and Mars from orbital and the surface at the Phoneix and Viking 2 landing sites. The Phoenix mission to Mars studied patterned ground in the vicinity of the spacecraft including the excavation of a trench revealing water permafrost beneath the surface. A study of patterned ground at the Haughton Impact structure on Devon Island used stereo-pair imaging and three-dimensional photographic models to catalog the type and occurrence of patterned ground in the study area. This image catalog was then used to provide new insight into photographic observations gathered by Phoenix. Stereo-pair imagery has been a valuable geoscience tool for decades and it is an ideal tool for comparative planetary geology studies. Stereo-pair images captured on Devon Island were turned into digital elevation models (DEMs) and comparisons were noted between the permafrost and patterned ground environment of Earth and Mars including variations in grain sorting, active layer thickness, and ice table depth. Recent advances in 360° cameras also enabled the creation of a detailed, immersive site models of patterned ground at selected sites in Haughton crater on Devon Island. The information from this ground truth study will enable the development and refinement of existing models to better evaluate patterned ground on Mars and predict its evolution.

On the mechanochemical theory of biological pattern formation with application to vasculogenesis.

PubMed

Murray, James D

2003-02-01

We first describe the Murray-Oster mechanical theory of pattern formation, the biological basis of which is experimentally well documented. The model quantifies the interaction of cells and the extracellular matrix via the cell-generated forces. The model framework is described in quantitative detail. Vascular endothelial cells, when cultured on gelled basement membrane matrix, rapidly aggregate into clusters while deforming the matrix into a network of cord-like structures tessellating the planar culture. We apply the mechanical theory of pattern formation to this culture system and show that neither strain-biased anisotropic cell traction nor cell migration are necessary for pattern formation: isotropic, strain-stimulated cell traction is sufficient to form the observed patterns. Predictions from the model were confirmed experimentally.

Spatiotemporal Patterns in a Predator-Prey Model with Cross-Diffusion Effect

NASA Astrophysics Data System (ADS)

Sambath, M.; Balachandran, K.; Guin, L. N.

The present research deals with the emergence of spatiotemporal patterns of a two-dimensional (2D) continuous predator-prey system with cross-diffusion effect. First, we work out the critical lines of Hopf and Turing bifurcations of the current model system in a 2D spatial domain by means of bifurcation theory. More specifically, the exact Turing region is specified in a two-parameter space. In effect, by choosing the cross-diffusion coefficient as one of the momentous parameter, we demonstrate that the model system undergoes a sequence of spatiotemporal patterns in a homogeneous environment through diffusion-driven instability. Our results via numerical simulation authenticate that cross-diffusion be able to create stationary patterns which enrich the findings of pattern formation in an ecosystem.

A mutual support mechanism through intercellular movement of CAPRICE and GLABRA3 can pattern the Arabidopsis root epidermis.

PubMed

Savage, Natasha Saint; Walker, Tom; Wieckowski, Yana; Schiefelbein, John; Dolan, Liam; Monk, Nicholas A M

2008-09-23

The patterning of the Arabidopsis root epidermis depends on a genetic regulatory network that operates both within and between cells. Genetic studies have identified a number of key components of this network, but a clear picture of the functional logic of the network is lacking. Here, we integrate existing genetic and biochemical data in a mathematical model that allows us to explore both the sufficiency of known network interactions and the extent to which additional assumptions about the model can account for wild-type and mutant data. Our model shows that an existing hypothesis concerning the autoregulation of WEREWOLF does not account fully for the expression patterns of components of the network. We confirm the lack of WEREWOLF autoregulation experimentally in transgenic plants. Rather, our modelling suggests that patterning depends on the movement of the CAPRICE and GLABRA3 transcriptional regulators between epidermal cells. Our combined modelling and experimental studies show that WEREWOLF autoregulation does not contribute to the initial patterning of epidermal cell fates in the Arabidopsis seedling root. In contrast to a patterning mechanism relying on local activation, we propose a mechanism based on lateral inhibition with feedback. The active intercellular movements of proteins that are central to our model underlie a mechanism for pattern formation in planar groups of cells that is centred on the mutual support of two cell fates rather than on local activation and lateral inhibition.

A Mutual Support Mechanism through Intercellular Movement of CAPRICE and GLABRA3 Can Pattern the Arabidopsis Root Epidermis

PubMed Central

Savage, Natasha Saint; Walker, Tom; Wieckowski, Yana; Schiefelbein, John; Dolan, Liam; Monk, Nicholas A. M

2008-01-01

The patterning of the Arabidopsis root epidermis depends on a genetic regulatory network that operates both within and between cells. Genetic studies have identified a number of key components of this network, but a clear picture of the functional logic of the network is lacking. Here, we integrate existing genetic and biochemical data in a mathematical model that allows us to explore both the sufficiency of known network interactions and the extent to which additional assumptions about the model can account for wild-type and mutant data. Our model shows that an existing hypothesis concerning the autoregulation of WEREWOLF does not account fully for the expression patterns of components of the network. We confirm the lack of WEREWOLF autoregulation experimentally in transgenic plants. Rather, our modelling suggests that patterning depends on the movement of the CAPRICE and GLABRA3 transcriptional regulators between epidermal cells. Our combined modelling and experimental studies show that WEREWOLF autoregulation does not contribute to the initial patterning of epidermal cell fates in the Arabidopsis seedling root. In contrast to a patterning mechanism relying on local activation, we propose a mechanism based on lateral inhibition with feedback. The active intercellular movements of proteins that are central to our model underlie a mechanism for pattern formation in planar groups of cells that is centred on the mutual support of two cell fates rather than on local activation and lateral inhibition. PMID:18816165

Tests of Si(111)-7 × 7 structural models by comparison with transmission electron diffraction patterns

NASA Astrophysics Data System (ADS)

McRae, E. G.; Petroff, P. M.

1984-11-01

Several structural models of the Si(111)-7 × 7 surface are tested by comparing calculated and observed transmission electron diffraction (TED) patterns. The models comprise "adatom" models where the unit mesh contains 12 adatoms or atom clusters in a locally (2 × 2) arrangement, and "triangle-dimer" models where the unit mesh contains 9 dimers or pairs of dimers bordering a triangular subunit of the unit mesh. The distribution of diffraction intensity among fractional-order spots is calculated kinematically and compared with TED patterns observed by Petroff and Wilson and others. No agreement is found for adatom models. Good but not perfect agreement is found for one triangle-dimer model.

From Modelling to Execution of Enterprise Integration Scenarios: The GENIUS Tool

NASA Astrophysics Data System (ADS)

Scheibler, Thorsten; Leymann, Frank

One of the predominant problems IT companies are facing today is Enterprise Application Integration (EAI). Most of the infrastructures built to tackle integration issues are proprietary because no standards exist for how to model, develop, and actually execute integration scenarios. EAI patterns gain importance for non-technical business users to ease and harmonize the development of EAI scenarios. These patterns describe recurring EAI challenges and propose possible solutions in an abstract way. Therefore, one can use those patterns to describe enterprise architectures in a technology neutral manner. However, patterns are documentation only used by developers and systems architects to decide how to implement an integration scenario manually. Thus, patterns are not theoretical thought to stand for artefacts that will immediately be executed. This paper presents a tool supporting a method how EAI patterns can be used to generate executable artefacts for various target platforms automatically using a model-driven development approach, hence turning patterns into something executable. Therefore, we introduce a continuous tool chain beginning at the design phase and ending in executing an integration solution in a completely automatically manner. For evaluation purposes we introduce a scenario demonstrating how the tool is utilized for modelling and actually executing an integration scenario.

TOPTRAC: Topical Trajectory Pattern Mining

PubMed Central

Kim, Younghoon; Han, Jiawei; Yuan, Cangzhou

2015-01-01

With the increasing use of GPS-enabled mobile phones, geo-tagging, which refers to adding GPS information to media such as micro-blogging messages or photos, has seen a surge in popularity recently. This enables us to not only browse information based on locations, but also discover patterns in the location-based behaviors of users. Many techniques have been developed to find the patterns of people's movements using GPS data, but latent topics in text messages posted with local contexts have not been utilized effectively. In this paper, we present a latent topic-based clustering algorithm to discover patterns in the trajectories of geo-tagged text messages. We propose a novel probabilistic model to capture the semantic regions where people post messages with a coherent topic as well as the patterns of movement between the semantic regions. Based on the model, we develop an efficient inference algorithm to calculate model parameters. By exploiting the estimated model, we next devise a clustering algorithm to find the significant movement patterns that appear frequently in data. Our experiments on real-life data sets show that the proposed algorithm finds diverse and interesting trajectory patterns and identifies the semantic regions in a finer granularity than the traditional geographical clustering methods. PMID:26709365

Optical Neural Classification Of Binary Patterns

NASA Astrophysics Data System (ADS)

Gustafson, Steven C.; Little, Gordon R.

1988-05-01

Binary pattern classification that may be implemented using optical hardware and neural network algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten characters) or no concise computation (as in NP-complete problems) are expected to be particularly amenable to this approach. For example, optical processors that efficiently classify binary patterns in accordance with their Boolean function complexity might be designed. As a candidate for such a design, an optical neural network model is discussed that is designed for binary pattern classification and that consists of an optical resonator with a dynamic multiplex-recorded reflection hologram and a phase conjugate mirror with thresholding and gain. In this model, learning or training examples of binary patterns may be recorded on the hologram such that one bit in each pattern marks the pattern class. Any input pattern, including one with an unknown class or marker bit, will be modified by a large number of parallel interactions with the reflection hologram and nonlinear mirror. After perhaps several seconds and 100 billion interactions, a steady-state pattern may develop with a marker bit that represents a minimum-Boolean-complexity classification of the input pattern. Computer simulations are presented that illustrate progress in understanding the behavior of this model and in developing a processor design that could have commanding and enduring performance advantages compared to current pattern classification techniques.

Torsion-inversion tunneling patterns in the CH-stretch vibrationally excited states of the G12 family of molecules including methylamine.

PubMed

Dawadi, Mahesh B; Bhatta, Ram S; Perry, David S

2013-12-19

Two torsion-inversion tunneling models (models I and II) are reported for the CH-stretch vibrationally excited states in the G12 family of molecules. The torsion and inversion tunneling parameters, h(2v) and h(3v), respectively, are combined with low-order coupling terms involving the CH-stretch vibrations. Model I is a group theoretical treatment starting from the symmetric rotor methyl CH-stretch vibrations; model II is an internal coordinate model including the local-local CH-stretch coupling. Each model yields predicted torsion-inversion tunneling patterns of the four symmetry species, A, B, E1, and E2, in the CH-stretch excited states. Although the predicted tunneling patterns for the symmetric CH-stretch excited state are the same as for the ground state, inverted tunneling patterns are predicted for the asymmetric CH-stretches. The qualitative tunneling patterns predicted are independent of the model type and of the particular coupling terms considered. In model I, the magnitudes of the tunneling splittings in the two asymmetric CH-stretch excited states are equal to half of that in the ground state, but in model II, they differ when the tunneling rate is fast. The model predictions are compared across the series of molecules methanol, methylamine, 2-methylmalonaldehyde, and 5-methyltropolone and to the available experimental data.

Study of Far—Field Directivity Pattern for Linear Arrays

NASA Astrophysics Data System (ADS)

Ana-Maria, Chiselev; Luminita, Moraru; Laura, Onose

2011-10-01

A model to calculate directivity pattern in far field is developed in this paper. Based on this model, the three-dimensional beam pattern is introduced and analyzed in order to investigate geometric parameters of linear arrays and their influences on the directivity pattern. Simulations in azimuthal plane are made to highlight the influence of transducers parameters, including number of elements and inter-element spacing. It is true that these parameters are important factors that influence the directivity pattern and the appearance of side-lobes for linear arrays.

In vitro burn model illustrating heat conduction patterns using compressed thermal papers.

PubMed

Lee, Jun Yong; Jung, Sung-No; Kwon, Ho

2015-01-01

To date, heat conduction from heat sources to tissue has been estimated by complex mathematical modeling. In the present study, we developed an intuitive in vitro skin burn model that illustrates heat conduction patterns inside the skin. This was composed of tightly compressed thermal papers with compression frames. Heat flow through the model left a trace by changing the color of thermal papers. These were digitized and three-dimensionally reconstituted to reproduce the heat conduction patterns in the skin. For standardization, we validated K91HG-CE thermal paper using a printout test and bivariate correlation analysis. We measured the papers' physical properties and calculated the estimated depth of heat conduction using Fourier's equation. Through contact burns of 5, 10, 15, 20, and 30 seconds on porcine skin and our burn model using a heated brass comb, and comparing the burn wound and heat conduction trace, we validated our model. The heat conduction pattern correlation analysis (intraclass correlation coefficient: 0.846, p < 0.001) and the heat conduction depth correlation analysis (intraclass correlation coefficient: 0.93, p < 0.001) showed statistically significant high correlations between the porcine burn wound and our model. Our model showed good correlation with porcine skin burn injury and replicated its heat conduction patterns. © 2014 by the Wound Healing Society.

Testing the limits of long-distance learning: Learning beyond a three-segment window

PubMed Central

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones since long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ('sh') and triggered a suffix that was either [−su] or [−∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. PMID:22303815

Dynamical spike solutions in a nonlocal model of pattern formation

NASA Astrophysics Data System (ADS)

Marciniak-Czochra, Anna; Härting, Steffen; Karch, Grzegorz; Suzuki, Kanako

2018-05-01

Coupling a reaction-diffusion equation with ordinary differential equa- tions (ODE) may lead to diffusion-driven instability (DDI) which, in contrast to the classical reaction-diffusion models, causes destabilization of both, constant solutions and Turing patterns. Using a shadow-type limit of a reaction-diffusion-ODE model, we show that in such cases the instability driven by nonlocal terms (a counterpart of DDI) may lead to formation of unbounded spike patterns.

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models

NASA Technical Reports Server (NTRS)

Keeler, James D.

1987-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models. [Sparse, Distributed Memory

NASA Technical Reports Server (NTRS)

Keeler, James D.

1988-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Model of an axially strained weakly guiding optical fiber modal pattern

NASA Technical Reports Server (NTRS)

Egalon, Claudio O.; Rogowski, Robert S.

1992-01-01

Axial strain can be determined by monitoring the modal pattern variation of an optical fiber. The results of a numerical model developed to calculate the modal pattern variation at the end of a weakly guiding optical fiber under axial strain is presented. Whenever an optical fiber is under stress, the optical path length, the index of refraction, and the propagation constants of each fiber mode change. In consequence, the modal phase term for the fields and the fiber output pattern are also modified. For multimode fibers, very complicated patterns result. The predicted patterns are presented, and an expression for the phase variation with strain is derived.

A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

2016-04-01

Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo.

Pattern formation in individual-based systems with time-varying parameters

NASA Astrophysics Data System (ADS)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Mountaintop island age determines species richness of boreal mammals in the American Southwest

USGS Publications Warehouse

Frey, J.K.; Bogan, M.A.; Yates, Terry L.

2007-01-01

Models that describe the mechanisms responsible for insular patterns of species richness include the equilibrium theory of island biogeography and the nonequilibrium vicariance model. The relative importance of dispersal or vicariance in structuring insular distribution patterns can be inferred from these models. Predictions of the alternative models were tested for boreal mammals in the American Southwest. Age of mountaintop islands of boreal habitat was determined by constructing a geographic cladogram based on characteristics of intervening valley barriers. Other independent variables included area and isolation of mountaintop islands. Island age was the most important predictor of species richness. In contrast with previous studies of species richness patterns in this system, these results supported the nonequilibrium vicariance model, which indicates that vicariance has been the primary determinant of species distribution patterns in this system.

Location Contexts of User Check-Ins to Model Urban Geo Life-Style Patterns

PubMed Central

Hasan, Samiul; Ukkusuri, Satish V.

2015-01-01

Geo-location data from social media offers us information, in new ways, to understand people's attitudes and interests through their activity choices. In this paper, we explore the idea of inferring individual life-style patterns from activity-location choices revealed in social media. We present a model to understand life-style patterns using the contextual information (e. g. location categories) of user check-ins. Probabilistic topic models are developed to infer individual geo life-style patterns from two perspectives: i) to characterize the patterns of user interests to different types of places and ii) to characterize the patterns of user visits to different neighborhoods. The method is applied to a dataset of Foursquare check-ins of the users from New York City. The co-existence of several location contexts and the corresponding probabilities in a given pattern provide useful information about user interests and choices. It is found that geo life-style patterns have similar items—either nearby neighborhoods or similar location categories. The semantic and geographic proximity of the items in a pattern reflects the hidden regularity in user preferences and location choice behavior. PMID:25970430

Cooperation in Harsh Environments and the Emergence of Spatial Patterns.

PubMed

Smaldino, Paul E

2013-11-01

This paper concerns the confluence of two important areas of research in mathematical biology: spatial pattern formation and cooperative dilemmas. Mechanisms through which social organisms form spatial patterns are not fully understood. Prior work connecting cooperation and pattern formation has often included unrealistic assumptions that shed doubt on the applicability of those models toward understanding real biological patterns. I investigated a more biologically realistic model of cooperation among social actors. The environment is harsh, so that interactions with cooperators are strictly needed to survive. Harshness is implemented via a constant energy deduction. I show that this model can generate spatial patterns similar to those seen in many naturally-occuring systems. Moreover, for each payoff matrix there is an associated critical value of the energy deduction that separates two distinct dynamical processes. In low-harshness environments, the growth of cooperator clusters is impeded by defectors, but these clusters gradually expand to form dense dendritic patterns. In very harsh environments, cooperators expand rapidly but defectors can subsequently make inroads to form reticulated patterns. The resulting web-like patterns are reminiscent of transportation networks observed in slime mold colonies and other biological systems.

How to Make a Neurocrystal: Modeling the developmental patterning of the fly's retina

NASA Astrophysics Data System (ADS)

Lubensky, David

2005-03-01

Animals' ability to create the complex patterns found in many organisms is an enduring source of wonder and a topic that has long drawn the interest of scientists of all stripes. Famously, it was an attempt to model developmental patterning that led to the discovery of the Turing instability. Here, we study one of the most remarkable and best-characterized examples of such pattern formation, the development of the fruit fly's compound eye. In the fly larva, a front of differentiation moves across the sheet of tissue that will become the adult retina. It leaves behind it a striking hexagonal array of cells marked by high levels of the protein Atonal. It has previously been noted that a standard activator-inhibitor model might explain this process [Meinhardt, 1992], but only recently has the basic genetic logic governing photoreceptor specification been deciphered [e.g. Frankfort and Mardon, 2002]. We build on these advances with the first model of retinal patterning based on experimentally verified interactions. Surprisingly, we conclude that a Turing-instability-based mechanism alone cannot reproduce the observed behavior. Instead, we propose that the pattern is generated primarily by a novel ``epitaxial'' process in which, as the front progresses, each newly-created row of unit cells acts as a template for the next one. A clear prediction of this model is that if the communication between successive rows is broken, even transiently, a striped pattern will appear. Preliminary experimental tests suggest that just such a phenomenon occurs in some mutants. Related patterning processes have been observed in systems as diverse as chick feather buds and vertebrate retinal ganglion cells [Pichaud, Treisman, and Desplan, 2001]; our model may thus describe an evolutionarily conserved module.

Is pigment patterning in fish skin determined by the Turing mechanism?

PubMed

Watanabe, Masakatsu; Kondo, Shigeru

2015-02-01

More than half a century ago, Alan Turing postulated that pigment patterns may arise from a mechanism that could be mathematically modeled based on the diffusion of two substances that interact with each other. Over the past 15 years, the molecular and genetic tools to verify this prediction have become available. Here, we review experimental studies aimed at identifying the mechanism underlying pigment pattern formation in zebrafish. Extensive molecular genetic studies in this model organism have revealed the interactions between the pigment cells that are responsible for the patterns. The mechanism discovered is substantially different from that predicted by the mathematical model, but it retains the property of 'local activation and long-range inhibition', a necessary condition for Turing pattern formation. Although some of the molecular details of pattern formation remain to be elucidated, current evidence confirms that the underlying mechanism is mathematically equivalent to the Turing mechanism. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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.

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.

Self-supervised ARTMAP.

PubMed

Amis, Gregory P; Carpenter, Gail A

2010-03-01

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative low-dimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.eu.edu/SSART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Patterns of Children's Adrenocortical Reactivity to Interparental Conflict and Associations with Child Adjustment: A Growth Mixture Modeling Approach

ERIC Educational Resources Information Center

Koss, Kalsea J.; George, Melissa R. W.; Davies, Patrick T.; Cicchetti, Dante; Cummings, E. Mark; Sturge-Apple, Melissa L.

2013-01-01

Examining children's physiological functioning is an important direction for understanding the links between interparental conflict and child adjustment. Utilizing growth mixture modeling, the present study examined children's cortisol reactivity patterns in response to a marital dispute. Analyses revealed three different patterns of cortisol…

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Spatio-temporal scan statistics for the detection of outbreaks involving common molecular subtypes: using human cases of Escherichia coli O157:H7 provincial PFGE pattern 8 (National Designation ECXAI.0001) in Alberta as an example.

PubMed

So, H C; Pearl, D L; von Königslöw, T; Louie, M; Chui, L; Svenson, L W

2013-08-01

Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed-field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space-time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space-time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space-time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space-time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern. © 2012 Blackwell Verlag GmbH.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

PubMed

Mendlik, Thomas; Gobiet, Andreas

In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

Immediate effects of modified landing pattern on a probabilistic tibial stress fracture model in runners.

PubMed

Chen, T L; An, W W; Chan, Z Y S; Au, I P H; Zhang, Z H; Cheung, R T H

2016-03-01

Tibial stress fracture is a common injury in runners. This condition has been associated with increased impact loading. Since vertical loading rates are related to the landing pattern, many heelstrike runners attempt to modify their footfalls for a lower risk of tibial stress fracture. Such effect of modified landing pattern remains unknown. This study examined the immediate effects of landing pattern modification on the probability of tibial stress fracture. Fourteen experienced heelstrike runners ran on an instrumented treadmill and they were given augmented feedback for landing pattern switch. We measured their running kinematics and kinetics during different landing patterns. Ankle joint contact force and peak tibial strains were estimated using computational models. We used an established mathematical model to determine the effect of landing pattern on stress fracture probability. Heelstrike runners experienced greater impact loading immediately after landing pattern switch (P<0.004). There was an increase in the longitudinal ankle joint contact force when they landed with forefoot (P=0.003). However, there was no significant difference in both peak tibial strains and the risk of tibial stress fracture in runners with different landing patterns (P>0.986). Immediate transitioning of the landing pattern in heelstrike runners may not offer timely protection against tibial stress fracture, despite a reduction of impact loading. Long-term effects of landing pattern switch remains unknown. Copyright © 2016 Elsevier Ltd. All rights reserved.

Model for screened, charge-regulated electrostatics of an eye lens protein: Bovine gammaB-crystallin

PubMed Central

Wahle, Christopher W.; Martini, K. Michael; Hollenbeck, Dawn M.; Langner, Andreas; Ross, David S.; Hamilton, John F.; Thurston, George M.

2018-01-01

We model screened, site-specific charge regulation of the eye lens protein bovine gammaB-crystallin (γ B) and study the probability distributions of its proton occupancy patterns. Using a simplified dielectric model, we solve the linearized Poisson-Boltzmann equation to calculate a 54 × 54 work-of-charging matrix, each entry being the modeled voltage at a given titratable site, due to an elementary charge at another site. The matrix quantifies interactions within patches of sites, including γB charge pairs. We model intrinsic pK values that would occur hypothetically in the absence of other charges, with use of experimental data on the dependence of pK values on aqueous solution conditions, the dielectric model, and literature values. We use Monte Carlo simulations to calculate a model grand-canonical partition function that incorporates both the work-of-charging and the intrinsic pK values for isolated γB molecules and we calculate the probabilities of leading proton occupancy configurations, for 4 < pH < 8 and Debye screening lengths from 6 to 20 Å. We select the interior dielectric value to model γB titration data. At pH 7.1 and Debye length 6.0 Å, on a given γB molecule the predicted top occupancy pattern is present nearly 20% of the time, and 90% of the time one or another of the first 100 patterns will be present. Many of these occupancy patterns differ in net charge sign as well as in surface voltage profile. We illustrate how charge pattern probabilities deviate from the multinomial distribution that would result from use of effective pK values alone and estimate the extents to which γB charge pattern distributions broaden at lower pH and narrow as ionic strength is lowered. These results suggest that for accurate modeling of orientation-dependent γB-γB interactions, consideration of numerous pairs of proton occupancy patterns will be needed. PMID:29346981

Model for screened, charge-regulated electrostatics of an eye lens protein: Bovine gammaB-crystallin.

PubMed

Wahle, Christopher W; Martini, K Michael; Hollenbeck, Dawn M; Langner, Andreas; Ross, David S; Hamilton, John F; Thurston, George M

2017-09-01

We model screened, site-specific charge regulation of the eye lens protein bovine gammaB-crystallin (γB) and study the probability distributions of its proton occupancy patterns. Using a simplified dielectric model, we solve the linearized Poisson-Boltzmann equation to calculate a 54×54 work-of-charging matrix, each entry being the modeled voltage at a given titratable site, due to an elementary charge at another site. The matrix quantifies interactions within patches of sites, including γB charge pairs. We model intrinsic pK values that would occur hypothetically in the absence of other charges, with use of experimental data on the dependence of pK values on aqueous solution conditions, the dielectric model, and literature values. We use Monte Carlo simulations to calculate a model grand-canonical partition function that incorporates both the work-of-charging and the intrinsic pK values for isolated γB molecules and we calculate the probabilities of leading proton occupancy configurations, for 4

Model for screened, charge-regulated electrostatics of an eye lens protein: Bovine gammaB-crystallin

NASA Astrophysics Data System (ADS)

Wahle, Christopher W.; Martini, K. Michael; Hollenbeck, Dawn M.; Langner, Andreas; Ross, David S.; Hamilton, John F.; Thurston, George M.

2017-09-01

We model screened, site-specific charge regulation of the eye lens protein bovine gammaB-crystallin (γ B ) and study the probability distributions of its proton occupancy patterns. Using a simplified dielectric model, we solve the linearized Poisson-Boltzmann equation to calculate a 54 ×54 work-of-charging matrix, each entry being the modeled voltage at a given titratable site, due to an elementary charge at another site. The matrix quantifies interactions within patches of sites, including γ B charge pairs. We model intrinsic p K values that would occur hypothetically in the absence of other charges, with use of experimental data on the dependence of p K values on aqueous solution conditions, the dielectric model, and literature values. We use Monte Carlo simulations to calculate a model grand-canonical partition function that incorporates both the work-of-charging and the intrinsic p K values for isolated γ B molecules and we calculate the probabilities of leading proton occupancy configurations, for 4

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.

Applications of Ontology Design Patterns in Biomedical Ontologies

PubMed Central

Mortensen, Jonathan M.; Horridge, Matthew; Musen, Mark A.; Noy, Natalya F.

2012-01-01

Ontology design patterns (ODPs) are a proposed solution to facilitate ontology development, and to help users avoid some of the most frequent modeling mistakes. ODPs originate from similar approaches in software engineering, where software design patterns have become a critical aspect of software development. There is little empirical evidence for ODP prevalence or effectiveness thus far. In this work, we determine the use and applicability of ODPs in a case study of biomedical ontologies. We encoded ontology design patterns from two ODP catalogs. We then searched for these patterns in a set of eight ontologies. We found five patterns of the 69 patterns. Two of the eight ontologies contained these patterns. While ontology design patterns provide a vehicle for capturing formally reoccurring models and best practices in ontology design, we show that today their use in a case study of widely used biomedical ontologies is limited. PMID:23304337

Inducing any virtual two-dimensional movement in humans by applying muscle tendon vibration.

PubMed

Roll, Jean-Pierre; Albert, Frédéric; Thyrion, Chloé; Ribot-Ciscar, Edith; Bergenheim, Mikael; Mattei, Benjamin

2009-02-01

In humans, tendon vibration evokes illusory sensation of movement. We developed a model mimicking the muscle afferent patterns corresponding to any two-dimensional movement and checked its validity by inducing writing illusory movements through specific sets of muscle vibrators. Three kinds of illusory movements were compared. The first was induced by vibration patterns copying the responses of muscle spindle afferents previously recorded by microneurography during imposed ankle movements. The two others were generated by the model. Sixteen different vibratory patterns were applied to 20 motionless volunteers in the absence of vision. After each vibration sequence, the participants were asked to name the corresponding graphic symbol and then to reproduce the illusory movement perceived. Results showed that the afferent patterns generated by the model were very similar to those recorded microneurographically during actual ankle movements (r=0.82). The model was also very efficient for generating afferent response patterns at the wrist level, if the preferred sensory directions of the wrist muscle groups were first specified. Using recorded and modeled proprioceptive patterns to pilot sets of vibrators placed at the ankle or wrist levels evoked similar illusory movements, which were correctly identified by the participants in three quarters of the trials. Our proprioceptive model, based on neurosensory data recorded in behaving humans, should then be a useful tool in fields of research such as sensorimotor learning, rehabilitation, and virtual reality.

Hydrologic controls on aperiodic spatial organization of the ridge-slough patterned landscape

NASA Astrophysics Data System (ADS)

Casey, Stephen T.; Cohen, Matthew J.; Acharya, Subodh; Kaplan, David A.; Jawitz, James W.

2016-11-01

A century of hydrologic modification has altered the physical and biological drivers of landscape processes in the Everglades (Florida, USA). Restoring the ridge-slough patterned landscape, a dominant feature of the historical system, is a priority but requires an understanding of pattern genesis and degradation mechanisms. Physical experiments to evaluate alternative pattern formation mechanisms are limited by the long timescales of peat accumulation and loss, necessitating model-based comparisons, where support for a particular mechanism is based on model replication of extant patterning and trajectories of degradation. However, multiple mechanisms yield a central feature of ridge-slough patterning (patch elongation in the direction of historical flow), limiting the utility of that characteristic for discriminating among alternatives. Using data from vegetation maps, we investigated the statistical features of ridge-slough spatial patterning (ridge density, patch perimeter, elongation, patch size distributions, and spatial periodicity) to establish more rigorous criteria for evaluating model performance and to inform controls on pattern variation across the contemporary system. Mean water depth explained significant variation in ridge density, total perimeter, and length : width ratios, illustrating an important pattern response to existing hydrologic gradients. Two independent analyses (2-D periodograms and patch size distributions) provide strong evidence against regular patterning, with the landscape exhibiting neither a characteristic wavelength nor a characteristic patch size, both of which are expected under conditions that produce regular patterns. Rather, landscape properties suggest robust scale-free patterning, indicating genesis from the coupled effects of local facilitation and a global negative feedback operating uniformly at the landscape scale. Critically, this challenges widespread invocation of scale-dependent negative feedbacks for explaining ridge-slough pattern origins. These results help discern among genesis mechanisms and provide an improved statistical description of the landscape that can be used to compare among model outputs, as well as to assess the success of future restoration projects.

Modeling of block copolymer dry etching for directed self-assembly lithography

NASA Astrophysics Data System (ADS)

Belete, Zelalem; Baer, Eberhard; Erdmann, Andreas

2018-03-01

Directed self-assembly (DSA) of block copolymers (BCP) is a promising alternative technology to overcome the limits of patterning for the semiconductor industry. DSA exploits the self-assembling property of BCPs for nano-scale manufacturing and to repair defects in patterns created during photolithography. After self-assembly of BCPs, to transfer the created pattern to the underlying substrate, selective etching of PMMA (poly (methyl methacrylate)) to PS (polystyrene) is required. However, the etch process to transfer the self-assemble "fingerprint" DSA patterns to the underlying layer is still a challenge. Using combined experimental and modelling studies increases understanding of plasma interaction with BCP materials during the etch process and supports the development of selective process that form well-defined patterns. In this paper, a simple model based on a generic surface model has been developed and an investigation to understand the etch behavior of PS-b-PMMA for Ar, and Ar/O2 plasma chemistries has been conducted. The implemented model is calibrated for etch rates and etch profiles with literature data to extract parameters and conduct simulations. In order to understand the effect of the plasma on the block copolymers, first the etch model was calibrated for polystyrene (PS) and poly (methyl methacrylate) (PMMA) homopolymers. After calibration of the model with the homopolymers etch rate, a full Monte-Carlo simulation was conducted and simulation results are compared with the critical-dimension (CD) and selectivity of etch profile measurement. In addition, etch simulations for lamellae pattern have been demonstrated, using the implemented model.

A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

PubMed

Revell, Christopher; Somveille, Marius

2017-08-29

In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

Pattern formation in a model for mountain pine beetle dispersal: linking model predictions to data.

PubMed

Strohm, S; Tyson, R C; Powell, J A

2013-10-01

Pattern formation occurs in a wide range of biological systems. This pattern formation can occur in mathematical models because of diffusion-driven instability or due to the interaction between reaction, diffusion, and chemotaxis. In this paper, we investigate the spatial pattern formation of attack clusters in a system for Mountain Pine Beetle. The pattern formation (aggregation) of the Mountain Pine Beetle in order to attack susceptible trees is crucial for their survival and reproduction. We use a reaction-diffusion equation with chemotaxis to model the interaction between Mountain Pine Beetle, Mountain Pine Beetle pheromones, and susceptible trees. Mathematical analysis is utilized to discover the spacing in-between beetle attacks on the susceptible landscape. The model predictions are verified by analysing aerial detection survey data of Mountain Pine Beetle Attack from the Sawtooth National Recreation Area. We find that the distance between Mountain Pine Beetle attack clusters predicted by our model closely corresponds to the observed attack data in the Sawtooth National Recreation Area. These results clarify the spatial mechanisms controlling the transition from incipient to epidemic populations and may lead to control measures which protect forests from Mountain Pine Beetle outbreak.

Frequency Distribution in Domestic Microwave Ovens and Its Influence on Heating Pattern.

PubMed

Luan, Donglei; Wang, Yifen; Tang, Juming; Jain, Deepali

2017-02-01

In this study, snapshots of operating frequency profiles of domestic microwave ovens were collected to reveal the extent of microwave frequency variations under different operation conditions. A computer simulation model was developed based on the finite difference time domain method to analyze the influence of the shifting frequency on heating patterns of foods in a microwave oven. The results showed that the operating frequencies of empty and loaded domestic microwave ovens varied widely even among ovens of the same model purchased on the same date. Each microwave oven had its unique characteristic operating frequencies, which were also affected by the location and shape of the load. The simulated heating patterns of a gellan gel model food when heated on a rotary plate agreed well with the experimental results, which supported the reliability of the developed simulation model. Simulation indicated that the heating patterns of a stationary model food load changed with the varying operating frequency. However, the heating pattern of a rotary model food load was not sensitive to microwave frequencies due to the severe edge heating overshadowing the effects of the frequency variations. © 2016 Institute of Food Technologists®.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates

NASA Astrophysics Data System (ADS)

Barberis, Lucas; Peruani, Fernando

2016-12-01

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit—due to the VC that breaks Newton's third law—various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving—locally polar—files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates.

