Regulation of intracellular free calcium concentration during heterocyst differentiation by HetR and NtcA in Anabaena sp. PCC 7120.

Science.gov (United States)

Shi, Yunming; Zhao, Weixing; Zhang, Wei; Ye, Zi; Zhao, Jindong

2006-07-25

Calcium ions are important to some prokaryotic cellular processes, such as heterocyst differentiation of cyanobacteria. Intracellular free Ca(2+)concentration, [Ca(2+)](i), increases several fold in heterocysts and is regulated by CcbP, a Ca(2+)-binding protein found in heterocyst-forming cyanobacteria. We demonstrate here that CcbP is degraded by HetR, a serine-type protease that controls heterocyst differentiation. The degradation depends on Ca(2+) and appears to be specific because HetR did not digest other tested proteins. CcbP was found to bind two Ca(2+) per molecule with K(D) values of 200 nM and 12.8 microM. Degradation of CcbP releases bound Ca(2+) that contributes significantly to the increase of [Ca(2+)](i) during the process of heterocyst differentiation in Anabaena sp. strain PCC 7120. We suggest that degradation of CcbP is a mechanism of positive autoregulation of HetR. The down-regulation of ccbP in differentiating cells and mature heterocysts, which also is critical to the regulation of [Ca(2+)](i), depends on NtcA. Coexpression of ntcA and a ccbP promoter-controlled gfp in Escherichia coli diminished production of GFP, and the decrease is enhanced by alpha-ketoglutarate. It was also found that NtcA could bind a fragment of the ccbP promoter containing an NtcA-binding sequence in a alpha-ketoglutarate-dependent fashion. Therefore, [Ca(2+)](i) is regulated by a collaboration of HetR and NtcA in heterocyst differentiation in Anabaena sp. strain PCC 7120.

C5 glycolipids of heterocystous cyanobacteria track symbiont abundance in the diatom Hemiaulus hauckii across the tropical North Atlantic

Science.gov (United States)

Bale, Nicole J.; Villareal, Tracy A.; Hopmans, Ellen C.; Brussaard, Corina P. D.; Besseling, Marc; Dorhout, Denise; Sinninghe Damsté, Jaap S.; Schouten, Stefan

2018-03-01

Diatom-diazotroph associations (DDAs) include marine heterocystous cyanobacteria found as exosymbionts and endosymbionts in multiple diatom species. Heterocysts are the site of N2 fixation and have thickened cell walls containing unique heterocyst glycolipids which maintain a low oxygen environment within the heterocyst. The endosymbiotic cyanobacterium Richelia intracellularis found in species of the diatom genus Hemiaulus and Rhizosolenia makes heterocyst glycolipids (HGs) which are composed of C30 and C32 diols and triols with pentose (C5) moieties that are distinct from limnetic cyanobacterial HGs with predominantly hexose (C6) moieties. Here we applied a method for analysis of intact polar lipids to the study of HGs in suspended particulate matter (SPM) and surface sediment from across the tropical North Atlantic. The study focused on the Amazon plume region, where DDAs are documented to form extensive surface blooms, in order to examine the utility of C5 HGs as markers for DDAs as well as their transportation to underlying sediments. C30 and C32 triols with C5 pentose moieties were detected in both marine SPM and surface sediments. We found a significant correlation between the water column concentration of these long-chain C5 HGs and DDA symbiont counts. In particular, the concentrations of both the C5 HGs (1-(O-ribose)-3,27,29-triacontanetriol (C5 HG30 triol) and 1-(O-ribose)-3,29,31-dotriacontanetriol (C5 HG32 triol)) in SPM exhibited a significant correlation with the number of Hemiaulus hauckii symbionts. This result strengthens the idea that long-chain C5 HGs can be applied as biomarkers for marine endosymbiotic heterocystous cyanobacteria. The presence of the same C5 HGs in surface sediment provides evidence that they are effectively transported to the sediment and hence have potential as biomarkers for studies of the contribution of DDAs to the paleo-marine N cycle.

Analysis of the early heterocyst Cys-proteome in the multicellular cyanobacterium Nostoc punctiforme reveals novel insights into the division of labor within diazotrophic filaments.

Science.gov (United States)

Sandh, Gustaf; Ramström, Margareta; Stensjö, Karin

2014-12-04

In the filamentous cyanobacterium Nostoc punctiforme ATCC 29133, removal of combined nitrogen induces the differentiation of heterocysts, a cell-type specialized in N2 fixation. The differentiation involves genomic, structural and metabolic adaptations. In cyanobacteria, changes in the availability of carbon and nitrogen have also been linked to redox regulated posttranslational modifications of protein bound thiol groups. We have here employed a thiol targeting strategy to relatively quantify the putative redox proteome in heterocysts as compared to N2-fixing filaments, 24 hours after combined nitrogen depletion. The aim of the study was to expand the coverage of the cell-type specific proteome and metabolic landscape of heterocysts. Here we report the first cell-type specific proteome of newly formed heterocysts, compared to N2-fixing filaments, using the cysteine-specific selective ICAT methodology. The data set defined a good quantitative accuracy of the ICAT reagent in complex protein samples. The relative abundance levels of 511 proteins were determined and 74% showed a cell-type specific differential abundance. The majority of the identified proteins have not previously been quantified at the cell-type specific level. We have in addition analyzed the cell-type specific differential abundance of a large section of proteins quantified in both newly formed and steady-state diazotrophic cultures in N. punctiforme. The results describe a wide distribution of members of the putative redox regulated Cys-proteome in the central metabolism of both vegetative cells and heterocysts of N. punctiforme. The data set broadens our understanding of heterocysts and describes novel proteins involved in heterocyst physiology, including signaling and regulatory proteins as well as a large number of proteins with unknown function. Significant differences in cell-type specific abundance levels were present in the cell-type specific proteomes of newly formed diazotrophic filaments

Cell wall amidase AmiC1 is required for cellular communication and heterocyst development in the cyanobacterium Anabaena PCC 7120 but not for filament integrity.

Science.gov (United States)

Berendt, Susanne; Lehner, Josef; Zhang, Yao Vincent; Rasse, Tobias M; Forchhammer, Karl; Maldener, Iris

2012-10-01

Filamentous cyanobacteria of the order Nostocales display typical properties of multicellular organisms. In response to nitrogen starvation, some vegetative cells differentiate into heterocysts, where fixation of N(2) takes place. Heterocysts provide a micro-oxic compartment to protect nitrogenase from the oxygen produced by the vegetative cells. Differentiation involves fundamental remodeling of the gram-negative cell wall by deposition of a thick envelope and by formation of a neck-like structure at the contact site to the vegetative cells. Cell wall-hydrolyzing enzymes, like cell wall amidases, are involved in peptidoglycan maturation and turnover in unicellular bacteria. Recently, we showed that mutation of the amidase homologue amiC2 gene in Nostoc punctiforme ATCC 29133 distorts filament morphology and function. Here, we present the functional characterization of two amiC paralogues from Anabaena sp. strain PCC 7120. The amiC1 (alr0092) mutant was not able to differentiate heterocysts or to grow diazotrophically, whereas the amiC2 (alr0093) mutant did not show an altered phenotype under standard growth conditions. In agreement, fluorescence recovery after photobleaching (FRAP) studies showed a lack of cell-cell communication only in the AmiC1 mutant. Green fluorescent protein (GFP)-tagged AmiC1 was able to complement the mutant phenotype to wild-type properties. The protein localized in the septal regions of newly dividing cells and at the neck region of differentiating heterocysts. Upon nitrogen step-down, no mature heterocysts were developed in spite of ongoing heterocyst-specific gene expression. These results show the dependence of heterocyst development on amidase function and highlight a pivotal but so far underestimated cellular process, the remodeling of peptidoglycan, for the biology of filamentous cyanobacteria.

Molecular phylogeny, population genetics, and evolution of heterocystous cyanobacteria using nifH gene sequences

Czech Academy of Sciences Publication Activity Database

Singh, P.; Singh, S. S.; Elster, Josef; Mishra, A. K.

2013-01-01

Roč. 250, č. 3 (2013), s. 751-764 ISSN 0033-183X Institutional support: RVO:67985939 Keywords : evolution * heterocystous cyanobacteria * nifH gene Subject RIV: EH - Ecology, Behaviour Impact factor: 3.171, year: 2013

The hetC Gene Is a Direct Target of the NtcA Transcriptional Regulator in Cyanobacterial Heterocyst Development

Science.gov (United States)

Muro-Pastor, Alicia M.; Valladares, Ana; Flores, Enrique; Herrero, Antonia

1999-01-01

The heterocyst is the site of nitrogen fixation in aerobically grown cultures of some filamentous cyanobacteria. Heterocyst development in Anabaena sp. strain PCC 7120 is dependent on the global nitrogen regulator NtcA and requires, among others, the products of the hetR and hetC genes. Expression of hetC, tested by RNA- DNA hybridization, was impaired in an ntcA mutant. A nitrogen-regulated, NtcA-dependent putative transcription start point was localized at nucleotide −571 with respect to the hetC translational start. Sequences upstream from this transcription start point exhibit the structure of the canonical cyanobacterial promoter activated by NtcA, and purified NtcA protein specifically bound to a DNA fragment containing this promoter. Activation of expression of hetC during heterocyst development appears thus to be directly operated by NtcA. NtcA-mediated activation of hetR expression was not impaired in a hetC mutant, indicating that HetC is not an NtcA-dependent element required for hetR induction. PMID:10542167

Auto-flotation of heterocyst enables the efficient production of renewable energy in cyanobacteria.

Science.gov (United States)

Chen, Ming; Li, Jihong; Zhang, Lei; Chang, Sandra; Liu, Chen; Wang, Jianlong; Li, Shizhong

2014-02-06

Utilizing cyanobacteria as a bioenergy resource is difficult due to the cost and energy consuming harvests of microalgal biomass. In this study, an auto-floating system was developed by increasing the photobiological H2 production in the heterocysts of filamentous cyanobacteria. An amount of 1.0 μM of diuron, which inhibited O2 production in cyanobacteria, resulted in a high rate of H2 production in heterocysts. The auto-floating process recovered 91.71% ± 1.22 of the accumulated microalgal biomass from the liquid media. Quantification analysis revealed that 0.72-1.10 μmol H2 per mg dry weight microalgal biomass was necessary to create this auto-floating system. Further bio-conversion by using anaerobic digestion converted the harvested microalgal biomass into biogas. Through this novel coupled system of photobiological H2 production and anaerobic digestion, a high level of light energy conversion efficiency from solar energy to bioenergy was attained with the values of 3.79% ± 0.76.

Seasonal lake surface water temperature trends reflected by heterocyst glycolipid-based molecular thermometers

Science.gov (United States)

Bauersachs, T.; Rochelmeier, J.; Schwark, L.

2015-06-01

It has been demonstrated that the relative distribution of heterocyst glycolipids (HGs) in cultures of N2-fixing heterocystous cyanobacteria is largely controlled by growth temperature, suggesting a potential use of these components in paleoenvironmental studies. Here, we investigated the effect of environmental parameters (e.g., surface water temperatures, oxygen concentrations and pH) on the distribution of HGs in a natural system using water column filtrates collected from Lake Schreventeich (Kiel, Germany) from late July to the end of October 2013. HPLC-ESI/MS (high-performance liquid chromatography coupled to electrospray ionization-mass spectrometry) analysis revealed a dominance of 1-(O-hexose)-3,25-hexacosanediols (HG26 diols) and 1-(O-hexose)-3-keto-25-hexacosanol (HG26 keto-ol) in the solvent-extracted water column filtrates, which were accompanied by minor abundances of 1-(O-hexose)-3,27-octacosanediol (HG28 diol) and 1-(O-hexose)-3-keto-27-octacosanol (HG28 keto-ol) as well as 1-(O-hexose)-3,25,27-octacosanetriol (HG28 triol) and 1-(O-hexose)-3-keto-25,27-octacosanediol (HG28 keto-diol). Fractional abundances of alcoholic and ketonic HGs generally showed strong linear correlations with surface water temperatures and no or only weak linear correlations with both oxygen concentrations and pH. Changes in the distribution of the most abundant diol and keto-ol (e.g., HG26 diol and HG26 keto-ol) were quantitatively expressed as the HDI26 (heterocyst diol index of 26 carbon atoms) with values of this index ranging from 0.89 in mid-August to 0.66 in mid-October. An average HDI26 value of 0.79, which translates into a calculated surface water temperature of 15.8 ± 0.3 °C, was obtained from surface sediments collected from Lake Schreventeich. This temperature - and temperatures obtained from other HG indices (e.g., HDI28 and HTI28) - is similar to the one measured during maximum cyanobacterial productivity in early to mid-September and suggests that HGs

Distributions of Heterocyst Glycolipids in Settling Particulate Matter Record Ecological and Environmental Parameters in a Tropical Lake

Science.gov (United States)

Meegan Kumar, D.; Hopmans, E.; S Sinninghe Damsté, J.; Schouten, S.; Bauersachs, T.; Werne, J. P.

2017-12-01

Temperature is a critical component of paleoenvironmental reconstructions, yet it is notoriously difficult to measure in terrestrial archives. Presented here is an investigation of unique glycolipids produced by heterocystous cyanobacteria, so-called heterocyst glycolipids (HGs), in the water column of Lake Malawi (East Africa). The goal of the study is to evaluate the potential of HGs to function as a paleotemperature proxy in tropical lacustrine environments. HGs in Lake Malawi were extracted from settling particulate matter (SPM) collected at bi-monthly intervals from 2011 - 2013. Sediment traps were moored in the metalimnion of both the north and south basins of the lake in order to evaluate the spatial and the temporal trends in lipid production and export. This study is the first to analyze HGs in SPM and contains the longest time-series of HG production in a natural environment to date. HGs are consistently present throughout the three-year study period, but maximum fluxes occur annually in December, coincident with the timing of cyanobacterial blooms in the lake. HGs in SPM appear to be sourced from living cyanobacteria populations, indicating rapid export of the lipids through the water column. Temperatures reconstructed with published HG-based indices, which are derived from the relative abundances of HG diols and triols to HG keto-(di)ols, do not accurately reflect the seasonal variability in measured surface water temperatures. Rather, the production of C28 HG keto-ols appears to be related to the timing of heterocyst differentiation. Heterocystous cyanobacteria in Lake Malawi may instead respond to growth temperatures by elongating the alkyl side chain of HG diols, as indicated by increases in the abundance of the C28 HG diol relative to the C26 HG diol with warmer surface water temperatures. Distributions of HGs thus may indeed provide a novel tool for paleotemperature reconstructions in tropical lakes.

Transcription activation by NtcA and 2-oxoglutarate of three genes involved in heterocyst differentiation in the cyanobacterium Anabaena sp. strain PCC 7120.

Science.gov (United States)

Valladares, Ana; Flores, Enrique; Herrero, Antonia

2008-09-01

In Anabaena sp. strain PCC 7120, differentiation of heterocysts takes place in response to the external cue of combined nitrogen deprivation, allowing the organism to fix atmospheric nitrogen in oxic environments. NtcA, a global transcriptional regulator of cyanobacteria, is required for activation of the expression of multiple genes involved in heterocyst differentiation, including key regulators that are specific to the process. We have set up a fully defined in vitro system, which includes the purified Anabaena RNA polymerase, and have studied the effects of NtcA and its signaling effector 2-oxoglutarate on RNA polymerase binding, open complex formation, and transcript production from promoters of the hetC, nrrA, and devB genes that are activated by NtcA at different stages of heterocyst differentiation. Both RNA polymerase and NtcA could specifically bind to the target DNA in the absence of any effector. 2-Oxoglutarate had a moderate positive effect on NtcA binding, and NtcA had a limited positive effect on RNA polymerase recruitment at the promoters. However, a stringent requirement of both NtcA and 2-oxoglutarate was observed for the detection of open complexes and transcript production at the three investigated promoters. These results support a key role for 2-oxoglutarate in transcription activation in the developing heterocyst.

H{sub 2} - photoproduction by a non-heterocystous cyanobacterium Plectonema boryanum : a model tool for biotechnological exploitation

Energy Technology Data Exchange (ETDEWEB)

Chaturvedi, S.; Sarkar, S.; Kashyap, A.K.; Pandey, K.D. [Banaras Hindu Univ., Varanasi (India). Dept. of Botany

2001-07-01

A parallel increase in nitrogenase activity and H{sub 2} evolution in Plectonema boryanum under microaerobic (Ar/N{sub 2}/CO{sub 2}: 72/24/4; v/v) phototrophic condition indicated that later process was nitrogenase mediated. Enhanced H{sub 2} photoproduction was observed in presence of reducing substances and metabolic inhibitors (DCMU and MSX). N{sub 2}-fixed during the process was simultaneously released in the medium as NH{sub 4}{sup +}. Further enhancement and sustainability in both the processes was achieved by immobilization in alginate or sponge. A comparison with heterocystous cyanobacteria suggested that Plectonema was efficient H{sub 2} producing organism. (orig.)

Comparison of plasmids from the cyanobacterium Nostoc PCC 7524 with two mutant strains unable to form heterocysts

NARCIS (Netherlands)

Reaston, J.; Hondel, C.A.M.J.J. van den; Ende, A. van der; Arkel, G.A. van; Stewart, W.D.P.; Herdman, M.

1980-01-01

Cyanobacteria (bluegreen bacteria) are O₂-evolving photosynthetic prokaryotes some species of which fix N₂ in air because the nitrogenase is protected from O₂ inactivation by being localized in differentiated cells called heterocysts. Recently much attention has been paid to the possible role

Heterologous expression of an algal hydrogenase in a heterocystous cyanobacterium

Energy Technology Data Exchange (ETDEWEB)

Thorsten Heidorn; Peter Lindblad [Dept. of Physiological Botany, Uppsala University, Villavogen 6, SE-752 36 Uppsala, (Sweden)

2006-07-01

For the expression of an active algal [FeFe] hydrogenase in the heterocystous cyanobacterium Nostoc punctiforme A TCC 29133 the Chlamydomonas reinhardtii hydrogenase gene hydA1 and the accessory genes hydEF and hydG are to be introduced into the cyanobacteria cells. The genes were amplified by PCR from EST clones, cloned into the cloning vector pBluescript SK+ and sequenced. An expression vector for multi-cistronic cloning, based on pSCR202, was constructed and for a functional test GFP was inserted as a reporter gene. The GFP construct was transformed into Nostoc punctiforme A TCC 29133 by electroporation and expression of GFP was visualized by fluorescence microscopy. (authors)

Heterologous expression of an algal hydrogenase in a heterocystous cyanobacterium

International Nuclear Information System (INIS)

Thorsten Heidorn; Peter Lindblad

2006-01-01

For the expression of an active algal [FeFe] hydrogenase in the heterocystous cyanobacterium Nostoc punctiforme A TCC 29133 the Chlamydomonas reinhardtii hydrogenase gene hydA1 and the accessory genes hydEF and hydG are to be introduced into the cyanobacteria cells. The genes were amplified by PCR from EST clones, cloned into the cloning vector pBluescript SK+ and sequenced. An expression vector for multi-cistronic cloning, based on pSCR202, was constructed and for a functional test GFP was inserted as a reporter gene. The GFP construct was transformed into Nostoc punctiforme A TCC 29133 by electroporation and expression of GFP was visualized by fluorescence microscopy. (authors)

Regulation of Development and Nitrogen Fixation in Anabaena

Energy Technology Data Exchange (ETDEWEB)

James W. Golden

2008-10-17

The regulation of development and cellular differentiation is important for all multicellular organisms. The nitrogen-fixing filamentous cyanobacterium Anabaena (also Nostoc) sp. PCC 7120 (hereafter Anabaena) provides a model of multicellular microbial development and pattern formation. Anabaena reduces N2 to ammonia in specialized terminally differentiated cells called heterocysts. A one-dimensional developmental pattern of single heterocysts regularly spaced along filaments of photosynthetic vegetative cells is established to form a multicellular organism composed of these two interdependent cell types. This multicellular growth pattern, the distinct phylogeny of cyanobacteria, and the suspected antiquity of heterocyst development make this an important model system. Our long-term goal is to understand the regulatory network required for heterocyst development and nitrogen fixation. This project is focused on two key aspects of heterocyst regulation: one, the mechanism by which HetR controls the initiation of differentiation, and two, the cis and trans acting factors required for expression of the nitrogen-fixation (nif) genes. HetR is thought to be a central regulator of heterocyst development but the partners and mechanisms involved in this regulation are unknown. Our recent results indicate that PatS and other signals that regulate heterocyst pattern cannot interact, directly or indirectly, with a R223W mutant of HetR. We plan to use biochemical and genetic approaches to identify proteins that interact with the HetR protein, which will help reveal the mechanisms underlying its regulation of development. Our second goal is to determine how the nif genes are expressed. It is important to understand the mechanisms controlling nif genes since they represent the culmination of the differentiation process and the essence of heterocyst function. The Anabaena genome lacks the genes required for expression of nif genes present in other organisms such as rpoN (sigma 54

Heterologous expression of an algal hydrogenase in a hetero-cystous cyanobacterium

Energy Technology Data Exchange (ETDEWEB)

Thorsten Heidorn; Peter Lindblad [Dept. of Physiological Botany, Uppsala University, V illavagen 6, SE-752 36 Uppsala, (Sweden)

2006-07-01

For the expression of an active algal [FeFe] hydrogenase in the hetero-cystous cyanobacterium Nostoc punctiforme A TCC 29133 the Chlamydomonas reinhardtii hydrogenase gene hydA1 and the accessory genes hydEF and hydG are to be introduced into the cyano-bacterial cells. The genes were amplified by PCR from EST clones, cloned into the cloning vector pBluescript SK+ and sequenced. An expression vector for multi-cistronic cloning, based on pSCR202, was constructed and for a functional test GFP was inserted as a reporter gene. The GFP construct was transformed into Nostoc punctiforme A TCC 29133 by electroporation and expression of GFP was visualized by fluorescence microscopy. (authors)

Heterologous expression of an algal hydrogenase in a hetero-cystous cyanobacterium

International Nuclear Information System (INIS)

Thorsten Heidorn; Peter Lindblad

2006-01-01

For the expression of an active algal [FeFe] hydrogenase in the hetero-cystous cyanobacterium Nostoc punctiforme A TCC 29133 the Chlamydomonas reinhardtii hydrogenase gene hydA1 and the accessory genes hydEF and hydG are to be introduced into the cyano-bacterial cells. The genes were amplified by PCR from EST clones, cloned into the cloning vector pBluescript SK+ and sequenced. An expression vector for multi-cistronic cloning, based on pSCR202, was constructed and for a functional test GFP was inserted as a reporter gene. The GFP construct was transformed into Nostoc punctiforme A TCC 29133 by electroporation and expression of GFP was visualized by fluorescence microscopy. (authors)

Chemotaxonomy of heterocystous cyanobacteria using FAME profiling as species markers.

Science.gov (United States)

Shukla, Ekta; Singh, Satya Shila; Singh, Prashant; Mishra, Arun Kumar

2012-07-01

The fatty acid methyl ester (FAME) analysis of the 12 heterocystous cyanobacterial strains showed different fatty acid profiling based on the presence/absence and the percentage of 13 different types of fatty acids. The major fatty acids viz. palmitic acid (16:0), hexadecadienoic acid (16:2), stearic acid (18:0), oleic acid (18:1), linoleic (18:2), and linolenic acid (18:3) were present among all the strains except Cylindrospermum musicola where oleic acid (18:1) was absent. All the strains showed high levels of polyunsaturated fatty acid (PUFAs; 41-68.35%) followed by saturated fatty acid (SAFAs; 1.82-40.66%) and monounsaturated fatty acid (0.85-24.98%). Highest percentage of PUFAs and essential fatty acid (linolenic acid; 18:3) was reported in Scytonema bohnerii which can be used as fatty acid supplement in medical and biotechnological purpose. The cluster analysis based on FAME profiling suggests the presence of two distinct clusters with Euclidean distance ranging from 0 to 25. S. bohnerii of cluster I was distantly related to the other strains of cluster II. The genotypes of cluster II were further divided into two subclusters, i.e., IIa with C. musicola showing great divergence with the other genotypes of IIb which was further subdivided into two groups. Subsubcluster IIb(1) was represented by a genotype, Anabaena sp. whereas subsubcluster IIb(2) was distinguished by two groups, i.e., one group having significant similarity among their three genotypes showed distant relation with the other group having closely related six genotypes. To test the validity of the fatty acid profiles as a marker, cluster analysis has also been generated on the basis of morphological attributes. Our results suggest that FAME profiling might be used as species markers in the study of polyphasic approach based taxonomy and phylogenetic relationship.

Patterns of data modeling

CERN Document Server

Blaha, Michael

2010-01-01

Best-selling author and database expert with more than 25 years of experience modeling application and enterprise data, Dr. Michael Blaha provides tried and tested data model patterns, to help readers avoid common modeling mistakes and unnecessary frustration on their way to building effective data models. Unlike the typical methodology book, "Patterns of Data Modeling" provides advanced techniques for those who have mastered the basics. Recognizing that database representation sets the path for software, determines its flexibility, affects its quality, and influences whether it succ

Modeling Architectural Patterns Using Architectural Primitives

NARCIS (Netherlands)

Zdun, Uwe; Avgeriou, Paris

2005-01-01

Architectural patterns are a key point in architectural documentation. Regrettably, there is poor support for modeling architectural patterns, because the pattern elements are not directly matched by elements in modeling languages, and, at the same time, patterns support an inherent variability that

Isolation and screening of heterocystous cyanobacterial strains for biodiesel production by evaluating the fuel properties from fatty acid methyl ester (FAME) profiles.

Science.gov (United States)

Anahas, Antonyraj Matharasi Perianaika; Muralitharan, Gangatharan

2015-05-01

This study reports on the biodiesel quality parameters of eleven heterocystous cyanobacterial strains based on fatty acid methyl esters (FAME) profiles. The biomass productivity of the tested cyanobacterial strains ranged from 9.33 to 20.67 mg L(-1) d(-1) while the lipid productivity varied between 0.65 and 2.358 mg L(-1) d(-1). The highest biomass and lipid productivity was observed for Calothrix sp. MBDU 013 but its lipid content is only 11.221 in terms of percent dry weight, next to the Anabaena sphaerica MBDU 105, whose lipid content is high. To identify the most competent isolate, a multi-criteria decision analyses (MCDA) was performed by including the key chemical and physical parameters of biodiesel calculated from FAME profiles. The isolate A.sphaerica MBDU 105 is the most promising biodiesel feed stock based on decision vector through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Workflow Patterns for Business Process Modeling

NARCIS (Netherlands)

Thom, Lucineia Heloisa; Lochpe, Cirano; Reichert, M.U.

For its reuse advantages, workflow patterns (e.g., control flow patterns, data patterns, resource patterns) are increasingly attracting the interest of both researchers and vendors. Frequently, business process or workflow models can be assembeled out of a set of recurrent process fragments (or

Validating EHR clinical models using ontology patterns.

Science.gov (United States)

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.

Amino Acid Transporters and Release of Hydrophobic Amino Acids in the Heterocyst-Forming Cyanobacterium Anabaena sp. Strain PCC 7120

Directory of Open Access Journals (Sweden)

Rafael Pernil

2015-04-01

Full Text Available Anabaena sp. strain PCC 7120 is a filamentous cyanobacterium that can use inorganic compounds such as nitrate or ammonium as nitrogen sources. In the absence of combined nitrogen, it can fix N2 in differentiated cells called heterocysts. Anabaena also shows substantial activities of amino acid uptake, and three ABC-type transporters for amino acids have been previously characterized. Seven new loci encoding predicted amino acid transporters were identified in the Anabaena genomic sequence and inactivated. Two of them were involved in amino acid uptake. Locus alr2535-alr2541 encodes the elements of a hydrophobic amino acid ABC-type transporter that is mainly involved in the uptake of glycine. ORF all0342 encodes a putative transporter from the dicarboxylate/amino acid:cation symporter (DAACS family whose inactivation resulted in an increased uptake of a broad range of amino acids. An assay to study amino acid release from Anabaena filaments to the external medium was set up. Net release of the alanine analogue α-aminoisobutyric acid (AIB was observed when transport system N-I (a hydrophobic amino acid ABC-type transporter was engaged in the uptake of a specific substrate. The rate of AIB release was directly proportional to the intracellular AIB concentration, suggesting leakage from the cells by diffusion.

Enforcing a security pattern in stakeholder goal models

OpenAIRE

Yu, Yijun; Kaiya, Haruhiko; Washizaki, Hironori; Xiong, Yingfei; Hu, Zhenjiang; Yoshioka, Nobukazu

2008-01-01

Patterns are useful knowledge about recurring problems and solutions. Detecting a security problem using patterns in requirements models may lead to its early solution. In order to facilitate early detection and resolution of security problems, in this paper, we formally describe a role-based access control (RBAC) as a pattern that may occur in stakeholder requirements models. We also implemented in our goal-oriented modeling tool the formally described pattern using model-driven queries and ...

Modelling biomechanics of bark patterning in grasstrees.

Science.gov (United States)

Dale, Holly; Runions, Adam; Hobill, David; Prusinkiewicz, Przemyslaw

2014-09-01

Bark patterns are a visually important characteristic of trees, typically attributed to fractures occurring during secondary growth of the trunk and branches. An understanding of bark pattern formation has been hampered by insufficient information regarding the biomechanical properties of bark and the corresponding difficulties in faithfully modelling bark fractures using continuum mechanics. This study focuses on the genus Xanthorrhoea (grasstrees), which have an unusual bark-like structure composed of distinct leaf bases connected by sticky resin. Due to its discrete character, this structure is well suited for computational studies. A dynamic computational model of grasstree development was created. The model captures both the phyllotactic pattern of leaf bases during primary growth and the changes in the trunk's width during secondary growth. A biomechanical representation based on a system of masses connected by springs is used for the surface of the trunk, permitting the emergence of fractures during secondary growth to be simulated. The resulting fracture patterns were analysed statistically and compared with images of real trees. The model reproduces key features of grasstree bark patterns, including their variability, spanning elongated and reticulate forms. The patterns produced by the model have the same statistical character as those seen in real trees. The model was able to support the general hypothesis that the patterns observed in the grasstree bark-like layer may be explained in terms of mechanical fractures driven by secondary growth. Although the generality of the results is limited by the unusual structure of grasstree bark, it supports the hypothesis that bark pattern formation is primarily a biomechanical phenomenon.

Molecular Diffusion through Cyanobacterial Septal Junctions

Directory of Open Access Journals (Sweden)

Mercedes Nieves-Morión

2017-01-01

Full Text Available Heterocyst-forming cyanobacteria grow as filaments in which intercellular molecular exchange takes place. During the differentiation of N2-fixing heterocysts, regulators are transferred between cells. In the diazotrophic filament, vegetative cells that fix CO2 through oxygenic photosynthesis provide the heterocysts with reduced carbon and heterocysts provide the vegetative cells with fixed nitrogen. Intercellular molecular transfer has been traced with fluorescent markers, including calcein, 5-carboxyfluorescein, and the sucrose analogue esculin, which are observed to move down their concentration gradient. In this work, we used fluorescence recovery after photobleaching (FRAP assays in the model heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 to measure the temperature dependence of intercellular transfer of fluorescent markers. We find that the transfer rate constants are directly proportional to the absolute temperature. This indicates that the “septal junctions” (formerly known as “microplasmodesmata” linking the cells in the filament allow molecular exchange by simple diffusion, without any activated intermediate state. This constitutes a novel mechanism for molecular transfer across the bacterial cytoplasmic membrane, in addition to previously characterized mechanisms for active transport and facilitated diffusion. Cyanobacterial septal junctions are functionally analogous to the gap junctions of metazoans.

Directional RNA deep sequencing sheds new light on the transcriptional response of Anabaena sp. strain PCC 7120 to combined-nitrogen deprivation

Directory of Open Access Journals (Sweden)

Head Steven R

2011-06-01

Full Text Available Abstract Background Cyanobacteria are potential sources of renewable chemicals and biofuels and serve as model organisms for bacterial photosynthesis, nitrogen fixation, and responses to environmental changes. Anabaena (Nostoc sp. strain PCC 7120 (hereafter Anabaena is a multicellular filamentous cyanobacterium that can "fix" atmospheric nitrogen into ammonia when grown in the absence of a source of combined nitrogen. Because the nitrogenase enzyme is oxygen sensitive, Anabaena forms specialized cells called heterocysts that create a microoxic environment for nitrogen fixation. We have employed directional RNA-seq to map the Anabaena transcriptome during vegetative cell growth and in response to combined-nitrogen deprivation, which induces filaments to undergo heterocyst development. Our data provide an unprecedented view of transcriptional changes in Anabaena filaments during the induction of heterocyst development and transition to diazotrophic growth. Results Using the Illumina short read platform and a directional RNA-seq protocol, we obtained deep sequencing data for RNA extracted from filaments at 0, 6, 12, and 21 hours after the removal of combined nitrogen. The RNA-seq data provided information on transcript abundance and boundaries for the entire transcriptome. From these data, we detected novel antisense transcripts within the UTRs (untranslated regions and coding regions of key genes involved in heterocyst development, suggesting that antisense RNAs may be important regulators of the nitrogen response. In addition, many 5' UTRs were longer than anticipated, sometimes extending into upstream open reading frames (ORFs, and operons often showed complex structure and regulation. Finally, many genes that had not been previously identified as being involved in heterocyst development showed regulation, providing new candidates for future studies in this model organism. Conclusions Directional RNA-seq data were obtained that provide

Chopper model of pattern recognition

NARCIS (Netherlands)

van Hemmen, J.L.; Enter, A.C.D. van

A simple model is proposed that allows an efficient storage and retrieval of random patterns. Also correlated patterns can be handled. The data are stored in an Ising-spin system with ferromagnetic interactions between all the spins and the main idea is to "chop" the system along the boundaries

Evaluation of toxicological impact of cartap hydrochloride on some physiological activities of a non-heterocystous cyanobacterium Leptolyngbya foveolarum.

Science.gov (United States)

Singh, D P; Khattar, J I S; Gupta, Meenu; Kaur, Gurdeep

2014-03-01

The present study was aimed to the evaluation of toxicological impact of insecticide cartap hydrochloride on photosynthesis and nitrogen assimilation of a non-heterocystous cyanoprokaryote Leptolyngbya foveolarum isolated from paddy fields of Punjab, India. The microorganism tolerated commercial grade insecticide up to 80 ppm. Lower concentration (20 ppm) of cartap supported good growth with high dry weight of biomass, total protein content, photosynthetic pigments, photosynthesis and respiration compared to untreated control cultures while higher concentrations (40 and 60 ppm) inhibited these parameters in a dose dependent manner. Treatment of the microorganism with 60 ppm cartap lowered the content of photosynthetic pigments with maximum inhibitory effect on phycoerythrin (70% decrease) followed by allophycocyanin (66% decrease). Rates of photosynthesis and respiration were inhibited by 63% and 45%, respectively, while PS-I, II and whole chain activity were decreased by 45%, 67% and 40% respectively, compared to untreated control cultures. Cartap at 60 ppm decreased nitrate and nitrite uptake by 31% and 61%, respectively, whereas uptake of ammonium was slightly increased (18%) in cartap (60 ppm) treated cells. Nitrate and nitrite reductase, and glutamine synthetase activities of the microorganism decreased by 36-50% in 60 ppm cartap. The low levels of growth, photosynthetic pigments and activities of nitrogen assimilating enzymes in cells grown in nitrogen depleted medium supplement with insecticide indicated that insecticide may be used by the organism as a nitrogen source. Copyright © 2014 Elsevier Inc. All rights reserved.

Pattern formation of a nonlocal, anisotropic interaction model

KAUST Repository

Burger, Martin

2017-11-24

We consider a class of interacting particle models with anisotropic, repulsive–attractive interaction forces whose orientations depend on an underlying tensor field. An example of this class of models is the so-called Kücken–Champod model describing the formation of fingerprint patterns. This class of models can be regarded as a generalization of a gradient flow of a nonlocal interaction potential which has a local repulsion and a long-range attraction structure. In contrast to isotropic interaction models the anisotropic forces in our class of models cannot be derived from a potential. The underlying tensor field introduces an anisotropy leading to complex patterns which do not occur in isotropic models. This anisotropy is characterized by one parameter in the model. We study the variation of this parameter, describing the transition between the isotropic and the anisotropic model, analytically and numerically. We analyze the equilibria of the corresponding mean-field partial differential equation and investigate pattern formation numerically in two dimensions by studying the dependence of the parameters in the model on the resulting patterns.

Pattern formation of a nonlocal, anisotropic interaction model

KAUST Repository

Burger, Martin; Dü ring, Bertram; Kreusser, Lisa Maria; Markowich, Peter A.; Schö nlieb, Carola-Bibiane

2017-01-01

We consider a class of interacting particle models with anisotropic, repulsive–attractive interaction forces whose orientations depend on an underlying tensor field. An example of this class of models is the so-called Kücken–Champod model describing the formation of fingerprint patterns. This class of models can be regarded as a generalization of a gradient flow of a nonlocal interaction potential which has a local repulsion and a long-range attraction structure. In contrast to isotropic interaction models the anisotropic forces in our class of models cannot be derived from a potential. The underlying tensor field introduces an anisotropy leading to complex patterns which do not occur in isotropic models. This anisotropy is characterized by one parameter in the model. We study the variation of this parameter, describing the transition between the isotropic and the anisotropic model, analytically and numerically. We analyze the equilibria of the corresponding mean-field partial differential equation and investigate pattern formation numerically in two dimensions by studying the dependence of the parameters in the model on the resulting patterns.

Generative models versus underlying symmetries to explain biological pattern.

Science.gov (United States)

Frank, S A

2014-06-01

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

The interplay between siderophore secretion and coupled iron and copper transport in the heterocyst-forming cyanobacterium Anabaena sp. PCC 7120.

Science.gov (United States)

Nicolaisen, Kerstin; Hahn, Alexander; Valdebenito, Marianne; Moslavac, Suncana; Samborski, Anastazia; Maldener, Iris; Wilken, Corinna; Valladares, Ana; Flores, Enrique; Hantke, Klaus; Schleiff, Enrico

2010-11-01

Iron uptake is essential for Gram-negative bacteria including cyanobacteria. In cyanobacteria, however, the iron demand is higher than in proteobacteria due to the function of iron as a cofactor in photosynthesis and nitrogen fixation, but our understanding of iron uptake by cyanobacteria stands behind the knowledge in proteobacteria. Here, two genes involved in this process in the heterocyst-forming cyanobacterium Anabaena sp. PCC 7120 were identified. ORF all4025 encodes SchE, a putative cytoplasmic membrane-localized transporter involved in TolC-dependent siderophore secretion. Inactivation of schE resulted in an enhanced sensitivity to high metal concentrations and decreased secretion of hydroxamate-type siderophores. ORF all4026 encodes a predicted outer membrane-localized TonB-dependent iron transporter, IacT. Inactivation of iacT resulted in decreased sensitivity to elevated iron and copper levels. Expression of iacT from the artificial trc promoter (P(trc)) resulted in sensitization against tested metals. Further analysis showed that iron and copper effects are synergistic because a decreased supply of iron induced a significant decrease of copper levels in the iacT insertion mutant but an increase of those levels in the strain carrying P(trc)-iacT. Our results unravel a link between iron and copper homeostasis in Anabaena sp. PCC 7120. Copyright © 2010 Elsevier B.V. All rights reserved.

Emergent patterns of social affiliation in primates, a model.

Directory of Open Access Journals (Sweden)

Ivan Puga-Gonzalez

2009-12-01

Full Text Available Many patterns of affiliative behaviour have been described for primates, for instance: reciprocation and exchange of grooming, grooming others of similar rank, reconciliation of fights, and preferential reconciliation with more valuable partners. For these patterns several functions and underlying cognitive processes have been suggested. It is, however, difficult to imagine how animals may combine these diverse considerations in their mind. Although the co-variation hypothesis, by limiting the social possibilities an individual has, constrains the number of cognitive considerations an individual has to take, it does not present an integrated theory of affiliative patterns either. In the present paper, after surveying patterns of affiliation in egalitarian and despotic macaques, we use an individual-based model with a high potential for self-organisation as a starting point for such an integrative approach. In our model, called GrooFiWorld, individuals group and, upon meeting each other, may perform a dominance interaction of which the outcomes of winning and losing are self-reinforcing. Besides, if individuals think they will be defeated, they consider grooming others. Here, the greater their anxiety is, the greater their "motivation" to groom others. Our model generates patterns similar to many affiliative patterns of empirical data. By merely increasing the intensity of aggression, affiliative patterns in the model change from those resembling egalitarian macaques to those resembling despotic ones. Our model produces such patterns without assuming in the mind of the individual the specific cognitive processes that are usually thought to underlie these patterns (such as recordkeeping of the acts given and received, a tendency to exchange, memory of the former fight, selective attraction to the former opponent, and estimation of the value of a relationship. Our model can be used as a null model to increase our understanding of affiliative

Turing patterns in a modified Lotka-Volterra model

International Nuclear Information System (INIS)

McGehee, Edward A.; Peacock-Lopez, Enrique

2005-01-01

In this Letter we consider a modified Lotka-Volterra model widely known as the Bazykin model, which is the MacArthur-Rosenzweig (MR) model that includes a prey-dependent response function and is modified with the inclusion of intraspecies interactions. We show that a quadratic intra-prey interaction term, which is the most realistic nonlinearity, yields sufficient conditions for Turing patterns. For the Bazykin model we find the Turing region in parameter space and Turing patterns in one dimension

Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology.

Science.gov (United States)

Grimm, Volker; Railsback, Steven F

2012-01-19

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.

Spatial separation of photosynthesis and ethanol production by cell type-specific metabolic engineering of filamentous cyanobacteria.

Science.gov (United States)

Ehira, Shigeki; Takeuchi, Takuto; Higo, Akiyoshi

2018-02-01

Cyanobacteria, which perform oxygenic photosynthesis, have drawn attention as hosts for the direct production of biofuels and commodity chemicals from CO 2 and H 2 O using light energy. Although cyanobacteria capable of producing diverse chemicals have been generated by metabolic engineering, anaerobic non-photosynthetic culture conditions are often necessary for their production. In this study, we conducted cell type-specific metabolic engineering of the filamentous cyanobacterium Anabaena sp. PCC 7120, which forms a terminally differentiated cell called a heterocyst with a semi-regular spacing of 10-15 cells. Because heterocysts are specialized cells for nitrogen fixation, the intracellular oxygen level of heterocysts is maintained very low even when adjacent cells perform oxygenic photosynthesis. Pyruvate decarboxylase of Zymomonas mobilis and alcohol dehydrogenase of Synechocystis sp. PCC 6803 were exclusively expressed in heterocysts. Ethanol production was concomitant with nitrogen fixation in genetically engineered Anabaena sp. PCC 7120. Engineering of carbon metabolism in heterocysts improved ethanol production, and strain ET14, with an extra copy of the invB gene expressed from a heterocyst-specific promoter, produced 130.9 mg L -1 of ethanol after 9 days. ET14 produced 1681.9 mg L -1 of ethanol by increasing the CO 2 supply. Ethanol production per heterocyst cell was approximately threefold higher than that per cell of unicellular cyanobacterium. This study demonstrates the potential of heterocysts for anaerobic production of biofuels and commodity chemicals under oxygenic photosynthetic conditions.

Cascading walks model for human mobility patterns.

Science.gov (United States)

Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

2015-01-01

Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns.

Pattern formation in superdiffusion Oregonator model

Science.gov (United States)

Feng, Fan; Yan, Jia; Liu, Fu-Cheng; He, Ya-Feng

2016-10-01

Pattern formations in an Oregonator model with superdiffusion are studied in two-dimensional (2D) numerical simulations. Stability analyses are performed by applying Fourier and Laplace transforms to the space fractional reaction-diffusion systems. Antispiral, stable turing patterns, and travelling patterns are observed by changing the diffusion index of the activator. Analyses of Floquet multipliers show that the limit cycle solution loses stability at the wave number of the primitive vector of the travelling hexagonal pattern. We also observed a transition between antispiral and spiral by changing the diffusion index of the inhibitor. Project supported by the National Natural Science Foundation of China (Grant Nos. 11205044 and 11405042), the Research Foundation of Education Bureau of Hebei Province, China (Grant Nos. Y2012009 and ZD2015025), the Program for Young Principal Investigators of Hebei Province, China, and the Midwest Universities Comprehensive Strength Promotion Project.

Spatio-temporal patterns in simple models of marine systems

Science.gov (United States)

Feudel, U.; Baurmann, M.; Gross, T.

2009-04-01

Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

Modelling of Patterns in Space and Time

CERN Document Server

Murray, James

1984-01-01

This volume contains a selection of papers presented at the work­ shop "Modelling of Patterns in Space and Time", organized by the 80nderforschungsbereich 123, "8tochastische Mathematische Modelle", in Heidelberg, July 4-8, 1983. The main aim of this workshop was to bring together physicists, chemists, biologists and mathematicians for an exchange of ideas and results in modelling patterns. Since the mathe­ matical problems arising depend only partially on the particular field of applications the interdisciplinary cooperation proved very useful. The workshop mainly treated phenomena showing spatial structures. The special areas covered were morphogenesis, growth in cell cultures, competition systems, structured populations, chemotaxis, chemical precipitation, space-time oscillations in chemical reactors, patterns in flames and fluids and mathematical methods. The discussions between experimentalists and theoreticians were especially interesting and effective. The editors hope that these proceedings reflect ...

Modeling and analyzing stripe patterns in fish skin

Science.gov (United States)

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.

A Multiscale Survival Process for Modeling Human Activity Patterns.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Voronoi cell patterns: Theoretical model and applications

Science.gov (United States)

González, Diego Luis; Einstein, T. L.

2011-11-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.

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

Science.gov (United States)

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

Numerical approaches to model perturbation fire in turing pattern formations

Science.gov (United States)

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.

Novel Lipid Biomarkers for Past Oceanic N2 Fixation

Science.gov (United States)

Bale, N. J.; Hopmans, E. C.; Villareal, T. A.; Zell, C. I.; Sinninghe Damsté, , J.; Schouten, S.

2014-12-01

Nitrogen-fixing cyanobacteria play important roles in the biogeochemical cycles of aquatic systems. Both heterocystous and non-heterocystous N2-fixing cyanobacteria are symbiotic with marine diatoms and thrive in low nutrient environments. These associations are significant exporters of carbon to the deep-sea, but suitable tracers for reconstructing their importance in past environments are lacking. We recently analyzed the heterocyst glycolipids (HGs) of the heterocystous Richelia intracellularis symbiont of the marine diatoms Hemiaulus hauckii and H. membranaceus and found unique C5 glycolipids with C30-32 carbon chains, a structure different from the C6 glycolipids detected in freshwater heterocystous cyanobacteria. We developed a high performance liquid chromatography/ multiple reaction monitoring mass spectrometry (HPLC/MS) method specific for trace analysis of long chain C5 HGs and applied it to suspended particulate matter (SPM) and surface sediment from the Amazon plume, a region known to harbor marine diatoms carrying heterocystous cyanobacteria as endosymbionts. C5 HGs were detected in both SPM and sediments demonstrating their biomarker potential. They were not detected in SPM or sediment from freshwater settings in the region. Rather, limnetic SPM and sediments contained C6 HGs which are established biomarkers for free-living heterocystous cyanobacteria. Glycolipids have been found preserved in sediments of up to 49 Ma old. Our development of the C5 biomarkers has the potential to improve our knowledge of the contribution of symbiotic cyanobacteria to the paleo-N-cycle.

Molecular Diffusion through Cyanobacterial Septal Junctions.

Science.gov (United States)

Nieves-Morión, Mercedes; Mullineaux, Conrad W; Flores, Enrique

2017-01-03

Heterocyst-forming cyanobacteria grow as filaments in which intercellular molecular exchange takes place. During the differentiation of N 2 -fixing heterocysts, regulators are transferred between cells. In the diazotrophic filament, vegetative cells that fix CO 2 through oxygenic photosynthesis provide the heterocysts with reduced carbon and heterocysts provide the vegetative cells with fixed nitrogen. Intercellular molecular transfer has been traced with fluorescent markers, including calcein, 5-carboxyfluorescein, and the sucrose analogue esculin, which are observed to move down their concentration gradient. In this work, we used fluorescence recovery after photobleaching (FRAP) assays in the model heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 to measure the temperature dependence of intercellular transfer of fluorescent markers. We find that the transfer rate constants are directly proportional to the absolute temperature. This indicates that the "septal junctions" (formerly known as "microplasmodesmata") linking the cells in the filament allow molecular exchange by simple diffusion, without any activated intermediate state. This constitutes a novel mechanism for molecular transfer across the bacterial cytoplasmic membrane, in addition to previously characterized mechanisms for active transport and facilitated diffusion. Cyanobacterial septal junctions are functionally analogous to the gap junctions of metazoans. Although bacteria are frequently considered just as unicellular organisms, there are bacteria that behave as true multicellular organisms. The heterocyst-forming cyanobacteria grow as filaments in which cells communicate. Intercellular molecular exchange is thought to be mediated by septal junctions. Here, we show that intercellular transfer of fluorescent markers in the cyanobacterial filament has the physical properties of simple diffusion. Thus, cyanobacterial septal junctions are functionally analogous to metazoan gap junctions

Modeling and inferring cleavage patterns in proliferating epithelia.

Directory of Open Access Journals (Sweden)

Ankit B Patel

2009-06-01

Full Text Available The regulation of cleavage plane orientation is one of the key mechanisms driving epithelial morphogenesis. Still, many aspects of the relationship between local cleavage patterns and tissue-level properties remain poorly understood. Here we develop a topological model that simulates the dynamics of a 2D proliferating epithelium from generation to generation, enabling the exploration of a wide variety of biologically plausible cleavage patterns. We investigate a spectrum of models that incorporate the spatial impact of neighboring cells and the temporal influence of parent cells on the choice of cleavage plane. Our findings show that cleavage patterns generate "signature" equilibrium distributions of polygonal cell shapes. These signatures enable the inference of local cleavage parameters such as neighbor impact, maternal influence, and division symmetry from global observations of the distribution of cell shape. Applying these insights to the proliferating epithelia of five diverse organisms, we find that strong division symmetry and moderate neighbor/maternal influence are required to reproduce the predominance of hexagonal cells and low variability in cell shape seen empirically. Furthermore, we present two distinct cleavage pattern models, one stochastic and one deterministic, that can reproduce the empirical distribution of cell shapes. Although the proliferating epithelia of the five diverse organisms show a highly conserved cell shape distribution, there are multiple plausible cleavage patterns that can generate this distribution, and experimental evidence suggests that indeed plants and fruitflies use distinct division mechanisms.

Modelling survival: exposure pattern, species sensitivity and uncertainty.

Science.gov (United States)

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.

Stripe patterns in a model for block polymers

NARCIS (Netherlands)

Peletier, M.A.; Veneroni, M.

2009-01-01

We consider a pattern-forming system in two space dimensions defined by an energy Ge. The functional Ge models strong phase separation in AB diblock copolymer melts, and patterns are represented by {0, 1}-valued functions; the values 0 and 1 correspond to the A and B phases. The parameter e is the

Stripe patterns in a model for block polymers

NARCIS (Netherlands)

Peletier, M.A.; Veneroni, M.

2010-01-01

We consider a pattern-forming system in two space dimensions defined by an energy Ge. The functional Ge models strong phase separation in AB diblock copolymer melts, and patterns are represented by {0, 1}-valued functions; the values 0 and 1 correspond to the A and B phases. The parameter e is the

BUSINESS MODEL PATTERNS FOR DISRUPTIVE TECHNOLOGIES

OpenAIRE

BENJAMIN AMSHOFF; CHRISTIAN DÜLME; JULIAN ECHTERFELD; JÜRGEN GAUSEMEIER

2015-01-01

Companies nowadays face a myriad of business opportunities as a direct consequence of manifold disruptive technology developments. As a basic characteristic, disruptive technologies lead to a severe shift in value-creation networks giving rise to new market segments. One of the key challenges is to anticipate the business logics within these nascent and formerly unknown markets. Business model patterns promise to tackle this challenge. They can be interpreted as proven business model elements...

Pattern Formation in Predator-Prey Model with Delay and Cross Diffusion

Directory of Open Access Journals (Sweden)

Xinze Lian

2013-01-01

Full Text Available We consider the effect of time delay and cross diffusion on the dynamics of a modified Leslie-Gower predator-prey model incorporating a prey refuge. Based on the stability analysis, we demonstrate that delayed feedback may generate Hopf and Turing instability under some conditions, resulting in spatial patterns. One of the most interesting findings is that the model exhibits complex pattern replication: the model dynamics exhibits a delay and diffusion controlled formation growth not only to spots, stripes, and holes, but also to spiral pattern self-replication. The results indicate that time delay and cross diffusion play important roles in pattern formation.

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

Science.gov (United States)

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.

Crossover patterning by the beam-film model: analysis and implications.

Directory of Open Access Journals (Sweden)

Liangran Zhang

2014-01-01

Full Text Available 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.

Tilted dipole model for bias-dependent photoluminescence pattern

Energy Technology Data Exchange (ETDEWEB)

Fujieda, Ichiro, E-mail: fujieda@se.ritsumei.ac.jp; Suzuki, Daisuke; Masuda, Taishi [Department of Electrical and Electronic Engineering, Ritsumeikan University, Kusatsu 525-8577 (Japan)

2014-12-14

In a guest-host system containing elongated dyes and a nematic liquid crystal, both molecules are aligned to each other. An external bias tilts these molecules and the radiation pattern of the system is altered. A model is proposed to describe this bias-dependent photoluminescence patterns. It divides the liquid crystal/dye layer into sub-layers that contain electric dipoles with specific tilt angles. Each sub-layer emits linearly polarized light. Its radiation pattern is toroidal and is determined by the tilt angle. Its intensity is assumed to be proportional to the power of excitation light absorbed by the sub-layer. This is calculated by the Lambert-Beer's Law. The absorption coefficient is assumed to be proportional to the cross-section of the tilted dipole moment, in analogy to the ellipsoid of refractive index, to evaluate the cross-section for each polarized component of the excitation light. Contributions from all the sub-layers are added to give a final expression for the radiation pattern. Self-absorption is neglected. The model is simplified by reducing the number of sub-layers. Analytical expressions are derived for a simple case that consists of a single layer with tilted dipoles sandwiched by two layers with horizontally-aligned dipoles. All the parameters except for the tilt angle can be determined by measuring transmittance of the excitation light. The model roughly reproduces the bias-dependent photoluminescence patterns of a cell containing 0.5 wt. % coumarin 6. It breaks down at large emission angles. Measured spectral changes suggest that the discrepancy is due to self-absorption and re-emission.

Turing patterns and long-time behavior in a three-species food-chain model

KAUST Repository

Parshad, Rana D.

2014-08-01

We consider a spatially explicit three-species food chain model, describing generalist top predator-specialist middle predator-prey dynamics. We investigate the long-time dynamics of the model and show the existence of a finite dimensional global attractor in the product space, L2(Ω). We perform linear stability analysis and show that the model exhibits the phenomenon of Turing instability, as well as diffusion induced chaos. Various Turing patterns such as stripe patterns, mesh patterns, spot patterns, labyrinth patterns and weaving patterns are obtained, via numerical simulations in 1d as well as in 2d. The Turing and non-Turing space, in terms of model parameters, is also explored. Finally, we use methods from nonlinear time series analysis to reconstruct a low dimensional chaotic attractor of the model, and estimate its fractal dimension. This provides a lower bound, for the fractal dimension of the attractor, of the spatially explicit model. © 2014 Elsevier Inc.

Type-2 fuzzy graphical models for pattern recognition

CERN Document Server

Zeng, Jia

2015-01-01

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

Cellular automaton modeling of biological pattern formation characterization, examples, and analysis

CERN Document Server

Deutsch, Andreas

2017-01-01

This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In ...

Spatiotemporal Patterns in a Ratio-Dependent Food Chain Model with Reaction-Diffusion

Directory of Open Access Journals (Sweden)

Lei Zhang

2014-01-01

Full Text Available Predator-prey models describe biological phenomena of pursuit-evasion interaction. And this interaction exists widely in the world for the necessary energy supplement of species. In this paper, we have investigated a ratio-dependent spatially extended food chain model. Based on the bifurcation analysis (Hopf and Turing, we give the spatial pattern formation via numerical simulation, that is, the evolution process of the system near the coexistence equilibrium point (u2*,v2*,w2*, and find that the model dynamics exhibits complex pattern replication. For fixed parameters, on increasing the control parameter c1, the sequence “holes → holes-stripe mixtures → stripes → spots-stripe mixtures → spots” pattern is observed. And in the case of pure Hopf instability, the model exhibits chaotic wave pattern replication. Furthermore, we consider the pattern formation in the case of which the top predator is extinct, that is, the evolution process of the system near the equilibrium point (u1*,v1*,0, and find that the model dynamics exhibits stripes-spots pattern replication. Our results show that reaction-diffusion model is an appropriate tool for investigating fundamental mechanism of complex spatiotemporal dynamics. It will be useful for studying the dynamic complexity of ecosystems.

Gait pattern recognition in cerebral palsy patients using neural network modelling

International Nuclear Information System (INIS)

Muhammad, J.; Gibbs, S.; Abboud, R.; Anand, S.

2015-01-01

Interpretation of gait data obtained from modern 3D gait analysis is a challenging and time consuming task. The aim of this study was to create neural network models which can recognise the gait patterns from pre- and post-treatment and the normal ones. Neural network is a method which works on the principle of learning from experience and then uses the obtained knowledge to predict the unknown. Methods: Twenty-eight patients with cerebral palsy were recruited as subjects whose gait was analysed in pre- and post-treatment. A group of twenty-six normal subjects also participated in this study as control group. All subjects gait was analysed using Vicon Nexus to obtain the gait parameters and kinetic and kinematic parameters of hip, knee and ankle joints in three planes of both limbs. The gait data was used as input to create neural network models. A total of approximately 300 trials were split into 70% and 30% to train and test the models, respectively. Different models were built using different parameters. The gait was categorised as three patterns, i.e., normal, pre- and post-treatments. Result: The results showed that the models using all parameters or using the joint angles and moments could predict the gait patterns with approximately 95% accuracy. Some of the models e.g., the models using joint power and moments, had lower rate in recognition of gait patterns with approximately 70-90% successful ratio. Conclusion: Neural network model can be used in clinical practice to recognise the gait pattern for cerebral palsy patients. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Boonthanome, Nouanesengsy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patchett, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States); Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bauer, Andy [Kitware Inc., Clifton Park, NY (United States); Chaudhary, Aashish [Kitware Inc., Clifton Park, NY (United States); Miller, Ross G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

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 file 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.