PubMed

Barberis, Lucas; Peruani, Fernando

2016-12-09

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit-due to the VC that breaks Newton's third law-various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving-locally polar-files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Analysing the teleconnection systems affecting the climate of the Carpathian Basin

NASA Astrophysics Data System (ADS)

Kristóf, Erzsébet; Bartholy, Judit; Pongrácz, Rita

2017-04-01

Nowadays, the increase of the global average near-surface air temperature is unequivocal. Atmospheric low-frequency variabilities have substantial impacts on climate variables such as air temperature and precipitation. Therefore, assessing their effects is essential to improve global and regional climate model simulations for the 21st century. The North Atlantic Oscillation (NAO) is one of the best-known atmospheric teleconnection patterns affecting the Carpathian Basin in Central Europe. Besides NAO, we aim to analyse other interannual-to-decadal teleconnection patterns, which might have significant impacts on the Carpathian Basin, namely, the East Atlantic/West Russia pattern, the Scandinavian pattern, the Mediterranean Oscillation, and the North-Sea Caspian Pattern. For this purpose primarily the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-20C atmospheric reanalysis dataset and multivariate statistical methods are used. The indices of each teleconnection pattern and their correlations with temperature and precipitation will be calculated for the period of 1961-1990. On the basis of these data first the long range (i. e. seasonal and/or annual scale) forecast ability is evaluated. Then, we aim to calculate the same indices of the relevant teleconnection patterns for the historical and future simulations of Coupled Model Intercomparison Project Phase 5 (CMIP5) models and compare them against each other using statistical methods. Our ultimate goal is to examine all available CMIP5 models and evaluate their abilities to reproduce the selected teleconnection systems. Thus, climate predictions for the 21st century for the Carpathian Basin may be improved using the best-performing models among all CMIP5 model simulations.

Application of pattern mixture models to address missing data in longitudinal data analysis using SPSS.

PubMed

Son, Heesook; Friedmann, Erika; Thomas, Sue A

2012-01-01

Longitudinal studies are used in nursing research to examine changes over time in health indicators. Traditional approaches to longitudinal analysis of means, such as analysis of variance with repeated measures, are limited to analyzing complete cases. This limitation can lead to biased results due to withdrawal or data omission bias or to imputation of missing data, which can lead to bias toward the null if data are not missing completely at random. Pattern mixture models are useful to evaluate the informativeness of missing data and to adjust linear mixed model (LMM) analyses if missing data are informative. The aim of this study was to provide an example of statistical procedures for applying a pattern mixture model to evaluate the informativeness of missing data and conduct analyses of data with informative missingness in longitudinal studies using SPSS. The data set from the Patients' and Families' Psychological Response to Home Automated External Defibrillator Trial was used as an example to examine informativeness of missing data with pattern mixture models and to use a missing data pattern in analysis of longitudinal data. Prevention of withdrawal bias, omitted data bias, and bias toward the null in longitudinal LMMs requires the assessment of the informativeness of the occurrence of missing data. Missing data patterns can be incorporated as fixed effects into LMMs to evaluate the contribution of the presence of informative missingness to and control for the effects of missingness on outcomes. Pattern mixture models are a useful method to address the presence and effect of informative missingness in longitudinal studies.

Emergent Feature Structures: Harmony Systems in Exemplar Models of Phonology

ERIC Educational Resources Information Center

Cole, Jennifer

2009-01-01

In exemplar models of phonology, phonotactic constraints are modeled as emergent from patterns of high activation between units that co-occur with statistical regularity, or as patterns of low activation or inhibition between units that co-occur less frequently or not at all. Exemplar models posit no a "priori" formal or representational…

Dynamic model based on voltage transfer curve for pattern formation in dielectric barrier glow discharge

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

Li, Ben; He, Feng; Ouyang, Jiting, E-mail: jtouyang@bit.edu.cn

2015-12-15

Simulation work is very important for understanding the formation of self-organized discharge patterns. Previous works have witnessed different models derived from other systems for simulation of discharge pattern, but most of these models are complicated and time-consuming. In this paper, we introduce a convenient phenomenological dynamic model based on the basic dynamic process of glow discharge and the voltage transfer curve (VTC) to study the dielectric barrier glow discharge (DBGD) pattern. VTC is an important characteristic of DBGD, which plots the change of wall voltage after a discharge as a function of the initial total gap voltage. In the modeling,more » the combined effect of the discharge conditions is included in VTC, and the activation-inhibition effect is expressed by a spatial interaction term. Besides, the model reduces the dimensionality of the system by just considering the integration effect of current flow. All these greatly facilitate the construction of this model. Numerical simulations turn out to be in good accordance with our previous fluid modeling and experimental result.« less

The representation of order information in auditory-verbal short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2014-05-14

Here we investigate how order information is represented in auditory-verbal short-term memory (STM). We used fMRI and a serial recall task to dissociate neural activity patterns representing the phonological properties of the items stored in STM from the patterns representing their order. For this purpose, we analyzed fMRI activity patterns elicited by different item sets and different orderings of those items. These fMRI activity patterns were compared with the predictions made by positional and chaining models of serial order. The positional models encode associations between items and their positions in a sequence, whereas the chaining models encode associations between successive items and retain no position information. We show that a set of brain areas in the postero-dorsal stream of auditory processing store associations between items and order as predicted by a positional model. The chaining model of order representation generates a different pattern similarity prediction, which was shown to be inconsistent with the fMRI data. Our results thus favor a neural model of order representation that stores item codes, position codes, and the mapping between them. This study provides the first fMRI evidence for a specific model of order representation in the human brain. Copyright © 2014 the authors 0270-6474/14/346879-08$15.00/0.

Modeling Child–Nature Interaction in a Nature Preschool: A Proof of Concept

PubMed Central

Kahn, Peter H.; Weiss, Thea; Harrington, Kit

2018-01-01

This article provides a proof of concept for an approach to modeling child–nature interaction based on the idea of interaction patterns: characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur – in more domestic or wild forms – given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one’s body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal, and being outside in weather. These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model. PMID:29896143

A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells

PubMed Central

Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

2016-01-01

Plant leaf epidermal cells exhibit a jigsaw puzzle–like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo. PMID:27054467

An equilibrium-point model for fast, single-joint movement: I. Emergence of strategy-dependent EMG patterns.

PubMed

Latash, M L; Gottlieb, G L

1991-09-01

We describe a model for the regulation of fast, single-joint movements, based on the equilibrium-point hypothesis. Limb movement follows constant rate shifts of independently regulated neuromuscular variables. The independently regulated variables are tentatively identified as thresholds of a length sensitive reflex for each of the participating muscles. We use the model to predict EMG patterns associated with changes in the conditions of movement execution, specifically, changes in movement times, velocities, amplitudes, and moments of limb inertia. The approach provides a theoretical neural framework for the dual-strategy hypothesis, which considers certain movements to be results of one of two basic, speed-sensitive or speed-insensitive strategies. This model is advanced as an alternative to pattern-imposing models based on explicit regulation of timing and amplitudes of signals that are explicitly manifest in the EMG patterns.

Surface modeling method for aircraft engine blades by using speckle patterns based on the virtual stereo vision system

NASA Astrophysics Data System (ADS)

Yu, Zhijing; Ma, Kai; Wang, Zhijun; Wu, Jun; Wang, Tao; Zhuge, Jingchang

2018-03-01

A blade is one of the most important components of an aircraft engine. Due to its high manufacturing costs, it is indispensable to come up with methods for repairing damaged blades. In order to obtain a surface model of the blades, this paper proposes a modeling method by using speckle patterns based on the virtual stereo vision system. Firstly, blades are sprayed evenly creating random speckle patterns and point clouds from blade surfaces can be calculated by using speckle patterns based on the virtual stereo vision system. Secondly, boundary points are obtained in the way of varied step lengths according to curvature and are fitted to get a blade surface envelope with a cubic B-spline curve. Finally, the surface model of blades is established with the envelope curves and the point clouds. Experimental results show that the surface model of aircraft engine blades is fair and accurate.

Large-Scale Atmospheric Circulation Patterns Associated with Temperature Extremes as a Basis for Model Evaluation: Methodological Overview and Results

NASA Astrophysics Data System (ADS)

Loikith, P. C.; Broccoli, A. J.; Waliser, D. E.; Lintner, B. R.; Neelin, J. D.

2015-12-01

Anomalous large-scale circulation patterns often play a key role in the occurrence of temperature extremes. For example, large-scale circulation can drive horizontal temperature advection or influence local processes that lead to extreme temperatures, such as by inhibiting moderating sea breezes, promoting downslope adiabatic warming, and affecting the development of cloud cover. Additionally, large-scale circulation can influence the shape of temperature distribution tails, with important implications for the magnitude of future changes in extremes. As a result of the prominent role these patterns play in the occurrence and character of extremes, the way in which temperature extremes change in the future will be highly influenced by if and how these patterns change. It is therefore critical to identify and understand the key patterns associated with extremes at local to regional scales in the current climate and to use this foundation as a target for climate model validation. This presentation provides an overview of recent and ongoing work aimed at developing and applying novel approaches to identifying and describing the large-scale circulation patterns associated with temperature extremes in observations and using this foundation to evaluate state-of-the-art global and regional climate models. Emphasis is given to anomalies in sea level pressure and 500 hPa geopotential height over North America using several methods to identify circulation patterns, including self-organizing maps and composite analysis. Overall, evaluation results suggest that models are able to reproduce observed patterns associated with temperature extremes with reasonable fidelity in many cases. Model skill is often highest when and where synoptic-scale processes are the dominant mechanisms for extremes, and lower where sub-grid scale processes (such as those related to topography) are important. Where model skill in reproducing these patterns is high, it can be inferred that extremes are being simulated for plausible physical reasons, boosting confidence in future projections of temperature extremes. Conversely, where model skill is identified to be lower, caution should be exercised in interpreting future projections.

A single-cell spiking model for the origin of grid-cell patterns

PubMed Central

Kempter, Richard

2017-01-01

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity. PMID:28968386

The numerical model of multi-layer insulation with a defined wrapping pattern immersed in superfluid helium

NASA Astrophysics Data System (ADS)

Malecha, Ziemowit; Lubryka, Eliza

2017-11-01

The numerical model of thin layers, characterized by a defined wrapping pattern can be a crucial element of many computational problems related to engineering and science. A motivating example is found in multilayer electrical insulation, which is an important component of superconducting magnets and other cryogenic installations. The wrapping pattern of the insulation can significantly affect heat transport and the performance of the considered instruments. The major objective of this study is to develop the numerical boundary conditions (BC) needed to model the wrapping pattern of thin insulation. An example of the practical application of the proposed BC includes the heat transfer of Rutherford NbTi cables immersed in super-fluid helium (He II) across thin layers of electrical insulation. The proposed BC and a mathematical model of heat transfer in He II are implemented in the open source CFD toolbox OpenFOAM. The implemented mathematical model and the BC are compared in the experiments. The study confirms that the thermal resistance of electrical insulation can be lowered by implementing the proper wrapping pattern. The proposed BC can be useful in the study of new patterns for wrapping schemes. The work has been supported by statutory funds from Polish Ministry for Science and Higher Education for the year of 2017.

Short pauses in thalamic deep brain stimulation promote tremor and neuronal bursting.

PubMed

Swan, Brandon D; Brocker, David T; Hilliard, Justin D; Tatter, Stephen B; Gross, Robert E; Turner, Dennis A; Grill, Warren M

2016-02-01

We conducted intraoperative measurements of tremor during DBS containing short pauses (⩽50 ms) to determine if there is a minimum pause duration that preserves tremor suppression. Nine subjects with ET and thalamic DBS participated during IPG replacement surgery. Patterns of DBS included regular 130 Hz stimulation interrupted by 0, 15, 25 or 50 ms pauses. The same patterns were applied to a model of the thalamic network to quantify effects of pauses on activity of model neurons. All patterns of DBS decreased tremor relative to 'off'. Patterns with pauses generated less tremor reduction than regular high frequency DBS. The model revealed that rhythmic burst-driver inputs to thalamus were masked during DBS, but pauses in stimulation allowed propagation of bursting activity. The mean firing rate of bursting-type model neurons as well as the firing pattern entropy of model neurons were both strongly correlated with tremor power across stimulation conditions. The temporal pattern of stimulation influences the efficacy of thalamic DBS. Pauses in stimulation resulted in decreased tremor suppression indicating that masking of pathological bursting is a mechanism of thalamic DBS for tremor. Pauses in stimulation decreased the efficacy of open-loop DBS for suppression of tremor. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Simulating pattern-process relationships to validate landscape genetic models

Treesearch

A. J. Shirk; S. A. Cushman; E. L. Landguth

2012-01-01

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

Model of an axially strained weakly guiding optical fiber modal pattern

NASA Technical Reports Server (NTRS)

Egalon, Claudio O.; Rogowski, Robert S.

1991-01-01

Axial strain may be determined by monitoring the modal pattern variation of an optical fiber. In this paper we present the results of a numerical model that has been developed to calculate the modal pattern variation at the end of a weakly guiding optical fiber under axial strain. Whenever an optical fiber is under stress, the optical path length, the index of refraction and the propagation constants of each fiber mode change. In consequence, the modal phase term of the fields and the fiber output pattern are also modified. For multimode fibers, very complicated patterns result. The predicted patterns are presented, and an expression for the phase variation with strain is derived.

Transregional Collaborative Research Centre 32: Patterns in Soil-Vegetation-Atmosphere-Systems

NASA Astrophysics Data System (ADS)

Masbou, M.; Simmer, C.; Kollet, S.; Boessenkool, K.; Crewell, S.; Diekkrüger, B.; Huber, K.; Klitzsch, N.; Koyama, C.; Vereecken, H.

2012-04-01

The soil-vegetation-atmosphere system is characterized by non-linear exchanges of mass, momentum and energy with complex patterns, structures and processes that act at different temporal and spatial scales. Under the TR32 framework, the characterisation of these structures and patterns will lead to a deeper qualitative and quantitative understanding of the SVA system, and ultimately to better predictions of the SVA state. Research in TR32 is based on three methodological pillars: Monitoring, Modelling and Data Assimilation. Focusing our research on the Rur Catchment (Germany), patterns are monitored since 2006 continuously using existing and novel geophysical and remote sensing techniques from the local to the catchment scale based on ground penetrating radar methods, induced polarization, radiomagnetotellurics, electrical resistivity tomography, boundary layer scintillometry, lidar techniques, cosmic-ray, microwave radiometry, and precipitation radars with polarization diversity. Modelling approaches involve development of scaled consistent coupled model platform: high resolution numerical weather prediction (NWP; 400m) and hydrological models (few meters). In the second phase (2011-2014), the focus is on the integration of models from the groundwater to the atmosphere for both the m- and km-scale and the extension of the experimental monitoring in respect to vegetation. The coupled modelling platform is based on the atmospheric model COSMO, the land surface model CLM and the hydrological model ParFlow. A scale consistent two-way coupling is performed using the external OASIS coupler. Example work includes the transfer of laboratory methods to the field; the measurements of patterns of soil-carbon, evapotranspiration and respiration measured in the field; catchment-scale modeling of exchange processes and the setup of an atmospheric boundary layer monitoring network. These modern and predominantly non-invasive measurement techniques are exploited in combination with advanced modelling systems by data assimilation to yield improved numerical models for the prediction of water-, energy and CO2-transfer by accounting for the patterns occurring at various scales.

Integument pattern formation involves genetic and epigenetic controls: feather arrays simulated by digital hormone models

PubMed Central

Jiang, Ting-Xin; Widelitz, Randall B.; Shen, Wei-Min; Will, Peter; Wu, Da-Yu; Lin, Chih-Min; Jung, Han-Sung; Chuong, Cheng-Ming

2015-01-01

Pattern formation is a fundamental morphogenetic process. Models based on genetic and epigenetic control have been proposed but remain controversial. Here we use feather morphogenesis for further evaluation. Adhesion molecules and/or signaling molecules were first expressed homogenously in feather tracts (restrictive mode, appear earlier) or directly in bud or inter-bud regions (de novo mode, appear later). They either activate or inhibit bud formation, but paradoxically co-localize in the bud. Using feather bud reconstitution, we showed that completely dissociated cells can reform periodic patterns without reference to previous positional codes. The patterning process has the characteristics of being self-organizing, dynamic and plastic. The final pattern is an equilibrium state reached by competition, and the number and size of buds can be altered based on cell number and activator/inhibitor ratio, respectively. We developed a Digital Hormone Model which consists of (1) competent cells without identity that move randomly in a space, (2) extracellular signaling hormones which diffuse by a reaction-diffusion mechanism and activate or inhibit cell adhesion, and (3) cells which respond with topological stochastic actions manifested as changes in cell adhesion. Based on probability, the results are cell clusters arranged in dots or stripes. Thus genetic control provides combinational molecular information which defines the properties of the cells but not the final pattern. Epigenetic control governs interactions among cells and their environment based on physical-chemical rules (such as those described in the Digital Hormone Model). Complex integument patterning is the sum of these two components of control and that is why integument patterns are usually similar but non-identical. These principles may be shared by other pattern formation processes such as barb ridge formation, fingerprints, pigmentation patterning, etc. The Digital Hormone Model can also be applied to swarming robot navigation, reaching intelligent automata and representing a self-re-configurable type of control rather than a follow-the-instruction type of control. PMID:15272377

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.

Statistical modeling of the Internet traffic dynamics: To which extent do we need long-term correlations?

NASA Astrophysics Data System (ADS)

Markelov, Oleg; Nguyen Duc, Viet; Bogachev, Mikhail

2017-11-01

Recently we have suggested a universal superstatistical model of user access patterns and aggregated network traffic. The model takes into account the irregular character of end user access patterns on the web via the non-exponential distributions of the local access rates, but neglects the long-term correlations between these rates. While the model is accurate for quasi-stationary traffic records, its performance under highly variable and especially non-stationary access dynamics remains questionable. In this paper, using an example of the traffic patterns from a highly loaded network cluster hosting the website of the 1998 FIFA World Cup, we suggest a generalization of the previously suggested superstatistical model by introducing long-term correlations between access rates. Using queueing system simulations, we show explicitly that this generalization is essential for modeling network nodes with highly non-stationary access patterns, where neglecting long-term correlations leads to the underestimation of the empirical average sojourn time by several decades under high throughput utilization.

Objective Auscultation of TCM Based on Wavelet Packet Fractal Dimension and Support Vector Machine.

PubMed

Yan, Jian-Jun; Guo, Rui; Wang, Yi-Qin; Liu, Guo-Ping; Yan, Hai-Xia; Xia, Chun-Ming; Shen, Xiaojing

2014-01-01

This study was conducted to illustrate that auscultation features based on the fractal dimension combined with wavelet packet transform (WPT) were conducive to the identification the pattern of syndromes of Traditional Chinese Medicine (TCM). The WPT and the fractal dimension were employed to extract features of auscultation signals of 137 patients with lung Qi-deficient pattern, 49 patients with lung Yin-deficient pattern, and 43 healthy subjects. With these features, the classification model was constructed based on multiclass support vector machine (SVM). When all auscultation signals were trained by SVM to decide the patterns of TCM syndromes, the overall recognition rate of model was 79.49%; when male and female auscultation signals were trained, respectively, to decide the patterns, the overall recognition rate of model reached 86.05%. The results showed that the methods proposed in this paper were effective to analyze auscultation signals, and the performance of model can be greatly improved when the distinction of gender was considered.

Spatiotemporal pattern formation in a prey-predator model under environmental driving forces

NASA Astrophysics Data System (ADS)

Sirohi, Anuj Kumar; Banerjee, Malay; Chakraborti, Anirban

2015-09-01

Many existing studies on pattern formation in the reaction-diffusion systems rely on deterministic models. However, environmental noise is often a major factor which leads to significant changes in the spatiotemporal dynamics. In this paper, we focus on the spatiotemporal patterns produced by the predator-prey model with ratio-dependent functional response and density dependent death rate of predator. We get the reaction-diffusion equations incorporating the self-diffusion terms, corresponding to random movement of the individuals within two dimensional habitats, into the growth equations for the prey and predator population. In order to have the noise added model, small amplitude heterogeneous perturbations to the linear intrinsic growth rates are introduced using uncorrelated Gaussian white noise terms. For the noise added system, we then observe spatial patterns for the parameter values lying outside the Turing instability region. With thorough numerical simulations we characterize the patterns corresponding to Turing and Turing-Hopf domain and study their dependence on different system parameters like noise-intensity, etc.

Radiation pattern of a borehole radar antenna

USGS Publications Warehouse

Ellefsen, K.J.; Wright, D.L.

2005-01-01

The finite-difference time-domain method was used to simulate radar waves that were generated by a transmitting antenna inside a borehole. The simulations were of four different models that included features such as a water-filled borehole and an antenna with resistive loading. For each model, radiation patterns for the far-field region were calculated. The radiation patterns show that the amplitude of the radar wave was strongly affected by its frequency, the water-filled borehole, the resistive loading of the antenna, and the external metal parts of the antenna (e.g., the cable head and the battery pack). For the models with a water-filled borehole, their normalized radiation patterns were practically identical to the normalized radiation pattern of a finite-length electric dipole when the wavelength in the formation was significantly greater than the total length of the radiating elements of the model antenna. The minimum wavelength at which this criterion was satisfied depended upon the features of the antenna, especially its external metal parts. ?? 2005 Society of Exploration Geophysicists. All rights reserved.

Objective Auscultation of TCM Based on Wavelet Packet Fractal Dimension and Support Vector Machine

PubMed Central

Yan, Jian-Jun; Wang, Yi-Qin; Liu, Guo-Ping; Yan, Hai-Xia; Xia, Chun-Ming; Shen, Xiaojing

2014-01-01

This study was conducted to illustrate that auscultation features based on the fractal dimension combined with wavelet packet transform (WPT) were conducive to the identification the pattern of syndromes of Traditional Chinese Medicine (TCM). The WPT and the fractal dimension were employed to extract features of auscultation signals of 137 patients with lung Qi-deficient pattern, 49 patients with lung Yin-deficient pattern, and 43 healthy subjects. With these features, the classification model was constructed based on multiclass support vector machine (SVM). When all auscultation signals were trained by SVM to decide the patterns of TCM syndromes, the overall recognition rate of model was 79.49%; when male and female auscultation signals were trained, respectively, to decide the patterns, the overall recognition rate of model reached 86.05%. The results showed that the methods proposed in this paper were effective to analyze auscultation signals, and the performance of model can be greatly improved when the distinction of gender was considered. PMID:24883068

A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

PubMed Central

Refahi, Yassin; Brunoud, Géraldine; Farcot, Etienne; Jean-Marie, Alain; Pulkkinen, Minna; Vernoux, Teva; Godin, Christophe

2016-01-01

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems. DOI: http://dx.doi.org/10.7554/eLife.14093.001 PMID:27380805

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar.

PubMed

Brown, Jason L; Cameron, Alison; Yoder, Anne D; Vences, Miguel

2014-10-09

Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

Modeling and forecasting rainfall patterns of southwest monsoons in North-East India as a SARIMA process

NASA Astrophysics Data System (ADS)

Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-02-01

Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North-East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

Repetition Is the Feature Behind the Attentional Bias for Recognizing Threatening Patterns.

PubMed

Shabbir, Maryam; Zon, Adelynn M Y; Thuppil, Vivek

2018-01-01

Animals attend to what is relevant in order to behave in an effective manner and succeed in their environments. In several nonhuman species, there is an evolved bias for attending to patterns indicative of threats in the natural environment such as dangerous animals. Because skins of many dangerous animals are typically repetitive, we propose that repetition is the key feature enabling recognition of evolutionarily important threats. The current study consists of two experiments where we measured participants' reactions to pictures of male and female models wearing clothing of various repeating (leopard skin, snakeskin, and floral print) and nonrepeating (camouflage, shiny, and plain) patterns. In Experiment 1, when models wearing patterns were presented side by side with total fixation duration as the measure, the repeating floral pattern was the most provocative, with total fixation duration significantly longer than all other patterns. Leopard and snakeskin patterns had total fixation durations that were significantly longer than the plain pattern. In Experiment 2, we employed a visual-search task where participants were required to find models wearing the various patterns in a setting of a crowded airport terminal. Participants detected leopard skin pattern and repetitive floral pattern significantly faster than two of the nonpatterned clothing styles. Our experimental findings support the hypothesis that repetition of specific visual features might facilitate target detection, especially those characterizing evolutionary important threats. Our findings that intricate, but nonthreatening repeating patterns can have similar attention-grabbing properties to animal skin patterns have important implications for the fashion industry and wildlife trade.

Testing the limits of long-distance learning: learning beyond a three-segment window.

PubMed

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones because long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant-harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ("sh") and triggered a suffix that was either [-su] or [-∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. Copyright © 2012 Cognitive Science Society, Inc.

A model of the transverse modes of stable and unstable porro-prism resonators using symmetry considerations

NASA Astrophysics Data System (ADS)

Burger, Liesl; Forbes, Andrew

2007-09-01

A simple model of a Porro prism laser resonator has been found to correctly predict the formation of the "petal" mode patterns typical of these resonators. A geometrical analysis of the petals suggests that these petals are the lowest-order modes of this type of resonator. Further use of the model reveals the formation of more complex beam patterns, and the nature of these patterns is investigated. Also, the output of stable and unstable resonator modes is presented.

Branching Patterns and Stepped Leaders in an Electric-Circuit Model for Creeping Discharge

NASA Astrophysics Data System (ADS)

Hidetsugu Sakaguchi,; Sahim M. Kourkouss,

2010-06-01

We construct a two-dimensional electric circuit model for creeping discharge. Two types of discharge, surface corona and surface leader, are modeled by a two-step function of conductance. Branched patterns of surface leaders surrounded by the surface corona appear in numerical simulation. The fractal dimension of branched discharge patterns is calculated by changing voltage and capacitance. We find that surface leaders often grow stepwise in time, as is observed in lightning leaders of thunder.

Investigation occurrences of turing pattern in Schnakenberg and Gierer-Meinhardt equation

NASA Astrophysics Data System (ADS)

Nurahmi, Annisa Fitri; Putra, Prama Setia; Nuraini, Nuning

2018-03-01

There are several types of animals with unusual, varied patterns on their skin. The skin pigmentation system influences this in the animal. On the other side, in 1950 Alan Turing formulated the mathematical theory of morphogenesis, where this model can bring up a spatial pattern or so-called Turing pattern. This research discusses the identification of Turing's model that can produce animal skin pattern. Investigations conducted on two types of equations: Schnakenberg (1979), and Gierer-Meinhardt (1972). In this research, parameters were explored to produce Turing's patter on that both equation. The numerical simulation in this research done using Neumann Homogeneous and Dirichlet Homogeneous boundary condition. The investigation of Schnakenberg equation yielded poison dart frog (Andinobates dorisswansonae) and ladybird (Coccinellidae septempunctata) pattern while skin fish pattern was showed by Gierer-Meinhardt equation.

A phenological mid-domain effect in flowering diversity.

PubMed

Morales, Manuel A; Dodge, Gary J; Inouye, David W

2005-01-01

In this paper, we test the mid-domain hypothesis as an explanation for observed patterns of flowering diversity in two sub-alpine communities of insect-pollinated plants. Observed species richness patterns showed an early-season increase in richness, a mid-season peak, and a late-season decrease. We show that a "mid-domain" null model can qualitatively match this pattern of flowering species richness, with R(2) values typically greater than 60%. We find significant or marginally significant departures from expected patterns of diversity for only 3 out of 12 year-site combinations. On the other hand, we do find a consistent pattern of departure when comparing observed versus null-model predicted flowering diversity averaged across years. Our results therefore support the hypothesis that ecological factors shape patterns of flowering phenology, but that the strength or nature of these environmental forcings may differ between years or the two habitats we studied, or may depend on species-specific characteristics of these plant communities. We conclude that mid-domain null models provide an important baseline from which to test departure of expected patterns of flowering diversity across temporal domains. Geometric constraints should be included first in the list of factors that drive seasonal patterns of flowering diversity.

Computation of the intensities of parametric holographic scattering patterns in photorefractive crystals.

PubMed

Schwalenberg, Simon

2005-06-01

The present work represents a first attempt to perform computations of output intensity distributions for different parametric holographic scattering patterns. Based on the model for parametric four-wave mixing processes in photorefractive crystals and taking into account realistic material properties, we present computed images of selected scattering patterns. We compare these calculated light distributions to the corresponding experimental observations. Our analysis is especially devoted to dark scattering patterns as they make high demands on the underlying model.

Heteroassociative storage of hippocampal pattern sequences in the CA3 subregion

PubMed Central

Recio, Renan S.; Reyes, Marcelo B.

2018-01-01

Background Recent research suggests that the CA3 subregion of the hippocampus has properties of both autoassociative network, due to its ability to complete partial cues, tolerate noise, and store associations between memories, and heteroassociative one, due to its ability to store and retrieve sequences of patterns. Although there are several computational models of the CA3 as an autoassociative network, more detailed evaluations of its heteroassociative properties are missing. Methods We developed a model of the CA3 subregion containing 10,000 integrate-and-fire neurons with both recurrent excitatory and inhibitory connections, and which exhibits coupled oscillations in the gamma and theta ranges. We stored thousands of pattern sequences using a heteroassociative learning rule with competitive synaptic scaling. Results We showed that a purely heteroassociative network model can (i) retrieve pattern sequences from partial cues with external noise and incomplete connectivity, (ii) achieve homeostasis regarding the number of connections per neuron when many patterns are stored when using synaptic scaling, (iii) continuously update the set of retrievable patterns, guaranteeing that the last stored patterns can be retrieved and older ones can be forgotten. Discussion Heteroassociative networks with synaptic scaling rules seem sufficient to achieve many desirable features regarding connectivity homeostasis, pattern sequence retrieval, noise tolerance and updating of the set of retrievable patterns. PMID:29312826

Self-organized pattern dynamics of somitogenesis model in embryos

NASA Astrophysics Data System (ADS)

Guan, Linan; Shen, Jianwei

2018-09-01

Somitogenesis, the sequential formation of a periodic pattern along the anteroposterior axis of vertebrate embryos, is one of the most obvious examples of the segmental patterning processes that take place during embryogenesis and also one of the major unresolved events in developmental biology. In this paper, we investigate the effect of diffusion on pattern formation use a modified two dimensional model which can be used to explain somitogenesis during embryonic development. This model is suitable for exploring a design space of somitogenesis and can explain many aspects of somitogenesis that previous models cannot. In the present paper, by analyzing the local linear stability of the equation, we acquired the conditions of Hopf bifurcation and Turing bifurcation. In addition, the amplitude equation near the Turing bifurcation point is obtained by using the methods of multi-scale expansion and symmetry analysis. By analyzing the stability of the amplitude equation, we know that there are various complex phenomena, including Spot pattern, mixture of spot-stripe patterns and labyrinthine. Finally, numerical simulation are given to verify the correctness of our theoretical results. Somitogenesis occupies an important position in the process of biological development, and as a pattern process can be used to investigate many aspects of embryogenesis. Therefore, our study helps greatly to cell differentiation, gene expression and embryonic development. What is more, it is of great significance for the diagnosis and treatment of human diseases to study the related knowledge of model biology.

A competitive complex formation mechanism underlies trichome patterning on Arabidopsis leaves

PubMed Central

Digiuni, Simona; Schellmann, Swen; Geier, Florian; Greese, Bettina; Pesch, Martina; Wester, Katja; Dartan, Burcu; Mach, Valerie; Srinivas, Bhylahalli Purushottam; Timmer, Jens; Fleck, Christian; Hulskamp, Martin

2008-01-01

Trichome patterning in Arabidopsis serves as a model system for de novo pattern formation in plants. It is thought to typify the theoretical activator–inhibitor mechanism, although this hypothesis has never been challenged by a combined experimental and theoretical approach. By integrating the key genetic and molecular data of the trichome patterning system, we developed a new theoretical model that allows the direct testing of the effect of experimental interventions and in the prediction of patterning phenotypes. We show experimentally that the trichome inhibitor TRIPTYCHON is transcriptionally activated by the known positive regulators GLABRA1 and GLABRA3. Further, we demonstrate by particle bombardment of protein fusions with GFP that TRIPTYCHON and CAPRICE but not GLABRA1 and GLABRA3 can move between cells. Finally, theoretical considerations suggest promoter swapping and basal overexpression experiments by means of which we are able to discriminate three biologically meaningful variants of the trichome patterning model. Our study demonstrates that the mutual interplay between theory and experiment can reveal a new level of understanding of how biochemical mechanisms can drive biological patterning processes. PMID:18766177

A new framework for an electrophotographic printer model

NASA Astrophysics Data System (ADS)

Colon-Lopez, Fermin A.

Digital halftoning is a printing technology that creates the illusion of continuous tone images for printing devices such as electrophotographic printers that can only produce a limited number of tone levels. Digital halftoning works because the human visual system has limited spatial resolution which blurs the printed dots of the halftone image, creating the gray sensation of a continuous tone image. Because the printing process is imperfect it introduces distortions to the halftone image. The quality of the printed image depends, among other factors, on the complex interactions between the halftone image, the printer characteristics, the colorant, and the printing substrate. Printer models are used to assist in the development of new types of halftone algorithms that are designed to withstand the effects of printer distortions. For example, model-based halftone algorithms optimize the halftone image through an iterative process that integrates a printer model within the algorithm. The two main goals of a printer model are to provide accurate estimates of the tone and of the spatial characteristics of the printed halftone pattern. Various classes of printer models, from simple tone calibrations to complex mechanistic models, have been reported in the literature. Existing models have one or more of the following limiting factors: they only predict tone reproduction, they depend on the halftone pattern, they require complex calibrations or complex calculations, they are printer specific, they reproduce unrealistic dot structures, and they are unable to adapt responses to new data. The two research objectives of this dissertation are (1) to introduce a new framework for printer modeling and (2) to demonstrate the feasibility of such a framework in building an electrophotographic printer model. The proposed framework introduces the concept of modeling a printer as a texture transformation machine. The basic premise is that modeling the texture differences between the output printed images and the input images encompasses all printing distortions. The feasibility of the framework was tested with a case study modeling a monotone electrophotographic printer. The printer model was implemented as a bank of feed-forward neural networks, each one specialized in modeling a group of textural features of the printed halftone pattern. The textural features were obtained using a parametric representation of texture developed from a multiresolution decomposition proposed by other researchers. The textural properties of halftone patterns were analyzed and the key texture parameters to be modeled by the bank were identified. Guidelines for the multiresolution texture decomposition and the model operational parameters and operational limits were established. A method for the selection of training sets based on the morphological properties of the halftone patterns was also developed. The model is fast and has the capability to continue to learn with additional training. The model can be easily implemented because it only requires a calibrated scanner. The model was tested with halftone patterns representing a range of spatial characteristics found in halftoning. Results show that the model provides accurate predictions for the tone and the spatial characteristics when modeling halftone patterns individually and it provides close approximations when modeling multiple halftone patterns simultaneously. The success of the model justifies continued research of this new printer model framework.

[Analysis of dietary pattern and diabetes mellitus influencing factors identified by classification tree model in adults of Fujian].

PubMed

Yu, F L; Ye, Y; Yan, Y S

2017-05-10

Objective: To find out the dietary patterns and explore the relationship between environmental factors (especially dietary patterns) and diabetes mellitus in the adults of Fujian. Methods: Multi-stage sampling method were used to survey residents aged ≥18 years by questionnaire, physical examination and laboratory detection in 10 disease surveillance points in Fujian. Factor analysis was used to identify the dietary patterns, while logistic regression model was applied to analyze relationship between dietary patterns and diabetes mellitus, and classification tree model was adopted to identify the influencing factors for diabetes mellitus. Results: There were four dietary patterns in the population, including meat, plant, high-quality protein, and fried food and beverages patterns. The result of logistic analysis showed that plant pattern, which has higher factor loading of fresh fruit-vegetables and cereal-tubers, was a protective factor for non-diabetes mellitus. The risk of diabetes mellitus in the population at T2 and T3 levels of factor score were 0.727 (95 %CI: 0.561-0.943) times and 0.736 (95 %CI : 0.573-0.944) times higher, respectively, than those whose factor score was in lowest quartile. Thirteen influencing factors and eleven group at high-risk for diabetes mellitus were identified by classification tree model. The influencing factors were dyslipidemia, age, family history of diabetes, hypertension, physical activity, career, sex, sedentary time, abdominal adiposity, BMI, marital status, sleep time and high-quality protein pattern. Conclusion: There is a close association between dietary patterns and diabetes mellitus. It is necessary to promote healthy and reasonable diet, strengthen the monitoring and control of blood lipids, blood pressure and body weight, and have good lifestyle for the prevention and control of diabetes mellitus.