Simulating discrete models of pattern formation by ion beam sputtering

International Nuclear Information System (INIS)

Hartmann, Alexander K; Kree, Reiner; Yasseri, Taha

2009-01-01

A class of simple, (2+1)-dimensional, discrete models is reviewed, which allow us to study the evolution of surface patterns on solid substrates during ion beam sputtering (IBS). The models are based on the same assumptions about the erosion process as the existing continuum theories. Several distinct physical mechanisms of surface diffusion are added, which allow us to study the interplay of erosion-driven and diffusion-driven pattern formation. We present results from our own work on evolution scenarios of ripple patterns, especially for longer timescales, where nonlinear effects become important. Furthermore we review kinetic phase diagrams, both with and without sample rotation, which depict the systematic dependence of surface patterns on the shape of energy depositing collision cascades after ion impact. Finally, we discuss some results from more recent work on surface diffusion with Ehrlich-Schwoebel barriers as the driving force for pattern formation during IBS and on Monte Carlo simulations of IBS with codeposition of surfactant atoms.

From lag synchronization to pattern formation in one-dimensional open flow models

International Nuclear Information System (INIS)

Liu Zengrong; Luo Jigui

2006-01-01

In this paper, the relation between synchronization and pattern formation in one-dimensional discrete and continuous open flow models is investigated in detail. Firstly a sufficient condition for globally asymptotical stability of lag/anticipating synchronization among lattices of these models is proved by analytic method. Then, by analyzing and simulating lag/anticipating synchronization in discrete case, three kinds of pattern of wave (it is called wave pattern) travelling in the lattices are discovered. Finally, a proper definition for these kinds of pattern is proposed

Long-time integration methods for mesoscopic models of pattern-forming systems

International Nuclear Information System (INIS)

Abukhdeir, Nasser Mohieddin; Vlachos, Dionisios G.; Katsoulakis, Markos; Plexousakis, Michael

2011-01-01

Spectral methods for simulation of a mesoscopic diffusion model of surface pattern formation are evaluated for long simulation times. Backwards-differencing time-integration, coupled with an underlying Newton-Krylov nonlinear solver (SUNDIALS-CVODE), is found to substantially accelerate simulations, without the typical requirement of preconditioning. Quasi-equilibrium simulations of patterned phases predicted by the model are shown to agree well with linear stability analysis. Simulation results of the effect of repulsive particle-particle interactions on pattern relaxation time and short/long-range order are discussed.

Simulating pattern-process relationships to validate landscape genetic models

Science.gov (United States)

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...

An Evaluation of ADLs on Modeling Patterns for Software Architecture

NARCIS (Netherlands)

Waqas Kamal, Ahmad; Avgeriou, Paris

2007-01-01

Architecture patterns provide solutions to recurring design problems at the architecture level. In order to model patterns during software architecture design, one may use a number of existing Architecture Description Languages (ADLs), including the UML, a generic language but also a de facto

Pattern-based approach for logical traffic isolation forensic modelling

CSIR Research Space (South Africa)

Dlamini, I

2009-08-01

Full Text Available reusability and flexibility of the LTI model. This model is viewed as a three-tier architecture, which for experimental purposes is composed of the following components: traffic generator, DiffServ network and the sink server. The Mediator pattern is used...

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

Science.gov (United States)

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.

General Business Model Patterns for Local Energy Management Concepts

International Nuclear Information System (INIS)

Facchinetti, Emanuele; Sulzer, Sabine

2016-01-01

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

General Business Model Patterns for Local Energy Management Concepts

Energy Technology Data Exchange (ETDEWEB)

Facchinetti, Emanuele, E-mail: emanuele.facchinetti@hslu.ch; Sulzer, Sabine [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland)

2016-03-03

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

Analyzing Unsaturated Flow Patterns in Fractured Rock Using an Integrated Modeling Approach

International Nuclear Information System (INIS)

Y.S. Wu; G. Lu; K. Zhang; L. Pan; G.S. Bodvarsson

2006-01-01

Characterizing percolation patterns in unsaturated fractured rock has posed a greater challenge to modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media and the great number of variables impacting unsaturated flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. It takes into account the coupled processes of fluid and heat flow and chemical isotopic transport in Yucca Mountain's highly heterogeneous, unsaturated fractured tuffs. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptualizations and their results of flow patterns in the unsaturated zone. In particular, this model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain's flow system is demonstrated to provide a practical modeling tool for characterizing flow and transport processes in complex subsurface systems

Mapping vegetation patterns in arable land using the models STICS and DAISY

Science.gov (United States)

Heuer, Antje; Casper, Markus

2010-05-01

Several statistical methods exist to detect spatial and / or temporal variability with regard to ecological data-analysis: Semivariance-analysis, Trend surface analysis, Kriging, Voronoi polygons, Moran's I and Mantel-test, to mention just some of them. In this contribution, we concentrate on spatial vegetation patterns within the soil-vegetation-atmosphere (SVAT) system. Using variography, spatial analysis with a geographic information system and self-organizing maps, spatial patterns of yield have been isolated in an agro-ecosystem (see poster contribution EGU 2009, EGU2009-8948). Data were derived from two agricultural plots, each about 5 hectare, in the area of Newel, located in Western Palatinate, Germany. The plots have been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. The aim of the present study is to find out if the existing natural spatial patterns can be mapped by means of SVAT models. If so, the discretization of a landscape according to its spatial patterns could be the basis for parameterization of SVAT models in order to model soil-vegetation-atmosphere interaction over a large area, that is for up-scaling. For this purpose the SVAT models STICS (developed by INRA, France) and DAISY (developed at Tåstrup University, Denmark) are applied. After a wide sensitivity analysis both models are parameterized with field data according to the given situation of each of the detected spatial patterns. The results of the simulation per representative location of a pattern are validated first with field data concerning yield, soil water content and soil nitrogen; besides, above ground dry matter, root depth and specific stress indices are used for validation. The conclusions that can be made with regard to up-scaling are discussed in detail. In a second step the results of the STICS model are compared with those of the DAISY model to analyse the models' behaviour, to get further knowledge about the inner structure

Testing a Conceptual Model of Working through Self-Defeating Patterns

Science.gov (United States)

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…

A stochastic differential equation model of diurnal cortisol patterns

Science.gov (United States)

Brown, E. N.; Meehan, P. M.; Dempster, A. P.

2001-01-01

Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.

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

Science.gov (United States)

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

A Pattern-Oriented Approach to a Methodical Evaluation of Modeling Methods

Directory of Open Access Journals (Sweden)

Michael Amberg

1996-11-01

Full Text Available The paper describes a pattern-oriented approach to evaluate modeling methods and to compare various methods with each other from a methodical viewpoint. A specific set of principles (the patterns is defined by investigating the notations and the documentation of comparable modeling methods. Each principle helps to examine some parts of the methods from a specific point of view. All principles together lead to an overall picture of the method under examination. First the core ("method neutral" meaning of each principle is described. Then the methods are examined regarding the principle. Afterwards the method specific interpretations are compared with each other and with the core meaning of the principle. By this procedure, the strengths and weaknesses of modeling methods regarding methodical aspects are identified. The principles are described uniformly using a principle description template according to descriptions of object oriented design patterns. The approach is demonstrated by evaluating a business process modeling method.

Specimen-specific modeling of hip fracture pattern and repair.

Science.gov (United States)

Ali, Azhar A; Cristofolini, Luca; Schileo, Enrico; Hu, Haixiang; Taddei, Fulvia; Kim, Raymond H; Rullkoetter, Paul J; Laz, Peter J

2014-01-22

Hip fracture remains a major health problem for the elderly. Clinical studies have assessed fracture risk based on bone quality in the aging population and cadaveric testing has quantified bone strength and fracture loads. Prior modeling has primarily focused on quantifying the strain distribution in bone as an indicator of fracture risk. Recent advances in the extended finite element method (XFEM) enable prediction of the initiation and propagation of cracks without requiring a priori knowledge of the crack path. Accordingly, the objectives of this study were to predict femoral fracture in specimen-specific models using the XFEM approach, to perform one-to-one comparisons of predicted and in vitro fracture patterns, and to develop a framework to assess the mechanics and load transfer in the fractured femur when it is repaired with an osteosynthesis implant. Five specimen-specific femur models were developed from in vitro experiments under a simulated stance loading condition. Predicted fracture patterns closely matched the in vitro patterns; however, predictions of fracture load differed by approximately 50% due to sensitivity to local material properties. Specimen-specific intertrochanteric fractures were induced by subjecting the femur models to a sideways fall and repaired with a contemporary implant. Under a post-surgical stance loading, model-predicted load sharing between the implant and bone across the fracture surface varied from 59%:41% to 89%:11%, underscoring the importance of considering anatomic and fracture variability in the evaluation of implants. XFEM modeling shows potential as a macro-level analysis enabling fracture investigations of clinical cohorts, including at-risk groups, and the design of robust implants. © 2013 Published by Elsevier Ltd.

Understanding Activation Patterns in Shared Circuits: Toward a Value Driven Model

Directory of Open Access Journals (Sweden)

Lisa Aziz-Zadeh

2018-05-01

Full Text Available Over the past decade many studies indicate that we utilize our own motor system to understand the actions of other people. This mirror neuron system (MNS has been proposed to be involved in social cognition and motor learning. However, conflicting findings regarding the underlying mechanisms that drive these shared circuits make it difficult to decipher a common model of their function. Here we propose adapting a “value-driven” model to explain discrepancies in the human mirror system literature and to incorporate this model with existing models. We will use this model to explain discrepant activation patterns in multiple shared circuits in the human data, such that a unified model may explain reported activation patterns from previous studies as a function of value.

Image decomposition model Shearlet-Hilbert-L2 with better performance for denoising in ESPI fringe patterns.

Science.gov (United States)

Xu, Wenjun; Tang, Chen; Su, Yonggang; Li, Biyuan; Lei, Zhenkun

2018-02-01

In this paper, we propose an image decomposition model Shearlet-Hilbert-L 2 with better performance for denoising in electronic speckle pattern interferometry (ESPI) fringe patterns. In our model, the low-density fringes, high-density fringes, and noise are, respectively, described by shearlet smoothness spaces, adaptive Hilbert space, and L 2 space and processed individually. Because the shearlet transform has superior directional sensitivity, our proposed Shearlet-Hilbert-L 2 model achieves commendable filtering results for various types of ESPI fringe patterns, including uniform density fringe patterns, moderately variable density fringe patterns, and greatly variable density fringe patterns. We evaluate the performance of our proposed Shearlet-Hilbert-L 2 model via application to two computer-simulated and nine experimentally obtained ESPI fringe patterns with various densities and poor quality. Furthermore, we compare our proposed model with windowed Fourier filtering and coherence-enhancing diffusion, both of which are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. We also compare our proposed model with the previous image decomposition model BL-Hilbert-L 2 .

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

Science.gov (United States)

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.

A TESSELLATION MODEL FOR CRACK PATTERNS ON SURFACES

Directory of Open Access Journals (Sweden)

Werner Nagel

2011-05-01

Full Text Available This paper presents a model of random tessellations that reflect several features of crack pattern. There are already several theoretical results derivedwhich indicate that thismodel can be an appropriate referencemodel. Some potential applications are presented in a tentative statistical study.

Comparative diversity and composition of nitrogen-fixing ...

African Journals Online (AJOL)

Three contrasting land use systems: reserve forests, rice fields and coal fields located at Upper Assam region of North East India were explored for documenting diversity and species composition of N2-fixing cyanobacteria. Altogether 24 taxa (16 heterocystous and 8 non-heterocystous) belonging to nine different genera ...

Simple models for studying complex spatiotemporal patterns of animal behavior

Science.gov (United States)

Tyutyunov, Yuri V.; Titova, Lyudmila I.

2017-06-01

Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

Computational design of patterned interfaces using reduced order models

International Nuclear Information System (INIS)

Vattre, A.J.; Abdolrahim, N.; Kolluri, K.; Demkowicz, M.J.

2014-01-01

Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit dislocation patterns by tailoring interface crystallography and composition. Our approach relies on a novel method for predicting the internal structure of interfaces: rather than obtaining it from resource-intensive atomistic simulations, we compute it using an efficient reduced order model based on anisotropic elasticity theory. Moreover, our strategy incorporates interface synthesis as a constraint on the design process. As an illustration, we apply our approach to the design of interfaces with rapid, 1-D point defect diffusion. Patterned interfaces may be integrated into the microstructure of composite materials, markedly improving performance. (authors)

Modelling Global Pattern Formations for Collaborative Learning Environments

DEFF Research Database (Denmark)

Grappiolo, Corrado; Cheong, Yun-Gyung; Khaled, Rilla

2012-01-01

We present our research towards the design of a computational framework capable of modelling the formation and evolution of global patterns (i.e. group structures) in a population of social individuals. The framework is intended to be used in collaborative environments, e.g. social serious games...

Modeling patterns of hot water use in households

Energy Technology Data Exchange (ETDEWEB)

Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

1996-01-01

This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

Patterns of glycogen turnover in liver characterized by computer modeling

International Nuclear Information System (INIS)

Youn, J.H.; Bergman, R.N.

1987-01-01

The authors used a computer model of liver glycogen turnover to reexamine the data of Devos and Hers, who reported the time course of accumulation in and loss from glycogen of label originating in [1- 14 C]galactose injected at different times after the start of refeeding of 40-h fasted mice or rats. In the present study computer representation of individual glycogen molecules was utilized to account for growth and degradation of glycogen according to specific hypothetical patterns. Using this model they could predict the accumulation and localization within glycogen of labeled glucose residues and compare the predictions with the previously published data. They considered three specific hypotheses of glycogen accumulation during refeeding: (1) simultaneous, (2) sequential, and (3) accelerating growth. Hypothetical patterns of glycogen degradation were (1) ordered and (2) random degradation. The pattern of glycogen synthesis consistent with experimental data was a steadily increasing number of growing glycogen molecules, whereas during degradation glycogen molecules are exposed to degrading enzymes randomly, rather than in a specific reverse order of synthesis. These patterns predict the existence of a specific mechanism for the steadily increasing seeding of new glycogen molecules during synthesis

Patterns of flavor signals in supersymmetric models

Energy Technology Data Exchange (ETDEWEB)

Goto, T. [KEK National High Energy Physics, Tsukuba (Japan)]|[Kyoto Univ. (Japan). YITP; Okada, Y. [KEK National High Energy Physics, Tsukuba (Japan)]|[Graduate Univ. for Advanced Studies, Tsukuba (Japan). Dept. of Particle and Nucelar Physics; Shindou, T. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[International School for Advanced Studies, Trieste (Italy); Tanaka, M. [Osaka Univ., Toyonaka (Japan). Dept. of Physics

2007-11-15

Quark and lepton flavor signals are studied in four supersymmetric models, namely the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b{yields}s(d) transition observables in B{sub d} and B{sub s} decays, taking the constraint from the B{sub s}- anti B{sub s} mixing recently observed at Tevatron into account. We also calculate lepton flavor violating processes {mu} {yields} e{gamma}, {tau} {yields} {mu}{gamma} and {tau} {yields} e{gamma} for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb and a future Super B Factory. (orig.)

Patterns of flavor signals in supersymmetric models

International Nuclear Information System (INIS)

Goto, T.; Tanaka, M.

2007-11-01

Quark and lepton flavor signals are studied in four supersymmetric models, namely the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b→s(d) transition observables in B d and B s decays, taking the constraint from the B s - anti B s mixing recently observed at Tevatron into account. We also calculate lepton flavor violating processes μ → eγ, τ → μγ and τ → eγ for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb and a future Super B Factory. (orig.)

An expanded Notch-Delta model exhibiting long-range patterning and incorporating MicroRNA regulation.

Directory of Open Access Journals (Sweden)

Jerry S Chen

2014-06-01

Full Text Available Notch-Delta signaling is a fundamental cell-cell communication mechanism that governs the differentiation of many cell types. Most existing mathematical models of Notch-Delta signaling are based on a feedback loop between Notch and Delta leading to lateral inhibition of neighboring cells. These models result in a checkerboard spatial pattern whereby adjacent cells express opposing levels of Notch and Delta, leading to alternate cell fates. However, a growing body of biological evidence suggests that Notch-Delta signaling produces other patterns that are not checkerboard, and therefore a new model is needed. Here, we present an expanded Notch-Delta model that builds upon previous models, adding a local Notch activity gradient, which affects long-range patterning, and the activity of a regulatory microRNA. This model is motivated by our experiments in the ascidian Ciona intestinalis showing that the peripheral sensory neurons, whose specification is in part regulated by the coordinate activity of Notch-Delta signaling and the microRNA miR-124, exhibit a sparse spatial pattern whereby consecutive neurons may be spaced over a dozen cells apart. We perform rigorous stability and bifurcation analyses, and demonstrate that our model is able to accurately explain and reproduce the neuronal pattern in Ciona. Using Monte Carlo simulations of our model along with miR-124 transgene over-expression assays, we demonstrate that the activity of miR-124 can be incorporated into the Notch decay rate parameter of our model. Finally, we motivate the general applicability of our model to Notch-Delta signaling in other animals by providing evidence that microRNAs regulate Notch-Delta signaling in analogous cell types in other organisms, and by discussing evidence in other organisms of sparse spatial patterns in tissues where Notch-Delta signaling is active.

A simplified memory network model based on pattern formations

Science.gov (United States)

Xu, Kesheng; Zhang, Xiyun; Wang, Chaoqing; Liu, Zonghua

2014-12-01

Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.

Model Building – A Circular Approach to Evaluate Multidimensional Patterns and Operationalized Procedures

Directory of Open Access Journals (Sweden)

Franz HAAS

2017-12-01

Full Text Available Managers operate in highly different fields. Decision-making can be based on models reflecting in part these differences. The challenge is to connect the respective models without too great a disruption. A threefold procedural approach is proposed by chaining a scheme of modeling in a complex field to an operationalized model to statistical multivariate methods. Multivariate pattern-detecting methods offer the chance to evaluate patterns within the complex field partly. This step completes the cycle of research and improved models can be used in a further cycle.

Modeling patterns of hot water use in households

Energy Technology Data Exchange (ETDEWEB)

Lutz, J.D.; Liu, Xiaomin; McMahon, J.E. [and others

1996-11-01

This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

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

Science.gov (United States)

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.

Mathematical modeling of high-rate Anammox UASB reactor based on granular packing patterns

International Nuclear Information System (INIS)

Tang, Chong-Jian; He, Rui; Zheng, Ping; Chai, Li-Yuan; Min, Xiao-Bo

2013-01-01

Highlights: ► A novel model was conducted to estimate volumetric nitrogen conversion rates. ► The packing patterns of the granules in Anammox reactor are investigated. ► The simple cubic packing pattern was simulated in high-rate Anammox UASB reactor. ► Operational strategies concerning sludge concentration were proposed by the modeling. -- Abstract: A novel mathematical model was developed to estimate the volumetric nitrogen conversion rates of a high-rate Anammox UASB reactor based on the packing patterns of granular sludge. A series of relationships among granular packing density, sludge concentration, hydraulic retention time and volumetric conversion rate were constructed to correlate Anammox reactor performance with granular packing patterns. It was suggested that the Anammox granules packed as the equivalent simple cubic pattern in high-rate UASB reactor with packing density of 50–55%, which not only accommodated a high concentration of sludge inside the reactor, but also provided large pore volume, thus prolonging the actual substrate conversion time. Results also indicated that it was necessary to improve Anammox reactor performance by enhancing substrate loading when sludge concentration was higher than 37.8 gVSS/L. The established model was carefully calibrated and verified, and it well simulated the performance of granule-based high-rate Anammox UASB reactor

Mathematical modeling of high-rate Anammox UASB reactor based on granular packing patterns

Energy Technology Data Exchange (ETDEWEB)

Tang, Chong-Jian, E-mail: chjtangzju@yahoo.com.cn [Department of Environmental Engineering, School of Metallurgical Science and Engineering, Central South University, Changsha 410083 (China); National Engineering Research Center for Control and Treatment of Heavy Metal Pollution, Changsha 410083 (China); He, Rui; Zheng, Ping [Department of Environmental Engineering, Zhejiang University, Zijingang Campus, Hangzhou 310058 (China); Chai, Li-Yuan; Min, Xiao-Bo [Department of Environmental Engineering, School of Metallurgical Science and Engineering, Central South University, Changsha 410083 (China); National Engineering Research Center for Control and Treatment of Heavy Metal Pollution, Changsha 410083 (China)

2013-04-15

Highlights: ► A novel model was conducted to estimate volumetric nitrogen conversion rates. ► The packing patterns of the granules in Anammox reactor are investigated. ► The simple cubic packing pattern was simulated in high-rate Anammox UASB reactor. ► Operational strategies concerning sludge concentration were proposed by the modeling. -- Abstract: A novel mathematical model was developed to estimate the volumetric nitrogen conversion rates of a high-rate Anammox UASB reactor based on the packing patterns of granular sludge. A series of relationships among granular packing density, sludge concentration, hydraulic retention time and volumetric conversion rate were constructed to correlate Anammox reactor performance with granular packing patterns. It was suggested that the Anammox granules packed as the equivalent simple cubic pattern in high-rate UASB reactor with packing density of 50–55%, which not only accommodated a high concentration of sludge inside the reactor, but also provided large pore volume, thus prolonging the actual substrate conversion time. Results also indicated that it was necessary to improve Anammox reactor performance by enhancing substrate loading when sludge concentration was higher than 37.8 gVSS/L. The established model was carefully calibrated and verified, and it well simulated the performance of granule-based high-rate Anammox UASB reactor.

Pattern solutions of the Klausmeier Model for banded vegetation in semi-arid environments I

International Nuclear Information System (INIS)

Sherratt, Jonathan A

2010-01-01

In many semi-arid environments, vegetation cover is sparse, and is self-organized into large-scale spatial patterns. In particular, banded vegetation is typical on hillsides. Mathematical modelling is widely used to study these banded patterns, and many models are effectively extensions of a coupled reaction–diffusion–advection system proposed by Klausmeier (1999 Science 284 1826–8). However, there is currently very little mathematical theory on pattern solutions of these equations. This paper is the first in a series whose aim is a comprehensive understanding of these solutions, which can act as a springboard both for future simulation-based studies of the Klausmeier model, and for analysis of model extensions. The author focusses on a particular part of parameter space, and derives expressions for the boundaries of the parameter region in which patterns occur. The calculations are valid to leading order at large values of the 'slope parameter', which reflects a comparison of the rate of water flow downhill with the rate of vegetation dispersal. The form of the corresponding patterns is also studied, and the author shows that the leading order equations change close to one boundary of the parameter region in which there are patterns, leading to a homoclinic solution. Conclusions are drawn on the way in which changes in mean annual rainfall affect pattern properties, including overall biomass productivity

The Holocene sedimentary record of cyanobacterial glycolipids in the Baltic Sea: an evaluation of their application as tracers of past nitrogen fixation

Directory of Open Access Journals (Sweden)

M. Sollai

2017-12-01

Full Text Available Heterocyst glycolipids (HGs are lipids exclusively produced by heterocystous dinitrogen-fixing cyanobacteria. The Baltic Sea is an ideal environment to study the distribution of HGs and test their potential as biomarkers because of its recurring summer phytoplankton blooms, dominated by a few heterocystous cyanobacterial species of the genera Nodularia and Aphanizomenon. A multi-core and a gravity core from the Gotland Basin were analyzed to determine the abundance and distribution of a suite of selected HGs at a high resolution to investigate the changes in past cyanobacterial communities during the Holocene. The HG distribution of the sediments deposited during the Modern Warm Period (MoWP was compared with those of cultivated heterocystous cyanobacteria, including those isolated from Baltic Sea waters, revealing high similarity. However, the abundance of HGs dropped substantially with depth, and this may be caused by either a decrease in the occurrence of the cyanobacterial blooms or diagenesis, resulting in partial destruction of the HGs. The record also shows that the HG distribution has remained stable since the Baltic turned into a brackish semi-enclosed basin ∼ 7200 cal. yr BP. This suggests that the heterocystous cyanobacterial species composition remained relatively stable as well. During the earlier freshwater phase of the Baltic (i.e., the Ancylus Lake and Yoldia Sea phases, the distribution of the HGs varied much more than in the subsequent brackish phase, and the absolute abundance of HGs was much lower than during the brackish phase. This suggests that the cyanobacterial community adjusted to the different environmental conditions in the basin. Our results confirm the potential of HGs as a specific biomarker of heterocystous cyanobacteria in paleo-environmental studies.

An equilibrium-point model of electromyographic patterns during single-joint movements based on experimentally reconstructed control signals.

Science.gov (United States)

Latash, M L; Goodman, S R

1994-01-01

The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns. Copyright © 1994. Published by Elsevier Ltd.

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

Science.gov (United States)

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

SOA Modeling Patterns for Service Oriented Discovery and Analysis

CERN Document Server

Bell, Michael

2010-01-01

Learn the essential tools for developing a sound service-oriented architecture. SOA Modeling Patterns for Service-Oriented Discovery and Analysis introduces a universal, easy-to-use, and nimble SOA modeling language to facilitate the service identification and examination life cycle stage. This business and technological vocabulary will benefit your service development endeavors and foster organizational software asset reuse and consolidation, and reduction of expenditure. Whether you are a developer, business architect, technical architect, modeler, business analyst, team leader, or manager,

Morphogenesis and pattern formation in biological systems experiments and models

CERN Document Server

Noji, Sumihare; Ueno, Naoto; Maini, Philip

2003-01-01

A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

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

Science.gov (United States)

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

A simple model for research interest evolution patterns

Science.gov (United States)

Jia, Tao; Wang, Dashun; Szymanski, Boleslaw

Sir Isaac Newton supposedly remarked that in his scientific career he was like ``...a boy playing on the sea-shore ...finding a smoother pebble or a prettier shell than ordinary''. His remarkable modesty and famous understatement motivate us to seek regularities in how scientists shift their research focus as the career develops. Indeed, despite intensive investigations on how microscopic factors, such as incentives and risks, would influence a scientist's choice of research agenda, little is known on the macroscopic patterns in the research interest change undertaken by individual scientists throughout their careers. Here we make use of over 14,000 authors' publication records in physics. By quantifying statistical characteristics in the interest evolution, we model scientific research as a random walk, which reproduces patterns in individuals' careers observed empirically. Despite myriad of factors that shape and influence individual choices of research subjects, we identified regularities in this dynamical process that are well captured by a simple statistical model. The results advance our understanding of scientists' behaviors during their careers and open up avenues for future studies in the science of science.

Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

Science.gov (United States)

Mendiguren, Gorka; Koch, Julian; Stisen, Simon

2017-11-01

Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

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

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren Gonzalez, Gorka

2018-01-01

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...... 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...

Modeling on bubbly to churn flow pattern transition in narrow rectangular channel

International Nuclear Information System (INIS)

Wang Yanlin; Chen Bingde; Huang Yanping; Wang Junfeng

2012-01-01

A theoretical model based on some reasonable concepts was developed to predict the bubbly flow to churn flow pattern transition in vertical narrow rectangular channel under flow boiling condition. The maximum size of ideal bubble in narrow rectangular channel was calculated based on previous literature. The thermal hydraulics boundary condition of bubbly to churn flow pattern transition was exported from Helmholtz and maximum size of ideal bubble. The theoretical model was validated by existent experimental data. (authors)

Spiking patterns of a hippocampus model in electric fields

International Nuclear Information System (INIS)

Men Cong; Wang Jiang; Qin Ying-Mei; Wei Xi-Le; Deng Bin; Che Yan-Qiu

2011-01-01

We develop a model of CA3 neurons embedded in a resistive array to mimic the effects of electric fields from a new perspective. Effects of DC and sinusoidal electric fields on firing patterns in CA3 neurons are investigated in this study. The firing patterns can be switched from no firing pattern to burst or from burst to fast periodic firing pattern with the increase of DC electric field intensity. It is also found that the firing activities are sensitive to the frequency and amplitude of the sinusoidal electric field. Different phase-locking states and chaotic firing regions are observed in the parameter space of frequency and amplitude. These findings are qualitatively in accordance with the results of relevant experimental and numerical studies. It is implied that the external or endogenous electric field can modulate the neural code in the brain. Furthermore, it is helpful to develop control strategies based on electric fields to control neural diseases such as epilepsy. (interdisciplinary physics and related areas of science and technology)

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms.

Science.gov (United States)

Bandyopadhyay, Promode R; Hellum, Aren M

2014-10-23

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime--laterally coupled, diffusively--which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common.

Turing and Non-Turing patterns in diffusive plankton model

Directory of Open Access Journals (Sweden)

N. K. Thakur

2015-03-01

Full Text Available In this paper, we investigate a Rosenzweig-McAurthur model and its variant for phytoplankton, zooplankton and fish population dynamics with Holling type II and III functional responses. We present the theoretical analysis of processes of pattern formation that involves organism distribution and their interaction of spatially distributed population with local diffusion. The choice of parameter values is important to study the effect of diffusion, also it depends more on the nonlinearity of the system. With the help of numerical simulations, we observe the formation of spatiotemporal patterns both inside and outside the Turing space.

Modeling of metal nanocluster growth on patterned substrates and surface pattern formation under ion bombardment

Energy Technology Data Exchange (ETDEWEB)

Numazawa, Satoshi

2012-11-01

This work addresses the metal nanocluster growth process on prepatterned substrates, the development of atomistic simulation method with respect to an acceleration of the atomistic transition states, and the continuum model of the ion-beam inducing semiconductor surface pattern formation mechanism. Experimentally, highly ordered Ag nanocluster structures have been grown on pre-patterned amorphous SiO{sub 2} surfaces by oblique angle physical vapor deposition at room temperature. Despite the small undulation of the rippled surface, the stripe-like Ag nanoclusters are very pronounced, reproducible and well-separated. The first topic is the investigation of this growth process with a continuum theoretical approach to the surface gas condensation as well as an atomistic cluster growth model. The atomistic simulation model is a lattice-based kinetic Monte-Carlo (KMC) method using a combination of a simplified inter-atomic potential and experimental transition barriers taken from the literature. An effective transition event classification method is introduced which allows a boost factor of several thousand compared to a traditional KMC approach, thus allowing experimental time scales to be modeled. The simulation predicts a low sticking probability for the arriving atoms, millisecond order lifetimes for single Ag monomers and {approx}1 nm square surface migration ranges of Ag monomers. The simulations give excellent reproduction of the experimentally observed nanocluster growth patterns. The second topic specifies the acceleration scheme utilized in the metallic cluster growth model. Concerning the atomistic movements, a classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements

Modeling of metal nanocluster growth on patterned substrates and surface pattern formation under ion bombardment

Energy Technology Data Exchange (ETDEWEB)

Numazawa, Satoshi

2012-11-01

This work addresses the metal nanocluster growth process on prepatterned substrates, the development of atomistic simulation method with respect to an acceleration of the atomistic transition states, and the continuum model of the ion-beam inducing semiconductor surface pattern formation mechanism. Experimentally, highly ordered Ag nanocluster structures have been grown on pre-patterned amorphous SiO{sub 2} surfaces by oblique angle physical vapor deposition at room temperature. Despite the small undulation of the rippled surface, the stripe-like Ag nanoclusters are very pronounced, reproducible and well-separated. The first topic is the investigation of this growth process with a continuum theoretical approach to the surface gas condensation as well as an atomistic cluster growth model. The atomistic simulation model is a lattice-based kinetic Monte-Carlo (KMC) method using a combination of a simplified inter-atomic potential and experimental transition barriers taken from the literature. An effective transition event classification method is introduced which allows a boost factor of several thousand compared to a traditional KMC approach, thus allowing experimental time scales to be modeled. The simulation predicts a low sticking probability for the arriving atoms, millisecond order lifetimes for single Ag monomers and {approx}1 nm square surface migration ranges of Ag monomers. The simulations give excellent reproduction of the experimentally observed nanocluster growth patterns. The second topic specifies the acceleration scheme utilized in the metallic cluster growth model. Concerning the atomistic movements, a classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements

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

Science.gov (United States)

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.

Physical optics modeling of modal patterns in a crossed porro prism resonator

CSIR Research Space (South Africa)

Litvin, IA

2006-07-01

Full Text Available A physical optics model is proposed to describe the transverse modal patterns in crossed Porro prism resonators. The model departs from earlier attempts in that the prisms are modeled as non-classical rotating elements with amplitude and phase...

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

DEFF Research Database (Denmark)

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran

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...... 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....

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

Science.gov (United States)

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

Modelling Behaviour Patterns of Pedestrians for Mobile Robot Trajectory Generation

Directory of Open Access Journals (Sweden)

Yusuke Tamura

2013-08-01

Full Text Available Robots are expected to be operated in environments where they coexist with humans, such as shopping malls and offices. Both the safety and efficiency of a robot are necessary in such environments. To achieve this, pedestrian behaviour should be accurately predicted. However, the behaviour is uncertain and cannot be easily predicted. This paper proposes a probabilistic method of determining pedestrian trajectory based on an estimation of pedestrian behaviour patterns. The proposed method focuses on the specific behaviour of pedestrians around the robot. The proposed model classifies the behaviours of pedestrians into definite patterns. The behaviour patterns, distribution of the positions of the pedestrians, and the direction of each behaviour pattern are determined by learning through observation. The behaviour pattern of a pedestrian can be estimated correctly by a likelihood calculation. A robot decides to move with an emphasis on either safety or efficiency depending on the result of the pattern estimation. If the pedestrian trajectory follows a known behaviour pattern, the robot would move with an emphasis on efficiency because the pedestrian trajectory can be predicted. Otherwise, the robot would move with an emphasis on safety because the behaviour of the pedestrian cannot be predicted. Experimental results show that robots can move efficiently and safely when passing by a pedestrian by applying the proposed method.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

OpenAIRE

Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

Simple model for polar cap convection patterns and generation of theta auroras

International Nuclear Information System (INIS)

Lyons, L.R.

1985-01-01

The simple addition of a uniform interplanetary magnetic field and the Earth's dipole magnetic field is used to evaluate electric field convection patterns over the polar caps that result from solar wind flow across open geomagnetic field lines. This model is found to account for observed polar-cap convection patterns as a function of the interplanetary magnetic field components B/sub y/ and B/sub z/. In particular, the model offers an explanation for sunward and antisunward convection over the polar caps for B/sub z/>0. Observed field-aligned current patterns within the polar cap and observed auroral arcs across the polar cap are also explained by the model. In addition, the model gives several predictions concerning the polar cap that should be testable. Effects of solar wind pressure and magnetospheric currents on magnetospheric electric and magnetic fields are neglected. That observed polar cap features are reproduced suggests that the neglected effects do not modify the large-scale topology of magnetospheric electric and magnetic fields along open polar cap field lines. Of course, the neglected effects significantly modify the magnetic geometry, so that the results of this paper are not quantitatively realistic and many details may be incorrect. Nevertheless, the model provides a simple explanation for many qualitative features of polar cap convection

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

Science.gov (United States)

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.

Use of 13N in studies of fixation of dinitrogen and assimilation of ammonium by cyanobacteria

International Nuclear Information System (INIS)

Meeks, J.C.; Wolk, C.P.; Thomas, J.; Austin, S.M.; Galonsky, A.; Michigan State Univ., East Lansing

1978-01-01

13 N (tsub(1/2)=10min) has been used to identify the initial products of assimilation of N 2 and NH 4 + by intact filaments of a number of cyanobacteria and by heterocysts isolated from Anabaena cylindrica. Ammonium, the amide nitrogen of glutamine, and the α-amino nitrogen of glutamate, in that order, were the first observed products of fixation of [ 13 N]N 2 . Amide-labelled glutamine was the initial product of metabolism of 13 NH 4 + by A. cylindrica grown with either NH 4 + or N 2 as the nitrogen source. Glutamate was the second major product of 13 NH 4 + assimilation. Isolated heterocysts form [ 13 N]glutamine but not [ 13 N]glutamate from [ 13 N]N 2 or 13 NH 4 + . Formation of [ 13 N]glutamine from [ 13 N]N 2 was inhibited by acetylene, indicating metabolic coupling of the activity of glutamine synthetase to that of nitrogenase in these cells. A diffusible substance produced by heterocysts inhibits nearby cells of the same filament from differentiating into heterocysts. Glutamine (or a derivative of glutamine) may be involved in inhibiting differentiation of vegetative cells. (author)

Voronoi Cell Patterns: theoretical model and application to submonolayer growth

Science.gov (United States)

González, Diego Luis; Einstein, T. L.

2012-02-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We apply our model to describe the Voronoi cell patterns of island nucleation for critical island sizes i=0,1,2,3. Experimental results for the Voronoi cells of InAs/GaAs quantum dots are also described by our model.

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

Directory of Open Access Journals (Sweden)

M. C. Demirel

2018-02-01

Full Text Available 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

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

Science.gov (United States)

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 (Ptibial 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.

On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

KAUST Repository

Moreo, P.

2009-11-14

The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

A hydroclimatic model of global fire patterns

Science.gov (United States)

Boer, Matthias

2015-04-01

Satellite-based earth observation is providing an increasingly accurate picture of global fire patterns. The highest fire activity is observed in seasonally dry (sub-)tropical environments of South America, Africa and Australia, but fires occur with varying frequency, intensity and seasonality in almost all biomes on Earth. The particular combination of these fire characteristics, or fire regime, is known to emerge from the combined influences of climate, vegetation, terrain and land use, but has so far proven difficult to reproduce by global models. Uncertainty about the biophysical drivers and constraints that underlie current global fire patterns is propagated in model predictions of how ecosystems, fire regimes and biogeochemical cycles may respond to projected future climates. Here, I present a hydroclimatic model of global fire patterns that predicts the mean annual burned area fraction (F) of 0.25° x 0.25° grid cells as a function of the climatic water balance. Following Bradstock's four-switch model, long-term fire activity levels were assumed to be controlled by fuel productivity rates and the likelihood that the extant fuel is dry enough to burn. The frequency of ignitions and favourable fire weather were assumed to be non-limiting at long time scales. Fundamentally, fuel productivity and fuel dryness are a function of the local water and energy budgets available for the production and desiccation of plant biomass. The climatic water balance summarizes the simultaneous availability of biologically usable energy and water at a site, and may therefore be expected to explain a significant proportion of global variation in F. To capture the effect of the climatic water balance on fire activity I focused on the upper quantiles of F, i.e. the maximum level of fire activity for a given climatic water balance. Analysing GFED4 data for annual burned area together with gridded climate data, I found that nearly 80% of the global variation in the 0.99 quantile of F

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

A collision avoidance model for two-pedestrian groups: Considering random avoidance patterns

Science.gov (United States)

Zhou, Zhuping; Cai, Yifei; Ke, Ruimin; Yang, Jiwei

2017-06-01

Grouping is a common phenomenon in pedestrian crowds and group modeling is still an open challenging problem. When grouping pedestrians avoid each other, different patterns can be observed. Pedestrians can keep close with group members and avoid other groups in cluster. Also, they can avoid other groups separately. Considering this randomness in avoidance patterns, we propose a collision avoidance model for two-pedestrian groups. In our model, the avoidance model is proposed based on velocity obstacle method at first. Then grouping model is established using Distance constrained line (DCL), by transforming DCL into the framework of velocity obstacle, the avoidance model and grouping model are successfully put into one unified calculation structure. Within this structure, an algorithm is developed to solve the problem when solutions of the two models conflict with each other. Two groups of bidirectional pedestrian experiments are designed to verify the model. The accuracy of avoidance behavior and grouping behavior is validated in the microscopic level, while the lane formation phenomenon and fundamental diagrams is validated in the macroscopic level. The experiments results show our model is convincing and has a good expansibility to describe three or more pedestrian groups.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

DEFF Research Database (Denmark)

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran

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...... 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....... 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...

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

Science.gov (United States)

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.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

Directory of Open Access Journals (Sweden)

Andrea Cuttone

Full Text Available 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.

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

Science.gov (United States)

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.

Latent Feature Models for Uncovering Human Mobility Patterns from Anonymized User Location Traces with Metadata

KAUST Repository

Alharbi, Basma Mohammed

2017-04-10

In the mobile era, data capturing individuals’ locations have become unprecedentedly available. Data from Location-Based Social Networks is one example of large-scale user-location data. Such data provide a valuable source for understanding patterns governing human mobility, and thus enable a wide range of research. However, mining and utilizing raw user-location data is a challenging task. This is mainly due to the sparsity of data (at the user level), the imbalance of data with power-law users and locations check-ins degree (at the global level), and more importantly the lack of a uniform low-dimensional feature space describing users. Three latent feature models are proposed in this dissertation. Each proposed model takes as an input a collection of user-location check-ins, and outputs a new representation space for users and locations respectively. To avoid invading users privacy, the proposed models are designed to learn from anonymized location data where only IDs - not geophysical positioning or category - of locations are utilized. To enrich the inferred mobility patterns, the proposed models incorporate metadata, often associated with user-location data, into the inference process. In this dissertation, two types of metadata are utilized to enrich the inferred patterns, timestamps and social ties. Time adds context to the inferred patterns, while social ties amplifies incomplete user-location check-ins. The first proposed model incorporates timestamps by learning from collections of users’ locations sharing the same discretized time. The second proposed model also incorporates time into the learning model, yet takes a further step by considering time at different scales (hour of a day, day of a week, month, and so on). This change in modeling time allows for capturing meaningful patterns over different times scales. The last proposed model incorporates social ties into the learning process to compensate for inactive users who contribute a large volume

Modelling and predicting biogeographical patterns in river networks

Directory of Open Access Journals (Sweden)

Sabela Lois

2016-04-01

Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

3D physical modeling for patterning process development

Science.gov (United States)

Sarma, Chandra; Abdo, Amr; Bailey, Todd; Conley, Will; Dunn, Derren; Marokkey, Sajan; Talbi, Mohamed

2010-03-01

In this paper we will demonstrate how a 3D physical patterning model can act as a forensic tool for OPC and ground-rule development. We discuss examples where the 2D modeling shows no issues in printing gate lines but 3D modeling shows severe resist loss in the middle. In absence of corrective measure, there is a high likelihood of line discontinuity post etch. Such early insight into process limitations of prospective ground rules can be invaluable for early technology development. We will also demonstrate how the root cause of broken poly-line after etch could be traced to resist necking in the region of STI step with the help of 3D models. We discuss different cases of metal and contact layouts where 3D modeling gives an early insight in to technology limitations. In addition such a 3D physical model could be used for early resist evaluation and selection for required ground-rule challenges, which can substantially reduce the cycle time for process development.

Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.

Science.gov (United States)

Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H

2014-12-30

For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. Copyright © 2014 John Wiley & Sons

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

Science.gov (United States)

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.

Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

Science.gov (United States)

Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

2017-09-01

We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern

Directory of Open Access Journals (Sweden)

Sylvia Jane Annatje Sumarauw

2007-06-01

Full Text Available Abstract Capital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern. Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition

Post-Hoc Pattern-Oriented Testing and Tuning of an Existing Large Model: Lessons from the Field Vole

DEFF Research Database (Denmark)

Topping, Christopher John; Dalkvist, Trine; Grimm, Volker

2012-01-01

Pattern-oriented modeling (POM) is a general strategy for modeling complex systems. In POM, multiple patterns observed at different scales and hierarchical levels are used to optimize model structure, to test and select sub-models of key processes, and for calibration. So far, POM has been used f...

Onset patterns in a simple model of localized parametric forcing.

Science.gov (United States)

Porter, J; Tinao, I; Laverón-Simavilla, A; Rodríguez, J

2013-10-01

We investigate pattern selection at onset in a parametrically and inhomogeneously forced partial differential equation obtained by generalizing Mathieu's equation to include spatial interactions. No separation of scales is assumed. The proposed model is directly relevant to the case of parametrically forced surface waves, such as cross-waves, excited by the horizontal vibration of a fluid, where the forcing is localized to a finite region near the endwall or wavemaker. The availability of analytical solutions in the limit of piecewise constant forcing allows us investigate in detail the dependence of selected eigenfunctions on spatial detuning, forcing width, damping, boundary conditions, and container size. A wide range of onset patterns are located and described, many of which are rotated, modulated, or both, and deviate far from simple crosswise oriented standing waves. The linear selection mechanisms governing this multiplicity of potential onset patterns are discussed.

Simulated small-angle scattering patterns for a plastically deformed model composite material

NARCIS (Netherlands)

Shenoy, V.B.; Cleveringa, H.H.M.; Phillips, R.; Giessen, E. van der; Needleman, A.

2000-01-01

The small-angle scattering patterns predicted by discrete dislocation plasticity versus local and non-local continuum plasticity theory are compared in a model problem. The problem considered is a two-dimensional model composite with elastic reinforcements in a crystalline matrix subject to

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

Science.gov (United States)

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.

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

Science.gov (United States)

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…

Simulation of organ patterning on the floral meristem using a polar auxin transport model.

Directory of Open Access Journals (Sweden)

Simon van Mourik

Full Text Available An intriguing phenomenon in plant development is the timing and positioning of lateral organ initiation, which is a fundamental aspect of plant architecture. Although important progress has been made in elucidating the role of auxin transport in the vegetative shoot to explain the phyllotaxis of leaf formation in a spiral fashion, a model study of the role of auxin transport in whorled organ patterning in the expanding floral meristem is not available yet. We present an initial simulation approach to study the mechanisms that are expected to play an important role. Starting point is a confocal imaging study of Arabidopsis floral meristems at consecutive time points during flower development. These images reveal auxin accumulation patterns at the positions of the organs, which strongly suggests that the role of auxin in the floral meristem is similar to the role it plays in the shoot apical meristem. This is the basis for a simulation study of auxin transport through a growing floral meristem, which may answer the question whether auxin transport can in itself be responsible for the typical whorled floral pattern. We combined a cellular growth model for the meristem with a polar auxin transport model. The model predicts that sepals are initiated by auxin maxima arising early during meristem outgrowth. These form a pre-pattern relative to which a series of smaller auxin maxima are positioned, which partially overlap with the anlagen of petals, stamens, and carpels. We adjusted the model parameters corresponding to properties of floral mutants and found that the model predictions agree with the observed mutant patterns. The predicted timing of the primordia outgrowth and the timing and positioning of the sepal primordia show remarkable similarities with a developing flower in nature.

Model uncertainties do not affect observed patterns of species richness in the Amazon

Science.gov (United States)

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo

2017-01-01

Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of

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

Science.gov (United States)

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.

A hidden Markov model approach to neuron firing patterns.

Science.gov (United States)

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-11-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.

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

Science.gov (United States)

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.

CHARACTERISTIC FEATURES OF MUELLER MATRIX PATTERNS FOR POLARIZATION SCATTERING MODEL OF BIOLOGICAL TISSUES

Directory of Open Access Journals (Sweden)

E DU

2014-01-01

Full Text Available We developed a model to describe polarized photon scattering in biological tissues. In this model, tissues are simplified to a mixture of scatterers and surrounding medium. There are two types of scatterers in the model: solid spheres and infinitely long solid cylinders. Variables related to the scatterers include: the densities and sizes of the spheres and cylinders, the orientation and angular distribution of cylinders. Variables related to the surrounding medium include: the refractive index, absorption coefficient and birefringence. In this paper, as a development we introduce an optical activity effect to the model. By comparing experiments and Monte Carlo simulations, we analyze the backscattering Mueller matrix patterns of several tissue-like media, and summarize the different effects coming from anisotropic scattering and optical properties. In addition, we propose a possible method to extract the optical activity values for tissues. Both the experimental and simulated results show that, by analyzing the Mueller matrix patterns, the microstructure and optical properties of the medium can be obtained. The characteristic features of Mueller matrix patterns are potentially powerful tools for studying the contrast mechanisms of polarization imaging for medical diagnosis.

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

Science.gov (United States)

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

2004-01-01

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 colocalize 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

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

Energy Technology Data Exchange (ETDEWEB)

Li, Ben; He, Feng; Ouyang, Jiting, E-mail: jtouyang@bit.edu.cn [School of Physics, Beijing Institute of Technology, Beijing 100081 (China); Duan, Xiaoxi [Research Center of Laser Fusion, CAEP, Mianyang 621900 (China)

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, 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.

Is the distribution of nitrogen-fixing cyanobacteria in the oceans related to temperature?

Science.gov (United States)

Stal, Lucas J

2009-07-01

Approximately 50% of the global natural fixation of nitrogen occurs in the oceans supporting a considerable part of the new primary production. Virtually all nitrogen fixation in the ocean occurs in the tropics and subtropics where the surface water temperature is 25°C or higher. It is attributed almost exclusively to cyanobacteria. This is remarkable firstly because diazotrophic cyanobacteria are found in other environments irrespective of temperature and secondly because primary production in temperate and cold oceans is generally limited by nitrogen. Cyanobacteria are oxygenic phototrophic organisms that evolved a variety of strategies protecting nitrogenase from oxygen inactivation. Free-living diazotrophic cyanobacteria in the ocean are of the non-heterocystous type, namely the filamentous Trichodesmium and the unicellular groups A-C. I will argue that warm water is a prerequisite for these diazotrophic organisms because of the low-oxygen solubility and high rates of respiration allowing the organism to maintain anoxic conditions in the nitrogen-fixing cell. Heterocystous cyanobacteria are abundant in freshwater and brackish environments in all climatic zones. The heterocyst cell envelope is a tuneable gas diffusion barrier that optimizes the influx of both oxygen and nitrogen, while maintaining anoxic conditions inside the cell. It is not known why heterocystous cyanobacteria are absent from the temperate and cold oceans and seas.

Visualization of channels connecting cells in filamentous nitrogen-fixing cyanobacteria.

Science.gov (United States)

Omairi-Nasser, Amin; Haselkorn, Robert; Austin, Jotham

2014-07-01

Cyanobacteria, formerly called blue-green algae, are abundant bacteria that carry out green plant photosynthesis, fixing CO2 and generating O2. Many species can also fix N2 when reduced nitrogen sources are scarce. Many studies imply the existence of intracellular communicating channels in filamentous cyanobacteria, in particular, the nitrogen-fixing species. In a species such as Anabaena, growth in nitrogen-depleted medium, in which ∼10% of the cells differentiate into anaerobic factories for nitrogen fixation (heterocysts), requires the transport of amino acids from heterocysts to vegetative cells, and reciprocally, the transport of sugar from vegetative cells to heterocysts. Convincing physical evidence for such channels has been slim. Using improved preservation of structure by high-pressure rapid freezing of samples for electron microscopy, coupled with high-resolution 3D tomography, it has been possible to visualize and measure the dimensions of channels that breach the peptidoglycan between vegetative cells and between heterocysts and vegetative cells. The channels appear to be straight tubes, 21 nm long and 14 nm in diameter for the latter and 12 nm long and 12 nm in diameter for the former.-Omairi-Nasser, A., Haselkorn, R., Austin, J. II. Visualization of channels connecting cells in filamentous nitrogen-fixing cyanobacteria. © FASEB.

Exploratory graphical models of functional and structural connectivity patterns for Alzheimer's Disease diagnosis

Directory of Open Access Journals (Sweden)

Andres eOrtiz

2015-11-01

Full Text Available Alzheimer’s Disease (AD is the most common neurodegenerative disease in elderly people. Itsdevelopment has been shown to be closely related to changes in the brain connectivity networkand in the brain activation patterns along with structural changes caused by the neurodegenerativeprocess.Methods to infer dependence between brain regions are usually derived from the analysis ofcovariance between activation levels in the different areas. However, these covariance-basedmethods are not able to estimate conditional independence between variables to factor out theinfluence of other regions. Conversely, models based on the inverse covariance, or precisionmatrix, such as Sparse Gaussian Graphical Models allow revealing conditional independencebetween regions by estimating the covariance between two variables given the rest as constant.This paper uses Sparse Inverse Covariance Estimation (SICE methods to learn undirectedgraphs in order to derive functional and structural connectivity patterns from Fludeoxyglucose(18F-FDG Position Emission Tomography (PET data and segmented Magnetic Resonanceimages (MRI, drawn from the ADNI database, for Control, MCI (Mild Cognitive ImpairmentSubjects and AD subjects. Sparse computation fits perfectly here as brain regions usually onlyinteract with a few other areas.The models clearly show different metabolic covariation patters between subject groups, revealingthe loss of strong connections in AD and MCI subjects when compared to Controls. Similarly,the variance between GM (Grey Matter densities of different regions reveals different structuralcovariation patterns between the different groups. Thus, the different connectivity patterns forcontrols and AD are used in this paper to select regions of interest in PET and GM images withdiscriminative power for early AD diagnosis. Finally, functional an structural models are combinedto leverage the classification accuracy.The results obtained in this work show the usefulness

Multivariate Cholesky models of human female fertility patterns in the NLSY.

Science.gov (United States)

Rodgers, Joseph Lee; Bard, David E; Miller, Warren B

2007-03-01

Substantial evidence now exists that variables measuring or correlated with human fertility outcomes have a heritable component. In this study, we define a series of age-sequenced fertility variables, and fit multivariate models to account for underlying shared genetic and environmental sources of variance. We make predictions based on a theory developed by Udry [(1996) Biosocial models of low-fertility societies. In: Casterline, JB, Lee RD, Foote KA (eds) Fertility in the United States: new patterns, new theories. The Population Council, New York] suggesting that biological/genetic motivations can be more easily realized and measured in settings in which fertility choices are available. Udry's theory, along with principles from molecular genetics and certain tenets of life history theory, allow us to make specific predictions about biometrical patterns across age. Consistent with predictions, our results suggest that there are different sources of genetic influence on fertility variance at early compared to later ages, but that there is only one source of shared environmental influence that occurs at early ages. These patterns are suggestive of the types of gene-gene and gene-environment interactions for which we must account to better understand individual differences in fertility outcomes.

Describing Growth Pattern of Bali Cows Using Non-linear Regression Models

Directory of Open Access Journals (Sweden)

Mohd. Hafiz A.W

2016-12-01

Full Text Available The objective of this study was to evaluate the best fit non-linear regression model to describe the growth pattern of Bali cows. Estimates of asymptotic mature weight, rate of maturing and constant of integration were derived from Brody, von Bertalanffy, Gompertz and Logistic models which were fitted to cross-sectional data of body weight taken from 74 Bali cows raised in MARDI Research Station Muadzam Shah Pahang. Coefficient of determination (R2 and residual mean squares (MSE were used to determine the best fit model in describing the growth pattern of Bali cows. Von Bertalanffy model was the best model among the four growth functions evaluated to determine the mature weight of Bali cattle as shown by the highest R2 and lowest MSE values (0.973 and 601.9, respectively, followed by Gompertz (0.972 and 621.2, respectively, Logistic (0.971 and 648.4, respectively and Brody (0.932 and 660.5, respectively models. The correlation between rate of maturing and mature weight was found to be negative in the range of -0.170 to -0.929 for all models, indicating that animals of heavier mature weight had lower rate of maturing. The use of non-linear model could summarize the weight-age relationship into several biologically interpreted parameters compared to the entire lifespan weight-age data points that are difficult and time consuming to interpret.

Post-hoc pattern-oriented testing and tuning of an existing large model: lessons from the field vole.

Directory of Open Access Journals (Sweden)

Christopher J Topping

Full Text Available Pattern-oriented modeling (POM is a general strategy for modeling complex systems. In POM, multiple patterns observed at different scales and hierarchical levels are used to optimize model structure, to test and select sub-models of key processes, and for calibration. So far, POM has been used for developing new models and for models of low to moderate complexity. It remains unclear, though, whether the basic idea of POM to utilize multiple patterns, could also be used to test and possibly develop existing and established models of high complexity. Here, we use POM to test, calibrate, and further develop an existing agent-based model of the field vole (Microtus agrestis, which was developed and tested within the ALMaSS framework. This framework is complex because it includes a high-resolution representation of the landscape and its dynamics, of the individual's behavior, and of the interaction between landscape and individual behavior. Results of fitting to the range of patterns chosen were generally very good, but the procedure required to achieve this was long and complicated. To obtain good correspondence between model and the real world it was often necessary to model the real world environment closely. We therefore conclude that post-hoc POM is a useful and viable way to test a highly complex simulation model, but also warn against the dangers of over-fitting to real world patterns that lack details in their explanatory driving factors. To overcome some of these obstacles we suggest the adoption of open-science and open-source approaches to ecological simulation modeling.

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

Science.gov (United States)

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.

Using species distribution modeling to delineate the botanical richness patterns and phytogeographical regions of China

Science.gov (United States)

Zhang, Ming-Gang; Slik, J. W. Ferry; Ma, Ke-Ping

2016-03-01

The millions of plant specimens that have been collected and stored in Chinese herbaria over the past ~110 years have recently been digitized and geo-referenced. Here we use this unique collection data set for species distribution modeling exercise aiming at mapping & explaining the botanical richness; delineating China’s phytogeographical regions and investigating the environmental drivers of the dissimilarity patterns. We modeled distributions of 6,828 woody plants using MaxEnt and remove the collection bias using null model. The continental China was divided into different phytogeographical regions based on the dissimilarity patterns. An ordination and Getis-Ord Gi* hotspot spatial statistics were used to analysis the environmental drivers of the dissimilarity patterns. We found that the annual precipitation and temperature stability were responsible for observed species diversity. The mechanisms causing dissimilarity pattern seems differ among biogeographical regions. The identified environmental drivers of the dissimilarity patterns for southeast, southwest, northwest and northeast are annual precipitation, topographic & temperature stability, water deficit and temperature instability, respectively. For effective conservation of China’s plant diversity, identifying the historical refuge and protection of high diversity areas in each of the identified floristic regions and their subdivisions will be essential.

DYNAMIC MATHEMATICAL MODEL OF URBAN SPATIAL PATTERN (RESIDENTIAL CHOICE OF LOCATION: MOBILITY VS EXTERNALITY

Directory of Open Access Journals (Sweden)

Rahma Fitriani

2015-01-01

Full Text Available Household’s residential choice of location determines urban spatial pattern (e.g sprawl. The static model which assumes that the choice has been affected by distance to the CBD and location specific externality, fails to capture the evoution of the pattern over time. Therefore this study proposes a dynamic version of the model. It analyses the effects of externalities on the optimal solution of development decision as function of time. It also derives the effect of mobility and externality on the rate of change of development pattern through time. When the increasing rate of utility is not as significant as the increasing rate of income, the externalities will delay the change of urban spatial pattern over time. If the mobility costs increase by large amount relative to the increase of income and inflation rate, then the mobility effect dominates the effects of externalities in delaying the urban expansion.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Tanaka, Simon; Iber, Dagmar

2013-01-01

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. (paper)

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

Science.gov (United States)

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.

Modeling the Geographic Consequence and Pattern of Dengue Fever Transmission in Thailand.