Perpetual Model Validation

DTIC Science & Technology

2017-03-01

models of software execution, for example memory access patterns, to check for security intrusions. Additional research was performed to tackle the...considered using indirect models of software execution, for example memory access patterns, to check for security intrusions. Additional research ...deterioration for example , no longer corresponds to the model used during verification time. Finally, the research looked at ways to combine hybrid systems

Evaluating the habitat capability model for Merriam's turkeys

Treesearch

Mark A. Rumble; Stanley H. Anderson

1995-01-01

Habitat capability (HABCAP) models for wildlife assist land managers in predicting the consequences of their management decisions. Models must be tested and refined prior to using them in management planning. We tested the predicted patterns of habitat selection of the R2 HABCAP model using observed patterns of habitats selected by radio-marked Merriam’s turkey (

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

PubMed

Marjaninejad, Ali; Finley, James M

2016-08-01

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

Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns

PubMed Central

Chérel, Guillaume; Cottineau, Clémentine; Reuillon, Romain

2015-01-01

Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic. PMID:26368917

Some considerations on the use of ecological models to predict species' geographic distributions

USGS Publications Warehouse

Peterjohn, B.G.

2001-01-01

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Clustering of Synoptic Pattern over the Korean Peninsula from Meteorological Models

NASA Astrophysics Data System (ADS)

Kim, Jinah; Heo, Kiyoung; Choi, Jungwoon; Jung, Sanghoon

2017-04-01

Numerical modeling data on meteorological and ocean science is one of example of big geographic data sources. The properties of the data including the volume, variety, and dynamic aspects pose new challenges for geographic visualization, and visual geoanalytics using big data analysis using machine learning method. A combination of algorithmic and visual approaches that make sense of large volumes of various types of spatiotemporal data are required to gain knowledge about complex phenomena. In the East coast of Korea, it is suffering from property damages and human causalities due to abnormal high waves (swell-like high-height waves). It is known to be caused by local meteorological conditions on the East Sea of Korean Peninsula in previous research and they proposed three kinds of pressure patterns that generate abnormal high waves. However, they cannot describe all kinds of pressure patterns that generate abnormal high waves. In our study, we propose unsupervised machine learning method for pattern clustering and applied it to classify a pattern which has occurred abnormal high waves using numerical meteorological model's reanalysis data from 2000 to 2015 and past historical records of accidents by abnormal high waves. About 25,000 patterns of total spatial distribution of sea surface pressure are clustered into 30 patterns and they are classified into seasonal sea level pressure patterns based on meteorological characteristics of Korean peninsula. Moreover, in order to determine the representative patterns which occurs abnormal high waves, we classified it again using historical accidents cases among the winter season pressure patterns. In this work, we clustered synoptic pattern over the Korean Peninsula in meteorological modeling reanalysis data and we could understand a seasonal variation through identifying the occurrence of clustered synoptic pattern. For the future work, we have to identify the relationship of wave modeling data for better understanding of abnormal high waves and we will develop pattern decision system to predict abnormal high waves in advances. This research was a part of the project titled "Development of Korea Operational Oceanographic System (KOOS), Phase 2" and "Investigation of Large Swell Waves and Rip currents and Development of The Disaster Response System," funded by the Ministry of Oceans & Fisheries Korea (Grant PM59691 and PM59240).

Modelling of Folding Patterns in Flat Membranes and Cylinders by Origami

NASA Astrophysics Data System (ADS)

Nojima, Taketoshi

This paper describes folding methods of thin flat sheets as well as cylindrical shells by modelling folding patterns through Japanese traditional Origami technique. New folding patterns have been devised in thin flat squared or circular membrane by modifying so called Miura-Ori in Japan (one node with 4 folding lines). Some folding patterns in cylindrical shells have newly been developed including spiral configurations. Devised foldable cylindrical shells were made by using polymer sheets, and it has been assured that they can be folded quite well. The devised models will make it possible to construct foldable/deployable space structures as well as to manufacture foldable industrial products and living goods, e. g., bottles for soft drinks.

Phase demodulation method from a single fringe pattern based on correlation with a polynomial form.

PubMed

Robin, Eric; Valle, Valéry; Brémand, Fabrice

2005-12-01

The method presented extracts the demodulated phase from only one fringe pattern. Locally, this method approaches the fringe pattern morphology with the help of a mathematical model. The degree of similarity between the mathematical model and the real fringe is estimated by minimizing a correlation function. To use an optimization process, we have chosen a polynomial form such as a mathematical model. However, the use of a polynomial form induces an identification procedure with the purpose of retrieving the demodulated phase. This method, polynomial modulated phase correlation, is tested on several examples. Its performance, in terms of speed and precision, is presented on very noised fringe patterns.

A mathematical basis for plant patterning derived from physico-chemical phenomena.

PubMed

Beleyur, Thejasvi; Abdul Kareem, Valiya Kadavu; Shaji, Anil; Prasad, Kalika

2013-04-01

The position of leaves and flowers along the stem axis generates a specific pattern, known as phyllotaxis. A growing body of evidence emerging from recent computational modeling and experimental studies suggests that regulators controlling phyllotaxis are chemical, e.g. the plant growth hormone auxin and its dynamic accumulation pattern by polar auxin transport, and physical, e.g. mechanical properties of the cell. Here we present comprehensive views on how chemical and physical properties of cells regulate the pattern of leaf initiation. We further compare different computational modeling studies to understand their scope in reproducing the observed patterns. Despite a plethora of experimental studies on phyllotaxis, understanding of molecular mechanisms of pattern initiation in plants remains fragmentary. Live imaging of growth dynamics and physicochemical properties at the shoot apex of mutants displaying stable changes from one pattern to another should provide mechanistic insights into organ initiation patterns. Copyright © 2013 WILEY Periodicals, Inc.

Patterns of Children’s Adrenocortical Reactivity to Interparental Conflict and Associations with Child Adjustment: A Growth Mixture Modeling Approach

PubMed Central

Koss, Kalsea J.; George, Melissa R. W.; Davies, Patrick T.; Cicchetti, Dante; Cummings, E. Mark; Sturge-Apple, Melissa L.

2013-01-01

Examining children’s physiological functioning is an important direction for understanding the links between interparental conflict and child adjustment. Utilizing growth mixture modeling, the present study examined children’s cortisol reactivity patterns in response to a marital dispute. Analyses revealed three different patterns of cortisol responses, consistent with both a sensitization and an attenuation hypothesis. Child-rearing disagreements and perceived threat were associated with children exhibiting a rising cortisol pattern whereas destructive conflict was related to children displaying a flat pattern. Physiologically rising patterns were also linked with emotional insecurity and internalizing and externalizing behaviors. Results supported a sensitization pattern of responses as maladaptive for children in response to marital conflict with evidence also linking an attenuation pattern with risk. The present study supports children’s adrenocortical functioning as one mechanism through which interparental conflict is related to children’s coping responses and psychological adjustment. PMID:22545835

Generation of Adaptive Gait Patterns for Quadruped Robot with CPG Network including Motor Dynamic Model

NASA Astrophysics Data System (ADS)

Son, Yurak; Kamano, Takuya; Yasuno, Takashi; Suzuki, Takayuki; Harada, Hironobu

This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environment. The CPGs act as the flexible oscillators of the joints and make the desired angle of the joints. The CPGs are mutually connected each other, and the sets of their coupling parameters are adjusted by genetic algorithm so that the quadruped robot can realize the stable and adequate gait patterns. As a result of generation, the suitable CPG networks for not only a walking straight gait pattern but also rotation gait patterns are obtained. Experimental results demonstrate that the proposed CPG networks are effective to automatically adjust the adaptive gait patterns for the tested quadruped robot under various environment. Furthermore, the target tracking control based on image processing is achieved by combining the generated gait patterns.

Marriage duration and divorce: the seven-year itch or a lifelong itch?

PubMed

Kulu, Hill

2014-06-01

Previous studies have shown that the risk of divorce is low during the first months of marriage; it then increases, reaches a maximum, and thereafter begins to decline. Some researchers consider this pattern consistent with the notion of a "seven-year itch," while others argue that the rising-falling pattern of divorce risk is a consequence of misspecification of longitudinal models because of omitted covariates or unobserved heterogeneity. The aim of this study is to investigate the causes of the rising-falling pattern of divorce risk. Using register data from Finland and applying multilevel hazard models, the analysis supports the rising-falling pattern of divorce by marriage duration: the risk of marital dissolution increases, reaches its peak, and then gradually declines. This pattern persists when I control for the sociodemographic characteristics of women and their partners. The inclusion of unobserved heterogeneity in the model leads to some changes in the shape of the baseline risk; however, the rising-falling pattern of the divorce risk persists.

Dynamic patterning by the Drosophila pair-rule network reconciles long-germ and short-germ segmentation

PubMed Central

2017-01-01

Drosophila segmentation is a well-established paradigm for developmental pattern formation. However, the later stages of segment patterning, regulated by the “pair-rule” genes, are still not well understood at the system level. Building on established genetic interactions, I construct a logical model of the Drosophila pair-rule system that takes into account the demonstrated stage-specific architecture of the pair-rule gene network. Simulation of this model can accurately recapitulate the observed spatiotemporal expression of the pair-rule genes, but only when the system is provided with dynamic “gap” inputs. This result suggests that dynamic shifts of pair-rule stripes are essential for segment patterning in the trunk and provides a functional role for observed posterior-to-anterior gap domain shifts that occur during cellularisation. The model also suggests revised patterning mechanisms for the parasegment boundaries and explains the aetiology of the even-skipped null mutant phenotype. Strikingly, a slightly modified version of the model is able to pattern segments in either simultaneous or sequential modes, depending only on initial conditions. This suggests that fundamentally similar mechanisms may underlie segmentation in short-germ and long-germ arthropods. PMID:28953896

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.

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

The Role of Rainfall Patterns in Seasonal Malaria Transmission

NASA Astrophysics Data System (ADS)

Bomblies, A.

2010-12-01

Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns also affect mosquito population dynamics. In this talk, I show that intraseasonal rainfall pattern describes 40% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal, demonstrating the necessity for detailed distributed hydrology modeling to explain the variance from this important effect. I apply a field validated, high spatial- and temporal-resolution hydrology model coupled with an entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in mosquito abundance, and time-integrated surface area of pools persisting longer than seven days explains 82% of the variance, showing an improved predictive ability when pool persistence is explicitly modeled at high spatio-temporal resolution. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.

A new computational approach to simulate pattern formation in Paenibacillus dendritiformis bacterial colonies

NASA Astrophysics Data System (ADS)

Tucker, Laura Jane

Under the harsh conditions of limited nutrient and hard growth surface, Paenibacillus dendritiformis in agar plates form two classes of patterns (morphotypes). The first class, called the dendritic morphotype, has radially directed branches. The second class, called the chiral morphotype, exhibits uniform handedness. The dendritic morphotype has been modeled successfully using a continuum model on a regular lattice; however, a suitable computational approach was not known to solve a continuum chiral model. This work details a new computational approach to solving the chiral continuum model of pattern formation in P. dendritiformis. The approach utilizes a random computational lattice and new methods for calculating certain derivative terms found in the model.

Patterns and Predictors of Language and Literacy Abilities 4-10 Years in the Longitudinal Study of Australian Children.

PubMed

Zubrick, Stephen R; Taylor, Catherine L; Christensen, Daniel

2015-01-01

Oral language is the foundation of literacy. Naturally, policies and practices to promote children's literacy begin in early childhood and have a strong focus on developing children's oral language, especially for children with known risk factors for low language ability. The underlying assumption is that children's progress along the oral to literate continuum is stable and predictable, such that low language ability foretells low literacy ability. This study investigated patterns and predictors of children's oral language and literacy abilities at 4, 6, 8 and 10 years. The study sample comprised 2,316 to 2,792 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Six developmental patterns were observed, a stable middle-high pattern, a stable low pattern, an improving pattern, a declining pattern, a fluctuating low pattern, and a fluctuating middle-high pattern. Most children (69%) fit a stable middle-high pattern. By contrast, less than 1% of children fit a stable low pattern. These results challenged the view that children's progress along the oral to literate continuum is stable and predictable. Multivariate logistic regression was used to investigate risks for low literacy ability at 10 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. Predictors were modelled as risk variables with the lowest level of risk as the reference category. In the multivariate model, substantial risks for low literacy ability at 10 years, in order of descending magnitude, were: low school readiness, Aboriginal and/or Torres Strait Islander status and low language ability at 8 years. Moderate risks were high temperamental reactivity, low language ability at 4 years, and low language ability at 6 years. The following risk factors were not statistically significant in the multivariate model: Low maternal consistency, low family income, health care card, child not read to at home, maternal smoking, maternal education, family structure, temperamental persistence, and socio-economic area disadvantage. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude did not do particularly well in predicting low literacy ability at 10 years.

The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory

PubMed Central

Fang, Jing; Demic, Selver; Cheng, Sen

2018-01-01

Major depressive disorder (MDD) is associated with an impairment of episodic memory, but the mechanisms underlying this deficit remain unclear. Animal models of MDD find impaired adult neurogenesis (AN) in the dentate gyrus (DG), and AN in DG has been suggested to play a critical role in reducing the interference between overlapping memories through pattern separation. Here, we study the effect of reduced AN in MDD on the accuracy of episodic memory using computational modeling. We focus on how memory is affected when periods with a normal rate of AN (asymptomatic states) alternate with periods with a low rate (depressive episodes), which has never been studied before. Also, unlike previous models of adult neurogenesis, which consider memories as static patterns, we model episodic memory as sequences of neural activity patterns. In our model, AN adds additional random components to the memory patterns, which results in the decorrelation of similar patterns. Consistent with previous studies, higher rates of AN lead to higher memory accuracy in our model, which implies that memories stored in the depressive state are impaired. Intriguingly, our model makes the novel prediction that memories stored in an earlier asymptomatic state are also impaired by a later depressive episode. This retrograde effect exacerbates with increased duration of the depressive episode. Finally, pattern separation at the sensory processing stage does not improve, but rather worsens, the accuracy of episodic memory retrieval, suggesting an explanation for why AN is found in brain areas serving memory rather than sensory function. In conclusion, while cognitive retrieval biases might contribute to episodic memory deficits in MDD, our model suggests a mechanistic explanation that affects all episodic memories, regardless of emotional relevance. PMID:29879169

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

DOE PAGES

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.; ...

2017-01-31

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

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

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Crustal deformation, the earthquake cycle, and models of viscoelastic flow in the asthenosphere

NASA Technical Reports Server (NTRS)

Cohen, S. C.; Kramer, M. J.

1983-01-01

The crustal deformation patterns associated with the earthquake cycle can depend strongly on the rheological properties of subcrustal material. Substantial deviations from the simple patterns for a uniformly elastic earth are expected when viscoelastic flow of subcrustal material is considered. The detailed description of the deformation pattern and in particular the surface displacements, displacement rates, strains, and strain rates depend on the structure and geometry of the material near the seismogenic zone. The origin of some of these differences are resolved by analyzing several different linear viscoelastic models with a common finite element computational technique. The models involve strike-slip faulting and include a thin channel asthenosphere model, a model with a varying thickness lithosphere, and a model with a viscoelastic inclusion below the brittle slip plane. The calculations reveal that the surface deformation pattern is most sensitive to the rheology of the material that lies below the slip plane in a volume whose extent is a few times the fault depth. If this material is viscoelastic, the surface deformation pattern resembles that of an elastic layer lying over a viscoelastic half-space. When the thickness or breath of the viscoelastic material is less than a few times the fault depth, then the surface deformation pattern is altered and geodetic measurements are potentially useful for studying the details of subsurface geometry and structure. Distinguishing among the various models is best accomplished by making geodetic measurements not only near the fault but out to distances equal to several times the fault depth. This is where the model differences are greatest; these differences will be most readily detected shortly after an earthquake when viscoelastic effects are most pronounced.

The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory.

PubMed

Fang, Jing; Demic, Selver; Cheng, Sen

2018-01-01

Major depressive disorder (MDD) is associated with an impairment of episodic memory, but the mechanisms underlying this deficit remain unclear. Animal models of MDD find impaired adult neurogenesis (AN) in the dentate gyrus (DG), and AN in DG has been suggested to play a critical role in reducing the interference between overlapping memories through pattern separation. Here, we study the effect of reduced AN in MDD on the accuracy of episodic memory using computational modeling. We focus on how memory is affected when periods with a normal rate of AN (asymptomatic states) alternate with periods with a low rate (depressive episodes), which has never been studied before. Also, unlike previous models of adult neurogenesis, which consider memories as static patterns, we model episodic memory as sequences of neural activity patterns. In our model, AN adds additional random components to the memory patterns, which results in the decorrelation of similar patterns. Consistent with previous studies, higher rates of AN lead to higher memory accuracy in our model, which implies that memories stored in the depressive state are impaired. Intriguingly, our model makes the novel prediction that memories stored in an earlier asymptomatic state are also impaired by a later depressive episode. This retrograde effect exacerbates with increased duration of the depressive episode. Finally, pattern separation at the sensory processing stage does not improve, but rather worsens, the accuracy of episodic memory retrieval, suggesting an explanation for why AN is found in brain areas serving memory rather than sensory function. In conclusion, while cognitive retrieval biases might contribute to episodic memory deficits in MDD, our model suggests a mechanistic explanation that affects all episodic memories, regardless of emotional relevance.

Modeling study on the flow patterns of gas-liquid flow for fast decarburization during the RH process

NASA Astrophysics Data System (ADS)

Li, Yi-hong; Bao, Yan-ping; Wang, Rui; Ma, Li-feng; Liu, Jian-sheng

2018-02-01

A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber: boiling pattern (BP), transition pattern (TP), and wave pattern (WP). The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.

A metric for quantifying El Niño pattern diversity with implications for ENSO-mean state interaction

NASA Astrophysics Data System (ADS)

Lemmon, Danielle E.; Karnauskas, Kristopher B.

2018-04-01

Recent research on the El Niño-Southern Oscillation (ENSO) phenomenon increasingly reveals the highly complex and diverse nature of ENSO variability. A method of quantifying ENSO spatial pattern uniqueness and diversity is presented, which enables (1) formally distinguishing between unique and "canonical" El Niño events, (2) testing whether historical model simulations aptly capture ENSO diversity by comparing with instrumental observations, (3) projecting future ENSO diversity using future model simulations, (4) understanding the dynamics that give rise to ENSO diversity, and (5) analyzing the associated diversity of ENSO-related atmospheric teleconnection patterns. Here we develop a framework for measuring El Niño spatial SST pattern uniqueness and diversity for a given set of El Niño events using two indices, the El Niño Pattern Uniqueness (EPU) index and El Niño Pattern Diversity (EPD) index, respectively. By applying this framework to instrumental records, we independently confirm a recent regime shift in El Niño pattern diversity with an increase in unique El Niño event sea surface temperature patterns. However, the same regime shift is not observed in historical CMIP5 model simulations; moreover, a comparison between historical and future CMIP5 model scenarios shows no robust change in future ENSO diversity. Finally, we support recent work that asserts a link between the background cooling of the eastern tropical Pacific and changes in ENSO diversity. This robust link between an eastern Pacific cooling mode and ENSO diversity is observed not only in instrumental reconstructions and reanalysis, but also in historical and future CMIP5 model simulations.

A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

NASA Astrophysics Data System (ADS)

Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

2017-08-01

Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

Median Hetero-Associative Memories Applied to the Categorization of True-Color Patterns

NASA Astrophysics Data System (ADS)

Vázquez, Roberto A.; Sossa, Humberto

Median associative memories (MED-AMs) are a special type of associative memory based on the median operator. This type of associative model has been applied to the restoration of gray scale images and provides better performance than other models, such as morphological associative memories, when the patterns are altered with mixed noise. Despite of his power, MED-AMs have not been applied in problems involving true-color patterns. In this paper we describe how a median hetero-associative memory (MED-HAM) could be applied in problems that involve true-color patterns. A complete study of the behavior of this associative model in the restoration of true-color images is performed using a benchmark of 14400 images altered by different type of noises. Furthermore, we describe how this model can be applied to an image categorization problem.

A Bayesian Model of Category-Specific Emotional Brain Responses

PubMed Central

Wager, Tor D.; Kang, Jian; Johnson, Timothy D.; Nichols, Thomas E.; Satpute, Ajay B.; Barrett, Lisa Feldman

2015-01-01

Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories—fear, anger, disgust, sadness, or happiness—is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches. PMID:25853490

Child Mortality Estimation: A Global Overview of Infant and Child Mortality Age Patterns in Light of New Empirical Data

PubMed Central

Guillot, Michel; Gerland, Patrick; Pelletier, François; Saabneh, Ameed

2012-01-01

Background The under-five mortality rate (the probability of dying between birth and age 5 y, also denoted in the literature as U5MR and 5 q 0) is a key indicator of child health, but it conceals important information about how this mortality is distributed by age. One important distinction is what amount of the under-five mortality occurs below age 1 y (1 q 0) versus at age 1 y and above (4 q 1). However, in many country settings, this distinction is often difficult to establish because of various types of data errors. As a result, it is common practice to resort to model age patterns to estimate 1 q 0 and 4 q 1 on the basis of an observed value of 5 q 0. The most commonly used model age patterns for this purpose are the Coale and Demeny and the United Nations systems. Since the development of these models, many additional sources of data for under-five mortality have become available, making possible a general evaluation of age patterns of infant and child mortality. In this paper, we do a systematic comparison of empirical values of 1 q 0 and 4 q 1 against model age patterns, and discuss whether observed deviations are due to data errors, or whether they reflect true epidemiological patterns not addressed in existing model life tables. Methods and Findings We used vital registration data from the Human Mortality Database, sample survey data from the World Fertility Survey and Demographic and Health Surveys programs, and data from Demographic Surveillance Systems. For each of these data sources, we compared empirical combinations of 1 q 0 and 4 q 1 against combinations provided by Coale and Demeny and United Nations model age patterns. We found that, on the whole, empirical values fall relatively well within the range provided by these models, but we also found important exceptions. Sub-Saharan African countries have a tendency to exhibit high values of 4 q 1 relative to 1 q 0, a pattern that appears to arise for the most part from true epidemiological causes. While this pattern is well known in the case of western Africa, we observed that it is more widespread than commonly thought. We also found that the emergence of HIV/AIDS, while perhaps contributing to high relative values of 4 q 1, does not appear to have substantially modified preexisting patterns. We also identified a small number of countries scattered in different parts of the world that exhibit unusually low values of 4 q 1 relative to 1 q 0, a pattern that is not likely to arise merely from data errors. Finally, we illustrate that it is relatively common for populations to experience changes in age patterns of infant and child mortality as they experience a decline in mortality. Conclusions Existing models do not appear to cover the entire range of epidemiological situations and trajectories. Therefore, model life tables should be used with caution for estimating 1 q 0 and 4 q 1 on the basis of 5 q 0. Moreover, this model-based estimation procedure assumes that the input value of 5 q 0 is correct, which may not always be warranted, especially in the case of survey data. A systematic evaluation of data errors in sample surveys and their impact on age patterns of 1 q 0 and 4 q 1 is urgently needed, along with the development of model age patterns of under-five mortality that would cover a wider range of epidemiological situations and trajectories. Please see later in the article for the Editors' Summary. PMID:22952438

'Adoption and attachment theory' the attachment models of adoptive mothers and the revision of attachment patterns of their late-adopted children.

PubMed

Pace, C S; Zavattini, G C

2011-01-01

This study examined the attachment patterns of late-adopted children (aged 4-7) and their adoptive mothers during the first 7- to 8-month period after adoption and aimed to evaluate the effect of adoptive mothers' attachment security on the revision of the attachment patterns of their late-adopted children. We assessed attachment patterns in 20 adoptive dyads and 12 genetically related dyads at two different times: T1 (time 1) within 2 months of adoption and T2 (time 2) 6 months after T1. The children's behavioural attachment patterns were assessed using the Separation-Reunion Procedure and the children's representational (verbal) attachment patterns using the Manchester Child Attachment Story Task. The attachment models of the adoptive mothers were classified using the Adult Attachment Interview. We found that there was a significant enhancement of the late-adopted children's attachment security across the time period considered (P= 0.008). Moreover, all the late-adopted children who showed a change from insecurity to security had adoptive mothers with secure attachment models (P= 0.044). However, the matching between maternal attachment models and late-adopted children's attachment patterns (behaviours and representations) was not significant. Our data suggest that revision of the attachment patterns in the late-adopted children is possible but gradual, and that the adoptive mothers' attachment security makes it more likely to occur. © 2010 Blackwell Publishing Ltd.

Pine invasions in treeless environments: dispersal overruns microsite heterogeneity.

PubMed

Pauchard, Aníbal; Escudero, Adrián; García, Rafael A; de la Cruz, Marcelino; Langdon, Bárbara; Cavieres, Lohengrin A; Esquivel, Jocelyn

2016-01-01

Understanding biological invasions patterns and mechanisms is highly needed for forecasting and managing these processes and their negative impacts. At small scales, ecological processes driving plant invasions are expected to produce a spatially explicit pattern driven by propagule pressure and local ground heterogeneity. Our aim was to determine the interplay between the intensity of seed rain, using distance to a mature plantation as a proxy, and microsite heterogeneity in the spreading of Pinus contorta in the treeless Patagonian steppe. Three one-hectare plots were located under different degrees of P. contorta invasion (Coyhaique Alto, 45° 30'S and 71° 42'W). We fitted three types of inhomogeneous Poisson models to each pine plot in an attempt for describing the observed pattern as accurately as possible: the "dispersal" models, "local ground heterogeneity" models, and "combined" models, using both types of covariates. To include the temporal axis in the invasion process, we analyzed both the pattern of young and old recruits and also of all recruits together. As hypothesized, the spatial patterns of recruited pines showed coarse scale heterogeneity. Early pine invasion spatial patterns in our Patagonian steppe site is not different from expectations of inhomogeneous Poisson processes taking into consideration a linear and negative dependency of pine recruit intensity on the distance to afforestations. Models including ground-cover predictors were able to describe the point pattern process only in a couple of cases but never better than dispersal models. This finding concurs with the idea that early invasions depend more on seed pressure than on the biotic and abiotic relationships seed and seedlings establish at the microsite scale. Our results show that without a timely and active management, P. contorta will invade the Patagonian steppe independently of the local ground-cover conditions.

Field-scale Prediction of Enhanced DNAPL Dissolution Using Partitioning Tracers and Flow Pattern Effects

NASA Astrophysics Data System (ADS)

Wang, F.; Annable, M. D.; Jawitz, J. W.

2012-12-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a PCE-contaminated dry cleaner site, located in Jacksonville, Florida. The EST is an analytical solution with field-measurable input parameters. Here, measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ alcohol (ethanol) flood. In addition, a simulated partitioning tracer test from a calibrated spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The ethanol prediction based on both the field partitioning tracer test and the UTCHEM tracer test simulation closely matched the field data. The PCE EST prediction showed a peak shift to an earlier arrival time that was concluded to be caused by well screen interval differences between the field tracer test and alcohol flood. This observation was based on a modeling assessment of potential factors that may influence predictions by using UTCHEM simulations. The imposed injection and pumping flow pattern at this site for both the partitioning tracer test and alcohol flood was more complex than the natural gradient flow pattern (NGFP). Both the EST model and UTCHEM were also used to predict PCE dissolution under natural gradient conditions, with much simpler flow patterns than the forced-gradient double five spot of the alcohol flood. The NGFP predictions based on parameters determined from tracer tests conducted with complex flow patterns underestimated PCE concentrations and total mass removal. This suggests that the flow patterns influence aqueous dissolution and that the aqueous dissolution under the NGFP is more efficient than dissolution under complex flow patterns.

Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja

Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features. These results show how the static landscape features can be controlled by adjusting the correlations between patterns. Finally, I explore the dynamical features of landscapes generated using neural network models such as the stability of minima and the transition rates between minima. The results from this project show that the stability depends on the correlations between patterns. It is also found that the transition rates between minima strongly depend on the type of bias applied and the correlation between patterns. The results from this part of the dissertation can be useful in engineering an energy landscape without even having the complete information about the associated minima of the landscape.

Turing mechanism underlying a branching model for lung morphogenesis.

PubMed

Xu, Hui; Sun, Mingzhu; Zhao, Xin

2017-01-01

The mammalian lung develops through branching morphogenesis. Two primary forms of branching, which occur in order, in the lung have been identified: tip bifurcation and side branching. However, the mechanisms of lung branching morphogenesis remain to be explored. In our previous study, a biological mechanism was presented for lung branching pattern formation through a branching model. Here, we provide a mathematical mechanism underlying the branching patterns. By decoupling the branching model, we demonstrated the existence of Turing instability. We performed Turing instability analysis to reveal the mathematical mechanism of the branching patterns. Our simulation results show that the Turing patterns underlying the branching patterns are spot patterns that exhibit high local morphogen concentration. The high local morphogen concentration induces the growth of branching. Furthermore, we found that the sparse spot patterns underlie the tip bifurcation patterns, while the dense spot patterns underlies the side branching patterns. The dispersion relation analysis shows that the Turing wavelength affects the branching structure. As the wavelength decreases, the spot patterns change from sparse to dense, the rate of tip bifurcation decreases and side branching eventually occurs instead. In the process of transformation, there may exists hybrid branching that mixes tip bifurcation and side branching. Since experimental studies have reported that branching mode switching from side branching to tip bifurcation in the lung is under genetic control, our simulation results suggest that genes control the switch of the branching mode by regulating the Turing wavelength. Our results provide a novel insight into and understanding of the formation of branching patterns in the lung and other biological systems.

Dewetting of patterned solid films: Towards a predictive modelling approach

NASA Astrophysics Data System (ADS)

Trautmann, M.; Cheynis, F.; Leroy, F.; Curiotto, S.; Pierre-Louis, O.; Müller, P.

2017-06-01

Owing to its ability to produce an assembly of nanoislands with controllable size and locations, the solid state dewetting of patterned films has recently received great attention. A simple Kinetic Monte Carlo model based on two reduced energetic parameters allows one to reproduce experimental observations of the dewetting morphological evolution of patterned films of Si(001) on SiO2 (or SOI for Silicon-on-Insulator) with various pattern designs. Thus, it is now possible to use KMC to drive further experiments and to optimize the pattern shapes to reach a desired dewetted structure. Comparisons between KMC simulations and dewetting experiments, at least for wire-shaped patterns, show that the prevailing dewetting mechanism depends on the wire width.

Nonlinear Structured Growth Mixture Models in Mplus and OpenMx

PubMed Central

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2014-01-01

Growth mixture models (GMMs; Muthén & Muthén, 2000; Muthén & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models because of their common use, flexibility in modeling many types of change patterns, the availability of statistical programs to fit such models, and the ease of programming. In this paper, we present additional ways of modeling nonlinear change patterns with GMMs. Specifically, we show how LCMs that follow specific nonlinear functions can be extended to examine the presence of multiple latent classes using the Mplus and OpenMx computer programs. These models are fit to longitudinal reading data from the Early Childhood Longitudinal Study-Kindergarten Cohort to illustrate their use. PMID:25419006

Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

NASA Astrophysics Data System (ADS)

Kitsunezaki, S.

In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

Dynamical systems techniques reveal the sexual dimorphic nature of motor patterns in birdsong

NASA Astrophysics Data System (ADS)

Mendez, J. M.; Alliende, J. A.; Amador, A.; Mindlin, G. B.

2006-10-01

In this work we analyze the pressure motor patterns used by canaries (Serinus canaria) during song, both in the cases of males and testosterone treated females. We found a qualitative difference between them which was not obvious from the acoustical features of the uttered songs. We also show the diversity of patterns, both for males and females, to be consistent with a recently proposed model for the dynamics of the oscine respiratory system. The model not only allows us to reproduce qualitative features of the different pressure patterns, but also to account for all the diversity of pressure patterns found in females.

Blood oxygen level dependent magnetic resonance imaging for detecting pathological patterns in lupus nephritis patients: a preliminary study using a decision tree model.

PubMed

Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng

2018-02-09

Precise renal histopathological diagnosis will guide therapy strategy in patients with lupus nephritis. Blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) has been applicable noninvasive technique in renal disease. This current study was performed to explore whether BOLD MRI could contribute to diagnose renal pathological pattern. Adult patients with lupus nephritis renal pathological diagnosis were recruited for this study. Renal biopsy tissues were assessed based on the lupus nephritis ISN/RPS 2003 classification. The Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) was used to obtain functional magnetic resonance parameter, R2* values. Several functions of R2* values were calculated and used to construct algorithmic models for renal pathological patterns. In addition, the algorithmic models were compared as to their diagnostic capability. Both Histopathology and BOLD MRI were used to examine a total of twelve patients. Renal pathological patterns included five classes III (including 3 as class III + V) and seven classes IV (including 4 as class IV + V). Three algorithmic models, including decision tree, line discriminant, and logistic regression, were constructed to distinguish the renal pathological pattern of class III and class IV. The sensitivity of the decision tree model was better than that of the line discriminant model (71.87% vs 59.48%, P < 0.001) and inferior to that of the Logistic regression model (71.87% vs 78.71%, P < 0.001). The specificity of decision tree model was equivalent to that of the line discriminant model (63.87% vs 63.73%, P = 0.939) and higher than that of the logistic regression model (63.87% vs 38.0%, P < 0.001). The Area under the ROC curve (AUROCC) of the decision tree model was greater than that of the line discriminant model (0.765 vs 0.629, P < 0.001) and logistic regression model (0.765 vs 0.662, P < 0.001). BOLD MRI is a useful non-invasive imaging technique for the evaluation of lupus nephritis. Decision tree models constructed using functions of R2* values may facilitate the prediction of renal pathological patterns.

Application of a model to analyze shoulder biomechanics in adult patients with spinal cord injury when walking with crutches in two different gait patterns.

PubMed

Perez-Rizo, Enrique; Trincado-Alonso, Fernando; Pérez-Nombela, Soraya; Del Ama-Espinosa, Antonio; Jiménez-Díaz, Fernando; Lozano-Berrio, Vicente; Gil-Agudo, Angel

2017-01-01

Specific biomechanical models have been developed to study gait using crutches. Clinical application of these models is needed in adult spinal cord injury (SCI) population walking with different patterns of gait with crutches to prevent overuse shoulder injuries. To apply a biomechanical model in a clinical environment to analyze shoulder in adult SCI patients walking with two different patterns of gait with crutches: two point reciprocal gait (RG) and swing-through gait (SG). Load cells were fixed to the distal ends and forearm cuffs of a pair of crutches. An active markers system was used for kinematics. Five cycles for each gait pattern were analyzed applying a biomechanical model of the upper limbs. Fifteen subjects with SCI were analyzed. The flexo-extension range of motion was significantly greater when using SG (p < 0.01). Similarly, the superior, posterior and medial forces were significantly stronger for SG in all 3 directions. Flexion, adduction and internal rotation torques were also greater in SG (p < 0.01). A biomechanical model was successfully applied to study shoulder biomechanics in adult patients with SCI walking with crutches in two different gait patterns. Greater loads exerted on the shoulder walking with SG were confirmed compared to RG.

Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes

PubMed Central

Fernández-Llatas, Carlos; Benedi, José-Miguel; García-Gómez, Juan M.; Traver, Vicente

2013-01-01

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection. PMID:24225907

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

NASA Astrophysics Data System (ADS)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

Ontology Design Patterns as Interfaces (invited)

NASA Astrophysics Data System (ADS)

Janowicz, K.