Science.gov (United States)

Bekoe, Collins; Pansombut, Tatdow; Riyapan, Pakwan; Kakchapati, Sampurna; Phon-On, Aniruth

2017-05-04

Dengue fever is one of the infectious diseases that is still a public health problem in Thailand. This study considers in detail, the geographic consequence, seasonal and pattern of dengue fever transmission among the 76 provinces of Thailand from 2003 to 2015. A cross-sectional study. The data for the study was from the Department of Disease Control under the Bureau of Epidemiology, Thailand. The quarterly effects and location on the transmission of dengue was modeled using an alternative additive log-linear model. The model fitted well as illustrated by the residual plots and the  Again, the model showed that dengue fever is high in the second quarter of every year from May to August. There was an evidence of an increase in the trend of dengue annually from 2003 to 2015. There was a difference in the distribution of dengue fever within and between provinces. The areas of high risks were the central and southern regions of Thailand. The log-linear model provided a simple medium of modeling dengue fever transmission. The results are very important in the geographic distribution of dengue fever patterns.

A generalized linear-quadratic model incorporating reciprocal time pattern of radiation damage repair

International Nuclear Information System (INIS)

Huang, Zhibin; Mayr, Nina A.; Lo, Simon S.; Wang, Jian Z.; Jia Guang; Yuh, William T. C.; Johnke, Roberta

2012-01-01

Purpose: It has been conventionally assumed that the repair rate for sublethal damage (SLD) remains constant during the entire radiation course. However, increasing evidence from animal studies suggest that this may not the case. Rather, it appears that the repair rate for radiation-induced SLD slows down with increasing time. Such a slowdown in repair would suggest that the exponential repair pattern would not necessarily accurately predict repair process. As a result, the purpose of this study was to investigate a new generalized linear-quadratic (LQ) model incorporating a repair pattern with reciprocal time. The new formulas were tested with published experimental data. Methods: The LQ model has been widely used in radiation therapy, and the parameter G in the surviving fraction represents the repair process of sublethal damage with T r as the repair half-time. When a reciprocal pattern of repair process was adopted, a closed form of G was derived analytically for arbitrary radiation schemes. The published animal data adopted to test the reciprocal formulas. Results: A generalized LQ model to describe the repair process in a reciprocal pattern was obtained. Subsequently, formulas for special cases were derived from this general form. The reciprocal model showed a better fit to the animal data than the exponential model, particularly for the ED50 data (reduced χ 2 min of 2.0 vs 4.3, p = 0.11 vs 0.006), with the following gLQ parameters: α/β = 2.6-4.8 Gy, T r = 3.2-3.9 h for rat feet skin, and α/β = 0.9 Gy, T r = 1.1 h for rat spinal cord. Conclusions: These results of repair process following a reciprocal time suggest that the generalized LQ model incorporating the reciprocal time of sublethal damage repair shows a better fit than the exponential repair model. These formulas can be used to analyze the experimental and clinical data, where a slowing-down repair process appears during the course of radiation therapy.

Formalization of the classification pattern: survey of classification modeling in information systems engineering.

Science.gov (United States)

Partridge, Chris; de Cesare, Sergio; Mitchell, Andrew; Odell, James

2018-01-01

Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the "one and the many." Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor's work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus

A model of hygiene practices and consumption patterns in the consumer phase

DEFF Research Database (Denmark)

Christensen, Bjarke Bak; Rosenquist, Hanne; Sommer, Helle Mølgaard

2005-01-01

A mathematical model is presented, which addresses individual hygiene practices during food preparation and consumption patterns in private homes. Further, the model links food preparers and consumers based on their relationship to household types. For different age and gender groups, the model...... was highest for young males (aged 18-29 years) and lowest for the elderly above 60 years of age. Children aged 0-4 years had a higher probability of ingesting a risk meal than children aged 5-17 years. This difference between age and gender groups was ascribed to the variations in the hygiene levels of food....... The simulated results show that the probability of ingesting a chicken risk meal at home does not only depend on the hygiene practices of the persons preparing the food, but also on the consumption patterns of consumers, and the relationship between people preparing and ingesting food. This finding supports...

An economic theory-based explanatory model of agricultural land-use patterns

NARCIS (Netherlands)

Diogo, V.; Koomen, E.; Kuhlman, T.

2015-01-01

An economic theory-based land-use modelling framework is presented aiming to explain the causal link between economic decisions and resulting spatial patterns of agricultural land use. The framework assumes that farmers pursue utility maximisation in agricultural production systems, while

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

Science.gov (United States)

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.

Modelling the effect of temperature on hatching and settlement patterns of meroplanktonic organisms: the case of octopus

Directory of Open Access Journals (Sweden)

Stelios Katsanevakis

2006-12-01

Full Text Available The duration of embryonic development and the planktonic stage of meroplanktonic species is highly temperature dependent and thus the seasonal temperature oscillations of temperate regions greatly affect the patterns of hatching and benthic settlement. Based on data from the literature on embryonic development and planktonic duration of Octopus vulgaris (common octopus in relation to temperature, and on observed temperature patterns, several models of hatching and settlement patterns were created. There was a good fit between observed settlement patterns and model predictions. Based on these models we concluded that in temperate regions: (1 when temperature is increasing (from early spring to mid summer the hatching and settlement periods tend to shorten, while when the temperature is decreasing (during autumn the hatching and settlement periods tend to lengthen; (2 hatching and settlement peaks are narrower and more intense than a spring spawning peak but wider and less intense than an autumn spawning peak; (3 at lower latitudes, hatching and settlement patterns tend to follow the spawning pattern more closely, (4 the periodic temperature pattern of temperate areas has the potential to cause a convergence of hatching during spring.

Exchange bias of patterned systems: Model and numerical simulation

International Nuclear Information System (INIS)

Garcia, Griselda; Kiwi, Miguel; Mejia-Lopez, Jose; Ramirez, Ricardo

2010-01-01

The magnitude of the exchange bias field of patterned systems exhibits a notable increase in relation to the usual bilayer systems, where a continuous ferromagnetic film is deposited on an antiferromagnet insulator. Here we develop a model, and implement a Monte Carlo calculation, to interpret the experimental observations which is consistent with experimental results, on the basis of assuming a small fraction of spins pinned ferromagnetically in the antiferromagnetic interface layer.

Patterns of flavour violation in models with vector-like quarks

Energy Technology Data Exchange (ETDEWEB)

Bobeth, Christoph [TUM Institute for Advanced Study, Lichtenbergstr. 2a, D-85748 Garching (Germany); Physik Department, TU München, James-Franck-Straße, D-85748 Garching (Germany); Excellence Cluster Universe, Technische Universität München,Boltzmannstr. 2, D-85748 Garching (Germany); Buras, Andrzej J. [TUM Institute for Advanced Study, Lichtenbergstr. 2a, D-85748 Garching (Germany); Physik Department, TU München, James-Franck-Straße, D-85748 Garching (Germany); Celis, Alejandro [Ludwig-Maximilians-Universität München, Fakultät für Physik,Arnold Sommerfeld Center for Theoretical Physics, 80333 München (Germany); Jung, Martin [TUM Institute for Advanced Study, Lichtenbergstr. 2a, D-85748 Garching (Germany); Excellence Cluster Universe, Technische Universität München,Boltzmannstr. 2, D-85748 Garching (Germany)

2017-04-13

We study the patterns of flavour violation in renormalisable extensions of the Standard Model (SM) that contain vector-like quarks (VLQs) in a single complex representation of either the SM gauge group G{sub SM} or G{sub SM}{sup ′}≡G{sub SM}⊗U(1){sub L{sub μ−L{sub τ}}}. We first decouple VLQs in the M=(1−10) TeV range and then at the electroweak scale also Z,Z{sup ′} gauge bosons and additional scalars to study the phenomenology. The results depend on the relative size of Z- and Z{sup ′}-induced flavour-changing neutral currents, as well as the size of |ΔF|=2 contributions including the effects of renormalisation group Yukawa evolution from M to the electroweak scale that turn out to be very important for models with right-handed currents through the generation of left-right operators. In addition to rare decays like P→ℓℓ̄, P→P{sup ′}ℓℓ̄, P→P{sup ′}νν̄ with P=K,B{sub s},B{sub d} and |ΔF|=2 observables we analyze the ratio ε{sup ′}/ε which appears in the SM to be significantly below the data. We study patterns and correlations between these observables which taken together should in the future allow for differentiating between VLQ models. In particular the patterns in models with left-handed and right-handed currents are markedly different from each other. Among the highlights are large Z-mediated new physics effects in Kaon observables in some of the models and significant effects in B{sub s,d}-observables. ε{sup ′}/ε can easily be made consistent with the data, implying then uniquely the suppression of K{sub L}→π{sup 0}νν̄. Significant enhancements of Br(K{sup +}→π{sup +}νν̄) are still possible. We point out that the combination of NP effects to |ΔF|=2 and |ΔF|=1 observables in a given meson system generally allows to determine the masses of VLQs in a given representation independently of the size of VLQ couplings.

A software tool to model genetic regulatory networks. Applications to the modeling of threshold phenomena and of spatial patterning in Drosophila.

Directory of Open Access Journals (Sweden)

Rui Dilão

Full Text Available We present a general methodology in order to build mathematical models of genetic regulatory networks. This approach is based on the mass action law and on the Jacob and Monod operon model. The mathematical models are built symbolically by the Mathematica software package GeneticNetworks. This package accepts as input the interaction graphs of the transcriptional activators and repressors of a biological process and, as output, gives the mathematical model in the form of a system of ordinary differential equations. All the relevant biological parameters are chosen automatically by the software. Within this framework, we show that concentration dependent threshold effects in biology emerge from the catalytic properties of genes and its associated conservation laws. We apply this methodology to the segment patterning in Drosophila early development and we calibrate the genetic transcriptional network responsible for the patterning of the gap gene proteins Hunchback and Knirps, along the antero-posterior axis of the Drosophila embryo. In this approach, the zygotically produced proteins Hunchback and Knirps do not diffuse along the antero-posterior axis of the embryo of Drosophila, developing a spatial pattern due to concentration dependent thresholds. This shows that patterning at the gap genes stage can be explained by the concentration gradients along the embryo of the transcriptional regulators.

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

Science.gov (United States)

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.

CHF Enhancement by Surface Patterning based on Hydrodynamic Instability Model

Energy Technology Data Exchange (ETDEWEB)

Seo, Han; Bang, In Cheol [UNIST, Ulsan (Korea, Republic of)

2015-05-15

If the power density of a device exceeds the CHF point, bubbles and vapor films will be covered on the whole heater surface. Because vapor films have much lower heat transfer capabilities compared to the liquid layer, the temperature of the heater surface will increase rapidly, and the device could be damaged due to the heater burnout. Therefore, the prediction and the enhancement of the CHF are essential to maximizing the efficient heat removal region. Numerous studies have been conducted to describe the CHF phenomenon, such as hydrodynamic instability theory, macrolayer dryout theory, hot/dry spot theory, and bubble interaction theory. The hydrodynamic instability model, proposed by Zuber, is the predominant CHF model that Helmholtz instability attributed to the CHF. Zuber assumed that the Rayleigh-Taylor (RT) instability wavelength is related to the Helmholtz wavelength. Lienhard and Dhir proposed a CHF model that Helmholtz instability wavelength is equal to the most dangerous RT wavelength. In addition, they showed the heater size effect using various heater surfaces. Lu et al. proposed a modified hydrodynamic theory that the Helmholtz instability was assumed to be the heater size and the area of the vapor column was used as a fitting factor. The modified hydrodynamic theories were based on the change of Helmholtz wavelength related to the RT instability wavelength. In the present study, the change of the RT instability wavelength, based on the heater surface modification, was conducted to show the CHF enhancement based on the heater surface patterning in a plate pool boiling. Sapphire glass was used as a base heater substrate, and the Pt film was used as a heating source. The patterning surface was based on the change of RT instability wavelength. In the present work the study of the CHF was conducted using bare Pt and patterned heating surfaces.

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

Science.gov (United States)

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.

Aggregation patterns from nonlocal interactions: Discrete stochastic and continuum modeling

KAUST Repository

Hackett-Jones, Emily J.

2012-04-17

Conservation equations governed by a nonlocal interaction potential generate aggregates from an initial uniform distribution of particles. We address the evolution and formation of these aggregating steady states when the interaction potential has both attractive and repulsive singularities. Currently, no existence theory for such potentials is available. We develop and compare two complementary solution methods, a continuous pseudoinverse method and a discrete stochastic lattice approach, and formally show a connection between the two. Interesting aggregation patterns involving multiple peaks for a simple doubly singular attractive-repulsive potential are determined. For a swarming Morse potential, characteristic slow-fast dynamics in the scaled inverse energy is observed in the evolution to steady state in both the continuous and discrete approaches. The discrete approach is found to be remarkably robust to modifications in movement rules, related to the potential function. The comparable evolution dynamics and steady states of the discrete model with the continuum model suggest that the discrete stochastic approach is a promising way of probing aggregation patterns arising from two- and three-dimensional nonlocal interaction conservation equations. © 2012 American Physical Society.

Toward robust phase-locking in Melibe swim central pattern generator models

Science.gov (United States)

Jalil, Sajiya; Allen, Dane; Youker, Joseph; Shilnikov, Andrey

2013-12-01

Small groups of interneurons, abbreviated by CPG for central pattern generators, are arranged into neural networks to generate a variety of core bursting rhythms with specific phase-locked states, on distinct time scales, which govern vital motor behaviors in invertebrates such as chewing and swimming. These movements in lower level animals mimic motions of organs in higher animals due to evolutionarily conserved mechanisms. Hence, various neurological diseases can be linked to abnormal movement of body parts that are regulated by a malfunctioning CPG. In this paper, we, being inspired by recent experimental studies of neuronal activity patterns recorded from a swimming motion CPG of the sea slug Melibe leonina, examine a mathematical model of a 4-cell network that can plausibly and stably underlie the observed bursting rhythm. We develop a dynamical systems framework for explaining the existence and robustness of phase-locked states in activity patterns produced by the modeled CPGs. The proposed tools can be used for identifying core components for other CPG networks with reliable bursting outcomes and specific phase relationships between the interneurons. Our findings can be employed for identifying or implementing the conditions for normal and pathological functioning of basic CPGs of animals and artificially intelligent prosthetics that can regulate various movements.

Spatial patterns of biodiversity conservation in a multiregional general equilibrium model

NARCIS (Netherlands)

Eppink, F.V.; Withagen, C.A.A.M.

2009-01-01

Migration dynamics and local biodiversity are interrelated in a way that is likely to affect patterns of regional specialisation. We assess this relationship with a New Economic Geography model that has been extended with biodiversity. Biodiversity is heterogeneous, and responds to habitat

Ontology and modeling patterns for state-based behavior representation

Science.gov (United States)

Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.;

Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

Science.gov (United States)

Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

2017-09-01

Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

Human Mobility Patterns and Cholera Epidemics: a Spatially Explicit Modeling Approach

Science.gov (United States)

Mari, L.; Bertuzzo, E.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2010-12-01

Cholera is an acute enteric disease caused by the ingestion of water or food contaminated by the bacterium Vibrio cholerae. Although most infected individuals do not develop severe symptoms, their stool may contain huge quantities of V.~cholerae cells. Therefore, while traveling or commuting, asymptomatic carriers can be responsible for the long-range dissemination of the disease. As a consequence, human mobility is an alternative and efficient driver for the spread of cholera, whose primary propagation pathway is hydrological transport through river networks. We present a multi-layer network model that accounts for the interplay between epidemiological dynamics, hydrological transport and long-distance dissemination of V.~cholerae due to human movement. In particular, building on top of state-of-the-art spatially explicit models for cholera spread through surface waters, we describe human movement and its effects on the propagation of the disease by means of a gravity-model approach borrowed from transportation theory. Gravity-like contact processes have been widely used in epidemiology, because they can satisfactorily depict human movement when data on actual mobility patterns are not available. We test our model against epidemiological data recorded during the cholera outbreak occurred in the KwaZulu-Natal province of South Africa during years 2000--2001. We show that human mobility does actually play an important role in the formation of the spatiotemporal patterns of cholera epidemics. In particular, long-range human movement may determine inter-catchment dissemination of V.~cholerae cells, thus in turn explaining the emergence of epidemic patterns that cannot be produced by hydrological transport alone. We also show that particular attention has to be devoted to study how heterogeneously distributed drinking water supplies and sanitation conditions may affect cholera transmission.

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

Science.gov (United States)

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.

A Novel Biped Pattern Generator Based on Extended ZMP and Extended Cart-Table Model

Directory of Open Access Journals (Sweden)

Guangbin Sun

2015-07-01

Full Text Available This paper focuses on planning patterns for biped walking on complex terrains. Two problems are solved: ZMP (zero moment point cannot be used on uneven terrain, and the conventional cart-table model does not allow vertical CM (centre of mass motion. For the ZMP definition problem, we propose the extended ZMP (EZMP concept as an extension of ZMP to uneven terrains. It can be used to judge dynamic balance on universal terrains. We achieve a deeper insight into the connection and difference between ZMP and EZMP by adding different constraints. For the model problem, we extend the cart-table model by using a dynamic constraint instead of constant height constraint, which results in a mathematically symmetric set of three equations. In this way, the vertical motion is enabled and the resultant equations are still linear. Based on the extended ZMP concept and extended cart-table model, a biped pattern generator using triple preview controllers is constructed and implemented simultaneously to three dimensions. Using the proposed pattern generator, the Atlas robot is simulated. The simulation results show the robot can walk stably on rather complex terrains by accurately tracking extended ZMP.

On Input Vector Representation for the SVR model of Reactor Core Loading Pattern Critical Parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2008-01-01

Determination and optimization of reactor core loading pattern is an important factor in nuclear power plant operation. The goal is to minimize the amount of enriched uranium (fresh fuel) and burnable absorbers placed in the core, while maintaining nuclear power plant operational and safety characteristics. The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. Recently, we proposed a new method for fast loading pattern evaluation based on general robust regression model relying on the state of the art research in the field of machine learning. We employed Support Vector Regression (SVR) technique. SVR is a supervised learning method in which model parameters are automatically determined by solving a quadratic optimization problem. The preliminary tests revealed a good potential of the SVR method application for fast and accurate reactor core loading pattern evaluation. However, some aspects of model development are still unresolved. The main objective of the work reported in this paper was to conduct additional tests and analyses required for full clarification of the SVR applicability for loading pattern evaluation. We focused our attention on the parameters defining input vector, primarily its structure and complexity, and parameters defining kernel functions. All the tests were conducted on the NPP Krsko reactor core, using MCRAC code for the calculation of reactor core loading pattern critical parameters. The tested input vector structures did not influence the accuracy of the models suggesting that the initially tested input vector, consisted of the number of IFBAs and the k-inf at the beginning of the cycle, is adequate. The influence of kernel function specific parameters (σ for RBF kernel

A Multi-Agent Modelling Approach to Simulate Dynamic Activity-Travel Patterns

NARCIS (Netherlands)

Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Bazzan, A.L.C.; Klügl, F.

2009-01-01

Contributing to the recent interest in the dynamics of activity-travel patterns, this chapter discusses a framework of an agent-based modeling approach focusing on the dynamic formation of (location) choice sets. Individual travelers are represented as agents, each with their cognition of the

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Morphodynamic modeling of the river pattern continuum (Invited)

Science.gov (United States)

Nicholas, A. P.

2013-12-01

Numerical models provide valuable tools for integrating understanding of fluvial processes and morphology. Moreover, they have considerable potential for use in investigating river responses to environmental change and catchment management, and for aiding the interpretation of alluvial deposits and landforms. For this potential to be realised fully, such models must be capable of representing diverse river styles and the spatial and temporal transitions between styles that are driven by changes in environmental forcing. However, while numerical modeling of rivers has advanced considerable over the past few decades, this has been accomplished largely by developing separate approaches to modeling single and multi-thread channels. Results are presented here from numerical simulations undertaken using a new model of river and floodplain co-evolution, applied to investigate the morphodynamics of large sand-bed rivers. This model solves the two-dimensional depth-averaged shallow water equations using a Godunov-type finite volume scheme, with a two-fraction representation of sediment transport, and includes the effects of secondary circulation, bank erosion and floodplain development due to the colonization of bar surfaces by vegetation. Simulation results demonstrate the feasibility of representing a wide range of fluvial styles (including braiding, meandering and anabranching channels) using relatively simple physics-based models, and provide insight into the controls on channel pattern diversity in large sand-bed rivers. Analysis of model sensitivity illustrates the important role of upstream boundary conditions as a control on channel dynamics. Moreover, this analysis highlights key uncertainties in model process representation and their implications for modelling river evolution in response to natural and anthropogenic-induced river disturbance.

A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

Directory of Open Access Journals (Sweden)

Benjamin G Schultz

Full Text Available Implicit learning (IL occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1 perceptual fluency may not be necessary to infer IL, or 2 conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency.

Firing patterns in the adaptive exponential integrate-and-fire model.

Science.gov (United States)

Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram

2008-11-01

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.

Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

OpenAIRE

Lahiru Iddamalgoda; Partha Sarathi Das; Partha Sarathi Das; Achala Aponso; Vijayaraghava Seshadri Sundararajan; Prashanth Suravajhala; Prashanth Suravajhala; Prashanth Suravajhala; Jayaraman K Valadi

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern r...

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

Science.gov (United States)

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.

A novel drag force coefficient model for gas–water two-phase flows under different flow patterns

Energy Technology Data Exchange (ETDEWEB)

Shang, Zhi, E-mail: shangzhi@tsinghua.org.cn

2015-07-15

Graphical abstract: - Highlights: • A novel drag force coefficient model was established. • This model realized to cover different flow patterns for CFD. • Numerical simulations were performed under wide range flow regimes. • Validations were carried out through comparisons to experiments. - Abstract: A novel drag force coefficient model has been developed to study gas–water two-phase flows. In this drag force coefficient model, the terminal velocities were calculated through the revised drift flux model. The revised drift flux is different from the traditional drift flux model because the natural curve movement of the bubble was revised through considering the centrifugal force. Owing to the revisions, the revised drift flux model was to extend to 3D. Therefore it is suitable for CFD applications. In the revised drift flux model, the different flow patterns of the gas–water two-phase flows were able to be considered. This model innovatively realizes the drag force being able to cover different flow patterns of gas–water two-phase flows on bubbly flow, slug flow, churn flow, annular flow and mist flow. Through the comparisons of the numerical simulations to the experiments in vertical upward and downward pipe flows, this model was validated.

Bifurcation analysis of oscillating network model of pattern recognition in the rabbit olfactory bulb

Science.gov (United States)

Baird, Bill

1986-08-01

A neural network model describing pattern recognition in the rabbit olfactory bulb is analysed to explain the changes in neural activity observed experimentally during classical Pavlovian conditioning. EEG activity recorded from an 8×8 arry of 64 electrodes directly on the surface on the bulb shows distinct spatial patterns of oscillation that correspond to the animal's recognition of different conditioned odors and change with conditioning to new odors. The model may be considered a variant of Hopfield's model of continuous analog neural dynamics. Excitatory and inhibitory cell types in the bulb and the anatomical architecture of their connection requires a nonsymmetric coupling matrix. As the mean input level rises during each breath of the animal, the system bifurcates from homogenous equilibrium to a spatially patterned oscillation. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of these unstable oscillatory modes independent of frequency. This allows a view of stored periodic attractors as fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

Using Petri nets for modeling enterprise integration patterns

NARCIS (Netherlands)

Fahland, D.; Gierds, C.

2012-01-01

Enterprise Integration Patterns are a collection of widely used patterns for integrating enterprise applications and business processes. These patterns informally represent typical design decisions for connecting enterprise applications. For the set of patterns collected by Hohpe and Woolf in

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

Science.gov (United States)

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…

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

Science.gov (United States)

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.

Modeling on bubbly to churn flow pattern transition for vertical upward flows in narrow rectangular channel

International Nuclear Information System (INIS)

Wang Yanlin; Chen Bingde; Huang Yanping; Wang Junfeng

2011-01-01

A theoretical model was developed to predict the bubbly to churn flow pattern transition for vertical upward flows in narrow rectangular channel. The model was developed based on the imbalance theory of Helmholtz and some reasonable assumptions. The maximum ideal bubble in narrow rectangular channel and the thermal hydraulics boundary condition leading to bubbly flow to churn flow pattern transition was calculated. The model was validated by experimental data from previous researches. Comparison between predicted result and experimental result shows a reasonable good agreement. (author)

Self-Organized Patterns Induced by Neimark-Sacker, Flip and Turing Bifurcations in a Discrete Predator-Prey Model with Lesie-Gower Functional Response

Directory of Open Access Journals (Sweden)

Feifan Zhang

2017-06-01

Full Text Available The formation of self-organized patterns in predator-prey models has been a very hot topic recently. The dynamics of these models, bifurcations and pattern formations are so complex that studies are urgently needed. In this research, we transformed a continuous predator-prey model with Lesie-Gower functional response into a discrete model. Fixed points and stability analyses were studied. Around the stable fixed point, bifurcation analyses including: flip, Neimark-Sacker and Turing bifurcation were done and bifurcation conditions were obtained. Based on these bifurcation conditions, parameters values were selected to carry out numerical simulations on pattern formation. The simulation results showed that Neimark-Sacker bifurcation induced spots, spirals and transitional patterns from spots to spirals. Turing bifurcation induced labyrinth patterns and spirals coupled with mosaic patterns, while flip bifurcation induced many irregular complex patterns. Compared with former studies on continuous predator-prey model with Lesie-Gower functional response, our research on the discrete model demonstrated more complex dynamics and varieties of self-organized patterns.

Introducing a rainfall compound distribution model based on weather patterns sub-sampling

Directory of Open Access Journals (Sweden)

F. Garavaglia

2010-06-01

Full Text Available This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis.

First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France.

The distribution of the multi-exponential weather patterns (MEWP is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.

Stochastic Modeling of Usage Patterns in a Web-Based Information System.

Science.gov (United States)

Chen, Hui-Min; Cooper, Michael D.

2002-01-01

Uses continuous-time stochastic models, mainly based on semi-Markov chains, to derive user state transition patterns, both in rates and in probabilities, in a Web-based information system. Describes search sessions from transaction logs of the University of California's MELVYL library catalog system and discusses sequential dependency. (Author/LRW)

Modelling ground deformation patterns associated with volcanic processes at the Okataina Volcanic Centre

Science.gov (United States)

Holden, L.; Cas, R.; Fournier, N.; Ailleres, L.

2017-09-01

The Okataina Volcanic Centre (OVC) is one of two large active rhyolite centres in the modern Taupo Volcanic Zone (TVZ) in the North Island of New Zealand. It is located in a complex section of the Taupo rift, a tectonically active section of the TVZ. The most recent volcanic unrest at the OVC includes the 1315 CE Kaharoa and 1886 Tarawera eruptions. Current monitoring activity at the OVC includes the use of continuous GPS receivers (cGPS), lake levelling and seismographs. The ground deformation patterns preceding volcanic activity the OVC are poorly constrained and restricted to predictions from basic modelling and comparison to other volcanoes worldwide. A better understanding of the deformation patterns preceding renewed volcanic activity is essential to determine if observed deformation is related to volcanic, tectonic or hydrothermal processes. Such an understanding also means that the ability of the present day cGPS network to detect these deformation patterns can also be assessed. The research presented here uses the finite element (FE) modelling technique to investigate ground deformation patterns associated with magma accumulation and diking processes at the OVC in greater detail. A number of FE models are produced and tested using Pylith software and incorporate characteristics of the 1315 CE Kaharoa and 1886 Tarawera eruptions, summarised from the existing body of research literature. The influence of a simple ring fault structure at the OVC on the modelled deformation is evaluated. The ability of the present-day continuous GPS (cGPS) GeoNet monitoring network to detect or observe the modelled deformation is also considered. The results show the modelled horizontal and vertical displacement fields have a number of key features, which include prominent lobe based regions extending northwest and southeast of the OVC. The results also show that the ring fault structure increases the magnitude of the displacements inside the caldera, in particular in the

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

Science.gov (United States)

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.

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

Science.gov (United States)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

DEFF Research Database (Denmark)

Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

2009-01-01

We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

Federated Access Control in Heterogeneous Intercloud Environment: Basic Models and Architecture Patterns

NARCIS (Netherlands)

Demchenko, Y.; Ngo, C.; de Laat, C.; Lee, C.

2014-01-01

This paper presents on-going research to define the basic models and architecture patterns for federated access control in heterogeneous (multi-provider) multi-cloud and inter-cloud environment. The proposed research contributes to the further definition of Intercloud Federation Framework (ICFF)

Large-scale hydrology in Europe : observed patterns and model performance

Energy Technology Data Exchange (ETDEWEB)

Gudmundsson, Lukas

2011-06-15

In a changing climate, terrestrial water storages are of great interest as water availability impacts key aspects of ecosystem functioning. Thus, a better understanding of the variations of wet and dry periods will contribute to fully grasp processes of the earth system such as nutrient cycling and vegetation dynamics. Currently, river runoff from small, nearly natural, catchments is one of the few variables of the terrestrial water balance that is regularly monitored with detailed spatial and temporal coverage on large scales. River runoff, therefore, provides a foundation to approach European hydrology with respect to observed patterns on large scales, with regard to the ability of models to capture these.The analysis of observed river flow from small catchments, focused on the identification and description of spatial patterns of simultaneous temporal variations of runoff. These are dominated by large-scale variations of climatic variables but also altered by catchment processes. It was shown that time series of annual low, mean and high flows follow the same atmospheric drivers. The observation that high flows are more closely coupled to large scale atmospheric drivers than low flows, indicates the increasing influence of catchment properties on runoff under dry conditions. Further, it was shown that the low-frequency variability of European runoff is dominated by two opposing centres of simultaneous variations, such that dry years in the north are accompanied by wet years in the south.Large-scale hydrological models are simplified representations of our current perception of the terrestrial water balance on large scales. Quantification of the models strengths and weaknesses is the prerequisite for a reliable interpretation of simulation results. Model evaluations may also enable to detect shortcomings with model assumptions and thus enable a refinement of the current perception of hydrological systems. The ability of a multi model ensemble of nine large

Modelling fast spreading patterns of airborne infectious diseases using complex networks

Science.gov (United States)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-04-01

The pandemics of SARS (2002/2003) and H1N1 (2009) have impressively shown the potential of epidemic outbreaks of infectious diseases in a world that is strongly connected. Global air travelling established an easy and fast opportunity for pathogens to migrate globally in only a few days. This made epidemiological prediction harder. By understanding this complex development and its link to climate change we can suggest actions to control a part of global human health affairs. In this study we combine the following data components to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human: em{Global Air Traffic Network (from openflights.org) with information on airports, airport location, direct flight connection, airplane type} em{Global population dataset (from SEDAC, NASA)} em{Susceptible-Infected-Recovered (SIR) compartmental model to simulate disease spreading in the vicinity of airports. A modified Susceptible-Exposed-Infected-Recovered (SEIR) model to analyze the impact of the incubation period.} em{WATCH-Forcing-Data-ERA-Interim (WFDEI) climate data: temperature, specific humidity, surface air pressure, and water vapor pressure} These elements are implemented into a complex network. Nodes inside the network represent airports. Each single node is equipped with its own SIR/SEIR compartmental model with node specific attributes. Edges between those nodes represent direct flight connections that allow infected individuals to move between linked nodes. Therefore the interaction of the set of unique SIR models creates the model dynamics we will analyze. To better figure out the influence on climate change on disease spreading patterns, we focus on Influenza-like-Illnesses (ILI). The transmission rate of ILI has a dependency on climate parameters like humidity and temperature. Even small changes of environmental variables can trigger significant differences in the global outbreak behavior. Apart from the direct

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

Directory of Open Access Journals (Sweden)

Fernando A Villanea

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

Information geometric analysis of phase transitions in complex patterns: the case of the Gray-Scott reaction–diffusion model

International Nuclear Information System (INIS)

Har-Shemesh, Omri; Quax, Rick; Hoekstra, Alfons G; Sloot, Peter M A

2016-01-01

The Fisher–Rao metric from information geometry is related to phase transition phenomena in classical statistical mechanics. Several studies propose to extend the use of information geometry to study more general phase transitions in complex systems. However, it is unclear whether the Fisher–Rao metric does indeed detect these more general transitions, especially in the absence of a statistical model. In this paper we study the transitions between patterns in the Gray-Scott reaction–diffusion model using Fisher information. We describe the system by a probability density function that represents the size distribution of blobs in the patterns and compute its Fisher information with respect to changing the two rate parameters of the underlying model. We estimate the distribution non-parametrically so that we do not assume any statistical model. The resulting Fisher map can be interpreted as a phase-map of the different patterns. Lines with high Fisher information can be considered as boundaries between regions of parameter space where patterns with similar characteristics appear. These lines of high Fisher information can be interpreted as phase transitions between complex patterns. (paper: disordered systems, classical and quantum)

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

Science.gov (United States)

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

Effect of different tree mortality patterns on stand development in the forest model SIBYLA

Directory of Open Access Journals (Sweden)

Trombik Jiří

2016-09-01

Full Text Available Forest mortality critically affects stand structure and the quality of ecosystem services provided by forests. Spruce bark beetle (Ips typographus generates rather complex infestation and mortality patterns, and implementation of such patterns in forest models is challenging. We present here the procedure, which allows to simulate the bark beetle-related tree mortality in the forest dynamics model Sibyla. We explored how sensitive various production and stand structure indicators are to tree mortality patterns, which can be generated by bark beetles. We compared the simulation outputs for three unmanaged forest stands with 40, 70 and 100% proportion of spruce as affected by the disturbance-related mortality that occurred in a random pattern and in a patchy pattern. The used tree species and age class-specific mortality rates were derived from the disturbance-related mortality records from Slovakia. The proposed algorithm was developed in the SQLite using the Python language, and the algorithm allowed us to define the degree of spatial clustering of dead trees ranging from a random distribution to a completely clustered distribution; a number of trees that died in either mode is set to remain equal. We found significant differences between the long-term developments of the three investigated forest stands, but we found very little effect of the tested mortality modes on stand increment, tree species composition and diversity, and tree size diversity. Hence, our hypothesis that the different pattern of dead trees emergence should affect the competitive interactions between trees and regeneration, and thus affect selected productivity and stand structure indicators was not confirmed.

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

Science.gov (United States)

Smith, James A.

2010-01-01

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

Regression models for linking patterns of growth to a later outcome: infant growth and childhood overweight

Directory of Open Access Journals (Sweden)

Andrew K. Wills

2016-04-01

Full Text Available Abstract Background Regression models are widely used to link serial measures of anthropometric size or changes in size to a later outcome. Different parameterisations of these models enable one to target different questions about the effect of growth, however, their interpretation can be challenging. Our objective was to formulate and classify several sets of parameterisations by their underlying growth pattern contrast, and to discuss their utility using an expository example. Methods We describe and classify five sets of model parameterisations in accordance with their underlying growth pattern contrast (conditional growth; being bigger v being smaller; becoming bigger and staying bigger; growing faster v being bigger; becoming and staying bigger versus being bigger. The contrasts are estimated by including different sets of repeated measures of size and changes in size in a regression model. We illustrate these models in the setting of linking infant growth (measured on 6 occasions: birth, 6 weeks, 3, 6, 12 and 24 months in weight-for-height-for-age z-scores to later childhood overweight at 8y using complete cases from the Norwegian Childhood Growth study (n = 900. Results In our expository example, conditional growth during all periods, becoming bigger in any interval and staying bigger through infancy, and being bigger from birth were all associated with higher odds of later overweight. The highest odds of later overweight occurred for individuals who experienced high conditional growth or became bigger in the 3 to 6 month period and stayed bigger, and those who were bigger from birth to 24 months. Comparisons between periods and between growth patterns require large sample sizes and need to consider how to scale associations to make comparisons fair; with respect to the latter, we show one approach. Conclusion Studies interested in detrimental growth patterns may gain extra insight from reporting several sets of growth pattern

Interference pattern in the collision of structures in the Bose-Einstein condensate dark matter model: Comparison with fluids

International Nuclear Information System (INIS)

Gonzalez, J. A; Guzman, F. S.

2011-01-01

In order to explore nonlinear effects on the distribution of matter during collisions within the Bose-Einstein condensate (BEC) dark matter model driven by the Schroedinger-Poisson system of equations, we study the head-on collision of structures and focus on the interference pattern formation in the density of matter during the collision process. We explore the possibility that the collision of two structures of fluid matter modeled with an ideal gas equation of state also forms interference patterns and found a negative result. Given that a fluid is the most common flavor of dark matter models, we conclude that one fingerprint of the BEC dark matter model is the pattern formation in the density during a collision of structures.

Color Mixing Correction for Post-printed Patterns on Colored Background Using Modified Particle Density Model

OpenAIRE

Suwa , Misako; Fujimoto , Katsuhito

2006-01-01

http://www.suvisoft.com; Color mixing occurs between background and foreground colors when a pattern is post-printed on a colored area because ink is not completely opaque. This paper proposes a new method for the correction of color mixing in line pattern such as characters and stamps, by using a modified particle density model. Parameters of the color correction can be calculated from two sets of foreground and background colors. By employing this method, the colors of foreground patterns o...

Three-pattern decomposition of global atmospheric circulation: part I—decomposition model and theorems

Science.gov (United States)

Hu, Shujuan; Chou, Jifan; Cheng, Jianbo

2018-04-01

In order to study the interactions between the atmospheric circulations at the middle-high and low latitudes from the global perspective, the authors proposed the mathematical definition of three-pattern circulations, i.e., horizontal, meridional and zonal circulations with which the actual atmospheric circulation is expanded. This novel decomposition method is proved to accurately describe the actual atmospheric circulation dynamics. The authors used the NCEP/NCAR reanalysis data to calculate the climate characteristics of those three-pattern circulations, and found that the decomposition model agreed with the observed results. Further dynamical analysis indicates that the decomposition model is more accurate to capture the major features of global three dimensional atmospheric motions, compared to the traditional definitions of Rossby wave, Hadley circulation and Walker circulation. The decomposition model for the first time realized the decomposition of global atmospheric circulation using three orthogonal circulations within the horizontal, meridional and zonal planes, offering new opportunities to study the large-scale interactions between the middle-high latitudes and low latitudes circulations.

Dinitrogen fixation by blue-green algae from paddy fields

International Nuclear Information System (INIS)

Thomas, J.

1978-01-01

Fluorescence emission spectra at 77K of isolated heterocysts of Anabaena L-31 do not show F685-695 but rather F715-730, thus confirming the absence of photosystem II and the presence of photosystem I. Recent work using radioactive nitrogen has been collated and a tentative scheme is outlined indicating the location of the enzymes and the pathways involved in the initial assimilation of nitrogen in blue-green algae. Glutamine synthetase extracted from heterocysts of Anabaena L-31 does not exhibit the adenylylation/deadenylylation phenomenon characteristic of the enzyme from bacteria. Our recent experiments suggest that nitrogenase in Anabaena is under dual control by glutamic acid and aspartic acid, the former inhibiting the enzyme synthesis and the latter relieving the inhibition. Two extracellular polypeptides have been obtained from this alga, one of which inhibits heterocyst formation whereas the other enhances heterocyst formation and partially relieves the inhibitory effect of the former. An extracellular substance, possibly a glycopeptide, has been obtained from A. torulosa, which stimulates sporulation. Studies with 24 Na and 22 Na indicate that A. torulosa, an alga from saline habitats, has an active photosynthesis-linked mechanism for the extrusion of sodium. Sodium is essential for optimum nitrogenase activity and growth. In field experiments inoculation with Nostoc 4 resulted in substantial increase in soil nitrogen. Paddy yield was comparable to those plots where 80kg N/ha of urea was used. (author)

Energy deposition patterns within limb models heated with a mini annular phased array (MAPA) applicator

International Nuclear Information System (INIS)

Guerquin-Kern, J.L.; Hagmann, M.J.; Charny, C.K.; Levin, R.L.

1986-01-01

A series of experiments has been carried out in order to characterize a MAPA applicator prior to possible clinical implementation. The energy deposition patterns were determined in several human limb models of different complexities. The maximum energy deposition observed in a homogeneous cylindrical phantom was found to be at the middle of the applicator. For more realistically shaped, homogeneous limb models, the point of maximum energy deposition was shifted towards a smaller cross-sectional region; this was also the case for isolated human legs. Furthermore, significant heating was observed in the bone of the isolated legs. Such phenomena illustrate the limitation of using classical 2-D numerical models for predicting the energy deposition patterns in heterogeneous bodies

Effects of early afterdepolarizations on excitation patterns in an accurate model of the human ventricles

Science.gov (United States)

Seemann, Gunnar; Panfilov, Alexander V.; Vandersickel, Nele

2017-01-01

Early Afterdepolarizations, EADs, are defined as the reversal of the action potential before completion of the repolarization phase, which can result in ectopic beats. However, the series of mechanisms of EADs leading to these ectopic beats and related cardiac arrhythmias are not well understood. Therefore, we aimed to investigate the influence of this single cell behavior on the whole heart level. For this study we used a modified version of the Ten Tusscher-Panfilov model of human ventricular cells (TP06) which we implemented in a 3D ventricle model including realistic fiber orientations. To increase the likelihood of EAD formation at the single cell level, we reduced the repolarization reserve (RR) by reducing the rapid delayed rectifier Potassium current and raising the L-type Calcium current. Varying these parameters defined a 2D parametric space where different excitation patterns could be classified. Depending on the initial conditions, by either exciting the ventricles with a spiral formation or burst pacing protocol, we found multiple different spatio-temporal excitation patterns. The spiral formation protocol resulted in the categorization of a stable spiral (S), a meandering spiral (MS), a spiral break-up regime (SB), spiral fibrillation type B (B), spiral fibrillation type A (A) and an oscillatory excitation type (O). The last three patterns are a 3D generalization of previously found patterns in 2D. First, the spiral fibrillation type B showed waves determined by a chaotic bi-excitable regime, i.e. mediated by both Sodium and Calcium waves at the same time and in same tissue settings. In the parameter region governed by the B pattern, single cells were able to repolarize completely and different (spiral) waves chaotically burst into each other without finishing a 360 degree rotation. Second, spiral fibrillation type A patterns consisted of multiple small rotating spirals. Single cells failed to repolarize to the resting membrane potential hence

Mathematics in Nature Modeling Patterns in the Natural World

CERN Document Server

Adam, John A

2011-01-01

From rainbows, river meanders, and shadows to spider webs, honeycombs, and the markings on animal coats, the visible world is full of patterns that can be described mathematically. Examining such readily observable phenomena, this book introduces readers to the beauty of nature as revealed by mathematics and the beauty of mathematics as revealed in nature.Generously illustrated, written in an informal style, and replete with examples from everyday life, Mathematics in Nature is an excellent and undaunting introduction to the ideas and methods of mathematical modeling. It illustrates how mathem

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

Science.gov (United States)

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.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

Science.gov (United States)

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

Unstable patterns and robust synchronization in a model of motor pathway in birdsong

International Nuclear Information System (INIS)

Moukam Kakmeni, F.M.; Bowong, S.; Nana, L.; Kofane, T.C.

2006-10-01

This paper investigates the fundamental dynamical mechanism responsible for transition to chaos in periodically modulated Duffing-Van der Pol oscillator. It is shown that a modulationally unstable pattern appears into an initially stable motionless state. A further spatiotemporal transition occurs with a sharp interface from the selected stable pattern to a stabilized pattern or chaotic state. Also, the synchronization of the chaotic state of the model is investigated. The results are discussed in the context of generalized synchronization. The main idea is to construct an augmented dynamical system from the synchronization error system, which is itself uncertain. The advantage of this method over existing results is that the synchronization time is explicitly computed. Numerical simulations are provided to verify the operation of the proposed algorithm. (author)

Numerical comparison of grid pattern diffraction effects through measurement and modeling with OptiScan software

Science.gov (United States)

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.

Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model.

Directory of Open Access Journals (Sweden)

Hyeyeong Choe

Full Text Available Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the

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

Science.gov (United States)

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.

Domestic dog roaming patterns in remote northern Australian indigenous communities and implications for disease modelling.

Science.gov (United States)

Hudson, Emily G; Brookes, Victoria J; Dürr, Salome; Ward, Michael P

2017-10-01

Although Australia is canine rabies free, the Northern Peninsula Area (NPA), Queensland and other northern Australian communities are at risk of an incursion due to proximity to rabies infected islands of Indonesia and existing disease spread pathways. Northern Australia also has large populations of free-roaming domestic dogs, presenting a risk of rabies establishment and maintenance should an incursion occur. Agent-based rabies spread models are being used to predict potential outbreak size and identify effective control strategies to aid incursion preparedness. A key component of these models is knowledge of dog roaming patterns to inform contact rates. However, a comprehensive understanding of how dogs utilise their environment and the heterogeneity of their movements to estimate contact rates is lacking. Using a novel simulation approach - and GPS data collected from 21 free-roaming domestic dogs in the NPA in 2014 and 2016 - we characterised the roaming patterns within this dog population. Multiple subsets from each individual dog's GPS dataset were selected representing different monitoring durations and a utilisation distribution (UD) and derived core (50%) and extended (95%) home ranges (HR) were estimated for each duration. Three roaming patterns were identified, based on changes in mean HR over increased monitoring durations, supported by assessment of maps of daily UDs of each dog. Stay-at-home dogs consolidated their HR around their owner's residence, resulting in a decrease in mean HR (both core and extended) as monitoring duration increased (median peak core and extended HR 0.336 and 3.696ha, respectively). Roamer dogs consolidated their core HR but their extended HR increased with longer monitoring durations, suggesting that their roaming patterns based on place of residence were more variable (median peak core and extended HR 0.391 and 6.049ha, respectively). Explorer dogs demonstrated large variability in their roaming patterns, with both core and

Generalized Pareto for Pattern-Oriented Random Walk Modelling of Organisms' Movements.

Directory of Open Access Journals (Sweden)

Sophie Bertrand

Full Text Available How organisms move and disperse is crucial to understand how population dynamics relates to the spatial heterogeneity of the environment. Random walk (RW models are typical tools to describe movement patterns. Whether Lévy or alternative RW better describes forager movements is keenly debated. We get around this issue using the Generalized Pareto Distribution (GPD. GPD includes as specific cases Normal, exponential and power law distributions, which underlie Brownian, Poisson-like and Lévy walks respectively. Whereas previous studies typically confronted a limited set of candidate models, GPD lets the most likely RW model emerge from the data. We illustrate the wide applicability of the method using GPS-tracked seabird foraging movements and fishing vessel movements tracked by Vessel Monitoring System (VMS, both collected in the Peruvian pelagic ecosystem. The two parameters from the fitted GPD, a scale and a shape parameter, provide a synoptic characterization of the observed movement in terms of characteristic scale and diffusive property. They reveal and quantify the variability, among species and individuals, of the spatial strategies selected by predators foraging on a common prey field. The GPD parameters constitute relevant metrics for (1 providing a synthetic and pattern-oriented description of movement, (2 using top predators as ecosystem indicators and (3 studying the variability of spatial behaviour among species or among individuals with different personalities.

Generalized Pareto for Pattern-Oriented Random Walk Modelling of Organisms' Movements.

Science.gov (United States)

Bertrand, Sophie; Joo, Rocío; Fablet, Ronan

2015-01-01

How organisms move and disperse is crucial to understand how population dynamics relates to the spatial heterogeneity of the environment. Random walk (RW) models are typical tools to describe movement patterns. Whether Lévy or alternative RW better describes forager movements is keenly debated. We get around this issue using the Generalized Pareto Distribution (GPD). GPD includes as specific cases Normal, exponential and power law distributions, which underlie Brownian, Poisson-like and Lévy walks respectively. Whereas previous studies typically confronted a limited set of candidate models, GPD lets the most likely RW model emerge from the data. We illustrate the wide applicability of the method using GPS-tracked seabird foraging movements and fishing vessel movements tracked by Vessel Monitoring System (VMS), both collected in the Peruvian pelagic ecosystem. The two parameters from the fitted GPD, a scale and a shape parameter, provide a synoptic characterization of the observed movement in terms of characteristic scale and diffusive property. They reveal and quantify the variability, among species and individuals, of the spatial strategies selected by predators foraging on a common prey field. The GPD parameters constitute relevant metrics for (1) providing a synthetic and pattern-oriented description of movement, (2) using top predators as ecosystem indicators and (3) studying the variability of spatial behaviour among species or among individuals with different personalities.

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

Science.gov (United States)

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

Towards an Explanation of Overeating Patterns Among Normal Weight College Women: Development and Validation of a Structural Equation Model

OpenAIRE

Russ, Christine Runyan II

1998-01-01

Although research describing relationships between psychosocial factors and various eating patterns is growing, a model which explains the mechanisms through which these factors may operate is lacking. A model to explain overeating patterns among normal weight college females was developed and tested. The model contained the following variables: global adjustment, eating and weight cognitions, emotional eating, and self-efficacy. Three hundred ninety-o...

Analog electronic model of the lobster pyloric central pattern generator

Energy Technology Data Exchange (ETDEWEB)

Volkovskii, A [Institute for Nonlinear Science, University of California San Diego, CA (United States); Brugioni, S [Institute for Nonlinear Science, University of California San Diego, CA (United States); Istituto Nazionale di Ottica Applicata Largo E. Fermi 6 50125 Florence (Italy); Levi, R [Institute for Nonlinear Science, University of California San Diego, CA (United States); Rabinovich, M [Institute for Nonlinear Science, University of California San Diego, CA (United States); Selverston, A [Institute for Nonlinear Science, University of California San Diego, CA (United States); Abarbane, H D I [Institute for Nonlinear Science, University of California San Diego, CA (United States)

2005-01-01

An electronic circuit intended to simulate the nonlinear dynamics of a simplified 3-cell model of the pyloric central pattern generator in California spiny lobster stomato gastric ganglion is presented. The model employs the synaptic phase locked loop (SPLL) concept where the frequency of oscillations of a postsynaptic cell is mainly controlled by the synaptic current which depends on the phase shift between the oscillations. The theoretical study showed that the system has a stable steady state with correct phase shifts between the oscillations and that this regime is stable when the frequency of the pacemaker cell is varied over a wide range. The main bifurcations in the system were studied analytically, in computer simulations, and in experiments with the electronic circuit. The experimental measurements are in good agreement with the expectations of the theoretical model.

Decay patterns of multi-quasiparticle bands—a model independent test of chiral symmetry

International Nuclear Information System (INIS)

Lawrie, E A

2017-01-01

Nuclear chiral systems exhibit chiral symmetry bands, built on left-handed and right-handed angular momentum nucleon configurations. The experimental search for such chiral systems revealed a number of suitable candidates, however an unambiguous identification of nuclear chiral symmetry is still outstanding. In this work it is shown that the decay patterns of chiral bands built on multi-quasiparticle configurations are different from those involving different single-particle configurations. It is suggested to use the observed decay patterns of chiral candidates as a new model-independent test of chiral symmetry. (paper)

Modeling and clustering water demand patterns from real-world smart meter data

Directory of Open Access Journals (Sweden)

N. Cheifetz

2017-08-01

Full Text Available Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR, a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

Modeling and clustering water demand patterns from real-world smart meter data

Science.gov (United States)

Cheifetz, Nicolas; Noumir, Zineb; Samé, Allou; Sandraz, Anne-Claire; Féliers, Cédric; Heim, Véronique

2017-08-01

Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

Science.gov (United States)

Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

Using dynamic Brownian bridge movement modelling to measure temporal patterns of habitat selection.

Science.gov (United States)

Byrne, Michael E; Clint McCoy, J; Hinton, Joseph W; Chamberlain, Michael J; Collier, Bret A

2014-09-01

Accurately describing animal space use is vital to understanding how wildlife use habitat. Improvements in GPS technology continue to facilitate collection of telemetry data at high spatial and temporal resolutions. Application of the recently introduced dynamic Brownian bridge movement model (dBBMM) to such data is promising as the method explicitly incorporates the behavioural heterogeneity of a movement path into the estimated utilization distribution (UD). Utilization distributions defining space use are normally estimated for time-scales ranging from weeks to months, obscuring much of the fine-scale information available from high-volume GPS data sets. By accounting for movement heterogeneity, the dBBMM provides a rigorous, behaviourally based estimate of space use between each set of relocations. Focusing on UDs generated between individual sets of locations allows us to quantify fine-scale circadian variation in habitat use. We used the dBBMM to estimate UDs bounding individual time steps for three terrestrial species with different life histories to illustrate how the method can be used to identify fine-scale variations in habitat use. We also demonstrate how dBBMMs can be used to characterize circadian patterns of habitat selection and link fine-scale patterns of habitat use to behaviour. We observed circadian patterns of habitat use that varied seasonally for a white-tailed deer (Odocoileus virginianus) and coyote (Canis latrans). We found seasonal patterns in selection by the white-tailed deer and were able to link use of conifer forests and agricultural fields to behavioural state of the coyote. Additionally, we were able to quantify the date in which a Rio Grande wild turkey (Meleagris gallopavo intermedia) initiated laying as well as when during the day, she was most likely to visit the nest site to deposit eggs. The ability to quantify circadian patterns of habitat use may have important implications for research and management of wildlife

Hidden Markov model analysis reveals the advantage of analytic eye movement patterns in face recognition across cultures.

Science.gov (United States)

Chuk, Tim; Crookes, Kate; Hayward, William G; Chan, Antoni B; Hsiao, Janet H

2017-12-01

It remains controversial whether culture modulates eye movement behavior in face recognition. Inconsistent results have been reported regarding whether cultural differences in eye movement patterns exist, whether these differences affect recognition performance, and whether participants use similar eye movement patterns when viewing faces from different ethnicities. These inconsistencies may be due to substantial individual differences in eye movement patterns within a cultural group. Here we addressed this issue by conducting individual-level eye movement data analysis using hidden Markov models (HMMs). Each individual's eye movements were modeled with an HMM. We clustered the individual HMMs according to their similarities and discovered three common patterns in both Asian and Caucasian participants: holistic (looking mostly at the face center), left-eye-biased analytic (looking mostly at the two individual eyes in addition to the face center with a slight bias to the left eye), and right-eye-based analytic (looking mostly at the right eye in addition to the face center). The frequency of participants adopting the three patterns did not differ significantly between Asians and Caucasians, suggesting little modulation from culture. Significantly more participants (75%) showed similar eye movement patterns when viewing own- and other-race faces than different patterns. Most importantly, participants with left-eye-biased analytic patterns performed significantly better than those using either holistic or right-eye-biased analytic patterns. These results suggest that active retrieval of facial feature information through an analytic eye movement pattern may be optimal for face recognition regardless of culture. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

Science.gov (United States)

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns

Directory of Open Access Journals (Sweden)

Yuwei Wang

2018-01-01

Full Text Available Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is based on binary logistic regression (BLR, but fully considers the spatio-temporally localized spatial associations or characterization of neighborhood interactions (NIs in the patterns of grassland vegetation. The BLR-NIs model was applied to a modeled vegetation degradation of grasslands in the Xilin river basin, Inner Mongolia, China. Residual trend analysis on the normalized difference vegetation index (RESTREND-NDVI, which excluded the climatic impact on vegetation dynamics, was adopted as a preprocessing step to derive three human-induced trajectory patterns (vegetation degradation, vegetation recovery, and no significant change in vegetation during two consecutive periods, T1 (2000–2008 and T2 (2007–2015. Human activities, including livestock grazing intensity and transportation accessibility measured by road network density, were included as explanatory variables for vegetation degradation, which was defined for locations if vegetation recovery or no significant change in vegetation in T1 and vegetation degradation in T2 were observed. Our work compared the results of BLR-NIs and the traditional BLR model that did not consider NIs. The study showed that: (1 both grazing intensity and road density had a positive correlation to vegetation degradation based on the traditional BLR model; (2 only road density was found to positively correlate to vegetation degradation by the BLR-NIs model; NIs appeared to be critical factors to predict vegetation degradation; and (3 including NIs in the BLR model improved the model performance substantially. The study provided evidence for the importance of including localized spatial

Pattern dynamics of vortex ripples in sand: Nonlinear modeling and experimental validation

DEFF Research Database (Denmark)

Andersen, Ken Haste; Abel, M.; Krug, J.

2002-01-01

Vortex ripples in sand are studied experimentally in a one-dimensional setup with periodic boundary conditions. The nonlinear evolution, far from the onset of instability, is analyzed in the framework of a simple model developed for homogeneous patterns. The interaction function describing the mass...... transport between neighboring ripples is extracted from experimental runs using a recently proposed method for data analysis, and the predictions of the model are compared to the experiment. An analytic explanation of the wavelength selection mechanism in the model is provided, and the width of the stable...... band of ripples is measured....

Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

Directory of Open Access Journals (Sweden)

Lahiru Iddamalgoda

2016-08-01

Full Text Available Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification and scoring based prioritization methods for determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI methods in conjunction with the K nearest neighbors’ could be used in accurately categorizing the genetic factors in disease causation

Helical Turing patterns in the Lengyel-Epstein model in thin cylindrical layers

Energy Technology Data Exchange (ETDEWEB)

Bánsági, T.; Taylor, A. F., E-mail: A.F.Taylor@sheffield.ac.uk [Department of Chemical and Biological Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD (United Kingdom)

2015-06-15

The formation of Turing patterns was investigated in thin cylindrical layers using the Lengyel-Epstein model of the chlorine dioxide-iodine-malonic acid reaction. The influence of the width of the layer W and the diameter D of the inner cylinder on the pattern with intrinsic wavelength l were determined in simulations with initial random noise perturbations to the uniform state for W < l/2 and D ∼ l or lower. We show that the geometric constraints of the reaction domain may result in the formation of helical Turing patterns with parameters that give stripes (b = 0.2) or spots (b = 0.37) in two dimensions. For b = 0.2, the helices were composed of lamellae and defects were likely as the diameter of the cylinder increased. With b = 0.37, the helices consisted of semi-cylinders and the orientation of stripes on the outer surface (and hence winding number) increased with increasing diameter until a new stripe appeared.

Helical Turing patterns in the Lengyel-Epstein model in thin cylindrical layers

International Nuclear Information System (INIS)

Bánsági, T.; Taylor, A. F.

2015-01-01

The formation of Turing patterns was investigated in thin cylindrical layers using the Lengyel-Epstein model of the chlorine dioxide-iodine-malonic acid reaction. The influence of the width of the layer W and the diameter D of the inner cylinder on the pattern with intrinsic wavelength l were determined in simulations with initial random noise perturbations to the uniform state for W < l/2 and D ∼ l or lower. We show that the geometric constraints of the reaction domain may result in the formation of helical Turing patterns with parameters that give stripes (b = 0.2) or spots (b = 0.37) in two dimensions. For b = 0.2, the helices were composed of lamellae and defects were likely as the diameter of the cylinder increased. With b = 0.37, the helices consisted of semi-cylinders and the orientation of stripes on the outer surface (and hence winding number) increased with increasing diameter until a new stripe appeared

Modeling photovoltaic performance in periodic patterned colloidal quantum dot solar cells.