2015-12-01

In recent years ontology design patterns (ODP) have gained popularity among knowledge engineers. ODPs are modular but self-contained building blocks that are reusable and extendible. They minimize the amount of ontological commitments and thereby are easier to integrate than large monolithic ontologies. Typically, patterns are not directly used to annotate data or to model certain domain problems but are combined and extended to form data and purpose-driven local ontologies that serve the needs of specific applications or communities. By relying on a common set of patterns these local ontologies can be aligned to improve interoperability and enable federated queries without enforcing a top-down model of the domain. In previous work, we introduced ontological views as layer on top of ontology design patterns to ease the reuse, combination, and integration of patterns. While the literature distinguishes multiple types of patterns, e.g., content patterns or logical patterns, we propose to use them as interfaces here to guide the development of ontology-driven systems.

A recovery principle provides insight into auxin pattern control in the Arabidopsis root

PubMed Central

Moore, Simon; Liu, Junli; Zhang, Xiaoxian; Lindsey, Keith

2017-01-01

Regulated auxin patterning provides a key mechanism for controlling root growth and development. We have developed a data-driven mechanistic model using realistic root geometry and formulated a principle to theoretically investigate quantitative auxin pattern recovery following auxin transport perturbation. This principle reveals that auxin patterning is potentially controlled by multiple combinations of interlinked levels and localisation of influx and efflux carriers. We demonstrate that (1) when efflux carriers maintain polarity but change levels, maintaining the same auxin pattern requires non-uniform and polar distribution of influx carriers; (2) the emergence of the same auxin pattern, from different levels of influx carriers with the same nonpolar localisation, requires simultaneous modulation of efflux carrier level and polarity; and (3) multiple patterns of influx and efflux carriers for maintaining an auxin pattern do not have spatially proportional correlation. This reveals that auxin pattern formation requires coordination between influx and efflux carriers. We further show that the model makes various predictions that can be experimentally validated. PMID:28220889

Spatiotemporal patterns in reaction-diffusion system and in a vibrated granular bed

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

Swinney, H.L.; Lee, K.J.; McCormick, W.D.

Experiments on a quasi-two-dimensional reaction-diffusion system reveal transitions from a uniform state to stationary hexagonal, striped, and rhombic spatial patterns. For other reactor conditions lamellae and self-replicating spot patterns are observed. These patterns form in continuously fed thin gel reactors that can be maintained indefinitely in well-defined nonequilibrium states. Reaction-diffusion models with two chemical species yield patterns similar to those observed in the experiments. Pattern formation is also being examined in vertically oscillated thin granular layers (typically 3-30 particle diameters deep). For small acceleration amplitudes, a granular layer is flat, but above a well-defined critical acceleration amplitude, spatial patterns spontaneouslymore » form. Disordered time-dependent granular patterns are observed as well as regular patterns of squares, stripes, and hexagons. A one-dimensional model consisting of a completely inelastic ball colliding with a sinusoidally oscillating platform provides a semi-quantitative description of most of the observed bifurcations between the different spatiotemporal regimes.« less

An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

PubMed Central

Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

Model of polar auxin transport coupled to mechanical forces retrieves robust morphogenesis along the Arabidopsis root

NASA Astrophysics Data System (ADS)

Romero-Arias, J. Roberto; Hernández-Hernández, Valeria; Benítez, Mariana; Alvarez-Buylla, Elena R.; Barrio, Rafael A.

2017-03-01

Stem cells are identical in many scales, they share the same molecular composition, DNA, genes, and genetic networks, yet they should acquire different properties to form a functional tissue. Therefore, they must interact and get some external information from their environment, either spatial (dynamical fields) or temporal (lineage). In this paper we test to what extent coupled chemical and physical fields can underlie the cell's positional information during development. We choose the root apical meristem of Arabidopsis thaliana to model the emergence of cellular patterns. We built a model to study the dynamics and interactions between the cell divisions, the local auxin concentration, and physical elastic fields. Our model recovers important aspects of the self-organized and resilient behavior of the observed cellular patterns in the Arabidopsis root, in particular, the reverse fountain pattern observed in the auxin transport, the PIN-FORMED (protein family of auxin transporters) polarization pattern and the accumulation of auxin near the region of maximum curvature in a bent root. Our model may be extended to predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions.

A LISREL Model for the Analysis of Repeated Measures with a Patterned Covariance Matrix.

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

1998-01-01

Presents a LISREL model for the estimation of the repeated measures analysis of variance (ANOVA) with a patterned covariance matrix. The model is demonstrated for a 5 x 2 (Time x Group) ANOVA in which the data are assumed to be serially correlated. Similarities with the Statistical Analysis System PROC MIXED model are discussed. (SLD)

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

PubMed

Retkute, Renata; Townsend, Alexandra J; Murchie, Erik H; Jensen, Oliver E; Preston, Simon P

2018-05-25

Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the complex ways that photosynthesis responds to changes in light intensity. Current methods to characterize light dynamics, such as ray-tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resulting data are complex and high-dimensional. This necessitates development of more economical models for summarizing the data and for simulating realistic light patterns over the course of a day. High-resolution reconstructions of field-grown plants are assembled in various configurations to form canopies, and a forward ray-tracing algorithm is applied to the canopies to compute light dynamics at high (1 min) temporal resolution. From the ray-tracer output, the sunlit or shaded state for each patch on the plants is determined, and these data are used to develop a novel stochastic model for the sunlit-shaded patterns. The model is designed to be straightforward to fit to data using maximum likelihood estimation, and fast to simulate from. For a wide range of contrasting 3-D canopies, the stochastic model is able to summarize, and replicate in simulations, key features of the light dynamics. When light patterns simulated from the stochastic model are used as input to a model of photoinhibition, the predicted reduction in carbon gain is similar to that from calculations based on the (extremely costly) ray-tracer data. The model provides a way to summarize highly complex data in a small number of parameters, and a cost-effective way to simulate realistic light patterns. Simulations from the model will be particularly useful for feeding into larger-scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of canopies.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

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.

Denoising by coupled partial differential equations and extracting phase by backpropagation neural networks for electronic speckle pattern interferometry.

PubMed

Tang, Chen; Lu, Wenjing; Chen, Song; Zhang, Zhen; Li, Botao; Wang, Wenping; Han, Lin

2007-10-20

We extend and refine previous work [Appl. Opt. 46, 2907 (2007)]. Combining the coupled nonlinear partial differential equations (PDEs) denoising model with the ordinary differential equations enhancement method, we propose the new denoising and enhancing model for electronic speckle pattern interferometry (ESPI) fringe patterns. Meanwhile, we propose the backpropagation neural networks (BPNN) method to obtain unwrapped phase values based on a skeleton map instead of traditional interpolations. We test the introduced methods on the computer-simulated speckle ESPI fringe patterns and experimentally obtained fringe pattern, respectively. The experimental results show that the coupled nonlinear PDEs denoising model is capable of effectively removing noise, and the unwrapped phase values obtained by the BPNN method are much more accurate than those obtained by the well-known traditional interpolation. In addition, the accuracy of the BPNN method is adjustable by changing the parameters of networks such as the number of neurons.

Antiferromagnetic order in the Hubbard model on the Penrose lattice

NASA Astrophysics Data System (ADS)

Koga, Akihisa; Tsunetsugu, Hirokazu

2017-12-01

We study an antiferromagnetic order in the ground state of the half-filled Hubbard model on the Penrose lattice and investigate the effects of quasiperiodic lattice structure. In the limit of infinitesimal Coulomb repulsion U →+0 , the staggered magnetizations persist to be finite, and their values are determined by confined states, which are strictly localized with thermodynamics degeneracy. The magnetizations exhibit an exotic spatial pattern, and have the same sign in each of cluster regions, the size of which ranges from 31 sites to infinity. With increasing U , they continuously evolve to those of the corresponding spin model in the U =∞ limit. In both limits of U , local magnetizations exhibit a fairly intricate spatial pattern that reflects the quasiperiodic structure, but the pattern differs between the two limits. We have analyzed this pattern change by a mode analysis by the singular value decomposition method for the fractal-like magnetization pattern projected into the perpendicular space.

Patterns of glaucomatous visual field loss in sita fields automatically identified using independent component analysis.

PubMed

Goldbaum, Michael H; Jang, Gil-Jin; Bowd, Chris; Hao, Jiucang; Zangwill, Linda M; Liebmann, Jeffrey; Girkin, Christopher; Jung, Tzyy-Ping; Weinreb, Robert N; Sample, Pamela A

2009-12-01

To determine if the patterns uncovered with variational Bayesian-independent component analysis-mixture model (VIM) applied to a large set of normal and glaucomatous fields obtained with the Swedish Interactive Thresholding Algorithm (SITA) are distinct, recognizable, and useful for modeling the severity of the field loss. SITA fields were obtained with the Humphrey Visual Field Analyzer (Carl Zeiss Meditec, Inc, Dublin, California) on 1,146 normal eyes and 939 glaucoma eyes from subjects followed by the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. VIM modifies independent component analysis (ICA) to develop separate sets of ICA axes in the cluster of normal fields and the 2 clusters of abnormal fields. Of 360 models, the model with the best separation of normal and glaucomatous fields was chosen for creating the maximally independent axes. Grayscale displays of fields generated by VIM on each axis were compared. SITA fields most closely associated with each axis and displayed in grayscale were evaluated for consistency of pattern at all severities. The best VIM model had 3 clusters. Cluster 1 (1,193) was mostly normal (1,089, 95% specificity) and had 2 axes. Cluster 2 (596) contained mildly abnormal fields (513) and 2 axes; cluster 3 (323) held mostly moderately to severely abnormal fields (322) and 5 axes. Sensitivity for clusters 2 and 3 combined was 88.9%. The VIM-generated field patterns differed from each other and resembled glaucomatous defects (eg, nasal step, arcuate, temporal wedge). SITA fields assigned to an axis resembled each other and the VIM-generated patterns for that axis. Pattern severity increased in the positive direction of each axis by expansion or deepening of the axis pattern. VIM worked well on SITA fields, separating them into distinctly different yet recognizable patterns of glaucomatous field defects. The axis and pattern properties make VIM a good candidate as a preliminary process for detecting progression.

Roll plane analysis of on-aircraft antennas

NASA Technical Reports Server (NTRS)

Burnside, W. D.; Marhefka, R. J.; Byu, C. L.

1974-01-01

Roll plane radiation patterns of on-aircraft antennas are analyzed using high frequency solutions. Aircraft-antenna pattern performance in which the aircraft is modelled in its most basic form is presented. The fuselage is assumed to be a perfectly conducting elliptic cylinder with the antennas mounted near the top or bottom. The wings are simulated by arbitrarily many sided flat plates and the engines by circular cylinders. The patterns in each case are verified by measured results taken on simple models as well as scale models of actual aircraft.

Application of a Genetic Algorithm and Multi Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the Workplace

DTIC Science & Technology

2008-06-01

postponed the fulfillment of her own Masters Degree by at least 18 months so that I would have the opportunity to earn mine. She is smart , lovely...GENETIC ALGORITHM AND MULTI AGENT SYSTEM TO EXPLORE EMERGENT PATTERNS OF SOCIAL RATIONALITY AND A DISTRESS-BASED MODEL FOR DECEIT IN THE WORKPLACE...of a Genetic Algorithm and Mutli Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the

Uniform modeling of bacterial colony patterns with varying nutrient and substrate

NASA Astrophysics Data System (ADS)

Schwarcz, Deborah; Levine, Herbert; Ben-Jacob, Eshel; Ariel, Gil

2016-04-01

Bacteria develop complex patterns depending on growth condition. For example, Bacillus subtilis exhibit five different patterns depending on substrate hardness and nutrient concentration. We present a unified integro-differential model that reproduces the entire experimentally observed morphology diagram at varying nutrient concentrations and substrate hardness. The model allows a comprehensive and quantitative comparison between experimental and numerical variables and parameters, such as colony growth rate, nutrient concentration and diffusion constants. As a result, the role of the different physical mechanisms underlying and regulating the growth of the colony can be evaluated.

Mechanism underlying the diverse collective behavior in the swarm oscillator model

NASA Astrophysics Data System (ADS)

Iwasa, Masatomo; Tanaka, Dan

2017-09-01

The swarm oscillator model describes the long-time behavior of interacting chemotactic particles, and it shows numerous types of macroscopic patterns. However, the reason why so many kinds of patterns emerge is not clear. In this study, we elucidate the mechanism underlying the diversity of the pattens by analyzing the model for two particles. Focusing on the behavior when the two particles are spatially close, we find that the dynamics is classified into eight types, which explain most of the observed 13 types of patterns.

Test pattern generation for ILA sequential circuits

NASA Technical Reports Server (NTRS)

Feng, YU; Frenzel, James F.; Maki, Gary K.

1993-01-01

An efficient method of generating test patterns for sequential machines implemented using one-dimensional, unilateral, iterative logic arrays (ILA's) of BTS pass transistor networks is presented. Based on a transistor level fault model, the method affords a unique opportunity for real-time fault detection with improved fault coverage. The resulting test sets are shown to be equivalent to those obtained using conventional gate level models, thus eliminating the need for additional test patterns. The proposed method advances the simplicity and ease of the test pattern generation for a special class of sequential circuitry.

A fingertip force prediction model for grasp patterns characterised from the chaotic behaviour of EEG.

PubMed

Roy, Rinku; Sikdar, Debdeep; Mahadevappa, Manjunatha; Kumar, C S

2018-05-19

A stable grasp is attained through appropriate hand preshaping and precise fingertip forces. Here, we have proposed a method to decode grasp patterns from motor imagery and subsequent fingertip force estimation model with a slippage avoidance strategy. We have developed a feature-based classification of electroencephalography (EEG) associated with imagination of the grasping postures. Chaotic behaviour of EEG for different grasping patterns has been utilised to capture the dynamics of associated motor activities. We have computed correlation dimension (CD) as the feature and classified with "one against one" multiclass support vector machine (SVM) to discriminate between different grasping patterns. The result of the analysis showed varying classification accuracies at different subband levels. Broad categories of grasping patterns, namely, power grasp and precision grasp, were classified at a 96.0% accuracy rate in the alpha subband. Furthermore, power grasp subtypes were classified with an accuracy of 97.2% in the upper beta subband, whereas precision grasp subtypes showed relatively lower 75.0% accuracy in the alpha subband. Following assessment of fingertip force distributions while grasping, a nonlinear autoregressive (NAR) model with proper prediction of fingertip forces was proposed for each grasp pattern. A slippage detection strategy has been incorporated with automatic recalibration of the regripping force. Intention of each grasp pattern associated with corresponding fingertip force model was virtualised in this work. This integrated system can be utilised as the control strategy for prosthetic hand in the future. The model to virtualise motor imagery based fingertip force prediction with inherent slippage correction for different grasp types ᅟ.

A new prospect in magnetic nanoparticle-based cancer therapy: Taking credit from mathematical tissue-mimicking phantom brain models.

PubMed

Saeedi, Mostafa; Vahidi, Omid; Goodarzi, Vahabodin; Saeb, Mohammad Reza; Izadi, Leila; Mozafari, Masoud

2017-11-01

Distribution patterns/performance of magnetic nanoparticles (MNPs) was visualized by computer simulation and experimental validation on agarose gel tissue-mimicking phantom (AGTMP) models. The geometry of a complex three-dimensional mathematical phantom model of a cancer tumor was examined by tomography imaging. The capability of mathematical model to predict distribution patterns/performance in AGTMP model was captured. The temperature profile vs. hyperthermia duration was obtained by solving bio-heat equations for four different MNPs distribution patterns and correlated with cell death rate. The outcomes indicated that bio-heat model was able to predict temperature profile throughout the tissue model with a reasonable precision, to be applied for complex tissue geometries. The simulation results on the cancer tumor model shed light on the effectiveness of the studied parameters. Copyright © 2017 Elsevier Inc. All rights reserved.

Short-Term Global Horizontal Irradiance Forecasting Based on Sky Imaging and Pattern Recognition

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

Hodge, Brian S; Feng, Cong; Cui, Mingjian

Accurate short-term forecasting is crucial for solar integration in the power grid. In this paper, a classification forecasting framework based on pattern recognition is developed for 1-hour-ahead global horizontal irradiance (GHI) forecasting. Three sets of models in the forecasting framework are trained by the data partitioned from the preprocessing analysis. The first two sets of models forecast GHI for the first four daylight hours of each day. Then the GHI values in the remaining hours are forecasted by an optimal machine learning model determined based on a weather pattern classification model in the third model set. The weather pattern ismore » determined by a support vector machine (SVM) classifier. The developed framework is validated by the GHI and sky imaging data from the National Renewable Energy Laboratory (NREL). Results show that the developed short-term forecasting framework outperforms the persistence benchmark by 16% in terms of the normalized mean absolute error and 25% in terms of the normalized root mean square error.« less

Making sense of sparse rating data in collaborative filtering via topographic organization of user preference patterns.

PubMed

Polcicová, Gabriela; Tino, Peter

2004-01-01

We introduce topographic versions of two latent class models (LCM) for collaborative filtering. Latent classes are topologically organized on a square grid. Topographic organization of latent classes makes orientation in rating/preference patterns captured by the latent classes easier and more systematic. The variation in film rating patterns is modelled by multinomial and binomial distributions with varying independence assumptions. In the first stage of topographic LCM construction, self-organizing maps with neural field organized according to the LCM topology are employed. We apply our system to a large collection of user ratings for films. The system can provide useful visualization plots unveiling user preference patterns buried in the data, without loosing potential to be a good recommender model. It appears that multinomial distribution is most adequate if the model is regularized by tight grid topologies. Since we deal with probabilistic models of the data, we can readily use tools from probability and information theories to interpret and visualize information extracted by our system.

A unified model explains commonness and rarity on coral reefs.

PubMed

Connolly, Sean R; Hughes, Terry P; Bellwood, David R

2017-04-01

Abundance patterns in ecological communities have important implications for biodiversity maintenance and ecosystem functioning. However, ecological theory has been largely unsuccessful at capturing multiple macroecological abundance patterns simultaneously. Here, we propose a parsimonious model that unifies widespread ecological relationships involving local aggregation, species-abundance distributions, and species associations, and we test this model against the metacommunity structure of reef-building corals and coral reef fishes across the western and central Pacific. For both corals and fishes, the unified model simultaneously captures extremely well local species-abundance distributions, interspecific variation in the strength of spatial aggregation, patterns of community similarity, species accumulation, and regional species richness, performing far better than alternative models also examined here and in previous work on coral reefs. Our approach contributes to the development of synthetic theory for large-scale patterns of community structure in nature, and to addressing ongoing challenges in biodiversity conservation at macroecological scales. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

A computational model of cerebral cortex folding.

PubMed

Nie, Jingxin; Guo, Lei; Li, Gang; Faraco, Carlos; Stephen Miller, L; Liu, Tianming

2010-05-21

The geometric complexity and variability of the human cerebral cortex have long intrigued the scientific community. As a result, quantitative description of cortical folding patterns and the understanding of underlying folding mechanisms have emerged as important research goals. This paper presents a computational 3D geometric model of cerebral cortex folding initialized by MRI data of a human fetal brain and deformed under the governance of a partial differential equation modeling cortical growth. By applying different simulation parameters, our model is able to generate folding convolutions and shape dynamics of the cerebral cortex. The simulations of this 3D geometric model provide computational experimental support to the following hypotheses: (1) Mechanical constraints of the skull regulate the cortical folding process. (2) The cortical folding pattern is dependent on the global cell growth rate of the whole cortex. (3) The cortical folding pattern is dependent on relative rates of cell growth in different cortical areas. (4) The cortical folding pattern is dependent on the initial geometry of the cortex. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Salt movements and faulting of the overburden - can numerical modeling predict the fault patterns above salt structures?

NASA Astrophysics Data System (ADS)

Clausen, O. R.; Egholm, D. L.; Wesenberg, R.

2012-04-01

Salt deformation has been the topic of numerous studies through the 20th century and up until present because of the close relation between commercial hydrocarbons and salt structure provinces of the world (Hudec & Jackson, 2007). The fault distribution in sediments above salt structures influences among other things the productivity due to the segmentation of the reservoir (Stewart 2006). 3D seismic data above salt structures can map such fault patterns in great detail and studies have shown that a variety of fault patterns exists. Yet, most patterns fall between two end members: concentric and radiating fault patterns. Here we use a modified version of the numerical spring-slider model introduced by Malthe-Sørenssen et al.(1998a) for simulating the emergence of small scale faults and fractures above a rising salt structure. The three-dimensional spring-slider model enables us to control the rheology of the deforming overburden, the mechanical coupling between the overburden and the underlying salt, as well as the kinematics of the moving salt structure. In this presentation, we demonstrate how the horizontal component on the salt motion influences the fracture patterns within the overburden. The modeling shows that purely vertical movement of the salt introduces a mesh of concentric normal faults in the overburden, and that the frequency of radiating faults increases with the amount of lateral movements across the salt-overburden interface. The two end-member fault patterns (concentric vs. radiating) can thus be linked to two different styles of salt movement: i) the vertical rising of a salt indenter and ii) the inflation of a 'salt-balloon' beneath the deformed strata. The results are in accordance with published analogue and theoretical models, as well as natural systems, and the model may - when used appropriately - provide new insight into how the internal dynamics of the salt in a structure controls the generation of fault patterns above the structure. The model is thus an important contribution to the understanding of small-scale faults, which may be unresolved by seismic data when the hydrocarbon production from reservoirs located above salt structures is optimized.

Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.

PubMed

Takaguchi, Taro; Masuda, Naoki; Holme, Petter

2013-01-01

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.

Effects of whole spine alignment patterns on neck responses in rear end impact.

PubMed

Sato, Fusako; Odani, Mamiko; Miyazaki, Yusuke; Yamazaki, Kunio; Östh, Jonas; Svensson, Mats

2017-02-17

The aim of this study was to investigate the whole spine alignment in automotive seated postures for both genders and the effects of the spinal alignment patterns on cervical vertebral motion in rear impact using a human finite element (FE) model. Image data for 8 female and 7 male subjects in a seated posture acquired by an upright open magnetic resonance imaging (MRI) system were utilized. Spinal alignment was determined from the centers of the vertebrae and average spinal alignment patterns for both genders were estimated by multidimensional scaling (MDS). An occupant FE model of female average size (162 cm, 62 kg; the AF 50 size model) was developed by scaling THUMS AF 05. The average spinal alignment pattern for females was implemented in the model, and model validation was made with respect to female volunteer sled test data from rear end impacts. Thereafter, the average spinal alignment pattern for males and representative spinal alignments for all subjects were implemented in the validated female model, and additional FE simulations of the sled test were conducted to investigate effects of spinal alignment patterns on cervical vertebral motion. The estimated average spinal alignment pattern was slight kyphotic, or almost straight cervical and less-kyphotic thoracic spine for the females and lordotic cervical and more pronounced kyphotic thoracic spine for the males. The AF 50 size model with the female average spinal alignment exhibited spine straightening from upper thoracic vertebra level and showed larger intervertebral angular displacements in the cervical spine than the one with the male average spinal alignment. The cervical spine alignment is continuous with the thoracic spine, and a trend of the relationship between cervical spine and thoracic spinal alignment was shown in this study. Simulation results suggested that variations in thoracic spinal alignment had a potential impact on cervical spine motion as well as cervical spinal alignment in rear end impact condition.

Worldwide patterns of ischemic heart disease mortality from 1980 to 2010.

PubMed

Gouvinhas, Cláudia; Severo, Milton; Azevedo, Ana; Lunet, Nuno

2014-01-01

The trends in the IHD mortality rates vary widely across countries, reflecting the heterogeneity in the variation of the exposure to the main risk factors and in the access to different management strategies among settings. We aimed to identify model-based patterns in the time trends in IHD mortality in 50 countries from the five continents, between 1980 and 2010. Mixed models were used to identify time trends in age-standardized mortality rates (ASMR) (age group 35+years; world standard population), all including random terms for intercept, slope, quadratic and cubic. Model-based clustering was used to identify the patterns. We identified five main patterns of IHD mortality trends in the last three decades, similar for men and women. Pattern 1 had the highest ASMR and pattern 2 exhibited the most pronounced decrease in ASMR during the entire study period. Pattern 3 was characterized by an initial increase in ASMR, followed by a sharp decline. Countries in pattern 4 had the lowest ASMR throughout the study period. It was further divided into patterns 4a (consistent decrease in ASMR throughout the period of analysis) and 4b (less pronounced declines and highest rates observed mostly between 1996 and 2004). There was no correspondence between the geographic or economical grouping of the analyzed countries and the patterns found in this study. Our study yielded a new framework for the description, interpretation and prediction of IHD mortality trends worldwide. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge

NASA Astrophysics Data System (ADS)

Lin, Y.; Bajcsy, P.; Valocchi, A. J.; Kim, C.; Wang, J.

2007-12-01

Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies.

Retrospective lifetime dietary patterns predict cognitive performance in community-dwelling older Australians.

PubMed

Hosking, Diane E; Nettelbeck, Ted; Wilson, Carlene; Danthiir, Vanessa

2014-07-28

Dietary intake is a modifiable exposure that may have an impact on cognitive outcomes in older age. The long-term aetiology of cognitive decline and dementia, however, suggests that the relevance of dietary intake extends across the lifetime. In the present study, we tested whether retrospective dietary patterns from the life periods of childhood, early adulthood, adulthood and middle age predicted cognitive performance in a cognitively healthy sample of 352 older Australian adults >65 years. Participants completed the Lifetime Diet Questionnaire and a battery of cognitive tests designed to comprehensively assess multiple cognitive domains. In separate regression models, lifetime dietary patterns were the predictors of cognitive factor scores representing ten constructs derived by confirmatory factor analysis of the cognitive test battery. All regression models were progressively adjusted for the potential confounders of current diet, age, sex, years of education, English as native language, smoking history, income level, apoE ɛ4 status, physical activity, other past dietary patterns and health-related variables. In the adjusted models, lifetime dietary patterns predicted cognitive performance in this sample of older adults. In models additionally adjusted for intake from the other life periods and mechanistic health-related variables, dietary patterns from the childhood period alone reached significance. Higher consumption of the 'coffee and high-sugar, high-fat extras' pattern predicted poorer performance on simple/choice reaction time, working memory, retrieval fluency, short-term memory and reasoning. The 'vegetable and non-processed' pattern negatively predicted simple/choice reaction time, and the 'traditional Australian' pattern positively predicted perceptual speed and retrieval fluency. Identifying early-life dietary antecedents of older-age cognitive performance contributes to formulating strategies for delaying or preventing cognitive decline.

Exploring the Argumentation Pattern in Modeling-Based Learning about Apparent Motion of Mars

ERIC Educational Resources Information Center

Park, Su-Kyeong

2016-01-01

This study proposed an analytic framework for coding students' dialogic argumentation and investigated the characteristics of the small-group argumentation pattern observed in modeling-based learning. The participants were 122 second grade high school students in South Korea divided into an experimental and a comparison group. Modeling-based…

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.

Modeling the Hydration Layer around Proteins: Applications to Small- and Wide-Angle X-Ray Scattering

PubMed Central

Virtanen, Jouko Juhani; Makowski, Lee; Sosnick, Tobin R.; Freed, Karl F.

2011-01-01

Small-/wide-angle x-ray scattering (SWAXS) experiments can aid in determining the structures of proteins and protein complexes, but success requires accurate computational treatment of solvation. We compare two methods by which to calculate SWAXS patterns. The first approach uses all-atom explicit-solvent molecular dynamics (MD) simulations. The second, far less computationally expensive method involves prediction of the hydration density around a protein using our new HyPred solvation model, which is applied without the need for additional MD simulations. The SWAXS patterns obtained from the HyPred model compare well to both experimental data and the patterns predicted by the MD simulations. Both approaches exhibit advantages over existing methods for analyzing SWAXS data. The close correspondence between calculated and observed SWAXS patterns provides strong experimental support for the description of hydration implicit in the HyPred model. PMID:22004761

Condensation and fractionation of rare earths in the solar nebula

NASA Technical Reports Server (NTRS)

Davis, A. M.; Grossman, L.

1979-01-01

The condensation behavior of the rare earth elements in the solar nebula is calculated on the basis of the most recent thermodynamic data in order to construct a model explaining group II rare earth element patterns in Allende inclusions. Models considered all involve the removal of large fractions of the more refractory heavy rare earth elements in an early condensate, followed by the condensation of the remainder at a lower temperature. It is shown that the model of Boynton (1975) in which one rare earth element component is dissolved nonideally in perovskite according to relative activity coefficients can not reasonably be made to fit the observed group II patterns. A model in which two rare earth components control the patterns and dissolve ideally in perovskite is proposed and shown to be able to account for the 20 patterns by variations of the perovskite removal temperature and the relative proportions of the two components.

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.

Characterizing brain patterns in conversion from mild cognitive impairment (MCI) to Alzheimer's disease

NASA Astrophysics Data System (ADS)

Silva R., Santiago S.; Giraldo, Diana L.; Romero, Eduardo

2017-11-01

Structural Magnetic Resonance (MR) brain images should provide quantitative information about the stage and progression of Alzheimer's disease. However, the use of MRI is limited and practically reduced to corroborate a diagnosis already performed with neuropsychological tools. This paper presents an automated strategy for extraction of relevant anatomic patterns related with the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) using T1-weighted MR images. The process starts by representing each of the possible classes with models generated from a linear combination of volumes. The difference between models allows us to establish which are the regions where relevant patterns might be located. The approach searches patterns in a space of brain sulci, herein approximated by the most representative gradients found in regions of interest defined by the difference between the linear models. This hypothesis is assessed by training a conventional SVM model with the found relevant patterns under a leave-one-out scheme. The resultant AUC was 0.86 for the group of women and 0.61 for the group of men.

Oscillations in Spurious States of the Associative Memory Model with Synaptic Depression

NASA Astrophysics Data System (ADS)

Murata, Shin; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato

2014-12-01

The associative memory model is a typical neural network model that can store discretely distributed fixed-point attractors as memory patterns. When the network stores the memory patterns extensively, however, the model has other attractors besides the memory patterns. These attractors are called spurious memories. Both spurious states and memory states are in equilibrium, so there is little difference between their dynamics. Recent physiological experiments have shown that the short-term dynamic synapse called synaptic depression decreases its efficacy of transmission to postsynaptic neurons according to the activities of presynaptic neurons. Previous studies revealed that synaptic depression destabilizes the memory states when the number of memory patterns is finite. However, it is very difficult to study the dynamical properties of the spurious states if the number of memory patterns is proportional to the number of neurons. We investigate the effect of synaptic depression on spurious states by Monte Carlo simulation. The results demonstrate that synaptic depression does not affect the memory states but mainly destabilizes the spurious states and induces periodic oscillations.

Contribution of intrinsic properties and synaptic inputs to motoneuron discharge patterns: a simulation study

PubMed Central

ElBasiouny, Sherif M.; Rymer, W. Zev; Heckman, C. J.

2012-01-01

Motoneuron discharge patterns reflect the interaction of synaptic inputs with intrinsic conductances. Recent work has focused on the contribution of conductances mediating persistent inward currents (PICs), which amplify and prolong the effects of synaptic inputs on motoneuron discharge. Certain features of human motor unit discharge are thought to reflect a relatively stereotyped activation of PICs by excitatory synaptic inputs; these features include rate saturation and de-recruitment at a lower level of net excitation than that required for recruitment. However, PIC activation is also influenced by the pattern and spatial distribution of inhibitory inputs that are activated concurrently with excitatory inputs. To estimate the potential contributions of PIC activation and synaptic input patterns to motor unit discharge patterns, we examined the responses of a set of cable motoneuron models to different patterns of excitatory and inhibitory inputs. The models were first tuned to approximate the current- and voltage-clamp responses of low- and medium-threshold spinal motoneurons studied in decerebrate cats and then driven with different patterns of excitatory and inhibitory inputs. The responses of the models to excitatory inputs reproduced a number of features of human motor unit discharge. However, the pattern of rate modulation was strongly influenced by the temporal and spatial pattern of concurrent inhibitory inputs. Thus, even though PIC activation is likely to exert a strong influence on firing rate modulation, PIC activation in combination with different patterns of excitatory and inhibitory synaptic inputs can produce a wide variety of motor unit discharge patterns. PMID:22031773

Reconfiguration of the pontomedullary respiratory network: a computational modeling study with coordinated in vivo experiments.

PubMed

Rybak, I A; O'Connor, R; Ross, A; Shevtsova, N A; Nuding, S C; Segers, L S; Shannon, R; Dick, T E; Dunin-Barkowski, W L; Orem, J M; Solomon, I C; Morris, K F; Lindsey, B G

2008-10-01

A large body of data suggests that the pontine respiratory group (PRG) is involved in respiratory phase-switching and the reconfiguration of the brain stem respiratory network. However, connectivity between the PRG and ventral respiratory column (VRC) in computational models has been largely ad hoc. We developed a network model with PRG-VRC connectivity inferred from coordinated in vivo experiments. Neurons were modeled in the "integrate-and-fire" style; some neurons had pacemaker properties derived from the model of Breen et al. We recapitulated earlier modeling results, including reproduction of activity profiles of different respiratory neurons and motor outputs, and their changes under different conditions (vagotomy, pontine lesions, etc.). The model also reproduced characteristic changes in neuronal and motor patterns observed in vivo during fictive cough and during hypoxia in non-rapid eye movement sleep. Our simulations suggested possible mechanisms for respiratory pattern reorganization during these behaviors. The model predicted that network- and pacemaker-generated rhythms could be co-expressed during the transition from gasping to eupnea, producing a combined "burst-ramp" pattern of phrenic discharges. To test this prediction, phrenic activity and multiple single neuron spike trains were monitored in vagotomized, decerebrate, immobilized, thoracotomized, and artificially ventilated cats during hypoxia and recovery. In most experiments, phrenic discharge patterns during recovery from hypoxia were similar to those predicted by the model. We conclude that under certain conditions, e.g., during recovery from severe brain hypoxia, components of a distributed network activity present during eupnea can be co-expressed with gasp patterns generated by a distinct, functionally "simplified" mechanism.

Rocks and Rain: orographic precipitation and the form of mountain ranges

NASA Astrophysics Data System (ADS)

Roe, G. H.; Anders, A. M.; Durran, D. R.; Montgomery, D. R.; Hallet, B.

2005-12-01

In mountainous landscapes patterns of erosion reflect patterns of precipitation that are, in turn, controlled by the orography. Ultimately therefore, the feedbacks between orography and the climate it creates are responsible for the sculpting of mountain ranges. Key questions concerning these interactions are: 1) how robust are patterns of precipitation on geologic time scales? and 2) how do those patterns affect landscape form? Since climate is by definition the statistics of weather, there is tremendous information to be gleaned from how patterns of precipitation vary between different weather events. However up to now sparse measurements and computational limitations have hampered our knowledge of such variations. For the Olympics in Washington State, a characteristic midlatitude mountain range, we report results from a high-resolution, state-of-the-art numerical weather prediction model and a dense network of precipitation gauges. Down to scales around 10 km, the patterns of precipitation are remarkably robust both storm-by-storm and year-to-year, lending confidence that they are indeed persistent on the relevant time scales. Secondly, the consequences of the coupled interactions are presented using a landscape evolution model coupled with a simple model of orographic precipitation that is able to substantially reproduce the observed precipitation patterns.

Statistical model for speckle pattern optimization.

PubMed

Su, Yong; Zhang, Qingchuan; Gao, Zeren

2017-11-27

Image registration is the key technique of optical metrologies such as digital image correlation (DIC), particle image velocimetry (PIV), and speckle metrology. Its performance depends critically on the quality of image pattern, and thus pattern optimization attracts extensive attention. In this article, a statistical model is built to optimize speckle patterns that are composed of randomly positioned speckles. It is found that the process of speckle pattern generation is essentially a filtered Poisson process. The dependence of measurement errors (including systematic errors, random errors, and overall errors) upon speckle pattern generation parameters is characterized analytically. By minimizing the errors, formulas of the optimal speckle radius are presented. Although the primary motivation is from the field of DIC, we believed that scholars in other optical measurement communities, such as PIV and speckle metrology, will benefit from these discussions.

A fractal growth model: Exploring the connection pattern of hubs in complex networks

NASA Astrophysics Data System (ADS)

Li, Dongyan; Wang, Xingyuan; Huang, Penghe

2017-04-01

Fractal is ubiquitous in many real-world networks. Previous researches showed that the strong disassortativity between the hub-nodes on all length scales was the key principle that gave rise to the fractal architecture of networks. Although fractal property emerged in some models, there were few researches about the fractal growth model and quantitative analyses about the strength of the disassortativity for fractal model. In this paper, we proposed a novel inverse renormalization method, named Box-based Preferential Attachment (BPA), to build the fractal growth models in which the Preferential Attachment was performed at box level. The proposed models provided a new framework that demonstrated small-world-fractal transition. Also, we firstly demonstrated the statistical characteristic of connection patterns of the hubs in fractal networks. The experimental results showed that, given proper growing scale and added edges, the proposed models could clearly show pure small-world or pure fractal or both of them. It also showed that the hub connection ratio showed normal distribution in many real-world networks. At last, the comparisons of connection pattern between the proposed models and the biological and technical networks were performed. The results gave useful reference for exploring the growth principle and for modeling the connection patterns for real-world networks.

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

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

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

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.

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

Complex Systems and Human Performance Modeling

DTIC Science & Technology

2013-12-01

human communication patterns can be implemented in a task network modeling tool. Although queues are a basic feature in many task network modeling...time. MODELING COMMUNICATIVE BEHAVIOR Barabasi (2010) argues that human communication patterns are “bursty”; that is, the inter-event arrival...Having implemented the methods advocated by Clauset et al. in C3TRACE, we have grown more confident that the human communication data discussed above

Research on the decision-making model of land-use spatial optimization

NASA Astrophysics Data System (ADS)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

Robust stochastic Turing patterns in the development of a one-dimensional cyanobacterial organism.

PubMed

Di Patti, Francesca; Lavacchi, Laura; Arbel-Goren, Rinat; Schein-Lubomirsky, Leora; Fanelli, Duccio; Stavans, Joel

2018-05-01

Under nitrogen deprivation, the one-dimensional cyanobacterial organism Anabaena sp. PCC 7120 develops patterns of single, nitrogen-fixing cells separated by nearly regular intervals of photosynthetic vegetative cells. We study a minimal, stochastic model of developmental patterns in Anabaena that includes a nondiffusing activator, two diffusing inhibitor morphogens, demographic fluctuations in the number of morphogen molecules, and filament growth. By tracking developing filaments, we provide experimental evidence for different spatiotemporal roles of the two inhibitors during pattern maintenance and for small molecular copy numbers, justifying a stochastic approach. In the deterministic limit, the model yields Turing patterns within a region of parameter space that shrinks markedly as the inhibitor diffusivities become equal. Transient, noise-driven, stochastic Turing patterns are produced outside this region, which can then be fixed by downstream genetic commitment pathways, dramatically enhancing the robustness of pattern formation, also in the biologically relevant situation in which the inhibitors' diffusivities may be comparable.

Pattern statistics on Markov chains and sensitivity to parameter estimation

PubMed Central

Nuel, Grégory

2006-01-01

Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). Results: In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of σ, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. Conclusion: We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation. PMID:17044916

Pattern statistics on Markov chains and sensitivity to parameter estimation.

PubMed

Nuel, Grégory

2006-10-17

In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of sigma, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation.

An exploration of spatial patterns of seasonal diarrhoeal morbidity in Thailand.

PubMed

McCormick, B J J; Alonso, W J; Miller, M A

2012-07-01

Studies of temporal and spatial patterns of diarrhoeal disease can suggest putative aetiological agents and environmental or socioeconomic drivers. Here, the seasonal patterns of monthly acute diarrhoeal morbidity in Thailand, where diarrhoeal morbidity is increasing, are explored. Climatic data (2003-2006) and Thai Ministry of Health annual reports (2003-2009) were used to construct a spatially weighted panel regression model. Seasonal patterns of diarrhoeal disease were generally bimodal with aetiological agents peaking at different times of the year. There is a strong association between daily mean temperature and precipitation and the incidence of hospitalization due to acute diarrhoea in Thailand leading to a distinct spatial pattern in the seasonal pattern of diarrhoea. Model performance varied across the country in relation to per capita GDP and population density. While climatic factors are likely to drive the general pattern of diarrhoeal disease in Thailand, the seasonality of diarrhoeal disease is dampened in affluent urban populations.

Observations of diffusion-limited aggregation-like patterns by atmospheric plasma jet

NASA Astrophysics Data System (ADS)

Chiu, Ching-Yang; Chu, Hong-Yu

2017-11-01

We report on the observations of diffusion-limited aggregation-like patterns during the thin film removal process by an atmospheric plasma jet. The fractal patterns are found to have various structures like dense branching and tree-like patterns. The determination of surface morphology reveals that the footprints of discharge bursts are not as random as expected. We propose a diffusion-limited aggregation model with a few extra requirements by analogy with the experimental results, and thereby present the beauty of nature. We show that the model simulates not only the shapes of the patterns similar to the experimental observations, but also the growing sequences of fluctuating, oscillatory, and zigzag traces.

Modifiability Tactics

DTIC Science & Technology

2007-09-01

The Pattern Understood in Terms of Tactics 44 13.4 Variants 44 14 Microkernel Pattern 45 14.1 Problem 45 14.2 Solution 45 14.3 The Pattern...Figure 12: Model-View-Controller Pattern Structure 42 Figure 13: Presentation-Abstraction-Control Pattern Structure 43 Figure 14: Microkernel ...Presentation- Abstraction- Control X X X X Microkernel X X X X X Reflection X X Each pattern is described in more detail in the

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

PubMed

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessing Airflow Sensitivity to Healthy and Diseased Lung Conditions in a Computational Fluid Dynamics Model Validated In Vitro.

PubMed

Sul, Bora; Oppito, Zachary; Jayasekera, Shehan; Vanger, Brian; Zeller, Amy; Morris, Michael; Ruppert, Kai; Altes, Talissa; Rakesh, Vineet; Day, Steven; Robinson, Risa; Reifman, Jaques; Wallqvist, Anders

2018-05-01

Computational models are useful for understanding respiratory physiology. Crucial to such models are the boundary conditions specifying the flow conditions at truncated airway branches (terminal flow rates). However, most studies make assumptions about these values, which are difficult to obtain in vivo. We developed a computational fluid dynamics (CFD) model of airflows for steady expiration to investigate how terminal flows affect airflow patterns in respiratory airways. First, we measured in vitro airflow patterns in a physical airway model, using particle image velocimetry (PIV). The measured and computed airflow patterns agreed well, validating our CFD model. Next, we used the lobar flow fractions from a healthy or chronic obstructive pulmonary disease (COPD) subject as constraints to derive different terminal flow rates (i.e., three healthy and one COPD) and computed the corresponding airflow patterns in the same geometry. To assess airflow sensitivity to the boundary conditions, we used the correlation coefficient of the shape similarity (R) and the root-mean-square of the velocity magnitude difference (Drms) between two velocity contours. Airflow patterns in the central airways were similar across healthy conditions (minimum R, 0.80) despite variations in terminal flow rates but markedly different for COPD (minimum R, 0.26; maximum Drms, ten times that of healthy cases). In contrast, those in the upper airway were similar for all cases. Our findings quantify how variability in terminal and lobar flows contributes to airflow patterns in respiratory airways. They highlight the importance of using lobar flow fractions to examine physiologically relevant airflow characteristics.

Advances in the use of observed spatial patterns of catchment hydrological response

NASA Astrophysics Data System (ADS)

Grayson, Rodger B.; Blöschl, Günter; Western, Andrew W.; McMahon, Thomas A.

Over the past two decades there have been repeated calls for the collection of new data for use in developing hydrological science. The last few years have begun to bear fruit from the seeds sown by these calls, through increases in the availability and utility of remote sensing data, as well as the execution of campaigns in research catchments aimed at providing new data for advancing hydrological understanding and predictive capability. In this paper we discuss some philosophical considerations related to model complexity, data availability and predictive performance, highlighting the potential of observed patterns in moving the science and practice of catchment hydrology forward. We then review advances that have arisen from recent work on spatial patterns, including in the characterisation of spatial structure and heterogeneity, and the use of patterns for developing, calibrating and testing distributed hydrological models. We illustrate progress via examples using observed patterns of snow cover, runoff occurrence and soil moisture. Methods for the comparison of patterns are presented, illustrating how they can be used to assess hydrologically important characteristics of model performance. These methods include point-to-point comparisons, spatial relationships between errors and landscape parameters, transects, and optimal local alignment. It is argued that the progress made to date augers well for future developments, but there is scope for improvements in several areas. These include better quantitative methods for pattern comparisons, better use of pattern information in data assimilation and modelling, and a call for improved archiving of data from field studies to assist in comparative studies for generalising results and developing fundamental understanding.

How predictable is the anomaly pattern of the Indian summer rainfall?

NASA Astrophysics Data System (ADS)

Li, Juan; Wang, Bin

2016-05-01

Century-long efforts have been devoted to seasonal forecast of Indian summer monsoon rainfall (ISMR). Most studies of seasonal forecast so far have focused on predicting the total amount of summer rainfall averaged over the entire India (i.e., all Indian rainfall index-AIRI). However, it is practically more useful to forecast anomalous seasonal rainfall distribution (anomaly pattern) across India. The unknown science question is to what extent the anomalous rainfall pattern is predictable. This study attempted to address this question. Assessment of the 46-year (1960-2005) hindcast made by the five state-of-the-art ENSEMBLE coupled dynamic models' multi-model ensemble (MME) prediction reveals that the temporal correlation coefficient (TCC) skill for prediction of AIRI is 0.43, while the area averaged TCC skill for prediction of anomalous rainfall pattern is only 0.16. The present study aims to estimate the predictability of ISMR on regional scales by using Predictable Mode Analysis method and to develop a set of physics-based empirical (P-E) models for prediction of ISMR anomaly pattern. We show that the first three observed empirical orthogonal function (EOF) patterns of the ISMR have their distinct dynamical origins rooted in an eastern Pacific-type La Nina, a central Pacific-type La Nina, and a cooling center near dateline, respectively. These equatorial Pacific sea surface temperature anomalies, while located in different longitudes, can all set up a specific teleconnection pattern that affects Indian monsoon and results in different rainfall EOF patterns. Furthermore, the dynamical models' skill for predicting ISMR distribution primarily comes primarily from these three modes. Therefore, these modes can be regarded as potentially predictable modes. If these modes are perfectly predicted, about 51 % of the total observed variability is potentially predictable. Based on understanding the lead-lag relationships between the lower boundary anomalies and the predictable modes, a set of P-E models is established to predict the principal component of each predictable mode, so that the ISMR anomaly pattern can be predicted by using the sum of the predictable modes. Three validation schemes are used to assess the performance of the P-E models' hindcast and independent forecast. The validated TCC skills of the P-E model here are more than doubled that of dynamical models' MME hindcast, suggesting a large room for improvement of the current dynamical prediction. The methodology proposed here can be applied to a wide range of climate prediction and predictability studies. The limitation and future improvement are also discussed.

An analytical model for the celestial distribution of polarized light, accounting for polarization singularities, wavelength and atmospheric turbidity

NASA Astrophysics Data System (ADS)

Wang, Xin; Gao, Jun; Fan, Zhiguo; Roberts, Nicholas W.

2016-06-01

We present a computationally inexpensive analytical model for simulating celestial polarization patterns in variable conditions. We combine both the singularity theory of Berry et al (2004 New J. Phys. 6 162) and the intensity model of Perez et al (1993 Sol. Energy 50 235-245) such that our single model describes three key sets of data: (1) the overhead distribution of the degree of polarization as well as the existence of neutral points in the sky; (2) the change in sky polarization as a function of the turbidity of the atmosphere; and (3) sky polarization patterns as a function of wavelength, calculated in this work from the ultra-violet to the near infra-red. To verify the performance of our model we generate accurate reference data using a numerical radiative transfer model and statistical comparisons between these two methods demonstrate no significant difference in almost all situations. The development of our analytical model provides a novel method for efficiently calculating the overhead skylight polarization pattern. This provides a new tool of particular relevance for our understanding of animals that use the celestial polarization pattern as a source of visual information.

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.

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 neural network model for transference and repetition compulsion based on pattern completion.

PubMed

Javanbakht, Arash; Ragan, Charles L

2008-01-01

In recent years because of the fascinating growth of the body of neuroscientific knowledge, psychoanalytic scientists have worked on models for the neurological substrates of key psychoanalytic concepts. Transference is an important example. In this article, the psychological process of transference is described, employing the neurological function of pattern completion in hippocampal and thalamo-cortical pathways. Similarly, repetition compulsion is seen as another type of such neurological function; however, it is understood as an attempt for mastery of the unknown, rather than simply for mastery of past experiences and perceptions. Based on this suggested model of neurological function, the myth of the psychoanalyst as blank screen is seen as impossible and ineffective, based on neurofunctional understandings of neuropsychological process. The mutative effect of psychoanalytic therapy, correcting patterns of pathological relatedness, is described briefly from conscious and unconscious perspectives. While cognitive understanding (insight) helps to modify transferentially restored, maladaptive patterns of relatedness, the development of more adaptive patterns is also contingent upon an affective experience (working through), which alters the neurological substrates of unconscious, pathological affective patterns and their neurological functional correlates.

Fiber Diffraction Data Indicate a Hollow Core for the Alzheimer’s Aβ Three-fold Symmetric Fibril

PubMed Central

McDonald, Michele; Box, Hayden; Bian, Wen; Kendall, Amy; Tycko, Robert; Stubbs, Gerald

2012-01-01

Amyloid β protein (Aβ), the principal component of the extracellular plaques found in the brains of Alzheimer’s disease patients, forms fibrils well suited to structural study by X-ray fiber diffraction. Fiber diffraction patterns from the 40-residue form Aβ(1–40) confirm a number of features of a three-fold symmetric Aβ model from solid state NMR, but suggest that the fibrils have a hollow core, not present in the original ssNMR models. Diffraction patterns calculated from a revised hollow three-fold model with a more regular β-sheet structure are in much better agreement with the observed diffraction data than patterns calculated from the original ssNMR model. Refinement of a hollow-core model against ssNMR data led to a revised ssNMR model, similar to the fiber diffraction model. PMID:22903058

Second-order oriented partial-differential equations for denoising in electronic-speckle-pattern interferometry fringes.

PubMed

Tang, Chen; Han, Lin; Ren, Hongwei; Zhou, Dongjian; Chang, Yiming; Wang, Xiaohang; Cui, Xiaolong

2008-10-01

We derive the second-order oriented partial-differential equations (PDEs) for denoising in electronic-speckle-pattern interferometry fringe patterns from two points of view. The first is based on variational methods, and the second is based on controlling diffusion direction. Our oriented PDE models make the diffusion along only the fringe orientation. The main advantage of our filtering method, based on oriented PDE models, is that it is very easy to implement compared with the published filtering methods along the fringe orientation. We demonstrate the performance of our oriented PDE models via application to two computer-simulated and experimentally obtained speckle fringes and compare with related PDE models.

A musculoskeletal foot model for clinical gait analysis.

PubMed

Saraswat, Prabhav; Andersen, Michael S; Macwilliams, Bruce A

2010-06-18

Several full body musculoskeletal models have been developed for research applications and these models may potentially be developed into useful clinical tools to assess gait pathologies. Existing full-body musculoskeletal models treat the foot as a single segment and ignore the motions of the intrinsic joints of the foot. This assumption limits the use of such models in clinical cases with significant foot deformities. Therefore, a three-segment musculoskeletal model of the foot was developed to match the segmentation of a recently developed multi-segment kinematic foot model. All the muscles and ligaments of the foot spanning the modeled joints were included. Muscle pathways were adjusted with an optimization routine to minimize the difference between the muscle flexion-extension moment arms from the model and moment arms reported in literature. The model was driven by walking data from five normal pediatric subjects (aged 10.6+/-1.57 years) and muscle forces and activation levels required to produce joint motions were calculated using an inverse dynamic analysis approach. Due to the close proximity of markers on the foot, small marker placement error during motion data collection may lead to significant differences in musculoskeletal model outcomes. Therefore, an optimization routine was developed to enforce joint constraints, optimally scale each segment length and adjust marker positions. To evaluate the model outcomes, the muscle activation patterns during walking were compared with electromyography (EMG) activation patterns reported in the literature. Model-generated muscle activation patterns were observed to be similar to the EMG activation patterns. Published by Elsevier Ltd.

Geographic patterns and dynamics of Alaskan climate interpolated from a sparse station record

USGS Publications Warehouse

Fleming, Michael D.; Chapin, F. Stuart; Cramer, W.; Hufford, Gary L.; Serreze, Mark C.

2000-01-01

Data from a sparse network of climate stations in Alaska were interpolated to provide 1-km resolution maps of mean monthly temperature and precipitation-variables that are required at high spatial resolution for input into regional models of ecological processes and resource management. The interpolation model is based on thin-plate smoothing splines, which uses the spatial data along with a digital elevation model to incorporate local topography. The model provides maps that are consistent with regional climatology and with patterns recognized by experienced weather forecasters. The broad patterns of Alaskan climate are well represented and include latitudinal and altitudinal trends in temperature and precipitation and gradients in continentality. Variations within these broad patterns reflect both the weakening and reduction in frequency of low-pressure centres in their eastward movement across southern Alaska during the summer, and the shift of the storm tracks into central and northern Alaska in late summer. Not surprisingly, apparent artifacts of the interpolated climate occur primarily in regions with few or no stations. The interpolation model did not accurately represent low-level winter temperature inversions that occur within large valleys and basins. Along with well-recognized climate patterns, the model captures local topographic effects that would not be depicted using standard interpolation techniques. This suggests that similar procedures could be used to generate high-resolution maps for other high-latitude regions with a sparse density of data.

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

Sub-annual paleoenvironmental information evaluated from intensity variations of fluorescent annual layers in a stalagmite from Ryuo-do Cave, Nagasaki Prefecture, western Japan

NASA Astrophysics Data System (ADS)

Sasaki, Hana; Onishi, Yuri; Ishihara, Yoshiro; Yoshimura, Kazuhisa

2017-04-01

Stalagmites can provide various types of paleoenvironmental information such as information on vegetation and climate changes. Fluorescent annual layers formed by humic substances (mainly fulvic acids: FA) in these stalagmites can also provide a time proxy, and a time series on precipitation. Fluorescence intensity patterns in these annual layers can be classified into symmetric, gradually increasing and gradually decreasing types. Onishi et al. (EGU2016) demonstrated the existence of these fluorescence intensity patterns in the annual layers, and their stratigraphic changes, by numerical simulations, and suggested that the patterns could provide paleoenvironmental information at a sub-annual resolution. In this study, we carried out an analysis of fluorescence intensity patterns in the annual layers of a stalagmite from Ryuo-do Cave, Nagasaki Prefecture, western Japan, and also simulated the patterns in the stalagmite, to obtain paleoenvironmental information. Fluorescence intensity patterns in the annual layers are strongly affected by annual variations in FA concentration and precipitation rates of calcite. As the result of simulations of fluorescence intensity patterns, cumulative variations and various types of pattern are reproduced. These differences are depending on time lags between the variation of the FA concentration in the drip waters, and that of the growth rate of the stalagmite. Co-precipitation models of FA are divided into the "Hiatus model" in which FA are preferentially preserved in the stalagmite when its growth rate is relatively low, and the "Partition coefficient (PC) model" in which FA concentrations in the stalagmite increase when the calcite precipitation rate is relatively high. However, various fluorescence intensity patterns in the annual layers could be formed under a combination or either of both of the models. Fluorescence intensity patterns in an annual layer in the stalagmite from Ryuo-do Cave, Nagasaki Prefecture, western Japan vary stratigraphically, and multiple types of fluorescence intensity pattern are observed in the stalagmite. When the co-precipitation of FA is governed by the hiatus model, it is suggested that a gradual increase in the annual layers will result from a large accumulation of calcite after the annual peak in the FA concentration, whereas there will be a gradual decrease if the main growth occurs before the annual peak in FA concentration. However, in the case of the PC model, a gradually increasing type of pattern is formed if the main growth occurs before the annual peak in FA concentration, and a gradually decreasing type is formed if the main growth occurs afterwards. If the annual peak of FA concentration occurs several months after high summer, it is suggested that intervals showing a gradually increasing type were formed in winter, and intervals showing a gradually decreasing type were formed in the early summer, in the case of the hiatus model. In the case of PC model, the seasons are reversed. In the climatic environment around the Ryuo-do Cave, the growth rates of stalagmites are affected by cave air circulation in winter and by rainfall (rainy season) in early summer.

Detecting Aberrant Response Patterns in the Rasch Model. Rapport 87-3.

ERIC Educational Resources Information Center

Kogut, Jan

In this paper, the detection of response patterns aberrant from the Rasch model is considered. For this purpose, a new person fit index, recently developed by I. W. Molenaar (1987) and an iterative estimation procedure are used in a simulation study of Rasch model data mixed with aberrant data. Three kinds of aberrant response behavior are…

46 CFR 160.047-1 - Incorporation by reference.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., Models AK-1, and AF-1. Sheet 2, Rev. 2—Cutting Pattern and General Arrangement, Models CKM-1 and CFM-1. Sheet 3, Rev. 2—Cutting Pattern and General Arrangement, Models CKS-1 and CFS-1. Sheet 4, Rev. 1—Pad... Business Service Center, General Services Administration, Washington, DC 20407; (3) The military...

Testing of DRAINMOD for Forested Watersheds with Non-Pattern Drainage

Treesearch

Devendra M. Amatya; Ge Sun; R. Wayne Skaggs; Carl C. Trettin

2003-01-01

Models like DRAINMOD and its forestry version, DRAINLOB, have been specifically developed as a field scale model for evaluating hydrologic effects of crops (trees), soil, and water management practices for lands with pattern drainage (i.e. with parallel ditches) on relatively flat, high water table soils. These models conduct a water balance between the ditches to...

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

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;

Patterns and controlling factors of species diversity in the Arctic Ocean

USGS Publications Warehouse

Yasuhara, Moriaki; Hunt, Gene; van Dijken, Gert; Arrigo, Kevin R.; Cronin, Thomas M.; Wollenburg, Jutta E.

2012-01-01

Aim  The Arctic Ocean is one of the last near-pristine regions on Earth, and, although human activities are expected to impact on Arctic ecosystems, we know very little about baseline patterns of Arctic Ocean biodiversity. This paper aims to describe Arctic Ocean-wide patterns of benthic biodiversity and to explore factors related to the large-scale species diversity patterns.Location  Arctic Ocean.Methods  We used large ostracode and foraminiferal datasets to describe the biodiversity patterns and applied comprehensive ecological modelling to test the degree to which these patterns are potentially governed by environmental factors, such as temperature, productivity, seasonality, ice cover and others. To test environmental control of the observed diversity patterns, subsets of samples for which all environmental parameters were available were analysed with multiple regression and model averaging.Results  Well-known negative latitudinal species diversity gradients (LSDGs) were found in metazoan Ostracoda, but the LSDGs were unimodal with an intermediate maximum with respect to latitude in protozoan foraminifera. Depth species diversity gradients were unimodal, with peaks in diversity shallower than those in other oceans. Our modelling results showed that several factors are significant predictors of diversity, but the significant predictors were different among shallow marine ostracodes, deep-sea ostracodes and deep-sea foraminifera.Main conclusions  On the basis of these Arctic Ocean-wide comprehensive datasets, we document large-scale diversity patterns with respect to latitude and depth. Our modelling results suggest that the underlying mechanisms causing these species diversity patterns are unexpectedly complex. The environmental parameters of temperature, surface productivity, seasonality of productivity, salinity and ice cover can all play a role in shaping large-scale diversity patterns, but their relative importance may depend on the ecological preferences of taxa and the oceanographic context of regions. These results suggest that a multiplicity of variables appear to be related to community structure in this system.

Patterns and Predictors of Language and Literacy Abilities 4-10 Years in the Longitudinal Study of Australian Children

PubMed Central

Zubrick, Stephen R.; Taylor, Catherine L.; Christensen, Daniel

2015-01-01

Aims Oral language is the foundation of literacy. Naturally, policies and practices to promote children’s literacy begin in early childhood and have a strong focus on developing children’s oral language, especially for children with known risk factors for low language ability. The underlying assumption is that children’s progress along the oral to literate continuum is stable and predictable, such that low language ability foretells low literacy ability. This study investigated patterns and predictors of children’s oral language and literacy abilities at 4, 6, 8 and 10 years. The study sample comprised 2,316 to 2,792 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Six developmental patterns were observed, a stable middle-high pattern, a stable low pattern, an improving pattern, a declining pattern, a fluctuating low pattern, and a fluctuating middle-high pattern. Most children (69%) fit a stable middle-high pattern. By contrast, less than 1% of children fit a stable low pattern. These results challenged the view that children’s progress along the oral to literate continuum is stable and predictable. Findings Multivariate logistic regression was used to investigate risks for low literacy ability at 10 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. Predictors were modelled as risk variables with the lowest level of risk as the reference category. In the multivariate model, substantial risks for low literacy ability at 10 years, in order of descending magnitude, were: low school readiness, Aboriginal and/or Torres Strait Islander status and low language ability at 8 years. Moderate risks were high temperamental reactivity, low language ability at 4 years, and low language ability at 6 years. The following risk factors were not statistically significant in the multivariate model: Low maternal consistency, low family income, health care card, child not read to at home, maternal smoking, maternal education, family structure, temperamental persistence, and socio-economic area disadvantage. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude did not do particularly well in predicting low literacy ability at 10 years. PMID:26352436

Using data tagging to improve the performance of Kanerva's sparse distributed memory

NASA Technical Reports Server (NTRS)

Rogers, David

1988-01-01

The standard formulation of Kanerva's sparse distributed memory (SDM) involves the selection of a large number of data storage locations, followed by averaging the data contained in those locations to reconstruct the stored data. A variant of this model is discussed, in which the predominant pattern is the focus of reconstruction. First, one architecture is proposed which returns the predominant pattern rather than the average pattern. However, this model will require too much storage for most uses. Next, a hybrid model is proposed, called tagged SDM, which approximates the results of the predominant pattern machine, but is nearly as efficient as Kanerva's original formulation. Finally, some experimental results are shown which confirm that significant improvements in the recall capability of SDM can be achieved using the tagged architecture.

Diatom-sedimentation feedback generates a self-organized geomorphic landscape on intertidal mudflats (Invited)

NASA Astrophysics Data System (ADS)

van de Koppel, J.; Weerman, E.; Herman, P.

2010-12-01

During spring, intertidal flats can exhibit strikingly regular spatial patterns of diatom-covered hummocks alternating with almost bare, water-filled hollows. We hypothesize that 1) the formation of this geomorphic landscape is caused by a strong interaction between benthic diatoms and sediment dynamics, inducing spatial self-organization, and 2) that self-organization affects ecosystem functioning by increasing the net average sedimentation on the tidal flat. We present a combined empirical and mathematical study to test the first hypothesis. We determined how the sediment erosion threshold varied with diatom cover and elevation. Our results were incorporated into a mathematical model to investigate whether the proposed mechanism could explain the formation of the observed patterns. Our mathematical model confirmed that the interaction between sedimentation, diatom growth and water redistribution could induce the formation of regular patterns on the intertidal mudflat. The model predicts that areas exhibiting spatially-self-organized patterns have increased sediment accretion and diatom biomass compared with areas lacking spatial patterns. We tested this prediction by following the sediment elevation during the season on both patterned and unpatterned parts of the mudflat. The results of our study confirmed our model prediction, as more sediment was found to accumulate in patterned parts of the mudflat, revealing how self-organization affected the functioning of mudflat ecosystems. Our study on intertidal mudflats provides a simple but clear-cut example of how the interaction between biological and geomorphological processes, through the process of self-organization, induces a self-organized geomorphic landscape.

Alternative mechanisms alter the emergent properties of self-organization in mussel beds

PubMed Central

Liu, Quan-Xing; Weerman, Ellen J.; Herman, Peter M. J.; Olff, Han; van de Koppel, Johan

2012-01-01

Theoretical models predict that spatial self-organization can have important, unexpected implications by affecting the functioning of ecosystems in terms of resilience and productivity. Whether and how these emergent effects depend on specific formulations of the underlying mechanisms are questions that are often ignored. Here, we compare two alternative models of regular spatial pattern formation in mussel beds that have different mechanistic descriptions of the facilitative interactions between mussels. The first mechanism involves a reduced mussel loss rate at high density owing to mutual protection between the mussels, which is the basis of prior studies on the pattern formation in mussels. The second mechanism assumes, based on novel experimental evidence, that mussels feed more efficiently on top of mussel-generated hummocks. Model simulations point out that the second mechanism produces very similar types of spatial patterns in mussel beds. Yet the mechanisms predict a strikingly contrasting effect of these spatial patterns on ecosystem functioning, in terms of productivity and resilience. In the first model, where high mussel densities reduce mussel loss rates, patterns are predicted to strongly increase productivity and decrease the recovery time of the bed following a disturbance. When pattern formation is generated by increased feeding efficiency on hummocks, only minor emergent effects of pattern formation on ecosystem functioning are predicted. Our results provide a warning against predictions of the implications and emergent properties of spatial self-organization, when the mechanisms that underlie self-organization are incompletely understood and not based on the experimental study. PMID:22418256

Mining patterns in persistent surveillance systems with smart query and visual analytics

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.; Shirkhodaie, Amir

2013-05-01

In Persistent Surveillance Systems (PSS) the ability to detect and characterize events geospatially help take pre-emptive steps to counter adversary's actions. Interactive Visual Analytic (VA) model offers this platform for pattern investigation and reasoning to comprehend and/or predict such occurrences. The need for identifying and offsetting these threats requires collecting information from diverse sources, which brings with it increasingly abstract data. These abstract semantic data have a degree of inherent uncertainty and imprecision, and require a method for their filtration before being processed further. In this paper, we have introduced an approach based on Vector Space Modeling (VSM) technique for classification of spatiotemporal sequential patterns of group activities. The feature vectors consist of an array of attributes extracted from generated sensors semantic annotated messages. To facilitate proper similarity matching and detection of time-varying spatiotemporal patterns, a Temporal-Dynamic Time Warping (DTW) method with Gaussian Mixture Model (GMM) for Expectation Maximization (EM) is introduced. DTW is intended for detection of event patterns from neighborhood-proximity semantic frames derived from established ontology. GMM with EM, on the other hand, is employed as a Bayesian probabilistic model to estimated probability of events associated with a detected spatiotemporal pattern. In this paper, we present a new visual analytic tool for testing and evaluation group activities detected under this control scheme. Experimental results demonstrate the effectiveness of proposed approach for discovery and matching of subsequences within sequentially generated patterns space of our experiments.

Patterns of Alloy Deformation by Pulsed Pressure

NASA Astrophysics Data System (ADS)

Chebotnyagin, L. M.; Potapov, V. V.; Lopatin, V. V.

2015-06-01

Patterns of alloy deformation for optimization of a welding regime are studied by the method of modeling and deformation profiles providing high deformation quality are determined. A model of stepwise kinetics of the alloy deformation by pulsed pressure from the expanding plasma channel inside of a deformable cylinder is suggested. The model is based on the analogy between the acoustic and electromagnetic wave processes in long lines. The shock wave pattern of alloy deformation in the presence of multiple reflections of pulsed pressure waves in the gap plasma channel - cylinder wall and the influence of unloading waves from free surfaces are confirmed.

Aggregate age-at-marriage patterns from individual mate-search heuristics.

PubMed

Todd, Peter M; Billari, Francesco C; Simão, Jorge

2005-08-01

The distribution of age at first marriage shows well-known strong regularities across many countries and recent historical periods. We accounted for these patterns by developing agent-based models that simulate the aggregate behavior of individuals who are searching for marriage partners. Past models assumed fully rational agents with complete knowledge of the marriage market; our simulated agents used psychologically plausible simple heuristic mate search rules that adjust aspiration levels on the basis of a sequence of encounters with potential partners. Substantial individual variation must be included in the models to account for the demographically observed age-at-marriage patterns.

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.

Interference in astronomical speckle patterns

NASA Technical Reports Server (NTRS)

Breckinridge, J. B.

1976-01-01

Astronomical speckle patterns are examined in an atmospheric-optics context in order to determine what kind of image quality is to be expected from several different imaging techniques. The model used to describe the instantaneous complex field distribution across the pupil of a large telescope regards the pupil as a deep phase grating with a periodicity given by the size of the cell of uniform phase or the refractive index structure function. This model is used along with an empirical formula derived purely from the physical appearance of the speckle patterns to discuss the orders of interference in astronomical speckle patterns.

Method of locating underground mines fires

DOEpatents

Laage, Linneas; Pomroy, William

1992-01-01

An improved method of locating an underground mine fire by comparing the pattern of measured combustion product arrival times at detector locations with a real time computer-generated array of simulated patterns. A number of electronic fire detection devices are linked thru telemetry to a control station on the surface. The mine's ventilation is modeled on a digital computer using network analysis software. The time reguired to locate a fire consists of the time required to model the mines' ventilation, generate the arrival time array, scan the array, and to match measured arrival time patterns to the simulated patterns.

Gas liquid flow at microgravity conditions - Flow patterns and their transitions

NASA Technical Reports Server (NTRS)

Dukler, A. E.; Fabre, J. A.; Mcquillen, J. B.; Vernon, R.

1987-01-01

The prediction of flow patterns during gas-liquid flow in conduits is central to the modern approach for modeling two phase flow and heat transfer. The mechanisms of transition are reasonably well understood for flow in pipes on earth where it has been shown that body forces largely control the behavior observed. This work explores the patterns which exist under conditions of microgravity when these body forces are suppressed. Data are presented which were obtained for air-water flow in tubes during drop tower experiments and Learjet trajectories. Preliminary models to explain the observed flow pattern map are evolved.

Spatial organization of bacterial chromosomes

PubMed Central

Wang, Xindan; Rudner, David Z.

2014-01-01

Bacterial chromosomes are organized in stereotypical patterns that are faithfully and robustly regenerated in daughter cells. Two distinct spatial patterns were described almost a decade ago in our most tractable model organisms. In recent years, analysis of chromosome organization in a larger and more diverse set of bacteria and a deeper characterization of chromosome dynamics in the original model systems have provided a broader and more complete picture of both chromosome organization and the activities that generate the observed spatial patterns. Here, we summarize these different patterns highlighting similarities and differences and discuss the protein factors that help establish and maintain them. PMID:25460798

Self-concept in fairness and rule establishment during a competitive game: a computational approach

PubMed Central

Lee, Sang Ho; Kim, Sung-Phil; Cho, Yang Seok

2015-01-01

People consider fairness as well as their own interest when making decisions in economic games. The present study proposes a model that encompasses the self-concept determined by one's own kindness as a factor of fairness. To observe behavioral patterns that reflect self-concept and fairness, a chicken game experiment was conducted. Behavioral data demonstrates four distinct patterns; “switching,” “mutual rush,” “mutual avoidance,” and “unfair” patterns. Model estimation of chicken game data shows that a model with self-concept predicts those behaviors better than previous models of fairness, suggesting that self-concept indeed affects human behavior in competitive economic games. Moreover, a non-stationary parameter analysis revealed the process of reaching consensus between the players in a game. When the models were fitted to a continuous time window, the parameters of the players in a pair with “switching” and “mutual avoidance” patterns became similar as the game proceeded, suggesting that the players gradually formed a shared rule during the game. In contrast, the difference of parameters between the players in the “unfair” and “mutual rush” patterns did not become stable. The outcomes of the present study showed that people are likely to change their strategy until they reach a mutually beneficial status. PMID:26441707

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.

Temporal patterns of mental model convergence: implications for distributed teams interacting in electronic collaboration spaces.