Science.gov (United States)

Fu, Yulan; Dinku, Abay G; Hara, Yukihiro; Miller, Christopher W; Vrouwenvelder, Kristina T; Lopez, Rene

2015-07-27

Colloidal quantum dot (CQD) solar cells have attracted tremendous attention mostly due to their wide absorption spectrum window and potentially low processability cost. The ultimate efficiency of CQD solar cells is highly limited by their high trap state density. Here we show that the overall device power conversion efficiency could be improved by employing photonic structures that enhance both charge generation and collection efficiencies. By employing a two-dimensional numerical model, we have calculated the characteristics of patterned CQD solar cells based of a simple grating structure. Our calculation predicts a power conversion efficiency as high as 11.2%, with a short circuit current density of 35.2 mA/cm2, a value nearly 1.5 times larger than the conventional flat design, showing the great potential value of patterned quantum dot solar cells.

Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

Directory of Open Access Journals (Sweden)

Junbao Zheng

2012-03-01

Full Text Available 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.

Practical 3-D Beam Pattern Based Channel Modeling for Multi-Polarized Massive MIMO Systems.

Science.gov (United States)

Aghaeinezhadfirouzja, Saeid; Liu, Hui; Balador, Ali

2018-04-12

In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) contributes various correlation weights for rays related towards/from the cluster, thus providing different elevation angle of arrivals (EAoAs) and elevation angle of departures (EAoDs) for each antenna element. These include the movements of the user that makes our channel to be a non-stationary model of clusters at the receiver (RX) on both the time and array axes. In addition, their impacts on 3-D massive MIMO channels are investigated via statistical properties including received spatial correlation. Additionally, the impact of elevation/azimuth angles of arrival on received spatial correlation is discussed. Furthermore, experimental validation of the proposed 3-D channel models on azimuth and elevation angles of the polarized antenna are specifically evaluated and compared through simulations. The proposed 3-D generic models are verified using relevant measurement data.

The pattern of eigenfrequencies of radial overtones which is predicted for a specified Earth-model

Directory of Open Access Journals (Sweden)

E. R. LAPWOOD

1977-06-01

Full Text Available In 1974 Anderssen and Cleary examined the distribution of eigenfrequencies
of radial overtones in torsional oscillations of Earth-models.
They pointed out that according to Sturm-Liouville theory this distribution
should approach asymptotically, for large overtone number m,
the value nnz/y, where y is the time taken by a shear-wave to travel
along a radius from the core-mantle interface to the surface, provided
elastic parameters vary continuously along the radius. They found that,
for all the models which they considered, the distributions of eigenfrequencies
deviated from the asymptote by amounts which depended on
the existence and size of internal discontinuities. Lapwood (1975 showed
that such deviations were to be expected from Sturm-Liouville theory,
and McNabb, Anderssen and Lapwood (1976 extended Sturm-Liouville
theory to apply to differential equations with discontinuous coefficients.
Anderssen (1977 used their results to show how to predict the pattern
of deviations —called by McNabb et al. the solotone effect— for a
given discontinuity in an Earth-model.
Recently Sato and Lapwood (1977, in a series of papers which will
be referred to here simply as I, II, III, have explored the solotone effect
for layered spherical shells, using approximations derived from an exacttheory which holds for uniform layering. They have shown how the
form of the pattern of eigenfrequencies, which is the graph of
S — YMUJI/N — m against m, where ,„CJI is the frequency of the m"'
overtone in the I"' (Legendre mode of torsional oscillation, is determined
as to periodicity (or quasi-periodicity by the thicknesses and velocities
of the layers, and as to amplitude by the amounts of the discontinuities
(III. The pattern of eigenfrequencies proves to be extremely sensitive
to small changes in layer-thicknesses in a model.
In

Actual building energy use patterns and their implications for predictive modeling

International Nuclear Information System (INIS)

Heidarinejad, Mohammad; Cedeño-Laurent, Jose G.; Wentz, Joshua R.; Rekstad, Nicholas M.; Spengler, John D.; Srebric, Jelena

2017-01-01

Highlights: • Developed three building categories based on energy use patterns of campus buildings. • Evaluated implication of temporal energy data granularity on predictive modeling. • Demonstrated importance of monitoring daily chilled water consumption. • Identified interval electricity data as an indicator of building operation schedules. • Demonstrated a calibration process for energy modeling of a campus building. - Abstract: The main goal of this study is to understand the patterns in which commercial buildings consume energy, rather than evaluating building energy use based on aggregate utility bills typically linked to building principal tenant activity or occupancy type. The energy consumption patterns define buildings as externally-load, internally-load, or mixed-load dominated buildings. Penn State and Harvard campuses serve as case studies for this particular research project. The buildings in these two campuses use steam, chilled water, and electricity as energy commodities and maintain databases of different resolutions to include minute, hourly, daily, and monthly data instances depending on the commodity and available data acquisition system. The results of this study show monthly steam consumption directly correlates to outdoor environmental conditions for 88% of the studied buildings, while chilled water consumption has negligible correlation to the outdoor environmental conditions. Thus, in terms of monthly chilled water consumption, 86% of buildings are internally-load and mixed-load dominated, respectively. Chilled water consumption is better suited for the daily analyses compared to the monthly and hourly analyses. While the influence of building operation schedules affects the analyses at the hourly level, the monthly chilled water consumptions are not good indicators of the building energy consumption patterns. Electricity consumption at the monthly (or seasonal) level can support the building energy simulation tools for the

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

Science.gov (United States)

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.

Computational model-informed design and bioprinting of cell-patterned constructs for bone tissue engineering.

Science.gov (United States)

Carlier, Aurélie; Skvortsov, Gözde Akdeniz; Hafezi, Forough; Ferraris, Eleonora; Patterson, Jennifer; Koç, Bahattin; Van Oosterwyck, Hans

2016-05-17

Three-dimensional (3D) bioprinting is a rapidly advancing tissue engineering technology that holds great promise for the regeneration of several tissues, including bone. However, to generate a successful 3D bone tissue engineering construct, additional complexities should be taken into account such as nutrient and oxygen delivery, which is often insufficient after implantation in large bone defects. We propose that a well-designed tissue engineering construct, that is, an implant with a specific spatial pattern of cells in a matrix, will improve the healing outcome. By using a computational model of bone regeneration we show that particular cell patterns in tissue engineering constructs are able to enhance bone regeneration compared to uniform ones. We successfully bioprinted one of the most promising cell-gradient patterns by using cell-laden hydrogels with varying cell densities and observed a high cell viability for three days following the bioprinting process. In summary, we present a novel strategy for the biofabrication of bone tissue engineering constructs by designing cell-gradient patterns based on a computational model of bone regeneration, and successfully bioprinting the chosen design. This integrated approach may increase the success rate of implanted tissue engineering constructs for critical size bone defects and also can find a wider application in the biofabrication of other types of tissue engineering constructs.

Patterns in coupled water and energy cycle: Modeling, synthesis with observations, and assessing the subsurface-landsurface interactions

Science.gov (United States)

Rahman, A.; Kollet, S. J.; Sulis, M.

2013-12-01

In the terrestrial hydrological cycle, the atmosphere and the free groundwater table act as the upper and lower boundary condition, respectively, in the non-linear two-way exchange of mass and energy across the land surface. Identifying and quantifying the interactions among various atmospheric-subsurface-landsurface processes is complicated due to the diverse spatiotemporal scales associated with these processes. In this study, the coupled subsurface-landsurface model ParFlow.CLM was applied over a ~28,000 km2 model domain encompassing the Rur catchment, Germany, to simulate the fluxes of the coupled water and energy cycle. The model was forced by hourly atmospheric data from the COSMO-DE model (numerical weather prediction system of the German Weather Service) over one year. Following a spinup period, the model results were synthesized with observed river discharge, soil moisture, groundwater table depth, temperature, and landsurface energy flux data at different sites in the Rur catchment. It was shown that the model is able to reproduce reasonably the dynamics and also absolute values in observed fluxes and state variables without calibration. The spatiotemporal patterns in simulated water and energy fluxes as well as the interactions were studied using statistical, geostatistical and wavelet transform methods. While spatial patterns in the mass and energy fluxes can be predicted from atmospheric forcing and power law scaling in the transition and winter months, it appears that, in the summer months, the spatial patterns are determined by the spatially correlated variability in groundwater table depth. Continuous wavelet transform techniques were applied to study the variability of the catchment average mass and energy fluxes at varying time scales. From this analysis, the time scales associated with significant interactions among different mass and energy balance components were identified. The memory of precipitation variability in subsurface hydrodynamics

Food pattern modeling shows that the 2010 Dietary Guidelines for sodium and potassium cannot be met simultaneously

Science.gov (United States)

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

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

Science.gov (United States)

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.

Assessment of nasal spray deposition pattern in a silicone human nose model using a color-based method.

Science.gov (United States)

Kundoor, Vipra; Dalby, Richard N

2010-01-01

To develop a simple and inexpensive method to visualize and quantify droplet deposition patterns. Deposition pattern was determined by uniformly coating the nose model with Sar-Gel (a paste that changes from white to purple on contact with water) and subsequently discharging sprays into the nose model. The color change was captured using a digital camera and analyzed using Adobe Photoshop. Several tests were conducted to validate the method. Deposition patterns of different nasal sprays (Ayr, Afrin, and Zicam) and different nasal drug delivery devices (Afrin nasal spray and PARI Sinustar nasal nebulizer) were compared. We also used the method to evaluate the effect of inhaled flow rate on nasal spray deposition. There was a significant difference in the deposition area for Ayr, Afrin, and Zicam. The deposition areas of Afrin nasal spray and PARI Sinustar nasal nebulizer (2 min and 5 min) were significantly different. Inhaled flow rate did not have a significant effect on the deposition pattern. Lower viscosity formulations (Ayr, Afrin) provided greater coverage than the higher viscosity formulation (Zicam). The nebulizer covered a greater surface area than the spray pump we evaluated. Aerosol deposition in the nose model was not affected by air flow conditions.

A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

Science.gov (United States)

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189

A Computational Model of Pattern Separation Efficiency in the Dentate Gyrus with Implications in Schizophrenia

Directory of Open Access Journals (Sweden)

Faramarz eFaghihi

2015-03-01

Full Text Available Information processing in the hippocampus begins by transferring spiking activity of the Entorhinal Cortex (EC into the Dentate Gyrus (DG. Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modelled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of neuron in the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking. This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed.

Modeling urbanization patterns with generative adversarial networks

OpenAIRE

Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta

2018-01-01

In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity.

Directory of Open Access Journals (Sweden)

Marc Breit

2015-08-01

Full Text Available The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS with the concept of stable isotope dilution (SID for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2, showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001. In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001, classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001. These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling

Effects of Modeling and Tempo Patterns as Practice Techniques on the Performance of High School Instrumentalists.

Science.gov (United States)

Henley, Paul T.

2001-01-01

Examines the effect of modeling conditions and tempo patterns on high school instrumentalists' performance. Focuses on high school students (n=60) who play wind instruments. Reports that the with-model condition was superior in rhythm and tempo percentage gain when compared to the no-model condition. Includes references. (CMK)

Modeling of hydroecological feedbacks predicts distinct classes of landscape pattern, process, and restoration potential in shallow aquatic ecosystems

Science.gov (United States)

Larsen, Laurel G.; Harvey, Judson W.

2011-01-01

It is widely recognized that interactions between vegetation and flow cause the emergence of channel patterns that are distinct from the standard Schumm classification of river channels. Although landscape pattern is known to be linked to ecosystem services such as habitat provision, pollutant removal, and sustaining biodiversity, the mechanisms responsible for the development and stability of different landscape patterns in shallow, vegetated flows have remained poorly understood. Fortunately, recent advances have made possible large-scale models of flow through vegetated environments that can be run over a range of environmental variables and over timescales of millennia. We describe a new, quasi-3D cellular automata model that couples simulations of shallow-water flow, bed shear stresses, sediment transport, and vegetation dynamics in an efficient manner. That efficiency allowed us to apply the model widely in order to determine how different hydroecological feedbacks control landscape pattern and process in various types of wetlands and floodplains. Distinct classes of landscape pattern were uniquely associated with specific types of allogenic and autogenic drivers in wetland flows. Regular, anisotropically patterned wetlands were dominated by allogenic processes (i.e., processes driven by periodic high water levels and flow velocities that redistribute sediment), relative to autogenic processes (e.g., vegetation production, peat accretion, and gravitational erosion). These anistropically patterned wetlands are therefore particularly prone to hydrologic disturbance. Other classes of wetlands that emerged from simulated interactions included maze-patterned, amorphous, and topographically noisy marshes, open marsh with islands, banded string-pool sequences perpendicular to flow, parallel deep and narrow channels flanked by marsh, and ridge-and-slough patterned marsh oriented parallel to flow. Because vegetation both affects and responds to the balance between the

Chimera patterns in the Kuramoto–Battogtokh model

International Nuclear Information System (INIS)

Smirnov, Lev; Osipov, Grigory; Pikovsky, Arkady

2017-01-01

Kuramoto and Battogtokh (2002 Nonlinear Phenom. Complex Syst . 5 380) discovered chimera states represented by stable coexisting synchrony and asynchrony domains in a lattice of coupled oscillators. After a reformulation in terms of a local order parameter, the problem can be reduced to partial differential equations. We find uniformly rotating, spatially periodic chimera patterns as solutions of a reversible ordinary differential equation, and demonstrate a plethora of such states. In the limit of neutral coupling they reduce to analytical solutions in the form of one- and two-point chimera patterns as well as localized chimera solitons. Patterns at weakly attracting coupling are characterized by virtue of a perturbative approach. Stability analysis reveals that only the simplest chimeras with one synchronous region are stable. (letter)

Chimera patterns in the Kuramoto-Battogtokh model

Science.gov (United States)

Smirnov, Lev; Osipov, Grigory; Pikovsky, Arkady

2017-02-01

Kuramoto and Battogtokh (2002 Nonlinear Phenom. Complex Syst. 5 380) discovered chimera states represented by stable coexisting synchrony and asynchrony domains in a lattice of coupled oscillators. After a reformulation in terms of a local order parameter, the problem can be reduced to partial differential equations. We find uniformly rotating, spatially periodic chimera patterns as solutions of a reversible ordinary differential equation, and demonstrate a plethora of such states. In the limit of neutral coupling they reduce to analytical solutions in the form of one- and two-point chimera patterns as well as localized chimera solitons. Patterns at weakly attracting coupling are characterized by virtue of a perturbative approach. Stability analysis reveals that only the simplest chimeras with one synchronous region are stable.

Analysis of 3D Modeling Software Usage Patterns for K-12 Students

Science.gov (United States)

Wu, Yi-Chieh; Liao, Wen-Hung; Chi, Ming-Te; Li, Tsai-Yen

2016-01-01

In response to the recent trend in maker movement, teachers are learning 3D techniques actively and bringing 3D printing into the classroom to enhance variety and creativity in designing lectures. This study investigates the usage pattern of a 3D modeling software, Qmodel Creator, which is targeted at K-12 students. User logs containing…

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

Science.gov (United States)

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling Patterns of Activities using Activity Curves.

Science.gov (United States)

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-06-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

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

Science.gov (United States)

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.

Discharge competence and pattern formation in peatlands: a meta-ecosystem model of the Everglades ridge-slough landscape.

Directory of Open Access Journals (Sweden)

James B Heffernan

Full Text Available Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1 this mechanism can produce spontaneous divergence of local elevation; 2 divergent and homogenous states can exhibit global bi-stability; and 3 feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.

Real-time nonlinear feedback control of pattern formation in (bio)chemical reaction-diffusion processes: a model study.

Science.gov (United States)

Brandt-Pollmann, U; Lebiedz, D; Diehl, M; Sager, S; Schlöder, J

2005-09-01

Theoretical and experimental studies related to manipulation of pattern formation in self-organizing reaction-diffusion processes by appropriate control stimuli become increasingly important both in chemical engineering and cellular biochemistry. In a model study, we demonstrate here exemplarily the application of an efficient nonlinear model predictive control (NMPC) algorithm to real-time optimal feedback control of pattern formation in a bacterial chemotaxis system modeled by nonlinear partial differential equations. The corresponding drift-diffusion model type is representative for many (bio)chemical systems involving nonlinear reaction dynamics and nonlinear diffusion. We show how the computed optimal feedback control strategy exploits the system inherent physical property of wave propagation to achieve desired control aims. We discuss various applications of our approach to optimal control of spatiotemporal dynamics.

Influence of model boundary conditions on blood flow patterns in a patient specific stenotic right coronary artery.

Science.gov (United States)

Liu, Biyue; Zheng, Jie; Bach, Richard; Tang, Dalin

2015-01-01

In literature, the effect of the inflow boundary condition was investigated by examining the impact of the waveform and the shape of the spatial profile of the inlet velocity on the cardiac hemodynamics. However, not much work has been reported on comparing the effect of the different combinations of the inlet/outlet boundary conditions on the quantification of the pressure field and flow distribution patterns in stenotic right coronary arteries. Non-Newtonian models were used to simulate blood flow in a patient-specific stenotic right coronary artery and investigate the influence of different boundary conditions on the phasic variation and the spatial distribution patterns of blood flow. The 3D geometry of a diseased artery segment was reconstructed from a series of IVUS slices. Five different combinations of the inlet and the outlet boundary conditions were tested and compared. The temporal distribution patterns and the magnitudes of the velocity, the wall shear stress (WSS), the pressure, the pressure drop (PD), and the spatial gradient of wall pressure (WPG) were different when boundary conditions were imposed using different pressure/velocity combinations at inlet/outlet. The maximum velocity magnitude in a cardiac cycle at the center of the inlet from models with imposed inlet pressure conditions was about 29% lower than that from models using fully developed inlet velocity data. Due to the fact that models with imposed pressure conditions led to blunt velocity profile, the maximum wall shear stress at inlet in a cardiac cycle from models with imposed inlet pressure conditions was about 29% higher than that from models with imposed inlet velocity boundary conditions. When the inlet boundary was imposed by a velocity waveform, the models with different outlet boundary conditions resulted in different temporal distribution patterns and magnitudes of the phasic variation of pressure. On the other hand, the type of different boundary conditions imposed at the

PREDICTION OF BLOOD PATTERN IN S-SHAPED MODEL OF ARTERY UNDER NORMAL BLOOD PRESSURE

Directory of Open Access Journals (Sweden)

Mohd Azrul Hisham Mohd Adib

2013-06-01

Full Text Available Athletes are susceptible to a wide variety of traumatic and non-traumatic vascular injuries to the lower limb. This paper aims to predict the three-dimensional flow pattern of blood through an S-shaped geometrical artery model. This model has created by using Fluid Structure Interaction (FSI software. The modeling of the geometrical S-shaped artery is suitable for understanding the pattern of blood flow under constant normal blood pressure. In this study, a numerical method is used that works on the assumption that the blood is incompressible and Newtonian; thus, a laminar type of flow can be considered. The authors have compared the results with a previous study with FSI validation simulation. The validation and verification of the simulation studies is performed by comparing the maximum velocity at t = 0.4 s, because at this time, the blood accelerates rapidly. In addition, the resulting blood flow at various times, under the same boundary conditions in the S-shaped geometrical artery model, is presented. The graph shows that velocity increases linearly with time. Thus, it can be concluded that the flow of blood increases with respect to the pressure inside the body.

Active patterning and asymmetric transport in a model actomyosin network

Energy Technology Data Exchange (ETDEWEB)

Wang, Shenshen [Department of Chemical Engineering and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Wolynes, Peter G. [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

2013-12-21

Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two-dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two-dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three-dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

Directory of Open Access Journals (Sweden)

Sylvia Hofmann

Full Text Available Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013 from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees. While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

Science.gov (United States)

Hofmann, Sylvia; Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F

2017-01-01

Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

A bio-inspired spatial patterning circuit.

Science.gov (United States)

Chen, Kai-Yuan; Joe, Danial J; Shealy, James B; Land, Bruce R; Shen, Xiling

2014-01-01

Lateral Inhibition (LI) is a widely conserved patterning mechanism in biological systems across species. Distinct from better-known Turing patterns, LI depend on cell-cell contact rather than diffusion. We built an in silico genetic circuit model to analyze the dynamic properties of LI. The model revealed that LI amplifies differences between neighboring cells to push them into opposite states, hence forming stable 2-D patterns. Inspired by this insight, we designed and implemented an electronic circuit that recapitulates LI patterning dynamics. This biomimetic system serve as a physical model to elucidate the design principle of generating robust patterning through spatial feedback, regardless of the underlying devices being biological or electrical.

Water Use Patterns in Vietnamese Hotels: Modeling Toilet and Shower Usage

Directory of Open Access Journals (Sweden)

Kanako Toyosada

2016-03-01

Full Text Available Water saving is a key issue in rapidly developing countries, such as Vietnam, that face various water resource management challenges. This study investigated water-use patterns in a hotel in Ho Chi Minh City in Vietnam. It aimed to quantify the efficiency of water-saving devices through modeling toilet and shower usage patterns, including water consumption. The shift in hourly consumption of cold and hot water was also identified. Analysis revealed that, on average, a full toilet flush occurs 3.3 times/day, a half flush 3.0 times/day, water consumption due to shower usage is 48.1 L/day, showering time is 7.3 min/day and the shower water temperature is 37.7 °C. Shifting levels of hot and cold water use revealed high activity in the morning time and that there are two peaks, occurring in the morning and at night.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

Science.gov (United States)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

Contextual snowflake modelling for pattern warehouse logical design

Indian Academy of Sciences (India)

being managed by the pattern warehouse management system (PWMS) ... The authors pointed out that the necessity to find out the relationship between patterns .... (i) Some customer queries can only be satisfied by specific DM technique.

Patterns and causes of species richness: a general simulation model for macroecology

DEFF Research Database (Denmark)

Gotelli, Nicholas J; Anderson, Marti J; Arita, Hector T

2009-01-01

to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models...... in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges...... in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell...

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

Science.gov (United States)

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

2009-01-01

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

Model-assisted template extraction SRAF application to contact holes patterns in high-end flash memory device fabrication

Science.gov (United States)

Seoud, Ahmed; Kim, Juhwan; Ma, Yuansheng; Jayaram, Srividya; Hong, Le; Chae, Gyu-Yeol; Lee, Jeong-Woo; Park, Dae-Jin; Yune, Hyoung-Soon; Oh, Se-Young; Park, Chan-Ha

2018-03-01

Sub-resolution assist feature (SRAF) insertion techniques have been effectively used for a long time now to increase process latitude in the lithography patterning process. Rule-based SRAF and model-based SRAF are complementary solutions, and each has its own benefits, depending on the objectives of applications and the criticality of the impact on manufacturing yield, efficiency, and productivity. Rule-based SRAF provides superior geometric output consistency and faster runtime performance, but the associated recipe development time can be of concern. Model-based SRAF provides better coverage for more complicated pattern structures in terms of shapes and sizes, with considerably less time required for recipe development, although consistency and performance may be impacted. In this paper, we introduce a new model-assisted template extraction (MATE) SRAF solution, which employs decision tree learning in a model-based solution to provide the benefits of both rule-based and model-based SRAF insertion approaches. The MATE solution is designed to automate the creation of rules/templates for SRAF insertion, and is based on the SRAF placement predicted by model-based solutions. The MATE SRAF recipe provides optimum lithographic quality in relation to various manufacturing aspects in a very short time, compared to traditional methods of rule optimization. Experiments were done using memory device pattern layouts to compare the MATE solution to existing model-based SRAF and pixelated SRAF approaches, based on lithographic process window quality, runtime performance, and geometric output consistency.

Modeling urbanization patterns at a global scale with generative adversarial networks

Science.gov (United States)

Albert, A. T.; Strano, E.; Gonzalez, M.

2017-12-01

Current demographic projections show that, in the next 30 years, global population growth will mostly take place in developing countries. Coupled with a decrease in density, such population growth could potentially double the land occupied by settlements by 2050. The lack of reliable and globally consistent socio-demographic data, coupled with the limited predictive performance underlying traditional urban spatial explicit models, call for developing better predictive methods, calibrated using a globally-consistent dataset. Thus, richer models of the spatial interplay between the urban built-up land, population distribution and energy use are central to the discussion around the expansion and development of cities, and their impact on the environment in the context of a changing climate. In this talk we discuss methods for, and present an analysis of, urban form, defined as the spatial distribution of macroeconomic quantities that characterize a city, using modern machine learning methods and best-available remote-sensing data for the world's largest 25,000 cities. We first show that these cities may be described by a small set of patterns in radial building density, nighttime luminosity, and population density, which highlight, to first order, differences in development and land use across the world. We observe significant, spatially-dependent variance around these typical patterns, which would be difficult to model using traditional statistical methods. We take a first step in addressing this challenge by developing CityGAN, a conditional generative adversarial network model for simulating realistic urban forms. To guide learning and measure the quality of the simulated synthetic cities, we develop a specialized loss function for GAN optimization that incorporates standard spatial statistics used by urban analysis experts. Our framework is a stark departure from both the standard physics-based approaches in the literature (that view urban forms as fractals with a

impact of vegetation on flow routing and sedimentation patterns : three-dimensional modeling for a tidal marsh

NARCIS (Netherlands)

Temmerman, S.; Bouma, T.J.; De Vries, M.B.; Wang, Z.B.; Govers, G.; Herman, P.M.J.

2005-01-01

A three-dimensional hydrodynamic and sediment transport model was used to study the relative impact of (1) vegetation, (2) micro-topography, and (3) water level fluctuations on the spatial flow and sedimentation patterns in a tidal marsh landscape during single inundation events. The model

Impact of vegetation on flow routing and sedimentation patterns : three-dimensional modeling for a tidal marsh

NARCIS (Netherlands)

Temmerman, S.; Bouma, T.J.; Govers, G.; Wang, Z.B.; de Vries, M.B.; Herman, P.M.J.

2005-01-01

A three-dimensional hydrodynamic and sediment transport model was used to study the relative impact of (1) vegetation, (2) micro-topography, and (3) water level fluctuations on the spatial flow and sedimentation patterns in a tidal marsh landscape during single inundation events. The model

Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

Science.gov (United States)

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

2018-04-01

The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

Mechanisms of Left-Right Coordination in Mammalian Locomotor Pattern Generation Circuits: A Mathematical Modeling View

Science.gov (United States)

Talpalar, Adolfo E.; Rybak, Ilya A.

2015-01-01

The locomotor gait in limbed animals is defined by the left-right leg coordination and locomotor speed. Coordination between left and right neural activities in the spinal cord controlling left and right legs is provided by commissural interneurons (CINs). Several CIN types have been genetically identified, including the excitatory V3 and excitatory and inhibitory V0 types. Recent studies demonstrated that genetic elimination of all V0 CINs caused switching from a normal left-right alternating activity to a left-right synchronized “hopping” pattern. Furthermore, ablation of only the inhibitory V0 CINs (V0D subtype) resulted in a lack of left-right alternation at low locomotor frequencies and retaining this alternation at high frequencies, whereas selective ablation of the excitatory V0 neurons (V0V subtype) maintained the left–right alternation at low frequencies and switched to a hopping pattern at high frequencies. To analyze these findings, we developed a simplified mathematical model of neural circuits consisting of four pacemaker neurons representing left and right, flexor and extensor rhythm-generating centers interacting via commissural pathways representing V3, V0D, and V0V CINs. The locomotor frequency was controlled by a parameter defining the excitation of neurons and commissural pathways mimicking the effects of N-methyl-D-aspartate on locomotor frequency in isolated rodent spinal cord preparations. The model demonstrated a typical left-right alternating pattern under control conditions, switching to a hopping activity at any frequency after removing both V0 connections, a synchronized pattern at low frequencies with alternation at high frequencies after removing only V0D connections, and an alternating pattern at low frequencies with hopping at high frequencies after removing only V0V connections. We used bifurcation theory and fast-slow decomposition methods to analyze network behavior in the above regimes and transitions between them. The model

Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts

International Nuclear Information System (INIS)

Fonseca, Jimeno A.; Schlueter, Arno

2015-01-01

Highlights: • A model to describe spatiotemporal building energy demand patterns was developed. • The model integrates existing methods in urban and energy planning domains. • The model is useful to analyze energy efficiency strategies in neighborhoods. • Applicability in educational, urban and energy planning practices was found. - Abstract: We introduce an integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts. The model addresses the need for a comprehensive method to identify present and potential states of building energy consumption in the context of urban transformation. The focus lies on determining the spatiotemporal variability of energy services in both standing and future buildings in the residential, commercial and industrial sectors. This detailed characterization facilitates the assessment of potential energy efficiency measures at the neighborhood and city district scales. In a novel approach we integrated existing methods in urban and energy planning domains such as spatial analysis, dynamic building energy modeling and energy mapping to provide a comprehensive, multi-scale and multi-dimensional model of analysis. The model is part of a geographic information system (GIS), which serves as a platform for the allocation and future dissemination of spatiotemporal data. The model is validated against measured data and a peer model for a city district in Switzerland. In this context, we present practical applications in the analysis of energy efficiency measures in buildings and urban zoning. We furthermore discuss potential applications in educational, urban and energy planning practices

Effects of lead accumulation on the Azolla caroliniana-Anabaena association.