PubMed

McComb, Sara; Kennedy, Deanna; Perryman, Rebecca; Warner, Norman; Letsky, Michael

2010-04-01

Our objective is to capture temporal patterns in mental model convergence processes and differences in these patterns between distributed teams using an electronic collaboration space and face-to-face teams with no interface. Distributed teams, as sociotechnical systems, collaborate via technology to work on their task. The way in which they process information to inform their mental models may be examined via team communication and may unfold differently than it does in face-to-face teams. We conducted our analysis on 32 three-member teams working on a planning task. Half of the teams worked as distributed teams in an electronic collaboration space, and the other half worked face-to-face without an interface. Using event history analysis, we found temporal interdependencies among the initial convergence points of the multiple mental models we examined. Furthermore, the timing of mental model convergence and the onset of task work discussions were related to team performance. Differences existed in the temporal patterns of convergence and task work discussions across conditions. Distributed teams interacting via an electronic interface and face-to-face teams with no interface converged on multiple mental models, but their communication patterns differed. In particular, distributed teams with an electronic interface required less overall communication, converged on all mental models later in their life cycles, and exhibited more linear cognitive processes than did face-to-face teams interacting verbally. Managers need unique strategies for facilitating communication and mental model convergence depending on teams' degrees of collocation and access to an interface, which in turn will enhance team performance.

Color-pattern analysis of eyespots in butterfly wings: a critical examination of morphogen gradient models.

PubMed

Otaki, Joji M

2011-06-01

Butterfly wing color patterns consist of many color-pattern elements such as eyespots. It is believed that eyespot patterns are determined by a concentration gradient of a single morphogen species released by diffusion from the prospective eyespot focus in conjunction with multiple thresholds in signal-receiving cells. As alternatives to this single-morphogen model, more flexible multiple-morphogen model and induction model can be proposed. However, the relevance of these conceptual models to actual eyespots has not been examined systematically. Here, representative eyespots from nymphalid butterflies were analyzed morphologically to determine if they are consistent with these models. Measurement of ring widths of serial eyespots from a single wing surface showed that the proportion of each ring in an eyespot is quite different among homologous rings of serial eyespots of different sizes. In asymmetric eyespots, each ring is distorted to varying degrees. In extreme cases, only a portion of rings is expressed remotely from the focus. Similarly, there are many eyespots where only certain rings are deleted, added, or expanded. In an unusual case, the central area of an eyespot is composed of multiple "miniature eyespots," but the overall macroscopic eyespot structure is maintained. These results indicate that each eyespot ring has independence and flexibility to a certain degree, which is less consistent with the single-morphogen model. Considering a "periodic eyespot", which has repeats of a set of rings, damage-induced eyespots in mutants, and a scale-size distribution pattern in an eyespot, the induction model is the least incompatible with the actual eyespot diversity.

The RiverFish Approach to Business Process Modeling: Linking Business Steps to Control-Flow Patterns

NASA Astrophysics Data System (ADS)

Zuliane, Devanir; Oikawa, Marcio K.; Malkowski, Simon; Alcazar, José Perez; Ferreira, João Eduardo

Despite the recent advances in the area of Business Process Management (BPM), today’s business processes have largely been implemented without clearly defined conceptual modeling. This results in growing difficulties for identification, maintenance, and reuse of rules, processes, and control-flow patterns. To mitigate these problems in future implementations, we propose a new approach to business process modeling using conceptual schemas, which represent hierarchies of concepts for rules and processes shared among collaborating information systems. This methodology bridges the gap between conceptual model description and identification of actual control-flow patterns for workflow implementation. We identify modeling guidelines that are characterized by clear phase separation, step-by-step execution, and process building through diagrams and tables. The separation of business process modeling in seven mutually exclusive phases clearly delimits information technology from business expertise. The sequential execution of these phases leads to the step-by-step creation of complex control-flow graphs. The process model is refined through intuitive table and diagram generation in each phase. Not only does the rigorous application of our modeling framework minimize the impact of rule and process changes, but it also facilitates the identification and maintenance of control-flow patterns in BPM-based information system architectures.

Bisous model-Detecting filamentary patterns in point processes

NASA Astrophysics Data System (ADS)

Tempel, E.; Stoica, R. S.; Kipper, R.; Saar, E.

2016-07-01

The cosmic web is a highly complex geometrical pattern, with galaxy clusters at the intersection of filaments and filaments at the intersection of walls. Identifying and describing the filamentary network is not a trivial task due to the overwhelming complexity of the structure, its connectivity and the intrinsic hierarchical nature. To detect and quantify galactic filaments we use the Bisous model, which is a marked point process built to model multi-dimensional patterns. The Bisous filament finder works directly with the galaxy distribution data and the model intrinsically takes into account the connectivity of the filamentary network. The Bisous model generates the visit map (the probability to find a filament at a given point) together with the filament orientation field. Using these two fields, we can extract filament spines from the data. Together with this paper we publish the computer code for the Bisous model that is made available in GitHub. The Bisous filament finder has been successfully used in several cosmological applications and further development of the model will allow to detect the filamentary network also in photometric redshift surveys, using the full redshift posterior. We also want to encourage the astro-statistical community to use the model and to connect it with all other existing methods for filamentary pattern detection and characterisation.

Response of deformation patterns to reorganizations of the southern San Andreas fault system since ca. 1.5 Ma

NASA Astrophysics Data System (ADS)

Cooke, M. L.; Fattaruso, L.; Dorsey, R. J.; Housen, B. A.

2015-12-01

Between ~1.5 and 1.1 Ma, the southern San Andreas fault system underwent a major reorganization that included initiation of the San Jacinto fault and termination of slip on the extensional West Salton detachment fault. The southern San Andreas fault itself has also evolved since this time, with several shifts in activity among fault strands within San Gorgonio Pass. We use three-dimensional mechanical Boundary Element Method models to investigate the impact of these changes to the fault network on deformation patterns. A series of snapshot models of the succession of active fault geometries explore the role of fault interaction and tectonic loading in abandonment of the West Salton detachment fault, initiation of the San Jacinto fault, and shifts in activity of the San Andreas fault. Interpreted changes to uplift patterns are well matched by model results. These results support the idea that growth of the San Jacinto fault led to increased uplift rates in the San Gabriel Mountains and decreased uplift rates in the San Bernardino Mountains. Comparison of model results for vertical axis rotation to data from paleomagnetic studies reveals a good match to local rotation patterns in the Mecca Hills and Borrego Badlands. We explore the mechanical efficiency at each step in the evolution, and find an overall trend toward increased efficiency through time. Strain energy density patterns are used to identify regions of off-fault deformation and potential incipient faulting. These patterns support the notion of north-to-south propagation of the San Jacinto fault during its initiation. The results of the present-day model are compared with microseismicity focal mechanisms to provide additional insight into the patterns of off-fault deformation within the southern San Andreas fault system.

Mechanisms underlying different onset patterns of focal seizures

PubMed Central

Trevelyan, Andrew J; Valentin, Antonio; Alarcon, Gonzalo

2017-01-01

Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types—low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the “healthy” surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome. PMID:28472032

Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

NASA Astrophysics Data System (ADS)

Yuan, Tianle; Oreopoulos, Lazaros; Platnick, Steven E.; Meyer, Kerry

2018-05-01

Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation, leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

PubMed Central

Yoshioka, Nayuta; Zangerl, Barbara; Nivison-Smith, Lisa; Khuu, Sieu K.; Jones, Bryan W.; Pfeiffer, Rebecca L.; Marc, Robert E.; Kalloniatis, Michael

2017-01-01

Purpose To characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease. Methods Single eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort. Results Pattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm). Conclusions Pattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease. PMID:28632847

Stochastic many-body problems in ecology, evolution, neuroscience, and systems biology

NASA Astrophysics Data System (ADS)

Butler, Thomas C.

Using the tools of many-body theory, I analyze problems in four different areas of biology dominated by strong fluctuations: The evolutionary history of the genetic code, spatiotemporal pattern formation in ecology, spatiotemporal pattern formation in neuroscience and the robustness of a model circadian rhythm circuit in systems biology. In the first two research chapters, I demonstrate that the genetic code is extremely optimal (in the sense that it manages the effects of point mutations or mistranslations efficiently), more than an order of magnitude beyond what was previously thought. I further show that the structure of the genetic code implies that early proteins were probably only loosely defined. Both the nature of early proteins and the extreme optimality of the genetic code are interpreted in light of recent theory [1] as evidence that the evolution of the genetic code was driven by evolutionary dynamics that were dominated by horizontal gene transfer. I then explore the optimality of a proposed precursor to the genetic code. The results show that the precursor code has only limited optimality, which is interpreted as evidence that the precursor emerged prior to translation, or else never existed. In the next part of the dissertation, I introduce a many-body formalism for reaction-diffusion systems described at the mesoscopic scale with master equations. I first apply this formalism to spatially-extended predator-prey ecosystems, resulting in the prediction that many-body correlations and fluctuations drive population cycles in time, called quasicycles. Most of these results were previously known, but were derived using the system size expansion [2, 3]. I next apply the analytical techniques developed in the study of quasi-cycles to a simple model of Turing patterns in a predator-prey ecosystem. This analysis shows that fluctuations drive the formation of a new kind of spatiotemporal pattern formation that I name "quasi-patterns." These quasi-patterns exist over a much larger range of physically accessible parameters than the patterns predicted in mean field theory and therefore account for the apparent observations in ecology of patterns in regimes where Turing patterns do not occur. I further show that quasi-patterns have statistical properties that allow them to be distinguished empirically from mean field Turing patterns. I next analyze a model of visual cortex in the brain that has striking similarities to the activator-inhibitor model of ecosystem quasi-pattern formation. Through analysis of the resulting phase diagram, I show that the architecture of the neural network in the visual cortex is configured to make the visual cortex robust to unwanted internally generated spatial structure that interferes with normal visual function. I also predict that some geometric visual hallucinations are quasi-patterns and that the visual cortex supports a new phase of spatially scale invariant behavior present far from criticality. In the final chapter, I explore the effects of fluctuations on cycles in systems biology, specifically the pervasive phenomenon of circadian rhythms. By exploring the behavior of a generic stochastic model of circadian rhythms, I show that the circadian rhythm circuit exploits leaky mRNA production to safeguard the cycle from failure. I also show that this safeguard mechanism is highly robust to changes in the rate of leaky mRNA production. Finally, I explore the failure of the deterministic model in two different contexts, one where the deterministic model predicts cycles where they do not exist, and another context in which cycles are not predicted by the deterministic model.

Improving contact layer patterning using SEM contour based etch model

NASA Astrophysics Data System (ADS)

Weisbuch, François; Lutich, Andrey; Schatz, Jirka; Hertzsch, Tino; Moll, Hans-Peter

2016-10-01

The patterning of the contact layer is modulated by strong etch effects that are highly dependent on the geometry of the contacts. Such litho-etch biases need to be corrected to ensure a good pattern fidelity. But aggressive designs contain complex shapes that can hardly be compensated with etch bias table and are difficult to characterize with standard CD metrology. In this work we propose to implement a model based etch compensation method able to deal with any contact configuration. With the help of SEM contours, it was possible to get reliable 2D measurements particularly helpful to calibrate the etch model. The selections of calibration structures was optimized in combination with model form to achieve an overall errRMS of 3nm allowing the implementation of the model in production.

Quantum Model of Emerging Grammars

NASA Technical Reports Server (NTRS)

Zak, M.

1999-01-01

A special class of quantum recurrent nets simulating Markov chains with absorbing states is introduced. The absorbing states are exploited for pattern recognition: each class of patterns, each combination of patterns acquires its own meaning.

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.

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.

Heterogeneity and Change in the Patterning of Adolescents' Perceptions of the Legitimacy of Parental Authority: A Latent Transition Model

PubMed Central

Cumsille, Patricio; Darling, Nancy; Flaherty, Brian; Martínez, María Loreto

2013-01-01

Changes in the patterning of adolescents' beliefs about the legitimate domains of parental authority were modeled in 2,611 Chilean adolescents, 11–16 years old. Transitions in adolescents' belief patterns were studied over 3 years. Latent transition analysis (LTA) revealed 3 distinct patterns of beliefs—parent control, shared control, and personal control—that differed in the extent to which adolescents believed that parents had legitimate authority over personal, prudential, and multidomain issues. Younger adolescents with fewer problem behaviors, higher self-efficacy, and more parental rules were more likely to espouse the parent control belief pattern. Adolescents' patterning of beliefs was relatively stable over time. Older adolescents with more problem behaviors and fewer parental rules were most likely to move away from the parental control status. PMID:19467001

Heterogeneity and change in the patterning of adolescents' perceptions of the legitimacy of parental authority: a latent transition model.

PubMed

Cumsille, Patricio; Darling, Nancy; Flaherty, Brian; Loreto Martínez, María

2009-01-01

Changes in the patterning of adolescents' beliefs about the legitimate domains of parental authority were modeled in 2,611 Chilean adolescents, 11-16 years old. Transitions in adolescents' belief patterns were studied over 3 years. Latent transition analysis (LTA) revealed 3 distinct patterns of beliefs-parent control, shared control, and personal control-that differed in the extent to which adolescents believed that parents had legitimate authority over personal, prudential, and multidomain issues. Younger adolescents with fewer problem behaviors, higher self-efficacy, and more parental rules were more likely to espouse the parent control belief pattern. Adolescents' patterning of beliefs was relatively stable over time. Older adolescents with more problem behaviors and fewer parental rules were most likely to move away from the parental control status.

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.

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.

Conditional Stochastic Models in Reduced Space: Towards Efficient Simulation of Tropical Cyclone Precipitation Patterns

NASA Astrophysics Data System (ADS)

Dodov, B.

2017-12-01

Stochastic simulation of realistic and statistically robust patterns of Tropical Cyclone (TC) induced precipitation is a challenging task. It is even more challenging in a catastrophe modeling context, where tens of thousands of typhoon seasons need to be simulated in order to provide a complete view of flood risk. Ultimately, one could run a coupled global climate model and regional Numerical Weather Prediction (NWP) model, but this approach is not feasible in the catastrophe modeling context and, most importantly, may not provide TC track patterns consistent with observations. Rather, we propose to leverage NWP output for the observed TC precipitation patterns (in terms of downscaled reanalysis 1979-2015) collected on a Lagrangian frame along the historical TC tracks and reduced to the leading spatial principal components of the data. The reduced data from all TCs is then grouped according to timing, storm evolution stage (developing, mature, dissipating, ETC transitioning) and central pressure and used to build a dictionary of stationary (within a group) and non-stationary (for transitions between groups) covariance models. Provided that the stochastic storm tracks with all the parameters describing the TC evolution are already simulated, a sequence of conditional samples from the covariance models chosen according to the TC characteristics at a given moment in time are concatenated, producing a continuous non-stationary precipitation pattern in a Lagrangian framework. The simulated precipitation for each event is finally distributed along the stochastic TC track and blended with a non-TC background precipitation using a data assimilation technique. The proposed framework provides means of efficient simulation (10000 seasons simulated in a couple of days) and robust typhoon precipitation patterns consistent with observed regional climate and visually undistinguishable from high resolution NWP output. The framework is used to simulate a catalog of 10000 typhoon seasons implemented in a flood risk model for Japan.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

Enhancing multiple-point geostatistical modeling: 1. Graph theory and pattern adjustment

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Sahimi, Muhammad

2016-03-01

In recent years, higher-order geostatistical methods have been used for modeling of a wide variety of large-scale porous media, such as groundwater aquifers and oil reservoirs. Their popularity stems from their ability to account for qualitative data and the great flexibility that they offer for conditioning the models to hard (quantitative) data, which endow them with the capability for generating realistic realizations of porous formations with very complex channels, as well as features that are mainly a barrier to fluid flow. One group of such models consists of pattern-based methods that use a set of data points for generating stochastic realizations by which the large-scale structure and highly-connected features are reproduced accurately. The cross correlation-based simulation (CCSIM) algorithm, proposed previously by the authors, is a member of this group that has been shown to be capable of simulating multimillion cell models in a matter of a few CPU seconds. The method is, however, sensitive to pattern's specifications, such as boundaries and the number of replicates. In this paper the original CCSIM algorithm is reconsidered and two significant improvements are proposed for accurately reproducing large-scale patterns of heterogeneities in porous media. First, an effective boundary-correction method based on the graph theory is presented by which one identifies the optimal cutting path/surface for removing the patchiness and discontinuities in the realization of a porous medium. Next, a new pattern adjustment method is proposed that automatically transfers the features in a pattern to one that seamlessly matches the surrounding patterns. The original CCSIM algorithm is then combined with the two methods and is tested using various complex two- and three-dimensional examples. It should, however, be emphasized that the methods that we propose in this paper are applicable to other pattern-based geostatistical simulation methods.

Simulating carbon dioxide exchange rates of deciduous tree species: evidence for a general pattern in biochemical changes and water stress response.

PubMed

Reynolds, Robert F; Bauerle, William L; Wang, Ying

2009-09-01

Deciduous trees have a seasonal carbon dioxide exchange pattern that is attributed to changes in leaf biochemical properties. However, it is not known if the pattern in leaf biochemical properties - maximum Rubisco carboxylation (V(cmax)) and electron transport (J(max)) - differ between species. This study explored whether a general pattern of changes in V(cmax), J(max), and a standardized soil moisture response accounted for carbon dioxide exchange of deciduous trees throughout the growing season. The model MAESTRA was used to examine V(cmax) and J(max) of leaves of five deciduous trees, Acer rubrum 'Summer Red', Betula nigra, Quercus nuttallii, Quercus phellos and Paulownia elongata, and their response to soil moisture. MAESTRA was parameterized using data from in situ measurements on organs. Linking the changes in biochemical properties of leaves to the whole tree, MAESTRA integrated the general pattern in V(cmax) and J(max) from gas exchange parameters of leaves with a standardized soil moisture response to describe carbon dioxide exchange throughout the growing season. The model estimates were tested against measurements made on the five species under both irrigated and water-stressed conditions. Measurements and modelling demonstrate that the seasonal pattern of biochemical activity in leaves and soil moisture response can be parameterized with straightforward general relationships. Over the course of the season, differences in carbon exchange between measured and modelled values were within 6-12 % under well-watered conditions and 2-25 % under water stress conditions. Hence, a generalized seasonal pattern in the leaf-level physiological change of V(cmax) and J(max), and a standardized response to soil moisture was sufficient to parameterize carbon dioxide exchange for large-scale evaluations. Simplification in parameterization of the seasonal pattern of leaf biochemical activity and soil moisture response of deciduous forest species is demonstrated. This allows reliable modelling of carbon exchange for deciduous trees, thus circumventing the need for extensive gas exchange experiments on different species.

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.

Applying an orographic precipitation model to improve mass balance modeling of the Juneau Icefield, AK

NASA Astrophysics Data System (ADS)

Roth, A. C.; Hock, R.; Schuler, T.; Bieniek, P.; Aschwanden, A.

2017-12-01

Mass loss from glaciers in Southeast Alaska is expected to alter downstream ecological systems as runoff patterns change. To investigate these potential changes under future climate scenarios, distributed glacier mass balance modeling is required. However, the spatial resolution gap between global or regional climate models and the requirements for glacier mass balance modeling studies must be addressed first. We have used a linear theory of orographic precipitation model to downscale precipitation from both the Weather Research and Forecasting (WRF) model and ERA-Interim to the Juneau Icefield region over the period 1979-2013. This implementation of the LT model is a unique parameterization that relies on the specification of snow fall speed and rain fall speed as tuning parameters to calculate the cloud time delay, τ. We assessed the LT model results by considering winter precipitation so the effect of melt was minimized. The downscaled precipitation pattern produced by the LT model captures the orographic precipitation pattern absent from the coarse resolution WRF and ERA-Interim precipitation fields. Observational data constraints limited our ability to determine a unique parameter combination and calibrate the LT model to glaciological observations. We established a reference run of parameter values based on literature and performed a sensitivity analysis of the LT model parameters, horizontal resolution, and climate input data on the average winter precipitation. The results of the reference run showed reasonable agreement with the available glaciological measurements. The precipitation pattern produced by the LT model was consistent regardless of parameter combination, horizontal resolution, and climate input data, but the precipitation amount varied strongly with these factors. Due to the consistency of the winter precipitation pattern and the uncertainty in precipitation amount, we suggest a precipitation index map approach to be used in combination with a distributed mass balance model for future mass balance modeling studies of the Juneau Icefield. The LT model has potential to be used in other regions in Alaska and elsewhere with strong orographic effects for improved glacier mass balance modeling and/or hydrological modeling.

Effects of friction reduction of micro-patterned array of rough slider bearing

NASA Astrophysics Data System (ADS)

Kim, M.; Lee, D. W.; Jeong, J. H.; Chung, W. S.; Park, J. K.

2017-08-01

Complex micro-scale patterns have attracted interest because of the functionality that can be created using this type of patterning. This study evaluates the frictional reduction effects of various micro patterns on a slider bearing surface which is operating under mixed lubrication. Due to the rapid growth of contact area under mixed lubrication, it has become important to study the phenomenon of asperity contact in bearings with a heavy load. New analysis using the modified Reynolds equation with both the average flow model and the contact model of asperities is conducted for the rough slider bearing. A numerical analysis is performed to determine the effects of surface roughness on a lubricated bearing. Several dented patterns such as, dot pattern, dashed line patterns are used to evaluate frictional reduction effects. To verify the analytical results, friction test for the micro-patterned samples are performed. From comparing the frictional reduction effects of patterned arrays, the design of them can control the frictional loss of bearings. Our results showed that the design of pattern array on the bearing surface was important to the friction reduction of bearings. To reduce frictional loss, the longitudinal direction of them was better than the transverse direction.

Modelling and formation of spatiotemporal patterns of fractional predation system in subdiffusion and superdiffusion scenarios

NASA Astrophysics Data System (ADS)

Owolabi, Kolade M.; Atangana, Abdon

2018-02-01

This paper primarily focused on the question of how population diffusion can affect the formation of the spatial patterns in the spatial fraction predator-prey system by Turing mechanisms. Our numerical findings assert that modeling by fractional reaction-diffusion equations should be considered as an appropriate tool for studying the fundamental mechanisms of complex spatiotemporal dynamics. We observe that pure Hopf instability gives rise to the formation of spiral patterns in 2D and pure Turing instability destroys the spiral pattern and results to the formation of chaotic or spatiotemporal spatial patterns. Existence and permanence of the species is also guaranteed with the 3D simulations at some instances of time for subdiffusive and superdiffusive scenarios.

Spatio-temporal patterns of bacteria caused by collective motion

NASA Astrophysics Data System (ADS)

Kitsunezaki, So

2006-04-01

In incubation experiments on bacterial colonies of Proteus mirabilis, collective motion of bacteria is found to generate macroscopic turbulent patterns on the surface of agar media. We propose a mathematical model to describe the time evolution of the positional and directional distributions of motile bacteria in such systems, and investigate this model both numerically and analytically. It is shown that as the average density of bacteria increases, nonuniform swarming patterns emerge from a uniform stationary state. For a sufficient large density, we find that spiral patterns are caused by interactions between the local bacteria densities and the rotational mode of the collective motion. Unidirectional spiral patterns similar to those observed in experiments appear in the case in which the equilibrium directional distribution is asymmetric.

Discovering Mendeleev's Model.

ERIC Educational Resources Information Center

Sterling, Donna

1996-01-01

Presents an activity that introduces the historical developments in science that led to the discovery of the periodic table and lets students experience scientific discovery firsthand. Enables students to learn about patterns among the elements and experience how scientists analyze data to discover patterns and build models. (JRH)

Improved pattern scaling approaches for the use in climate impact studies

NASA Astrophysics Data System (ADS)

Herger, Nadja; Sanderson, Benjamin M.; Knutti, Reto

2015-05-01

Pattern scaling is a simple way to produce climate projections beyond the scenarios run with expensive global climate models (GCMs). The simplest technique has known limitations and assumes that a spatial climate anomaly pattern obtained from a GCM can be scaled by the global mean temperature (GMT) anomaly. We propose alternatives and assess their skills and limitations. One approach which avoids scaling is to consider a period in a different scenario with the same GMT change. It is attractive as it provides patterns of any temporal resolution that are consistent across variables, and it does not distort variability. Second, we extend the traditional approach with a land-sea contrast term, which provides the largest improvements over the traditional technique. When interpolating between known bounding scenarios, the proposed methods significantly improve the accuracy of the pattern scaled scenario with little computational cost. The remaining errors are much smaller than the Coupled Model Intercomparison Project Phase 5 model spread.

Optimized temporal pattern of brain stimulation designed by computational evolution

PubMed Central

Brocker, David T.; Swan, Brandon D.; So, Rosa Q.; Turner, Dennis A.; Gross, Robert E.; Grill, Warren M.

2017-01-01

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson’s disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We used the temporal pattern of stimulation as a novel parameter of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson’s disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in the parkinsonian rat and in patients. Both optimized and standard stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution to design temporal pattern of stimulation to increase the efficiency of brain stimulation in Parkinson’s disease, thereby requiring substantially less energy than traditional brain stimulation. PMID:28053151

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.

Biogeographic patterns in ocean microbes emerge in a neutral agent-based model.

PubMed

Hellweger, Ferdi L; van Sebille, Erik; Fredrick, Neil D

2014-09-12

A key question in ecology and evolution is the relative role of natural selection and neutral evolution in producing biogeographic patterns. We quantify the role of neutral processes by simulating division, mutation, and death of 100,000 individual marine bacteria cells with full 1 million-base-pair genomes in a global surface ocean circulation model. The model is run for up to 100,000 years and output is analyzed using BLAST (Basic Local Alignment Search Tool) alignment and metagenomics fragment recruitment. Simulations show the production and maintenance of biogeographic patterns, characterized by distinct provinces subject to mixing and periodic takeovers by neighbors (coalescence), after which neutral evolution reestablishes the province and the patterns reorganize. The emergent patterns are substantial (e.g., down to 99.5% DNA identity between North and Central Pacific provinces) and suggest that microbes evolve faster than ocean currents can disperse them. This approach can also be used to explore environmental selection. Copyright © 2014, American Association for the Advancement of Science.

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.

Unravelling variation in feeding, social interaction and growth patterns among pigs using an agent-based model.

PubMed

Boumans, Iris J M M; de Boer, Imke J M; Hofstede, Gert Jan; Bokkers, Eddie A M

2018-07-01

Domesticated pigs, Sus scrofa, vary considerably in feeding, social interaction and growth patterns. This variation originates partly from genetic variation that affects physiological factors and partly from behavioural strategies (avoid or approach) in competitive food resource situations. Currently, it is unknown how variation in physiological factors and in behavioural strategies among animals contributes to variation in feeding, social interaction and growth patterns in animals. The aim of this study was to unravel causation of variation in these patterns among pigs. We used an agent-based model to explore the effects of physiological factors and behavioural strategies in pigs on variation in feeding, social interaction and growth patterns. Model results show that variation in feeding, social interaction and growth patterns are caused partly by chance, such as time effects and coincidence of conflicts. Furthermore, results show that seemingly contradictory empirical findings in literature can be explained by variation in pig characteristics (i.e. growth potential, positive feedback, dominance, and coping style). Growth potential mainly affected feeding and growth patterns, whereas positive feedback, dominance and coping style affected feeding patterns, social interaction patterns, as well as growth patterns. Variation in behavioural strategies among pigs can reduce aggression at group level, but also make some pigs more susceptible to social constraints inhibiting them from feeding when they want to, especially low-ranking pigs and pigs with a passive coping style. Variation in feeding patterns, such as feeding rate or meal frequency, can indicate social constraints. Feeding patterns, however, can say something different about social constraints at group versus individual level. A combination of feeding patterns, such as a decreased feed intake, an increased feeding rate, and an increased meal frequency might, therefore, be needed to measure social constraints at individual level. Copyright © 2018 Elsevier Inc. All rights reserved.

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 mechanical model for deformable and mesh pattern wheel of lunar roving vehicle

NASA Astrophysics Data System (ADS)

Liang, Zhongchao; Wang, Yongfu; Chen, Gang (Sheng); Gao, Haibo

2015-12-01

As an indispensable tool for astronauts on lunar surface, the lunar roving vehicle (LRV) is of great significance for manned lunar exploration. An LRV moves on loose and soft lunar soil, so the mechanical property of its wheels directly affects the mobility performance. The wheels used for LRV have deformable and mesh pattern, therefore, the existing mechanical theory of vehicle wheel cannot be used directly for analyzing the property of LRV wheels. In this paper, a new mechanical model for LRV wheel is proposed. At first, a mechanical model for a rigid normal wheel is presented, which involves in multiple conventional parameters such as vertical load, tangential traction force, lateral force, and slip ratio. Secondly, six equivalent coefficients are introduced to amend the rigid normal wheel model to fit for the wheels with deformable and mesh-pattern in LRV application. Thirdly, the values of the six equivalent coefficients are identified by using experimental data obtained in an LRV's single wheel testing. Finally, the identified mechanical model for LRV's wheel with deformable and mesh pattern are further verified and validated by using additional experimental results.

Influence of urban pattern on inundation flow in floodplains of lowland rivers.

PubMed

Bruwier, M; Mustafa, A; Aliaga, D G; Archambeau, P; Erpicum, S; Nishida, G; Zhang, X; Pirotton, M; Teller, J; Dewals, B

2018-05-01

The objective of this paper is to investigate the respective influence of various urban pattern characteristics on inundation flow. A set of 2000 synthetic urban patterns were generated using an urban procedural model providing locations and shapes of streets and buildings over a square domain of 1×1km 2 . Steady two-dimensional hydraulic computations were performed over the 2000 urban patterns with identical hydraulic boundary conditions. To run such a large amount of simulations, the computational efficiency of the hydraulic model was improved by using an anisotropic porosity model. This model computes on relatively coarse computational cells, but preserves information from the detailed topographic data through porosity parameters. Relationships between urban characteristics and the computed inundation water depths have been based on multiple linear regressions. Finally, a simple mechanistic model based on two district-scale porosity parameters, combining several urban characteristics, is shown to capture satisfactorily the influence of urban characteristics on inundation water depths. The findings of this study give guidelines for more flood-resilient urban planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Sequence memory based on coherent spin-interaction neural networks.

PubMed

Xia, Min; Wong, W K; Wang, Zhijie

2014-12-01

Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

Respiratory morbidity of pattern and model makers exposed to wood, plastic, and metal products

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

Robins, T.G.; Haboubi, G.; Demers, R.Y.

Pattern and model makers are skilled tradespersons who may be exposed to hardwoods, softwoods, phenol-formaldehyde resin-impregnated woods, epoxy and polyester/styrene resin systems, and welding and metal-casting fumes. The relationship of respiratory symptoms (wheezing, chronic bronchitis, dyspnea) and pulmonary function (FVC% predicted, FEV1% predicted, FEV1/FVC% predicted) with interview-derived cumulative exposure estimates to specific workplace agents and to all work with wood, plastic, or metal products was investigated in 751 pattern and model makers in southeast Michigan. In stratified analyses and age- and smoking-adjusted linear and logistic regression models, measures of cumulative wood exposures were associated with decrements in pulmonary function andmore » dyspnea, but not with other symptoms. In similar analyses, measures of cumulative plastic exposures were associated with wheezing, chronic bronchitis, and dyspnea, but not with decrements in pulmonary function. Prior studies of exposure levels among pattern and model makers and of respiratory health effects of specific agents among other occupational groups support the plausibility of wood-related effects more strongly than that of plastic-related effects.« less

Structural and electron diffraction scaling of twisted graphene bilayers

NASA Astrophysics Data System (ADS)

Zhang, Kuan; Tadmor, Ellad B.

2018-03-01

Multiscale simulations are used to study the structural relaxation in twisted graphene bilayers and the associated electron diffraction patterns. The initial twist forms an incommensurate moiré pattern that relaxes to a commensurate microstructure comprised of a repeating pattern of alternating low-energy AB and BA domains surrounding a high-energy AA domain. The simulations show that the relaxation mechanism involves a localized rotation and shrinking of the AA domains that scales in two regimes with the imposed twist. For small twisting angles, the localized rotation tends to a constant; for large twist, the rotation scales linearly with it. This behavior is tied to the inverse scaling of the moiré pattern size with twist angle and is explained theoretically using a linear elasticity model. The results are validated experimentally through a simulated electron diffraction analysis of the relaxed structures. A complex electron diffraction pattern involving the appearance of weak satellite peaks is predicted for the small twist regime. This new diffraction pattern is explained using an analytical model in which the relaxation kinematics are described as an exponentially-decaying (Gaussian) rotation field centered on the AA domains. Both the angle-dependent scaling and diffraction patterns are in quantitative agreement with experimental observations. A Matlab program for extracting the Gaussian model parameters accompanies this paper.

Evaluating methods to visualize patterns of genetic differentiation on a landscape.

PubMed

House, Geoffrey L; Hahn, Matthew W

2018-05-01

With advances in sequencing technology, research in the field of landscape genetics can now be conducted at unprecedented spatial and genomic scales. This has been especially evident when using sequence data to visualize patterns of genetic differentiation across a landscape due to demographic history, including changes in migration. Two recent model-based visualization methods that can highlight unusual patterns of genetic differentiation across a landscape, SpaceMix and EEMS, are increasingly used. While SpaceMix's model can infer long-distance migration, EEMS' model is more sensitive to short-distance changes in genetic differentiation, and it is unclear how these differences may affect their results in various situations. Here, we compare SpaceMix and EEMS side by side using landscape genetics simulations representing different migration scenarios. While both methods excel when patterns of simulated migration closely match their underlying models, they can produce either un-intuitive or misleading results when the simulated migration patterns match their models less well, and this may be difficult to assess in empirical data sets. We also introduce unbundled principal components (un-PC), a fast, model-free method to visualize patterns of genetic differentiation by combining principal components analysis (PCA), which is already used in many landscape genetics studies, with the locations of sampled individuals. Un-PC has characteristics of both SpaceMix and EEMS and works well with simulated and empirical data. Finally, we introduce msLandscape, a collection of tools that streamline the creation of customizable landscape-scale simulations using the popular coalescent simulator ms and conversion of the simulated data for use with un-PC, SpaceMix and EEMS. © 2017 John Wiley & Sons Ltd.

Reaction-diffusion pattern in shoot apical meristem of plants.

PubMed

Fujita, Hironori; Toyokura, Koichi; Okada, Kiyotaka; Kawaguchi, Masayoshi

2011-03-29

A fundamental question in developmental biology is how spatial patterns are self-organized from homogeneous structures. In 1952, Turing proposed the reaction-diffusion model in order to explain this issue. Experimental evidence of reaction-diffusion patterns in living organisms was first provided by the pigmentation pattern on the skin of fishes in 1995. However, whether or not this mechanism plays an essential role in developmental events of living organisms remains elusive. Here we show that a reaction-diffusion model can successfully explain the shoot apical meristem (SAM) development of plants. SAM of plants resides in the top of each shoot and consists of a central zone (CZ) and a surrounding peripheral zone (PZ). SAM contains stem cells and continuously produces new organs throughout the lifespan. Molecular genetic studies using Arabidopsis thaliana revealed that the formation and maintenance of the SAM are essentially regulated by the feedback interaction between WUSHCEL (WUS) and CLAVATA (CLV). We developed a mathematical model of the SAM based on a reaction-diffusion dynamics of the WUS-CLV interaction, incorporating cell division and the spatial restriction of the dynamics. Our model explains the various SAM patterns observed in plants, for example, homeostatic control of SAM size in the wild type, enlarged or fasciated SAM in clv mutants, and initiation of ectopic secondary meristems from an initial flattened SAM in wus mutant. In addition, the model is supported by comparing its prediction with the expression pattern of WUS in the wus mutant. Furthermore, the model can account for many experimental results including reorganization processes caused by the CZ ablation and by incision through the meristem center. We thus conclude that the reaction-diffusion dynamics is probably indispensable for the SAM development of plants.

Reaction-Diffusion Pattern in Shoot Apical Meristem of Plants

PubMed Central

Fujita, Hironori; Toyokura, Koichi; Okada, Kiyotaka; Kawaguchi, Masayoshi

2011-01-01

A fundamental question in developmental biology is how spatial patterns are self-organized from homogeneous structures. In 1952, Turing proposed the reaction-diffusion model in order to explain this issue. Experimental evidence of reaction-diffusion patterns in living organisms was first provided by the pigmentation pattern on the skin of fishes in 1995. However, whether or not this mechanism plays an essential role in developmental events of living organisms remains elusive. Here we show that a reaction-diffusion model can successfully explain the shoot apical meristem (SAM) development of plants. SAM of plants resides in the top of each shoot and consists of a central zone (CZ) and a surrounding peripheral zone (PZ). SAM contains stem cells and continuously produces new organs throughout the lifespan. Molecular genetic studies using Arabidopsis thaliana revealed that the formation and maintenance of the SAM are essentially regulated by the feedback interaction between WUSHCEL (WUS) and CLAVATA (CLV). We developed a mathematical model of the SAM based on a reaction-diffusion dynamics of the WUS-CLV interaction, incorporating cell division and the spatial restriction of the dynamics. Our model explains the various SAM patterns observed in plants, for example, homeostatic control of SAM size in the wild type, enlarged or fasciated SAM in clv mutants, and initiation of ectopic secondary meristems from an initial flattened SAM in wus mutant. In addition, the model is supported by comparing its prediction with the expression pattern of WUS in the wus mutant. Furthermore, the model can account for many experimental results including reorganization processes caused by the CZ ablation and by incision through the meristem center. We thus conclude that the reaction-diffusion dynamics is probably indispensable for the SAM development of plants. PMID:21479227

Resource competition model predicts zonation and increasing nutrient use efficiency along a wetland salinity gradient

USGS Publications Warehouse

Schoolmaster, Donald; Stagg, Camille L.

2018-01-01

A trade-off between competitive ability and stress tolerance has been hypothesized and empirically supported to explain the zonation of species across stress gradients for a number of systems. Since stress often reduces plant productivity, one might expect a pattern of decreasing productivity across the zones of the stress gradient. However, this pattern is often not observed in coastal wetlands that show patterns of zonation along a salinity gradient. To address the potentially complex relationship between stress, zonation, and productivity in coastal wetlands, we developed a model of plant biomass as a function of resource competition and salinity stress. Analysis of the model confirms the conventional wisdom that a trade-off between competitive ability and stress tolerance is a necessary condition for zonation. It also suggests that a negative relationship between salinity and production can be overcome if (1) the supply of the limiting resource increases with greater salinity stress or (2) nutrient use efficiency increases with increasing salinity. We fit the equilibrium solution of the dynamic model to data from Louisiana coastal wetlands to test its ability to explain patterns of production across the landscape gradient and derive predictions that could be tested with independent data. We found support for a number of the model predictions, including patterns of decreasing competitive ability and increasing nutrient use efficiency across a gradient from freshwater to saline wetlands. In addition to providing a quantitative framework to support the mechanistic hypotheses of zonation, these results suggest that this simple model is a useful platform to further build upon, simulate and test mechanistic hypotheses of more complex patterns and phenomena in coastal wetlands.

Formation mechanism of complex pattern on fishes' skin

NASA Astrophysics Data System (ADS)

Li, Xia; Liu, Shuhua

2009-10-01

In this paper, the formation mechanism of the complex patterns observed on the skin of fishes has been investigated by a two-coupled reaction diffusion model. The effects of coupling strength between two layers play an important role in the pattern-forming process. It is found that only the epidermis layer can produce complicated patterns that have structures on more than one length scale. These complicated patterns including super-stripe pattern, mixture of spots and stripe, and white-eye pattern are similar to the pigmentation patterns on fishes' skin.

Enterprise Pattern: integrating the business process into a unified enterprise model of modern service company

NASA Astrophysics Data System (ADS)

Li, Ying; Luo, Zhiling; Yin, Jianwei; Xu, Lida; Yin, Yuyu; Wu, Zhaohui

2017-01-01

Modern service company (MSC), the enterprise involving special domains, such as the financial industry, information service industry and technology development industry, depends heavily on information technology. Modelling of such enterprise has attracted much research attention because it promises to help enterprise managers to analyse basic business strategies (e.g. the pricing strategy) and even optimise the business process (BP) to gain benefits. While the existing models proposed by economists cover the economic elements, they fail to address the basic BP and its relationship with the economic characteristics. Those proposed in computer science regardless of achieving great success in BP modelling perform poorly in supporting the economic analysis. Therefore, the existing approaches fail to satisfy the requirement of enterprise modelling for MSC, which demands simultaneous consideration of both economic analysing and business processing. In this article, we provide a unified enterprise modelling approach named Enterprise Pattern (EP) which bridges the gap between the BP model and the enterprise economic model of MSC. Proposing a language named Enterprise Pattern Description Language (EPDL) covering all the basic language elements of EP, we formulate the language syntaxes and two basic extraction rules assisting economic analysis. Furthermore, we extend Business Process Model and Notation (BPMN) to support EPDL, named BPMN for Enterprise Pattern (BPMN4EP). The example of mobile application platform is studied in detail for a better understanding of EPDL.

Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather

Treesearch

Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Michael D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot

2006-01-01

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...

Pattern classification using an olfactory model with PCA feature selection in electronic noses: study and application.

PubMed

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

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.

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

A feature illustration and application of azimuthal P receiver function patterns

NASA Astrophysics Data System (ADS)

Eckhardt, C.; Rabbel, W.

2009-12-01

Based on a synthetic catalog of thirty azimuthal patterns of P receiver functions for crustal structures down to thirty km depth we have summarized and illustrated the most important azimuthal features. We have constructed five model classes encompassing (an-)isotropic horizontal and dipping layers. The model classes were initialized by in situ observations of three deep reflection seismic profiles (DEKORP) of varying high reflective zones and a spiral shaped foliation scheme of an upper crustal bore hole out of the German Continental Deep Drilling Program (KTB). Up to fourteen azimuthal features were extracted out of the synthetic patterns and could be grouped into an already known fundamental part, a multiple part and into an extension part. Each feature was rated by a specific grade A, B, C to inform about the type of its initialization ((an-) isotropy and/or layer dipping). We have evaluated the fourteen features on the synthetic patterns to apply a hierarchical classification. From the classification of the model objects we found that nearly eighty percent of the models are well explained by the fundamental part. The hierarchical order of the model objects can be used as a template to screen real observed azimuthal patterns to find a starting model for a forward modeling or an inversion procedure. For one station of the German Regional Seismic Network (GRSN) we have evaluated the features and screened them through the template. A forward simulation of the azimuthal pattern, using the modified first found model explanation out of the hierarchical order for station MOX, leads to a good coincidence between the real and the simulated pattern. The final 1D model could be divided into an upper crustal part (8 km deep) with an axis of symmetry tilt of 55° and 20°NW trend (direction of axis tilt) and a lower crustal part (24 km thickness) with an axis of symmetry of increasing tilt from 55° to 85° and a trend orientation of 20°SE. For the simulation we have assumed 8 and 7 percent of negative P+S anisotropy for hexagonal symmetry of the upper and lower crust, respectively. From the synthetic and the real observations it is evident that additional boundaries beside the Moho discontinuity are merely detectable for certain circumstances in an azimuthal resolution and will be blinded out in the traditional radial stack.

Exploring the patterns and evolution of self-organized urban street networks through modeling

NASA Astrophysics Data System (ADS)

Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan

2013-03-01

As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.

The Relation Between Rotation Deformity and Nerve Root Stress in Lumbar Scoliosis

NASA Astrophysics Data System (ADS)

Kim, Ho-Joong; Lee, Hwan-Mo; Moon, Seong-Hwan; Chun, Heoung-Jae; Kang, Kyoung-Tak

Even though several finite element models of lumbar spine were introduced, there has been no model including the neural structure. Therefore, the authors made the novel lumbar spine finite element model including neural structure. Using this model, we investigated the relation between the deformity pattern and nerve root stress. Two lumbar models with different types of curve pattern (lateral bending and lateral bending with rotation curve) were made. In the model of lateral bending curves without rotation, the principal compressive nerve root stress on the concave side was greater than the principal tensile stress on the convex side at the apex vertebra. Contrarily, in the lateral bending curve with rotational deformity, the nerve stress on the convex side was higher than that on the concave side. Therefore, this study elicit that deformity pattern could have significantly influence on the nerve root stress in the lumbar spine.

Environmental drivers and spatial dependency in wildfire ignition patterns of northwestern Patagonia.

PubMed

Mundo, Ignacio A; Wiegand, Thorsten; Kanagaraj, Rajapandian; Kitzberger, Thomas

2013-07-15

Fire management requires an understanding of the spatial characteristics of fire ignition patterns and how anthropogenic and natural factors influence ignition patterns across space. In this study we take advantage of a recent fire ignition database (855 points) to conduct a comprehensive analysis of the spatial pattern of fire ignitions in the western area of Neuquén province (57,649 km(2)), Argentina, for the 1992-2008 period. The objectives of our study were to better understand the spatial pattern and the environmental drivers of the fire ignitions, with the ultimate aim of supporting fire management. We conducted our analyses on three different levels: statistical "habitat" modelling of fire ignition (natural, anthropogenic, and all causes) based on an information theoretic approach to test several competing hypotheses on environmental drivers (i.e. topographic, climatic, anthropogenic, land cover, and their combinations); spatial point pattern analysis to quantify additional spatial autocorrelation in the ignition patterns; and quantification of potential spatial associations between fires of different causes relative to towns using a novel implementation of the independence null model. Anthropogenic fire ignitions were best predicted by the most complex habitat model including all groups of variables, whereas natural ignitions were best predicted by topographic, climatic and land-cover variables. The spatial pattern of all ignitions showed considerable clustering at intermediate distances (<40 km) not captured by the probability of fire ignitions predicted by the habitat model. There was a strong (linear) and highly significant increase in the density of fire ignitions with decreasing distance to towns (<5 km), but fire ignitions of natural and anthropogenic causes were statistically independent. A two-dimensional habitat model that quantifies differences between ignition probabilities of natural and anthropogenic causes allows fire managers to delineate target areas for consideration of major preventive treatments, strategic placement of fuel treatments, and forecasting of fire ignition. The techniques presented here can be widely applied to situations where a spatial point pattern is jointly influenced by extrinsic environmental factors and intrinsic point interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.

What happens between pure hydraulic and buckling mechanisms of blowout fractures?

PubMed

Nagasao, Tomohisa; Miyamoto, Junpei; Shimizu, Yusuke; Jiang, Hua; Nakajima, Tatsuo

2010-06-01

The present study aims to evaluate how the ratio of the hydraulic and buckling mechanisms affects blowout fracture patterns, when these two mechanisms work simultaneously. Three-dimensional computer-aided-design (CAD)models were generated simulating ten skulls. To simulate impact, 1.2J was applied on the orbital region of these models in four patterns. Pattern 1: All the energy works to cause the hydraulic effect. Pattern 2: Two-thirds of the energy works to cause the hydraulic effect; one-third of the energy works to cause the buckling effect. Pattern 3: One-third of the energy works to cause the hydraulic effect; two-thirds of the energy works to cause the buckling effect. Pattern 4: The entire energy quantum works to cause the buckling effect. Using the finite element method, the regions where fractures were theoretically expected to occur were calculated and were compared between the four patterns. More fracture damage occurred for Pattern 1 than Pattern 2, and for Pattern 3 than for Pattern 4. The hydraulic and buckling mechanisms interact with one another. When these two mechanisms are combined, the orbital walls tend to develop serious fractures. Copyright (c) 2009 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

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

Inferring a District-Based Hierarchical Structure of Social Contacts from Census Data

PubMed Central

Yu, Zhiwen; Liu, Jiming; Zhu, Xianjun

2015-01-01

Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual’s social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model. PMID:25679787

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.

Network properties of interstitial cells of Cajal affect intestinal pacemaker activity and motor patterns, according to a mathematical model of weakly coupled oscillators.

PubMed

Wei, Ruihan; Parsons, Sean P; Huizinga, Jan D

2017-03-01

What is the central question of this study? What are the effects of interstitial cells of Cajal (ICC) network perturbations on intestinal pacemaker activity and motor patterns? What is the main finding and its importance? Two-dimensional modelling of the ICC pacemaker activity according to a phase model of weakly coupled oscillators showed that network properties (coupling strength between oscillators, frequency gradient and frequency noise) strongly influence pacemaker network activity and subsequent motor patterns. The model explains motor patterns observed in physiological conditions and provides predictions and testable hypotheses for effects of ICC loss and frequency modulation on the motor patterns. Interstitial cells of Cajal (ICC) are the pacemaker cells of gut motility and are associated with motility disorders. Interstitial cells of Cajal form a network, but the contributions of its network properties to gut physiology and dysfunction are poorly understood. We modelled an ICC network as a two-dimensional network of weakly coupled oscillators with a frequency gradient and showed changes over time in video and graphical formats. Model parameters were obtained from slow-wave-driven contraction patterns in the mouse intestine and pacemaker slow-wave activities from the cat intestine. Marked changes in propagating oscillation patterns (including changes from propagation to non-propagating) were observed by changing network parameters (coupling strength between oscillators, the frequency gradient and frequency noise), which affected synchronization, propagation velocity and occurrence of dislocations (termination of an oscillation). Complete uncoupling of a circumferential ring of oscillators caused the proximal and distal section to desynchronize, but complete synchronization was maintained with only a single oscillator connecting the sections with high enough coupling. The network of oscillators could withstand loss; even with 40% of oscillators lost randomly within the network, significant synchronization and anterograde propagation remained. A local increase in pacemaker frequency diminished anterograde propagation; the effects were strongly dependent on location, frequency gradient and coupling strength. In summary, the model puts forth the hypothesis that fundamental changes in oscillation patterns (ICC slow-wave activity or circular muscle contractions) can occur through physiological modulation of network properties. Strong evidence is provided to accept the ICC network as a system of coupled oscillators. © 2016 The Authors. Experimental Physiology © 2016 The Physiological Society.

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

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

Marre, O.; El Boustani, S.; Fregnac, Y.

We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogatesmore » that reproduce the spatial and temporal correlations of a given data set.« less

Mechanical models for the self-organization of tubular patterns.

PubMed

Guo, Chin-Lin

2013-01-01

Organogenesis, such as long tubule self-organization, requires long-range coordination of cell mechanics to arrange cell positions and to remodel the extracellular matrix. While the current mainstream in the field of tissue morphogenesis focuses primarily on genetics and chemical signaling, the influence of cell mechanics on the programming of patterning cues in tissue morphogenesis has not been adequately addressed. Here, we review experimental evidence and propose quantitative mechanical models by which cells can create tubular patterns.

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.

Do patients with chronic pain show autonomic arousal when confronted with feared movements? An experimental investigation of the fear-avoidance model.

PubMed

Glombiewski, Julia Anna; Riecke, Jenny; Holzapfel, Sebastian; Rief, Winfried; König, Stephan; Lachnit, Harald; Seifart, Ulf

2015-03-01

The relevance of a phobia-based conceptualization of fear for individuals with chronic pain has been much debated in the literature. This study investigated whether patients with highly fearful chronic low back pain show distinct physiological reaction patterns compared with less fearful patients when anticipating aversive back pain-related movements. We used an idiosyncratic fear induction paradigm and collected 2 different measures of autonomic nervous system activation and muscle tension in the lower back. We identified 2 distinct psychophysiological response patterns. One pattern was characterized by a moderate increase in skin conductance, interbeat interval (IBI) increase, and muscle tension increase in the lower back. This response was interpreted as an attention reaction to a moderately stressful event. The other pattern, found in 58% of the participants, was characterized by a higher skin conductance response, IBI decrease, and muscle tension increase in the lower back. According to Bradley and Lang defense cascade model, this response is typical of a fear reaction. Participants showing the psychophysiological pattern typical of fear also had elevated scores on some self-report measures of components of the fear-avoidance model, relative to participants showing the reaction pattern characteristic of attention. This study is the first to provide psychophysiological evidence for the fear-avoidance model of chronic pain.

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.

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)

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.

A Neuro-Musculo-Skeletal Model for Insects With Data-driven Optimization.

PubMed

Guo, Shihui; Lin, Juncong; Wöhrl, Toni; Liao, Minghong

2018-02-01

Simulating the locomotion of insects is beneficial to many areas such as experimental biology, computer animation and robotics. This work proposes a neuro-musculo-skeletal model, which integrates the biological inspirations from real insects and reproduces the gait pattern on virtual insects. The neural system is a network of spiking neurons, whose spiking patterns are controlled by the input currents. The spiking pattern provides a uniform representation of sensory information, high-level commands and control strategy. The muscle models are designed following the characteristic Hill-type muscle with customized force-length and force-velocity relationships. The model parameters, including both the neural and muscular components, are optimized via an approach of evolutionary optimization, with the data captured from real insects. The results show that the simulated gait pattern, including joint trajectories, matches the experimental data collected from real ants walking in the free mode. The simulated character is capable of moving at different directions and traversing uneven terrains.

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.

Modeling of blob-hole correlations in GPI edge turbulence data

NASA Astrophysics Data System (ADS)

Myra, J. R.; Russell, D. A.; Zweben, S. J.

2017-10-01

Gas-puff imaging (GPI) observations made on NSTX have revealed two-point spatial correlation patterns in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this work, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlation patterns that are qualitatively similar to the GPI data in many respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored. The possibility of using the model to ascertain new information about edge turbulence is discussed. Work supported by the U.S. Department of Energy Office of Science, Office of Fusion Energy Sciences under Award Number DE-FG02-02ER54678.

Spatiotemporal ecohydrological patterns and processes in temperate uplands: linking field observations and model results

NASA Astrophysics Data System (ADS)

Dodd, N. H.; Baird, A. J.; Wainwright, J.; Dunn, S. M.

2011-12-01

There are obvious surface expressions - in terms of vegetation patterning - of ecohydrological feedbacks on dryland and peatland hillslopes. Much less is known about subsurface ecohydrological patterns, and whether or not they 'map onto' surface patterns. Likewise, few attempts have been made to investigate how such ecohydrological patterns affect whole-hillslope hydrological behaviour or how widespread they are in non-dryland and non-peatland hillslopes. In this study we investigate surface and near- surface patterning in temperate hillslopes, which to date have been the focus of much hydrological work but little ecohydrological work. In particular, we consider the extent to which the direct and the indirect effects of past and present plant assemblages on local and whole-hillslope soil moisture conditions may contribute to patterning. We have conducted a field study of two temperate upland hillslopes in Northern Scotland, UK, on one of which human intervention plays a major part in shaping the landscape. Repeat measurements have been made of near- surface soil-moisture content, taken at lag distances of 0.25 m to 20 m, under different antecedent hydrological conditions together with characterisation of plant assemblages at the same points through both ground-based vegetation surveys of 1 m × 1 m plots and kite aerial photography (KAP) of > 20 m2 plots. Results from this have indicated that changes in ecohydrological patterns can occur over small spatial scales (< 1 m2) and short time scales (< 1 day). Comparison of values of near-surface soil moisture content with topographic wetness indices, calculated using 1 -m resolution topographic data collected in the field, has highlighted that topography does not explain all of the spatial variation in soil moisture content at this scale. KAP images allowed detection of vegetation patterns not obvious from the ground. Comparison of KAP images and historic aerial photographs has highlighted the persistence of vegetation patterns over time at both sites, and that the current structure of the landscape is clearly related to current and past vegetation management practices. Evidence of sustained patterning under relatively steady environmental conditions has prompted us to consider how internal system dynamics such as competition and facilitation between different plant assemblages, and persistence of ecological memory at a range of timescales may lead to a range of ecohydrological behaviours at the scale of whole hillslopes. To help conceptualize ways in which patterning may arise, we have built a two-dimensional cellular automata-type model in which local interactions between biotic and abiotic components have the potential to lead to emergence of larger-scale patterns within the model landscape. Results from the field study have been used to gauge how well temperate hillslope ecohydrological dynamics are represented in our model, and to check that local neighbourhood patterns in the model outputs resemble real-world patterning. Key words: temperate upland ecohydrology, plant assemblage dynamics, ecological memory, kite aerial photography, cellular automata.

Combinatorial Histone Acetylation Patterns Are Generated by Motif-Specific Reactions.

PubMed

Blasi, Thomas; Feller, Christian; Feigelman, Justin; Hasenauer, Jan; Imhof, Axel; Theis, Fabian J; Becker, Peter B; Marr, Carsten

2016-01-27

Post-translational modifications (PTMs) are pivotal to cellular information processing, but how combinatorial PTM patterns ("motifs") are set remains elusive. We develop a computational framework, which we provide as open source code, to investigate the design principles generating the combinatorial acetylation patterns on histone H4 in Drosophila melanogaster. We find that models assuming purely unspecific or lysine site-specific acetylation rates were insufficient to explain the experimentally determined motif abundances. Rather, these abundances were best described by an ensemble of models with acetylation rates that were specific to motifs. The model ensemble converged upon four acetylation pathways; we validated three of these using independent data from a systematic enzyme depletion study. Our findings suggest that histone acetylation patterns originate through specific pathways involving motif-specific acetylation activity. Copyright © 2016 Elsevier Inc. All rights reserved.

Combined Effects of Diurnal and Nonsynchronous Surface Stresses on Europa

NASA Technical Reports Server (NTRS)

Stempel, M. M.; Pappalardo, R. T.; Wahr, J.; Barr, A. C.

2004-01-01

To date, modeling of the surface stresses on Europa has considered tidal, nonsynchronous, and polar wander sources of stress. The results of such models can be used to match lineament orientations with candidate stress patterns. We present a rigorous surface stress model for Europa that will facilitate comparison of principal stresses to lineament orientation, and which will be available in the public domain. Nonsynchronous rotation and diurnal motion contribute to a stress pattern that deforms the surface of Europa. Over the 85-hour orbital period, the diurnal stress pattern acts on the surface, with a maximum magnitude of approximately 0.1 MPa. The nonsynchronous stress pattern sweeps over the surface due to differential rotation of the icy shell relative to the tidally locked interior of the moon. Nonsynchronous stress builds cumulatively with approximately 0.1 MPa per degree of shell rotation.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

PubMed

Gurarie, David; Karl, Stephan; Zimmerman, Peter A; King, Charles H; St Pierre, Timothy G; Davis, Timothy M E

2012-01-01

Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Ranking GCM Estimates of Twentieth Century Precipitation Seasonality in the Western U.S. and its Influence on Floristic Provinces.

NASA Astrophysics Data System (ADS)

Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Ironside, K.; Cobb, N. S.

2008-12-01

Floristic provinces of the western United States (west of 100W) can be segregated into three regions defined by significant seasonal precipitation during the months of: 1) November-March (Mediterranean); 2) July- September (Monsoonal); or, 3) May-June (Rocky Mountain). This third region is best defined by the absence of the late spring-early summer drought that affects regions 1 and 2. Each of these precipitation regimes is characterized by distinct vegetation types and fire seasonality adapted to that particular cycle of seasonal moisture availability and deficit. Further, areas where these regions blend from one to another can support even more complex seasonal patterns and resulting distinctive vegetation types. As a result, modeling the effects of climates on these ecosystems requires confidence that GCMs can at least approximate these sub- continental seasonal precipitation patterns. We evaluated the late Twentieth Century (1950-1999 AD) estimates of annual precipitation seasonality produced by 22 GCMs contained within the IPCC Fourth Assessment (AR4). These modeled estimates were compared to values from the PRISM dataset, extrapolated from station data, over the same historical period for the 3 seasonal periods defined above. The correlations between GCM estimates and PRISM values were ranked using 4 measures: 1) A map pattern relationship based on the correlation coefficient, 2) A map pattern relationship based on the congruence coefficient, 3) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation amounts, and, 4) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation percentages of the annual total. For each of the four metrics, the rank order of models was very similar. The ranked order of the performance of the different models quantified aspects of the model performance visible in the mapped results. While some models represented the seasonal patterns very well, others showed little correspondence with the regional patterns, especially for the summer monsoon period. These sub-continental patterns were especially well simulated over this period by the UKMO-HadGEM1, ECHAM5/MPI-OM, and the MRI-CGCM2 model runs.

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.

Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity

PubMed Central

Chavlis, Spyridon; Petrantonakis, Panagiotis C.

2016-01-01

ABSTRACT The hippocampus plays a key role in pattern separation, the process of transforming similar incoming information to highly dissimilar, nonverlapping representations. Sparse firing granule cells (GCs) in the dentate gyrus (DG) have been proposed to undertake this computation, but little is known about which of their properties influence pattern separation. Dendritic atrophy has been reported in diseases associated with pattern separation deficits, suggesting a possible role for dendrites in this phenomenon. To investigate whether and how the dendrites of GCs contribute to pattern separation, we build a simplified, biologically relevant, computational model of the DG. Our model suggests that the presence of GC dendrites is associated with high pattern separation efficiency while their atrophy leads to increased excitability and performance impairments. These impairments can be rescued by restoring GC sparsity to control levels through various manipulations. We predict that dendrites contribute to pattern separation as a mechanism for controlling sparsity. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27784124

Behavioral and Temporal Pattern Detection Within Financial Data With Hidden Information

DTIC Science & Technology

2012-02-01

probabilistic pattern detector to monitor the pattern. 15. SUBJECT TERMS Runtime verification, Hidden data, Hidden Markov models, Formal specifications...sequences in many other fields besides financial systems [L, TV, LC, LZ ]. Rather, the technique suggested in this paper is positioned as a hybrid...operation of the pattern detector . Section 7 describes the operation of the probabilistic pattern-matching monitor, and section 8 describes three

Coarse Grained Modeling of Block Copolymer Lithography: The Effects of Pattern Design on the Thermodynamics and Kinetics of the Directed Self Assembly of Block Copolymers

NASA Astrophysics Data System (ADS)

Garner, Grant Parker

The directed self assembly of block copolymers is an exciting complimentary technique for the fabrication of nanoscale structures for lithographic applications. Typically a directed self assembly process is driven through substrates with chemical (chemoepitaxy) or topographical (graphoepitaxy) guiding features. These patterning strategies have led to the ability to assemble structures with a high degree of perfection over large areas. However, a guiding pattern has not been created which assembles the desired features with a defect density that is commensurate with industrial standards of 1 defect/100cm 2. This work focuses on using molecular simulations on the Theoretically Informed Coarse Grained model to provide design rules for substrate patterns which drive the assembly of desired, device-oriented morphologies. Prior to the work presented in Chapter 2, the TICG model has been used in conjunction with a chemical pattern that is approximated as a hard-impenetrable surface. As many experimental systems use polymer brushes to help guide the polymer melt deposited on the substrate, this work analyzes the consequences of such an assumption by comparing a model where the polymer brush is explicitly implemented to the hard-wall substrate used in the past. Then, a methodology which utilizes a evolutionary optimization method is used to map the parameters of the more detailed model to the hard-surface model. This provides a qualitative understanding of how to interpret the model parameters used in previous works in the context of real experimental pattern designs. Chapter 3 discuss the concept of competitive assemblies in regards to defining a thermodynamic processing window in design space for assembling lines-and-spaces. The most competitive assembly to the desired orientation of the lamella is defined as a rotation of assembled lamella to the underlying pattern. Thermodynamic integration is used to calculate the free-energy difference between these assemblies over chemical patterns with varied design parameters. Local maximums in the free-energy difference are observed over pattern designs that are in qualitatively agreement with the pattern designs which produce the most perfect assemblies in experiments. The analysis is extended to study how choice of chemistry impacts this thermodynamic selection for the desired morphology. Finally, Chapter 4 provides insight into the kinetics of patterned directed self-assembly by investigating cylinder forming block copolymers within cylindrical confinements. Through the use of the string method, the minimum free-energy path between a defective state and the desired assembled morphology is calculated and clear transition states are highlighted. The effects of key parameters of the confinement design on the calculated minimum free energy path are calculated to identify design rules which should lead to a better understanding of optimal connement design for eliminating defects. In addition, a specific modification to existing cylindrical confinements is discussed as a possibility for tackling the problem of placement accuracy for a cylinder that is assembled within the confinement.

Spontaneous emergence of milling (vortex state) in a Vicsek-like model

NASA Astrophysics Data System (ADS)

Costanzo, A.; Hemelrijk, C. K.

2018-04-01

Collective motion is of interest to laymen and scientists in different fields. In groups of animals, many patterns of collective motion arise such as polarized schools and mills (i.e. circular motion). Collective motion can be generated in computational models of different degrees of complexity. In these models, moving individuals coordinate with others nearby. In the more complex models, individuals attract each other, aligning their headings, and avoiding collisions. Simpler models may include only one or two of these types of interactions. The collective pattern that interests us here is milling, which is observed in many animal species. It has been reproduced in the more complex models, but not in simpler models that are based only on alignment, such as the well-known Vicsek model. Our aim is to provide insight in the minimal conditions required for milling by making minimal modifications to the Vicsek model. Our results show that milling occurs when both the field of view and the maximal angular velocity are decreased. Remarkably, apart from milling, our minimal model also exhibits many of the other patterns of collective motion observed in animal groups.

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.

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Pattern selection in solidification

NASA Technical Reports Server (NTRS)

Langer, J. S.

1984-01-01

Directional solidification of alloys produces a wide variety of cellular or lamellar structures which, depending upon growth conditions, may be reproducibly regular or may behave chaotically. It is not well understood how these patterns are selected and controlled or even whether there ever exist sharp selection mechanisms. A related phenomenon is the spatial propagation of a pattern into a system which has been caused to become unstable against pattern-forming deformations. This phenomenon has some features in common with the propagation of sidebranching modes in dendritic solidification. In a class of one-dimensional models, the nonlinear system can be shown to select the propagating mode in which the leading edge of the pattern is just marginally stable. This stability principle, when applicable, predicts both the speed of propagation and the geometrical characteristics of the pattern which forms behind the moving front. A boundary-layer model for fully two or three dimensional solidification problems appears to exhibit similar mathematical behavior.

Experimental investigation on the heat transfer characteristics and flow pattern in vertical narrow channels heated from one side

NASA Astrophysics Data System (ADS)

Huang, Lihao; Li, Gang; Tao, Leren

2016-07-01

Experimental investigation for the flow boiling of water in a vertical rectangular channel was conducted to reveal the boiling heat transfer mechanism and flow patterns map aspects. The onset of nucleate boiling went upward with the increasing of the working fluid mass flow rate or the decreasing of the inlet working fluid temperature. As the vapour quality was increased, the local heat transfer coefficient increased first, then decreased, followed by various flow patterns. The test data from other researchers had a similar pattern transition for the bubble-slug flow and the slug-annular flow. Flow pattern transition model analysis was performed to make the comparison with current test data. The slug-annular and churn-annular transition models showed a close trend with current data except that the vapor phase superficial velocity of flow pattern transition was much higher than that of experimental data.

Analysis of utilization of desert habitats with dynamic simulation

USGS Publications Warehouse

Williams, B.K.

1986-01-01

The effects of climate and herbivores on cool desert shrubs in north-western Utah were investigated with a dynamic simulation model. Cool desert shrublands are extensively managed as grazing lands, and are defoliated annually by domestic livestock. A primary production model was used to simulate harvest yields and shrub responses under a variety of climatic regimes and defoliation patterns. The model consists of six plant components, and it is based on equations of growth analysis. Plant responses were simulated under various combinations of 20 annual weather patterns and 14 defoliation strategies. Results of the simulations exhibit some unexpected linearities in model behavior, and emphasize the importance of both the pattern of climate and the level of plant vigor in determining optimal harvest strategies. Model behaviors are interpreted in terms of shrub morphology, physiology and ecology.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

PubMed Central

Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals’ daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient. PMID:28076375

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

PubMed

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.

Tidal Dissipation Within the Jupiter Moon Io - A Numerical Approach

NASA Astrophysics Data System (ADS)

Steinke, Teresa; van der Wal, Wouter; Hu, Haiyang; Vermeersen, Bert

2017-04-01

Satellite images and recent Earth-based observations of the innermost of the Galilean moons reveal a conspicuous pattern of volcanic hotspots and paterae on its surface. This pattern is associated with the heat flux originating from tidal dissipation in Io's mantle and asthenosphere. As shown by many analytical studies [e.g. Segatz et al. 1988], the local heat flux pattern depends on the rheology and structure of the satellite's interior and therefore could reveal constraints on Io's present interior. However, non-linear processes, different rheologies, and in particular lateral variations arising from the spatial heating pattern are difficult to incorporate in analytical 1D models but might be crucial. This motivates the development of a 3D finite element model of a layered body disturbed by a tidal potential. As a first step of this project we present a 3D finite element model of a spherically stratified body of linear viscoelastic rheology. For validation, we compare the resulting tidal deformation and local heating patterns with the results obtained by analytical models. Numerical errors increase with lower values of the asthenosphere viscosity. Currently, the numerical model allows realistic simulation down to viscosities of 1018 Pa s. Furthermore, we investigate an adequate way to deal with the relaxation of false modes that arise at the onset of the periodic tidal potential series in the numerical approach. Segatz, M., Spohn, T., Ross, M. N., Schubert, G. (1988). Tidal dissipation, surface heat flow, and figure of viscoelastic models of Io. Icarus, 75(2), 187-206.

The Effects of industrial workers' food choice attribute on sugar intake pattern and job satisfaction with Structural Equcation Model

PubMed Central

Park, Young Il

2016-01-01

BACKGROUND/OBJECTIVES This research analyzes the effects of the food choices of industrial workers according to their sugar intake pattern on their job satisfaction through the construction of a model on the relationship between sugar intake pattern and job satisfaction. SUBJECTS/METHODS Surveys were collected from May to July 2015. A statistical analysis of the 775 surveys from Kyungsangnam-do was conducted using SPSS13.0 for Windows and SEM was performed using the AMOS 5.0 statistics package. RESULTS The reliability of the data was confirmed by an exploratory factor analysis through a Cronbach's alpha coefficient, and the measurement model was proven to be appropriate by a confirmatory factor analysis in conjunction with AMOS. The results of factor analysis on food choice, sugar intake pattern and job satisfaction were categorized into five categories. The reliability of these findings was supported by a Cronbach's alpha coefficient of 0.6 and higher for all factors except confection (0.516) and dairy products (0.570). The multicollinearity results did not indicate a problem between the variables since the highest correlation coefficient was 0.494 (P < 0.01). In an attempt to study the sugar intake pattern in accordance with the food choices and job satisfaction of industrial workers, a structural equation model was constructed and analyzed. CONCLUSIONS All tests confirmed that the model satisfied the recommended levels for the goodness of fit index, and thus, the overall research model was proven to be appropriate. PMID:27478555

Food pattern modeling shows that the 2010 Dietary Guidelines for sodium and potassium cannot be met simultaneously

PubMed Central

Maillot, Matthieu; Monsivais, Pablo; Drewnowski, Adam

2013-01-01

The 2010 US Dietary Guidelines recommended limiting intake of sodium to 1500 mg/d for people older than 50 years, African Americans, and those suffering from chronic disease. The guidelines recommended that all other people consume less than 2300 mg sodium and 4700 mg of potassium per day. The theoretical feasibility of meeting the sodium and potassium guidelines while simultaneously maintaining nutritional adequacy of the diet was tested using food pattern modeling based on linear programming. Dietary data from the National Health and Nutrition Examination Survey 2001-2002 were used to create optimized food patterns for 6 age-sex groups. Linear programming models determined the boundary conditions for the potassium and sodium content of the modeled food patterns that would also be compatible with other nutrient goals. Linear programming models also sought to determine the amounts of sodium and potassium that both would be consistent with the ratio of Na to K of 0.49 and would cause the least deviation from the existing food habits. The 6 sets of food patterns were created before and after an across-the-board 10% reduction in sodium content of all foods in the Food and Nutrition Database for Dietary Studies. Modeling analyses showed that the 2010 Dietary Guidelines for sodium were incompatible with potassium guidelines and with nutritionally adequate diets, even after reducing the sodium content of all US foods by 10%. Feasibility studies should precede or accompany the issuing of dietary guidelines to the public. PMID:23507224

The Influences of Family Leisure Patterns on Perceptions of Family Functioning.

ERIC Educational Resources Information Center

Zabriskie, Ramon B.; McCormick, Bryan P.

2001-01-01

Conducted a preliminary test of a model of family leisure functioning by examining the relationship of core and balance family leisure patterns to family cohesion and adaptability. Hypothesized that core leisure patterns address family needs for stability and facilitate cohesive relationships, whereas balance leisure patterns address the need for…

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

Characterization of fracture aperture for groundwater flow and transport

NASA Astrophysics Data System (ADS)

Sawada, A.; Sato, H.; Tetsu, K.; Sakamoto, K.

2007-12-01

This paper presents experiments and numerical analyses of flow and transport carried out on natural fractures and transparent replica of fractures. The purpose of this study was to improve the understanding of the role of heterogeneous aperture patterns on channelization of groundwater flow and dispersion in solute transport. The research proceeded as follows: First, a precision plane grinder was applied perpendicular to the fracture plane to characterize the aperture distribution on a natural fracture with 1 mm of increment size. Although both time and labor were intensive, this approach provided a detailed, three dimensional picture of the pattern of fracture aperture. This information was analyzed to provide quantitative measures for the fracture aperture distribution, including JRC (Joint Roughness Coefficient) and fracture contact area ratio. These parameters were used to develop numerical models with corresponding synthetic aperture patterns. The transparent fracture replica and numerical models were then used to study how transport is affected by the aperture spatial pattern. In the transparent replica, transmitted light intensity measured by a CCD camera was used to image channeling and dispersion due to the fracture aperture spatial pattern. The CCD image data was analyzed to obtain the quantitative fracture aperture and tracer concentration data according to Lambert-Beer's law. The experimental results were analyzed using the numerical models. Comparison of the numerical models to the transparent replica provided information about the nature of channeling and dispersion due to aperture spatial patterns. These results support to develop a methodology for defining representative fracture aperture of a simplified parallel fracture model for flow and transport in heterogeneous fractures for contaminant transport analysis.

Fibrous dosage forms by wet 3D-micro-patterning: process design, manufacture, and drug release rate.

PubMed

Blaesi, Aron H; Saka, Nannaji

2018-06-19

Recently, we have introduced fibrous dosage forms prepared by 3D-micro-patterning of drug-laden viscous melts. Such dosage forms enable predictable microstructures and increased drug release rates, and they can be manufactured continuously. However, melt processing is not applicable if the melting temperature of the formulation is greater than the degradation temperature of the drug or of the excipient. In this work, therefore, a continuous wet micro-patterning process that operates at ambient temperature is presented. The excipient is plasticized by a solvent and the patterned dosage form is solidified by air drying. Process models show that the micro-patterning time is the ratio of the fiber length in the dosage form and the velocity of the fiber stream. It was 1.3 minutes in the experiments, but can be reduced further. The drying time is limited by the diffusive flux of solvent through the fibers: it was about 3 minutes for the experimental conditions. Furthermore, models are developed to illustrate the effects of fiber radius, inter-fiber spacing, viscosity of the drug-excipient-solvent mixture, and drying conditions on the microstructure of the dosage form. Models and experimental results show that for a viscosity of the wet fibers of the order 10 3 Pa·s, both the patterned microstructure is well preserved and the crossed fibers are well bonded. Finally, the drug release rate by the dosage forms is experimentally determined and theoretically modeled. The results of the experiments validate the models fairly. Copyright © 2018. Published by Elsevier B.V.

A Systematic Review of Global Drivers of Ant Elevational Diversity

PubMed Central

Szewczyk, Tim; McCain, Christy M.

2016-01-01

Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns. PMID:27175999

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Modeling apparent color for visual evaluation of camouflage fabrics

NASA Astrophysics Data System (ADS)

Ramsey, S.; Mayo, T.; Shabaev, A.; Lambrakos, S. G.

2017-08-01

As the U.S. Navy, Army, and Special Operations Forces progress towards fielding more advanced uniforms with multi-colored and highly detailed camouflage patterning, additional test methodologies are necessary in evaluating color in these types of camouflage textiles. The apparent color is the combination of all visible wavelengths (380-760 nm) of light reflected from large (>=1m2 ) fabric sample sizes for a given standoff distance (10-25ft). Camouflage patterns lose resolution with increasing standoff distance, and eventually all colors within the pattern appear monotone (the "apparent color" of the pattern). This paper presents an apparent color prediction model that can be used for evaluation of camouflage fabrics.

Investigating the effect of invasion characteristics on onion thrips (Thysanoptera: Thripidae) populations in onions with a temperature-driven process model.

PubMed

Mo, Jianhua; Stevens, Mark; Liu, De Li; Herron, Grant

2009-12-01

A temperature-driven process model was developed to describe the seasonal patterns of populations of onion thrips, Thrips tabaci Lindeman, in onions. The model used daily cohorts (individuals of the same developmental stage and daily age) as the population unit. Stage transitions were modeled as a logistic function of accumulated degree-days to account for variability in development rate among individuals. Daily survival was modeled as a logistic function of daily mean temperature. Parameters for development, survival, and fecundity were estimated from published data. A single invasion event was used to initiate the population process, starting at 1-100 d after onion emergence (DAE) for 10-100 d at the daily rate of 0.001-0.9 adults/plant/d. The model was validated against five observed seasonal patterns of onion thrips populations from two unsprayed sites in the Riverina, New South Wales, Australia, during 2003-2006. Performance of the model was measured by a fit index based on the proportion of variations in observed data explained by the model (R (2)) and the differences in total thrips-days between observed and predicted populations. Satisfactory matching between simulated and observed seasonal patterns was obtained within the ranges of invasion parameters tested. Model best-fit was obtained at invasion starting dates of 6-98 DAE with a daily invasion rate of 0.002-0.2 adults/plant/d and an invasion duration of 30-100 d. Under the best-fit invasion scenarios, the model closely reproduced the observed seasonal patterns, explaining 73-95% of variability in adult and larval densities during population increase periods. The results showed that small invasions of adult thrips followed by a gradual population build-up of thrips within onion crops were sufficient to bring about the observed seasonal patterns of onion thrips populations in onion. Implications of the model on timing of chemical controls are discussed.

Short-term forecasting of urban rail transit ridership based on ARIMA and wavelet decomposition

NASA Astrophysics Data System (ADS)

Wang, Xuemei; Zhang, Ning; Chen, Ying; Zhang, Yunlong

2018-05-01

Due to different functions and land use types, there are significant differences in ridership patterns among different urban rail transit stations. Considering the characteristics of different ridership and coping with the uncertainty, periodical and stochastic natures of short-term passenger flow, and this paper proposes a novel hybrid methodology that combines the autoregressive integrated moving average (ARIMA) model and wavelet decomposition, which has strong strengths in signal processing, to short-term ridership forecasting. The seasonal ARIMA is used to represent the relatively stable and regular ridership patterns while the wavelet decomposition is used to capture the stochastic or sometimes drastic changing characteristics of ridership patterns. The inclusion of wavelet decomposition and reconstruction provides the hybrid model with a unique strength in capturing sudden change in ridership patterns associated with certain rail stations. The case study is carried out by analyzing real ridership data of Metro Line 1 in Nanjing, China. The experimental results indicate that the hybrid method is superior to the individual ARIMA model for all ridership patterns, but particularly advantageous in predicting ridership at stations often associated with sudden pattern changes due to special events.

Ventilatory Patterning in a Mouse Model of Stroke

PubMed Central

Koo, Brian B; Strohl, Kingman P; Gillombardo, Carl B; Jacono, Frank J

2010-01-01

Cheyne-Stokes respiration (CSR) is a breathing pattern characterized by waxing and waning of breath volume and frequency, and is often recognized following stroke, when causal pathways are often obscure. We used an animal model to address the hypothesis that cerebral infarction is a mechanism for producing breathing instability. Fourteen male A/J mice underwent either stroke (n=7) or sham (n=7) procedure. Ventilation was measured using whole body plethysmography. Respiratory rate (RR), tidal volume (VT) and minute ventilation (Ve) mean values and coefficient of variation were computed for ventilation and oscillatory behavior. In addition, the ventilatory data were computationally fit to models to quantify autocorrelation, mutual information, sample entropy and a nonlinear complexity index. At the same time post procedure, stroke when compared to sham animal breathing consisted of a lower RR and autocorrelation, higher coefficient of variation for VT and higher coefficient of variation for Ve. Mutual information and the nonlinear complexity index were higher in breathing following stroke which also demonstrated a waxing/waning pattern. The absence of stroke in the sham animals was verified anatomically. We conclude that ventilatory pattern following cerebral infarction demonstrated increased variability with increased nonlinear patterning and a waxing/waning pattern, consistent with CSR. PMID:20472101

Dynamic sensory cues shape song structure in Drosophila

NASA Astrophysics Data System (ADS)

Coen, Philip; Clemens, Jan; Weinstein, Andrew J.; Pacheco, Diego A.; Deng, Yi; Murthy, Mala

2014-03-01

The generation of acoustic communication signals is widespread across the animal kingdom, and males of many species, including Drosophilidae, produce patterned courtship songs to increase their chance of success with a female. For some animals, song structure can vary considerably from one rendition to the next; neural noise within pattern generating circuits is widely assumed to be the primary source of such variability, and statistical models that incorporate neural noise are successful at reproducing the full variation present in natural songs. In direct contrast, here we demonstrate that much of the pattern variability in Drosophila courtship song can be explained by taking into account the dynamic sensory experience of the male. In particular, using a quantitative behavioural assay combined with computational modelling, we find that males use fast modulations in visual and self-motion signals to pattern their songs, a relationship that we show is evolutionarily conserved. Using neural circuit manipulations, we also identify the pathways involved in song patterning choices and show that females are sensitive to song features. Our data not only demonstrate that Drosophila song production is not a fixed action pattern, but establish Drosophila as a valuable new model for studies of rapid decision-making under both social and naturalistic conditions.

Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model

NASA Astrophysics Data System (ADS)

Gristey, Jake J.; Chiu, J. Christine; Gurney, Robert J.; Morcrette, Cyril J.; Hill, Peter G.; Russell, Jacqueline E.; Brindley, Helen E.

2018-04-01

A globally complete, high temporal resolution and multiple-variable approach is employed to analyse the diurnal cycle of Earth's outgoing energy flows. This is made possible via the use of Met Office model output for September 2010 that is assessed alongside regional satellite observations throughout. Principal component analysis applied to the long-wave component of modelled outgoing radiation reveals dominant diurnal patterns related to land surface heating and convective cloud development, respectively explaining 68.5 and 16.0 % of the variance at the global scale. The total variance explained by these first two patterns is markedly less than previous regional estimates from observations, and this analysis suggests that around half of the difference relates to the lack of global coverage in the observations. The first pattern is strongly and simultaneously coupled to the land surface temperature diurnal variations. The second pattern is strongly coupled to the cloud water content and height diurnal variations, but lags the cloud variations by several hours. We suggest that the mechanism controlling the delay is a moistening of the upper troposphere due to the evaporation of anvil cloud. The short-wave component of modelled outgoing radiation, analysed in terms of albedo, exhibits a very dominant pattern explaining 88.4 % of the variance that is related to the angle of incoming solar radiation, and a second pattern explaining 6.7 % of the variance that is related to compensating effects from convective cloud development and marine stratocumulus cloud dissipation. Similar patterns are found in regional satellite observations, but with slightly different timings due to known model biases. The first pattern is controlled by changes in surface and cloud albedo, and Rayleigh and aerosol scattering. The second pattern is strongly coupled to the diurnal variations in both cloud water content and height in convective regions but only cloud water content in marine stratocumulus regions, with substantially shorter lag times compared with the long-wave counterpart. This indicates that the short-wave radiation response to diurnal cloud development and dissipation is more rapid, which is found to be robust in the regional satellite observations. These global, diurnal radiation patterns and their coupling with other geophysical variables demonstrate the process-level understanding that can be gained using this approach and highlight a need for global, diurnal observing systems for Earth outgoing radiation in the future.

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.

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

[Sustainable development of the three economic patterns in China: The application of genuine progress indicator in the sustainability assessment of six typical cities.

PubMed

Li, Jing; Huang, Lu; Yan, Li Jiao

2016-06-01

Three economic patterns, i.e., Zhujiang Model, Wenzhou Model and Sunan Model, were all generated in the developed areas of China. Sustainability assessment of those areas plays an important role in guiding future development of the economy of China. Genuine progress indicator (GPI) was adopted in this study to evaluate the sustainability of 6 typical cities (Guangzhou, Shenzhen, Wenzhou, Suzhou, Wuxi, and Changzhou) of the three economic patterns from 1995 to 2012. During the study period, the values of GDP for the six cities had experienced exponential growth, while the values of GPI started to increase since 2005 after a relatively constant period between 1995 and 2005. The gap between GPI and GDP had been widening from a historical perspective. Zhujiang Model made great progress in economic growth, however, the economic, social, and environmental costs were evident. It should tackle income inequality, traffic jam, and environmental pollution to reach sustainability. The development of Wenzhou Model slowed down in the late pe-riod, with inadequate potential to develop. Its income inequality was tough, social and economic development was slow, and the economic development pattern needed to be urgently changed. Sunan Model had a higher value of GPI and the potential to reach sustainability, with remarkable growth of economy, median level of the GPI costs, and steady improvement of social development, although its natural resources were depleted. Three economic patterns should focus on the three dimensions of sustainability (economy, environment, and society), and Zhujiang Model and Wenzhou Model needed to be more active to search for transition of their development.

Remotely Sensed Based Lake/Reservoir Routing in Congo River Basin

NASA Astrophysics Data System (ADS)

Raoufi, R.; Beighley, E.; Lee, H.

2017-12-01

Lake and reservoir dynamics can influence local to regional water cycles but are often not well represented in hydrologic models. One challenge that limits their inclusion in models is the need for detailed storage-discharge behavior that can be further complicated in reservoirs where specific operation rules are employed. Here, the Hillslope River Routing (HRR) model is combined with a remotely sensed based Reservoir Routing (RR) method and applied to the Congo River Basin. Given that topographic data are often continuous over the entire terrestrial surface (i.e., does not differentiate between land and open water), the HRR-RR model integrates topographic derived river networks and catchment boundaries (e.g., HydroSHEDs) with water boundary extents (e.g., Global Lakes and Wetlands Database) to develop the computational framework. The catchments bordering lakes and reservoirs are partitioned into water and land portions, where representative flowpath characteristics are determined and vertical water balance and lateral routings is performed separately on each partition based on applicable process models (e.g., open water evaporation vs. evapotranspiration). To enable reservoir routing, remotely sensed water surface elevations and extents are combined to determine the storage change time series. Based on the available time series, representative storage change patterns are determined. Lake/reservoir routing is performed by combining inflows from the HRR-RR model and the representative storage change patterns to determine outflows. In this study, a suite of storage change patterns derived from remotely sensed measurements are determined representative patterns for wet, dry and average conditions. The HRR-RR model dynamically selects and uses the optimal storage change pattern for the routing process based on these hydrologic conditions. The HRR-RR model results are presented to highlight the importance of lake attenuation/routing in the Congo Basin.

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.

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.

Four not six: Revealing culturally common facial expressions of emotion.

PubMed

Jack, Rachael E; Sun, Wei; Delis, Ioannis; Garrod, Oliver G B; Schyns, Philippe G

2016-06-01

As a highly social species, humans generate complex facial expressions to communicate a diverse range of emotions. Since Darwin's work, identifying among these complex patterns which are common across cultures and which are culture-specific has remained a central question in psychology, anthropology, philosophy, and more recently machine vision and social robotics. Classic approaches to addressing this question typically tested the cross-cultural recognition of theoretically motivated facial expressions representing 6 emotions, and reported universality. Yet, variable recognition accuracy across cultures suggests a narrower cross-cultural communication supported by sets of simpler expressive patterns embedded in more complex facial expressions. We explore this hypothesis by modeling the facial expressions of over 60 emotions across 2 cultures, and segregating out the latent expressive patterns. Using a multidisciplinary approach, we first map the conceptual organization of a broad spectrum of emotion words by building semantic networks in 2 cultures. For each emotion word in each culture, we then model and validate its corresponding dynamic facial expression, producing over 60 culturally valid facial expression models. We then apply to the pooled models a multivariate data reduction technique, revealing 4 latent and culturally common facial expression patterns that each communicates specific combinations of valence, arousal, and dominance. We then reveal the face movements that accentuate each latent expressive pattern to create complex facial expressions. Our data questions the widely held view that 6 facial expression patterns are universal, instead suggesting 4 latent expressive patterns with direct implications for emotion communication, social psychology, cognitive neuroscience, and social robotics. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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.

Imbalanced target prediction with pattern discovery on clinical data repositories.

PubMed

Chan, Tak-Ming; Li, Yuxi; Chiau, Choo-Chiap; Zhu, Jane; Jiang, Jie; Huo, Yong

2017-04-20

Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice. We propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed. We compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values < 0.01, Wilcoxon signed rank test) favorable averaged testing G-means and F1-scores (harmonic mean of precision and sensitivity). Without requiring sophisticated technical processing of data and tweaking, the prediction performance of pattern discovery is consistently comparable to the best achievable performance. Pattern discovery has demonstrated to be robust and valuable for target prediction on existing clinical data repositories with imbalance and noise. The prediction results and interpretable patterns can provide insights in an agile and inexpensive way for the potential formal studies.

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.

Biomechanical Analyses of the Efficacy of Patterns of Maternal Effort on Second-Stage Progress

PubMed Central

Lien, Kuo-Cheng; DeLancey, John O.L.; Ashton-Miller, James A.

2009-01-01

OBJECTIVE To develop and use a biomechanical computer model to simulate the effect of varying the timing of voluntary maternal pushes during uterine contraction on second-stage labor duration. METHODS Published initial pelvic floor geometry was imported into technical computing software to build a simplified 3-D biomechanical model with six representative viscoelastic levator muscle bands interconnected by a hyperelastic iliococcygeal raphé. An incompressible sphere simulated the molded fetal head. Forces from uterine contraction and voluntary expulsive efforts were summed to push the model fetal head along the Curve of Carus opposed by the resistance of the pelvic floor structures to stretch. Holding uterine maximal contraction force and push strength constant, pushes were timed before (“Pre”), at (“Peak”), and after (“Post”) maximal uterine contraction force. The effect of different combinations of pushes on second stage duration and the number of pushes required for delivery were evaluated. RESULTS Calculated second stage durations ranged from 57.5 minutes (“triple” or Pre-Peak-Post pattern) to 75.8 minutes (“pre-push” and “post-push” patterns). Delivery with the “triple push” pattern required 59 voluntary pushes, while the “peak push” pattern required 23 voluntary pushes, a 61% reduction. The corresponding reduction for the “pre-and-peak push” pattern was 29%, the “peak-and-post push” pattern was 30%, the “pre-push” pattern was 54%, and the “post-push” pattern was 56%. CONCLUSION Although the “triple push” pattern resulted in a 16% shorter second stage, this came at the energetic expense of a 61% increase in the number of pushes required. PMID:19305333

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2012-12-01

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

Speckle in the diffraction patterns of Hendricks-Teller and icosahedral glass models

NASA Technical Reports Server (NTRS)

Garg, Anupam; Levine, Dov

1988-01-01

It is shown that the X-ray diffraction patterns from the Hendricks-Teller model for layered systems and the icosahedral glass models for the icosahedral phases show large fluctuations between nearby scattering wave vectors and from sample to sample, that are quite analogous to laser speckle. The statistics of these fluctuations are studied analytically for the first model and via computer simulations for the second. The observability of these effects is discussed briefly.

Building emotional resilience over 14 sessions of emotion focused therapy: Micro-longitudinal analyses of productive emotional patterns.

PubMed

Pascual-Leone, A; Yeryomenko, N; Sawashima, T; Warwar, S

2017-05-04

Pascual-Leone and Greenberg's sequential model of emotional processing has been used to explore process in over 24 studies. This line of research shows emotional processing in good psychotherapy often follows a sequential order, supporting a saw-toothed pattern of change within individual sessions (progressing "2-steps-forward, 1-step-back"). However, one cannot assume that local in-session patterns are scalable across an entire course of therapy. Thus, the primary objective of this exploratory study was to consider how the sequential patterns identified by Pascual-Leone, may apply across entire courses of treatment. Intensive emotion coding in two separate single-case designs were submitted for quantitative analyses of longitudinal patterns. Comprehensive coding in these cases involved recording observations for every emotional event in an entire course of treatment (using the Classification of Affective-Meaning States), which were then treated as a 9-point ordinal scale. Applying multilevel modeling to each of the two cases showed significant patterns of change over a large number of sessions, and those patterns were either nested at the within-session level or observed at the broader session-by-session level of change. Examining successful treatment cases showed several theoretically coherent kinds of temporal patterns, although not always in the same case. Clinical or methodological significance of this article: This is the first paper to demonstrate systematic temporal patterns of emotion over the course of an entire treatment. (1) The study offers a proof of concept that longitudinal patterns in the micro-processes of emotion can be objectively derived and quantified. (2) It also shows that patterns in emotion may be identified on the within-session level, as well as the session-by-session level of analysis. (3) Finally, observed processes over time support the ordered pattern of emotional states hypothesized in Pascual-Leone and Greenberg's ( 2007 ) model of emotional processing.

Modeling Development in Retinal Afferents: Retinotopy, Segregation, and EphrinA/EphA Mutants

PubMed Central

Godfrey, Keith B.; Swindale, Nicholas V.

2014-01-01

During neural development, neurons extend axons to target areas of the brain. Through processes of growth, branching and retraction these axons establish stereotypic patterns of connectivity. In the visual system, these patterns include retinotopic organization and the segregation of individual axons onto different subsets of target neurons based on the eye of origin (ocular dominance) or receptive field type (ON or OFF). Characteristic disruptions to these patterns occur when neural activity or guidance molecule expression is perturbed. In this paper we present a model that explains how these developmental patterns might emerge as a result of the coordinated growth and retraction of individual axons and synapses responding to position-specific markers, trophic factors and spontaneous neural activity. This model derives from one presented earlier (Godfrey et al., 2009) but which is here extended to account for a wider range of phenomena than previously described. These include ocular dominance and ON-OFF segregation and the results of altered ephrinA and EphA guidance molecule expression. The model takes into account molecular guidance factors, realistic patterns of spontaneous retinal wave activity, trophic molecules, homeostatic mechanisms, axon branching and retraction rules and intra-axonal signaling mechanisms that contribute to the survival of nearby synapses on an axon. We show that, collectively, these mechanisms can account for a wider range of phenomena than previous models of retino-tectal development. PMID:25122119

Transition of spiral calcium waves between multiple stable patterns can be triggered by a single calcium spark in a fire-diffuse-fire model

PubMed Central

Tang, Ai-Hui; Wang, Shi-Qiang

2009-01-01

Spiral patterns have been found in various nonequilibrium systems. The Ca2+-induced Ca2+ release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca2+ spark upon excitation. We imaged the spiral Ca2+ waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca2+ spark. PMID:19792039

Transition of spiral calcium waves between multiple stable patterns can be triggered by a single calcium spark in a fire-diffuse-fire model.

PubMed

Tang, Ai-Hui; Wang, Shi-Qiang

2009-09-01

Spiral patterns have been found in various nonequilibrium systems. The Ca(2+)-induced Ca(2+) release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca(2+) spark upon excitation. We imaged the spiral Ca(2+) waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca(2+) spark.

Hormone-Mediated Pattern Formation in Seedling of Plants: a Competitive Growth Dynamics Model

NASA Astrophysics Data System (ADS)

Kawaguchi, Satoshi; Mimura, Masayasu; Ohya, Tomoyuki; Oikawa, Noriko; Okabe, Hirotaka; Kai, Shoichi

2001-10-01

An ecologically relevant pattern formation process mediated by hormonal interactions among growing seedlings is modeled based on the experimental observations on the effects of indole acetic acid, which can act as an inhibitor and activator of root growth depending on its concentration. In the absence of any lateral root with constant hormone-sensitivity, the edge effect phenomenon is obtained depending on the secretion rate of hormone from the main root. Introduction of growth-stage-dependent hormone-sensitivity drastically amplifies the initial randomness, resulting in spatially irregular macroscopic patterns. When the lateral root growth is introduced, periodic patterns are obtained whose periodicity depends on the length of lateral roots. The growth-stage-dependent hormone-sensitivity and the lateral root growth are crucial for macroscopic periodic-pattern formation.

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.

Understanding and Changing Food Consumption Behavior Among Children: The Comprehensive Child Consumption Patterns Model.

PubMed

Jeffries, Jayne K; Noar, Seth M; Thayer, Linden

2015-01-01

Current theoretical models attempting to explain diet-related weight status among children center around three individual-level theories. Alone, these theories fail to explain why children are engaging or not engaging in health-promoting eating behaviors. Our Comprehensive Child Consumption Patterns model takes a comprehensive approach and was developed specifically to help explain child food consumption behavior and addresses many of the theoretical gaps found in previous models, including integration of the life course trajectory, key influencers, perceived behavioral control, and self-regulation. Comprehensive Child Consumption Patterns model highlights multiple levels of the socioecological model to explain child food consumption, illustrating how negative influence at multiple levels can lead to caloric imbalance and contribute to child overweight and obesity. Recognizing the necessity for multi-level and system-based interventions, this model serves as a template for holistic, integrated interventions to improve child eating behavior, ultimately impacting life course health development. © The Author(s) 2015.

Hetero-association for pattern translation

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Lu, Thomas T.; Yang, Xiangyang

1991-09-01

A hetero-association neural network using an interpattern association algorithm is presented. By using simple logical rules, hetero-association memory can be constructed based on the association between the input-output reference patterns. For optical implementation, a compact size liquid crystal television neural network is used. Translations between the English letters and the Chinese characters as well as Arabic and Chinese numerics are demonstrated. The authors have shown that the hetero-association model can perform more effectively in comparison to the Hopfield model in retrieving large numbers of similar patterns.

High storage capacity in the Hopfield model with auto-interactions—stability analysis

NASA Astrophysics Data System (ADS)

Rocchi, Jacopo; Saad, David; Tantari, Daniele

2017-11-01

Recent studies point to the potential storage of a large number of patterns in the celebrated Hopfield associative memory model, well beyond the limits obtained previously. We investigate the properties of new fixed points to discover that they exhibit instabilities for small perturbations and are therefore of limited value as associative memories. Moreover, a large deviations approach also shows that errors introduced to the original patterns induce additional errors and increased corruption with respect to the stored patterns.

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.

Increase in flood risk resulting from climate change in a developed urban watershed - the role of storm temporal patterns

NASA Astrophysics Data System (ADS)

Hettiarachchi, Suresh; Wasko, Conrad; Sharma, Ashish

2018-03-01

The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity-duration-frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081-2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.

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

Foundations for Streaming Model Transformations by Complex Event Processing.

PubMed

Dávid, István; Ráth, István; Varró, Dániel

2018-01-01

Streaming model transformations represent a novel class of transformations to manipulate models whose elements are continuously produced or modified in high volume and with rapid rate of change. Executing streaming transformations requires efficient techniques to recognize activated transformation rules over a live model and a potentially infinite stream of events. In this paper, we propose foundations of streaming model transformations by innovatively integrating incremental model query, complex event processing (CEP) and reactive (event-driven) transformation techniques. Complex event processing allows to identify relevant patterns and sequences of events over an event stream. Our approach enables event streams to include model change events which are automatically and continuously populated by incremental model queries. Furthermore, a reactive rule engine carries out transformations on identified complex event patterns. We provide an integrated domain-specific language with precise semantics for capturing complex event patterns and streaming transformations together with an execution engine, all of which is now part of the Viatra reactive transformation framework. We demonstrate the feasibility of our approach with two case studies: one in an advanced model engineering workflow; and one in the context of on-the-fly gesture recognition.

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

Association between Dietary Patterns during Pregnancy and Birth Size Measures in a Diverse Population in Southern US

PubMed Central

Colón-Ramos, Uriyoán; Racette, Susan B.; Ganiban, Jody; Nguyen, Thuy G.; Kocak, Mehmet; Carroll, Kecia N.; Völgyi, Eszter; Tylavsky, Frances A.

2015-01-01

Despite increased interest in promoting nutrition during pregnancy, the association between maternal dietary patterns and birth outcomes has been equivocal. We examined maternal dietary patterns during pregnancy as a determinant of offspring’s birth weight-for-length (WLZ), weight-for-age (WAZ), length-for-age (LAZ), and head circumference (HCZ) Z-scores in Southern United States (n = 1151). Maternal diet during pregnancy was assessed by seven dietary patterns. Multivariable linear regression models described the association of WLZ, WAZ, LAZ, and HCZ with diet patterns controlling for other maternal and child characteristics. In bivariate analyses, WAZ and HCZ were significantly lower for processed and processed-Southern compared to healthy dietary patterns, whereas LAZ was significantly higher for these patterns. In the multivariate models, mothers who consumed a healthy-processed dietary pattern had children with significantly higher HCZ compared to the ones who consumed a healthy dietary pattern (HCZ β: 0.36; p = 0.019). No other dietary pattern was significantly associated with any of the birth outcomes. Instead, the major outcome determinants were: African American race, pre-pregnancy BMI, and gestational weight gain. These findings justify further investigation about socio-environmental and genetic factors related to race and birth outcomes in this population. PMID:25690420

The "Chaos" Pattern in Piaget's Theory of Cognitive Development.

ERIC Educational Resources Information Center

Lindsay, Jean S.

Piaget's theory of the cognitive development of the child is related to the recently developed non-linear "chaos" model. The term "chaos" refers to the tendency of dynamical, non-linear systems toward irregular, sometimes unpredictable, deterministic behavior. Piaget identified this same pattern in his model of cognitive…

Cognitive Diagnostic Attribute-Level Discrimination Indices

ERIC Educational Resources Information Center

Henson, Robert; Roussos, Louis; Douglas, Jeff; He, Xuming

2008-01-01

Cognitive diagnostic models (CDMs) model the probability of correctly answering an item as a function of an examinee's attribute mastery pattern. Because estimation of the mastery pattern involves more than a continuous measure of ability, reliability concepts introduced by classical test theory and item response theory do not apply. The cognitive…

Organizational Change, Absenteeism, and Welfare Dependency

ERIC Educational Resources Information Center

Roed, Knut; Fevang, Elisabeth

2007-01-01

Based on Norwegian register data, we set up a multivariate mixed proportional hazard model (MMPH) to analyze nurses' pattern of work, sickness absence, nonemployment, and social insurance dependency from 1992 to 2000, and how that pattern was affected by workplace characteristics. The model is estimated by means of the nonparametric…

Linking Models: Reasoning from Patterns to Tables and Equations

ERIC Educational Resources Information Center

Switzer, J. Matt

2013-01-01

Patterns are commonly used in middle years mathematics classrooms to teach students about functions and modelling with tables, graphs, and equations. Grade 6 students are expected to, "continue and create sequences involving whole numbers, fractions and decimals," and "describe the rule used to create the sequence." (Australian…

Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

NASA Astrophysics Data System (ADS)

Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

2007-12-01

The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of rainfall-runoff event analysis for model development as well as model diagnostics.

Discovering weighted patterns in intron sequences using self-adaptive harmony search and back-propagation algorithms.

PubMed

Huang, Yin-Fu; Wang, Chia-Ming; Liou, Sing-Wu

2013-01-01

A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete.

Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms

PubMed Central

Wang, Chia-Ming; Liou, Sing-Wu

2013-01-01

A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete. PMID:23737711

Artificial intelligence techniques for modeling database user behavior

NASA Technical Reports Server (NTRS)

Tanner, Steve; Graves, Sara J.

1990-01-01

The design and development of the adaptive modeling system is described. This system models how a user accesses a relational database management system in order to improve its performance by discovering use access patterns. In the current system, these patterns are used to improve the user interface and may be used to speed data retrieval, support query optimization and support a more flexible data representation. The system models both syntactic and semantic information about the user's access and employs both procedural and rule-based logic to manipulate the model.

Automated sample plan selection for OPC modeling

NASA Astrophysics Data System (ADS)

Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

2014-03-01

It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

Generative Models of Segregation: Investigating Model-Generated Patterns of Residential Segregation by Ethnicity and Socioeconomic Status

PubMed Central

Fossett, Mark

2011-01-01

This paper considers the potential for using agent models to explore theories of residential segregation in urban areas. Results of generative experiments conducted using an agent-based simulation of segregation dynamics document that varying a small number of model parameters representing constructs from urban-ecological theories of segregation can generate a wide range of qualitatively distinct and substantively interesting segregation patterns. The results suggest how complex, macro-level patterns of residential segregation can arise from a small set of simple micro-level social dynamics operating within particular urban-demographic contexts. The promise and current limitations of agent simulation studies are noted and optimism is expressed regarding the potential for such studies to engage and contribute to the broader research literature on residential segregation. PMID:21379372

Modeling forest harvesting effects on landscape pattern in the Northwest Wisconsin Pine Barrens

Treesearch

Volker C. Radeloff; David J. Mladenoff; Eric J. Gustafson; Robert M. Scheller; Patrick A. Zollner; Hong S. Heilman; H. Resit Akcakaya

2006-01-01

Forest management shapes landscape patterns, and these patterns often differ significantly from those typical for natural disturbance regimes. This may affect wildlife habitat and other aspects of ecosystem function. Our objective was to examine the effects of different forest management decisions on landscape pattern in a fire adapted ecosystem. We used a factorial...

Torsion sensing based on patterned piezoelectric beams

NASA Astrophysics Data System (ADS)

Cha, Youngsu; You, Hangil

2018-03-01

In this study, we investigated the sensing characteristics of piezoelectric beams under torsional loads. We used partially patterned piezoelectric beams to sense torsion. In particular, the piezoelectric patches are located symmetrically with respect to the line of the shear center of the beam. The patterned piezoelectric beam is modeled as a slender beam, and its electrical responses are obtained by piezoelectric electromechanical equations. To validate the modeling framework, experiments are performed using a setup that forces pure torsional deformation. Three different geometric configurations of the patterned piezoelectric layer are used for the experiments. The frequency and amplitude of the forced torsional load are systematically varied in order to study the behavior of the piezoelectric sensor. Experimental results demonstrate that two voltage outputs of the piezoelectric beam are approximately out of phase with identical amplitude. Moreover, the length of the piezoelectric layers has a significant influence on the sensing properties. Our theoretical predictions using the model support the experimental findings.

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

PubMed

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

Predicting spiral wave patterns from cell properties in a model of biological self-organization

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Numerical comparison of grid pattern diffraction effects through measurement and modeling with OptiScan software

NASA Astrophysics Data System (ADS)

Murray, Ian B.; Densmore, Victor; Bora, Vaibhav; Pieratt, Matthew W.; Hibbard, Douglas L.; Milster, Tom D.

2011-06-01

Coatings of various metalized patterns are used for heating and electromagnetic interference (EMI) shielding applications. Previous work has focused on macro differences between different types of grids, and has shown good correlation between measurements and analyses of grid diffraction. To advance this work, we have utilized the University of Arizona's OptiScan software, which has been optimized for this application by using the Babinet Principle. When operating on an appropriate computer system, this algorithm produces results hundreds of times faster than standard Fourier-based methods, and allows realistic cases to be modeled for the first time. By using previously published derivations by Exotic Electro-Optics, we compare diffraction performance of repeating and randomized grid patterns with equivalent sheet resistance using numerical performance metrics. Grid patterns of each type are printed on optical substrates and measured energy is compared against modeled energy.