Science.gov (United States)

Roberts, Anne E; Boylen, Charles W; Nierzwicki-Bauer, Sandra A

2014-04-01

The effect of lead accumulation on photopigment production, mineral nutrition, and Anabaena vegetative cell size and heterocyst formation in Azolla caroliniana was investigated. Plants were exposed to 0, 1, 5, 10, and 20 mg L(-1) lead acetate for ten days. Lead accumulation increased when plants were treated with higher lead concentrations. Results revealed a statistically significant decline in total chlorophyll, chlorophyll a, chlorophyll b, and carotenoids in 5, 10, and 20 mg Pb L(-1) treatment groups as compared to plants with 0 or 1 mg Pb L(-1) treatments. No statistically significant change in anthocyanin production was observed. Calcium, magnesium, and zinc concentrations in plants decreased in increasing treatment groups, whereas sodium and potassium concentrations increased. Nitrogen and carbon were also found to decrease in plant tissue. Anabaena vegetative cells decreased in size and heterocyst frequency declined rapidly in a Pb dose-dependent manner. These results indicate that, while A. caroliniana removes lead from aqueous solution, the heavy metal causes physiological and biochemical changes by impairing photosynthesis, changing mineral nutrition, and impeding the growth and formation of heterocysts of the symbiotic cyanobacteria that live within leaf cavities of the fronds. Copyright © 2014. Published by Elsevier Inc.

Modeling patterns of coral bleaching at a remote Central Pacific atoll.

Science.gov (United States)

Williams, Gareth J; Knapp, Ingrid S; Maragos, James E; Davy, Simon K

2010-09-01

A mild bleaching event (9.2% prevalence) at Palmyra Atoll occurred in response to the 2009 ENSO, when mean water temperature reached 29.8-30.1 degrees C. Prevalence among both abundant and sparse taxa varied with no clear pattern in susceptibility relating to coral morphology. Seven taxon-specific models showed that turbidity exacerbated while prior exposure to higher background temperatures alleviated bleaching, with these predictors explaining an average 16.3% and 11.5% variation in prevalence patterns, respectively. Positive associations occurred between bleaching prevalence and both immediate temperature during the bleaching event (average 8.4% variation explained) and increased sand cover (average 3.7%). Despite these associations, mean unexplained variation in prevalence equalled 59%. Lower bleaching prevalence in areas experiencing higher background temperatures suggests acclimation to temperature stress among several coral genera, while WWII modifications may still be impacting the reefs via shoreline sediment re-distribution and increased turbidity, exacerbating coral bleaching susceptibility during periods of high temperature stress. Copyright 2010 Elsevier Ltd. All rights reserved.

Characterizing long-term patterns of weight change in China using latent class trajectory modeling.

Directory of Open Access Journals (Sweden)

Lauren Paynter

Full Text Available Over the past three decades, obesity-related diseases have increased tremendously in China, and are now the leading causes of morbidity and mortality. Patterns of weight change can be used to predict risk of obesity-related diseases, increase understanding of etiology of disease risk, identify groups at particularly high risk, and shape prevention strategies.Latent class trajectory modeling was used to compute weight change trajectories for adults aged 18 to 66 using the China Health and Nutrition Survey (CHNS data (n = 12,611. Weight change trajectories were computed separately for males and females by age group at baseline due to differential age-related patterns of weight gain in China with urbanization. Generalized linear mixed effects models examined the association between weight change trajectories and baseline characteristics including urbanicity, BMI category, age, and year of study entry.Trajectory classes were identified for each of six age-sex subgroups corresponding to various degrees of weight loss, maintenance and weight gain. Baseline BMI status was a significant predictor of trajectory membership for all age-sex subgroups. Baseline overweight/obesity increased odds of following 'initial loss with maintenance' trajectories. We found no significant association between baseline urbanization and trajectory membership after controlling for other covariates.Trajectory analysis identified patterns of weight change for age by gender groups. Lack of association between baseline urbanization status and trajectory membership suggests that living in a rural environment at baseline was not protective. Analyses identified age-specific nuances in weight change patterns, pointing to the importance of subgroup analyses in future research.

Characterization of free breathing patterns with 5D lung motion model

Energy Technology Data Exchange (ETDEWEB)

Zhao Tianyu; Lu Wei; Yang Deshan; Mutic, Sasa; Noel, Camille E.; Parikh, Parag J.; Bradley, Jeffrey D.; Low, Daniel A. [Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri 63110 (United States)

2009-11-15

Purpose: To determine the quiet respiration breathing motion model parameters for lung cancer and nonlung cancer patients. Methods: 49 free breathing patient 4DCT image datasets (25 scans, cine mode) were collected with simultaneous quantitative spirometry. A cross-correlation registration technique was employed to track the lung tissue motion between scans. The registration results were applied to a lung motion model: X-vector=X-vector{sub 0}+{alpha}-vector{beta}-vector f, where X-vector is the position of a piece of tissue located at reference position X-vector{sub 0} during a reference breathing phase (zero tidal volume v, zero airflow f). {alpha}-vector is a parameter that characterizes the motion due to air filling (motion as a function of tidal volume v) and {beta}-vector is the parameter that accounts for the motion due to the imbalance of dynamical stress distributions during inspiration and exhalation that causes lung motion hysteresis (motion as a function of airflow f). The parameters {alpha}-vector and {beta}-vector together provide a quantitative characterization of breathing motion that inherently includes the complex hysteresis interplay. The {alpha}-vector and {beta}-vector distributions were examined for each patient to determine overall general patterns and interpatient pattern variations. Results: For 44 patients, the greatest values of |{alpha}-vector| were observed in the inferior and posterior lungs. For the rest of the patients, |{alpha}-vector| reached its maximum in the anterior lung in three patients and the lateral lung in two patients. The hysteresis motion {beta}-vector had greater variability, but for the majority of patients, |{beta}-vector| was largest in the lateral lungs. Conclusions: This is the first report of the three-dimensional breathing motion model parameters for a large cohort of patients. The model has the potential for noninvasively predicting lung motion. The majority of patients exhibited similar |{alpha}-vector| maps

Nitrogen fixation on a coral reef

Energy Technology Data Exchange (ETDEWEB)

Mague, T.H.; Holm-Hansen, O.

1975-06-01

Benthic, heterocystous blue-green algae (genera Calothrix, Hormothamnion and Nostoc) from Eniwetok Atoll were found to reduce acetylene at rapid rates. Slight acetylene reduction was associated with samples of Rhizoclonium (Chlorophyceae) and Oscillatoria (a cyanophyte lacking heterocysts), but this may have been due to contamination by epiphytes. There was virtually no acetylene reduction by phytoplankton, and nutrient enrichment experiments failed to selectively increase the numbers or activity of N/sub 2/-fixing algae in surface water samples. The Nostoc required light for acetylene reduction. Nitrogen fixation by this species could have supplied up to 11 ..mu..g N/cm/sup 2//day to the ecosystem. (auth)

A Model of Bus Bunching under Reliability-based Passenger Arrival Patterns

OpenAIRE

Fonzone, Achille; Schmöcker, Jan-Dirk; Liu, Ronghui

2015-01-01

If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustr...

Risk attitudes in a changing environment: An evolutionary model of the fourfold pattern of risk preferences.

Science.gov (United States)

Mallpress, Dave E W; Fawcett, Tim W; Houston, Alasdair I; McNamara, John M

2015-04-01

A striking feature of human decision making is the fourfold pattern of risk attitudes, involving risk-averse behavior in situations of unlikely losses and likely gains, but risk-seeking behavior in response to likely losses and unlikely gains. Current theories to explain this pattern assume particular psychological processes to reproduce empirical observations, but do not address whether it is adaptive for the decision maker to respond to risk in this way. Here, drawing on insights from behavioral ecology, we build an evolutionary model of risk-sensitive behavior, to investigate whether particular types of environmental conditions could favor a fourfold pattern of risk attitudes. We consider an individual foraging in a changing environment, where energy is needed to prevent starvation and build up reserves for reproduction. The outcome, in terms of reproductive value (a rigorous measure of evolutionary success), of a one-off choice between a risky and a safe gain, or between a risky and a safe loss, determines the risk-sensitive behavior we should expect to see in this environment. Our results show that the fourfold pattern of risk attitudes may be adaptive in an environment in which conditions vary stochastically but are autocorrelated in time. In such an environment the current options provide information about the likely environmental conditions in the future, which affect the optimal pattern of risk sensitivity. Our model predicts that risk preferences should be both path dependent and affected by the decision maker's current state. (c) 2015 APA, all rights reserved).

Response of biological soil crust diazotrophs to season, altered summer precipitation and year-round increased temperature in an arid grassland of the Colorado Plateau, USA

Directory of Open Access Journals (Sweden)

Chris M Yeager

2012-10-01

Full Text Available Biological soil crusts (biocrusts, which supply significant amounts of fixed nitrogen into terrestrial ecosystems worldwide (~33 Tg y-1, are likely to respond to changes in temperature and precipitation associated with climate change. Using nifH gene-based surveys, we explored variation in the diazotrophic community of biocrusts of the Colorado Plateau, USA in response to season (autumn vs. spring, as well as field manipulations that increased the frequency of small-volume precipitation events and year-round soil temperature. Abundance of nifH genes in biocrusts ranged from 3x106 – 1x108 g-1 soil, and nifH from heterocystous cyanobacteria closely related to Scytonema hyalinum, Spirirestis rafaelensis, and Nostoc commune comprised > 98% of the total. Although there was no apparent seasonal effect on total nifH gene abundance in the biocrusts, T-RFLP analysis revealed a strong seasonal pattern in nifH composition. Spirirestis nifH abundance was estimated to oscillate 1 to >2 orders of magnitude between autumn (low and spring (high. A year-round increase of soil temperature (2 − 3 °C had little effect on the diazotroph community structure over 2 years. Altered summer precipitation had little impact on diazotroph community structure over the first 1.5 years of the study, when natural background patterns across years and seasons superseded any treatment effects. However, after the second summer of treatments, nifH abundance was 2.6 fold lower in biocrusts receiving altered precipitation. Heterocystous cyanobacteria were apparently more resilient to altered precipitation than other cyanobacteria. The results demonstrate that diazotrophic community composition of biocrusts in this semi-arid grassland undergoes strong seasonal shifts and that the abundance of its dominant members decreased in response to more frequent, small-volume precipitation events.

Response of biological soil crust diazotrophs to season, altered summer precipitation, and year-round increased temperature in an arid grassland of the Colorado Plateau, USA

Science.gov (United States)

Yeager, Chris M.; Kuske, Cheryl R.; Carney, Travis D.; Johnson, Shannon L.; Ticknor, Lawrence O.; Belnap, Jayne

2012-01-01

Biological soil crusts (biocrusts), which supply significant amounts of fixed nitrogen into terrestrial ecosystems worldwide (~33Tg y-1), are likely to respond to changes in temperature and precipitation associated with climate change. Using nifH gene-based surveys, we explored variation in the diazotrophic community of biocrusts of the Colorado Plateau, USA in response to season (autumn vs. spring), as well as field manipulations that increased the frequency of small volume precipitation events and year-round soil temperature. Abundance of nifH genes in biocrusts ranged from 3×106 to 1×8 g-1 soil, and nifH from heterocystous cyanobacteria closely related to Scytonema hyalinum, Spirirestis rafaelensis, and Nostoc commune comprised >98% of the total. Although there was no apparent seasonal effect on total nifH gene abundance in the biocrusts, T-RFLP analysis revealed a strong seasonal pattern in nifH composition. Spirirestis nifH abundance was estimated to oscillate 1 to >2 orders of magnitude between autumn (low) and spring (high). A year-round increase of soil temperature (2–3°C) had little effect on the diazotroph community structure over 2 years. Altered summer precipitation had little impact on diazotroph community structure over the first 1.5years of the study, when natural background patterns across years and seasons superseded any treatment effects. However, after the second summer of treatments, nifH abundance was 2.6-fold lower in biocrusts receiving altered precipitation. Heterocystous cyanobacteria were apparently more resilient to altered precipitation than other cyanobacteria. The results demonstrate that diazotrophic community composition of biocrusts in this semi-arid grassland undergoes strong seasonal shifts and that the abundance of its dominant members decreased in response to more frequent, small volume precipitation events.

An evaluation of the coping patterns of rape victims: integration with a schema-based information-processing model.

Science.gov (United States)

Littleton, Heather

2007-08-01

The current study sought to provide an expansion of Resick and Schnicke's information-processing model of interpersonal violence response. Their model posits that interpersonal violence threatens victims' schematic beliefs and that victims can resolve this threat through assimilation, accommodation, or overaccommodation. In addition, it is hypothesized that how victims resolve schematic threat affects their coping strategies. To test this hypothesis, a cluster analysis of rape victims' coping patterns was conducted. Victims' coping patterns were related to distress, self-worth, and rape label in ways consistent with predictions. Thus, future research should focus on the implications of how victims integrate trauma with schemas.

A Data-Driven Modeling Strategy for Smart Grid Power Quality Coupling Assessment Based on Time Series Pattern Matching

Directory of Open Access Journals (Sweden)

Hao Yu

2018-01-01

Full Text Available This study introduces a data-driven modeling strategy for smart grid power quality (PQ coupling assessment based on time series pattern matching to quantify the influence of single and integrated disturbance among nodes in different pollution patterns. Periodic and random PQ patterns are constructed by using multidimensional frequency-domain decomposition for all disturbances. A multidimensional piecewise linear representation based on local extreme points is proposed to extract the patterns features of single and integrated disturbance in consideration of disturbance variation trend and severity. A feature distance of pattern (FDP is developed to implement pattern matching on univariate PQ time series (UPQTS and multivariate PQ time series (MPQTS to quantify the influence of single and integrated disturbance among nodes in the pollution patterns. Case studies on a 14-bus distribution system are performed and analyzed; the accuracy and applicability of the FDP in the smart grid PQ coupling assessment are verified by comparing with other time series pattern matching methods.

Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies.

Science.gov (United States)

Du, Qingyun; Zhang, Mingxiao; Li, Yayan; Luan, Hui; Liang, Shi; Ren, Fu

2016-04-20

Incorporating the information of hypertension, this paper applies Bayesian multi-disease analysis to model the spatial patterns of Ischemic Heart Disease (IHD) risks. Patterns of harmful alcohol intake (HAI) and overweight/obesity are also modelled as they are common risk factors contributing to both IHD and hypertension. The hospitalization data of IHD and hypertension in 2012 were analyzed with three Bayesian multi-disease models at the sub-district level of Shenzhen. Results revealed that the IHD high-risk cluster shifted slightly north-eastward compared with the IHD Standardized Hospitalization Ratio (SHR). Spatial variations of overweight/obesity and HAI were found to contribute most to the IHD patterns. Identified patterns of IHD risk would benefit IHD integrated prevention. Spatial patterns of overweight/obesity and HAI could supplement the current disease surveillance system by providing information about small-area level risk factors, and thus benefit integrated prevention of related chronic diseases. Middle southern Shenzhen, where high risk of IHD, overweight/obesity, and HAI are present, should be prioritized for interventions, including alcohol control, innovative healthy diet toolkit distribution, insurance system revision, and community-based chronic disease intervention. Related health resource planning is also suggested to focus on these areas first.

Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

Science.gov (United States)

Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

Innervation pattern of the suprascapular nerve within supraspinatus: a three-dimensional computer modeling study.

Science.gov (United States)

Hermenegildo, J A; Roberts, S L; Kim, S Y

2014-05-01

The relationship between the innervation pattern of the suprascapular nerve (SSN) and the muscle architecture of supraspinatus has not been thoroughly investigated. The supraspinatus is composed of two architecturally distinct regions: anterior and posterior. Each of these regions is further subdivided into three parts: superficial, middle and deep. The purpose of this study was to investigate the course of the SSN throughout the volume of supraspinatus and to relate the intramuscular branches to the distinct regions and parts of the supraspinatus. The SSN was dissected in thirty formalin embalmed cadaveric specimens and digitized throughout the muscle volume in six of those specimens. The digitized data were modeled using Autodesk(®) Maya(®) 2011. The three-dimensional (3D) models were used to relate the intramuscular innervation pattern to the muscle and tendon architecture defined by Kim et al. (2007, Clin Anat 20:648-655). The SSN bifurcated into two main trunks: medial and lateral. All parts of the anterior region were predominantly innervated by the medial trunk and its proximal and medial branches, whereas all parts of the posterior region predominantly by the lateral trunk and its posterolateral and/or posteromedial branches. The posterior region also received innervation from the proximal branch of the medial trunk in half of the specimens. These findings provide evidence that the anterior and posterior regions are distinct with respect to their innervation. The 3D map of the innervation pattern will aid in planning future clinical studies investigating muscle activation patterns and provide insight into possible injury of the nerve with supraspinatus pathology and surgical techniques. Copyright © 2013 Wiley Periodicals, Inc.

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

Science.gov (United States)

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

2002-12-01

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

Modeling the developmental patterns of auditory evoked magnetic fields in children.

Directory of Open Access Journals (Sweden)

Rupesh Kotecha

Full Text Available BACKGROUND: As magnetoencephalography (MEG is of increasing utility in the assessment of deficits and development delays in brain disorders in pediatrics, it becomes imperative to fully understand the functional development of the brain in children. METHODOLOGY: The present study was designed to characterize the developmental patterns of auditory evoked magnetic responses with respect to age and gender. Sixty children and twenty adults were studied with a 275-channel MEG system. CONCLUSIONS: Three main responses were identified at approximately 46 ms (M50, 71 ms (M70 and 106 ms (M100 in latency for children. The latencies of M70 and M100 shortened with age in both hemispheres; the latency of M50 shortened with age only in the right hemisphere. Analysis of developmental lateralization patterns in children showed that the latency of the right hemispheric evoked responses shortened faster than the corresponding left hemispheric responses. The latency of M70 in the right hemisphere highly correlated to the age of the child. The amplitudes of the M70 responses increased with age and reached their peaks in children 12-14 years of age, after which they decreased with age. The source estimates for the M50 and M70 responses indicated that they were generated in different subareas in the Heschl's gyrus in children, while not localizable in adults. Furthermore, gender also affected developmental patterns. The latency of M70 in the right hemisphere was proposed to be an index of auditory development in children, the modeling equation is 85.72-1.240xAge (yrs. Our results demonstrate that there is a clear developmental pattern in the auditory cortex and underscore the importance of M50 and M70 in the developing brain.

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

Science.gov (United States)

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.

A high-resolution stochastic model of domestic activity patterns and electricity demand

International Nuclear Information System (INIS)

Widen, Joakim; Waeckelgard, Ewa

2010-01-01

Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings' indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.

Optimal Cropping Pattern Based on Multiple Economic, Regional, and Agricultural Sustainability Criteria in Sari, Iran: Application of a Consolidated Model of AHP and Linear Programming

Directory of Open Access Journals (Sweden)

E. Fallahi

2016-10-01

Full Text Available Introduction: Determining a suitable cropping pattern is an important task for planners and requires an exact and realistic decision-making process based on several goals and criteria corresponding to secure the interest of agricultural beneficiaries in long-term. Accordingly, this study reviews the current pattern operated by farmers in Sari, Iran, and intends to provide a cropping pattern that considers the multifold regional and agricultural sustainability criteria along with economic considerations. Materials and Methods: In order to achieve the study goals, a consolidated model of AHP and Linear Programming was applied. For this purpose, we constructed a three-level AHP, including a goal (determining the weight of each crop, seven criteria, and seven alternatives. Profitability, compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop were considered as the criteria in the model. Seven alternative crops including rice, wheat, rapeseed, barley, soybean, clover, and vegetables were considered too. The next step is determining the weight of each criterion with regard to the goal and the weight of each alternative with regard to each criteria. By multiplying these weights, final weights for various crops were obtained from the model. Derived weights for each crop were then applied as objective function coefficients in the Linear Programming model and the model was solved subject to the constraints. Results and Discussion: Optimal cropping pattern determined based on the consolidated model of AHP and Linear Programming and the results compared to a scenario that only looks forward to maximizing the economic interests. Due to the low profitability of rapeseed and barley, these crops eliminated from the pattern in the profit-maximizing scenario. According to the results, the

Compare local pocket and global protein structure models by small structure patterns

KAUST Repository

Cui, Xuefeng

2015-09-09

Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria include root mean squared deviation (RMSD), MaxSub score, TM-score, GDT-TS and GDT-HA scores. All these criteria require calculation of rigid transformations to superimpose the the predicted protein structure to the native protein structure. Yet, how to obtain the rigid transformations is unknown or with high time complexity, and, hence, heuristic algorithms were proposed. In this work, we carefully design various small structure patterns, including the ones specifically tuned for local pockets. Such structure patterns are biologically meaningful, and address the issue of relying on a sufficient number of backbone residue fragments for existing methods. We sample the rigid transformations from these small structure patterns; and the optimal superpositions yield by these small structures are refined and reported. As a result, among 11; 669 pairs of predicted and native local protein pocket models from the CASP10 dataset, the GDT-TS scores calculated by our method are significantly higher than those calculated by LGA. Moreover, our program is computationally much more efficient. Source codes and executables are publicly available at http://www.cbrc.kaust.edu.sa/prosta/

Geodesic patterns

KAUST Repository

Pottmann, Helmut; Huang, Qixing; Deng, Bailin; Schiftner, Alexander; Kilian, Martin; Guibas, Leonidas J.; Wallner, Johannes

2010-01-01

Geodesic curves in surfaces are not only minimizers of distance, but they are also the curves of zero geodesic (sideways) curvature. It turns out that this property makes patterns of geodesics the basic geometric entity when dealing with the cladding of a freeform surface with wooden panels which do not bend sideways. Likewise a geodesic is the favored shape of timber support elements in freeform architecture, for reasons of manufacturing and statics. Both problem areas are fundamental in freeform architecture, but so far only experimental solutions have been available. This paper provides a systematic treatment and shows how to design geodesic patterns in different ways: The evolution of geodesic curves is good for local studies and simple patterns; the level set formulation can deal with the global layout of multiple patterns of geodesics; finally geodesic vector fields allow us to interactively model geodesic patterns and perform surface segmentation into panelizable parts. © 2010 ACM.

Geodesic patterns

KAUST Repository

Pottmann, Helmut

2010-07-26

Geodesic curves in surfaces are not only minimizers of distance, but they are also the curves of zero geodesic (sideways) curvature. It turns out that this property makes patterns of geodesics the basic geometric entity when dealing with the cladding of a freeform surface with wooden panels which do not bend sideways. Likewise a geodesic is the favored shape of timber support elements in freeform architecture, for reasons of manufacturing and statics. Both problem areas are fundamental in freeform architecture, but so far only experimental solutions have been available. This paper provides a systematic treatment and shows how to design geodesic patterns in different ways: The evolution of geodesic curves is good for local studies and simple patterns; the level set formulation can deal with the global layout of multiple patterns of geodesics; finally geodesic vector fields allow us to interactively model geodesic patterns and perform surface segmentation into panelizable parts. © 2010 ACM.

Modeling the differentiation of A- and C-type baroreceptor firing patterns

DEFF Research Database (Denmark)

Sturdy, Jacob; Ottesen, Johnny T.; Olufsen, Mette

2017-01-01

The baroreceptor neurons serve as the primary transducers of blood pressure for the autonomic nervous system and are thus critical in enabling the body to respond effectively to changes in blood pressure. These neurons can be separated into two types (A and C) based on the myelination...... of their axons and their distinct firing patterns elicited in response to specific pressure stimuli. This study has developed a comprehensive model of the afferent baroreceptor discharge built on physiological knowledge of arterial wall mechanics, firing rate responses to controlled pressure stimuli, and ion...

Global stability and pattern formation in a nonlocal diffusive Lotka-Volterra competition model

Science.gov (United States)

Ni, Wenjie; Shi, Junping; Wang, Mingxin

2018-06-01

A diffusive Lotka-Volterra competition model with nonlocal intraspecific and interspecific competition between species is formulated and analyzed. The nonlocal competition strength is assumed to be determined by a diffusion kernel function to model the movement pattern of the biological species. It is shown that when there is no nonlocal intraspecific competition, the dynamics properties of nonlocal diffusive competition problem are similar to those of classical diffusive Lotka-Volterra competition model regardless of the strength of nonlocal interspecific competition. Global stability of nonnegative constant equilibria are proved using Lyapunov or upper-lower solution methods. On the other hand, strong nonlocal intraspecific competition increases the system spatiotemporal dynamic complexity. For the weak competition case, the nonlocal diffusive competition model may possess nonconstant positive equilibria for some suitably large nonlocal intraspecific competition coefficients.

Pattern-mixture models for analyzing normal outcome data with proxy respondents.

Science.gov (United States)

Shardell, Michelle; Hicks, Gregory E; Miller, Ram R; Langenberg, Patricia; Magaziner, Jay

2010-06-30

Studies of older adults often involve interview questions regarding subjective constructs such as perceived disability. In some studies, when subjects are unable (e.g. due to cognitive impairment) or unwilling to respond to these questions, proxies (e.g. relatives or other care givers) are recruited to provide responses in place of the subject. Proxies are usually not approached to respond on behalf of subjects who respond for themselves; thus, for each subject, data from only one of the subject or proxy are available. Typically, proxy responses are simply substituted for missing subject responses, and standard complete-data analyses are performed. However, this approach may introduce measurement error and produce biased parameter estimates. In this paper, we propose using pattern-mixture models that relate non-identifiable parameters to identifiable parameters to analyze data with proxy respondents. We posit three interpretable pattern-mixture restrictions to be used with proxy data, and we propose estimation procedures using maximum likelihood and multiple imputation. The methods are applied to a cohort of elderly hip-fracture patients. (c) 2010 John Wiley & Sons, Ltd.

Comparison of bioassays with different exposure time patterns: the added value of dynamic modelling in predictive ecotoxicology.

Science.gov (United States)

Billoir, Elise; Delhaye, Hèlène; Forfait, Carole; Clément, Bernard; Triffault-Bouchet, Gaëlle; Charles, Sandrine; Delignette-Muller, Marie Laure

2012-01-01

The purpose of this study was to compare Daphnia magna responses to cadmium between two toxicity experiments performed in static and flow-through conditions. As a consequence of how water was renewed, the two experiments were characterised by two different exposure time patterns for daphnids, time-varying and constant, respectively. Basing on survival, growth and reproduction, we addressed the questions of organism development and sensitivity to cadmium. Classical analysis methods are not designed to deal with the time dimension and therefore not suitable to compare effects of different exposure time patterns. We used instead a dynamic modelling framework taking all timepoints and the time course of exposure into account, making comparable the results obtained from our two experiments. This modelling framework enabled us to detect an improvement of organism development in flow-through conditions compared to static ones and infer similar sensitivity to cadmium for both exposure time patterns. Copyright © 2011 Elsevier Inc. All rights reserved.

Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies

Directory of Open Access Journals (Sweden)

Qingyun Du

2016-04-01

Full Text Available Incorporating the information of hypertension, this paper applies Bayesian multi-disease analysis to model the spatial patterns of Ischemic Heart Disease (IHD risks. Patterns of harmful alcohol intake (HAI and overweight/obesity are also modelled as they are common risk factors contributing to both IHD and hypertension. The hospitalization data of IHD and hypertension in 2012 were analyzed with three Bayesian multi-disease models at the sub-district level of Shenzhen. Results revealed that the IHD high-risk cluster shifted slightly north-eastward compared with the IHD Standardized Hospitalization Ratio (SHR. Spatial variations of overweight/obesity and HAI were found to contribute most to the IHD patterns. Identified patterns of IHD risk would benefit IHD integrated prevention. Spatial patterns of overweight/obesity and HAI could supplement the current disease surveillance system by providing information about small-area level risk factors, and thus benefit integrated prevention of related chronic diseases. Middle southern Shenzhen, where high risk of IHD, overweight/obesity, and HAI are present, should be prioritized for interventions, including alcohol control, innovative healthy diet toolkit distribution, insurance system revision, and community-based chronic disease intervention. Related health resource planning is also suggested to focus on these areas first.

Characterization of the hupSL promoter activity in Nostoc punctiforme ATCC 29133

Science.gov (United States)

2009-01-01

Background In cyanobacteria three enzymes are directly involved in the hydrogen metabolism; a nitrogenase that produces molecular hydrogen, H2, as a by-product of nitrogen fixation, an uptake hydrogenase that recaptures H2 and oxidize it, and a bidirectional hydrogenase that can both oxidize and produce H2.Nostoc punctiforme ATCC 29133 is a filamentous dinitrogen fixing cyanobacterium containing a nitrogenase and an uptake hydrogenase but no bidirectional hydrogenase. Generally, little is known about the transcriptional regulation of the cyanobacterial uptake hydrogenases. In this study gel shift assays showed that NtcA has a specific affinity to a region of the hupSL promoter containing a predicted NtcA binding site. The predicted NtcA binding site is centred at 258.5 bp upstream the transcription start point (tsp). To further investigate the hupSL promoter, truncated versions of the hupSL promoter were fused to either gfp or luxAB, encoding the reporter proteins Green Fluorescent Protein and Luciferase, respectively. Results Interestingly, all hupsSL promoter deletion constructs showed heterocyst specific expression. Unexpectedly the shortest promoter fragment, a fragment covering 57 bp upstream and 258 bp downstream the tsp, exhibited the highest promoter activity. Deletion of the NtcA binding site neither affected the expression to any larger extent nor the heterocyst specificity. Conclusion Obtained data suggest that the hupSL promoter in N. punctiforme is not strictly dependent on the upstream NtcA cis element and that the shortest promoter fragment (-57 to tsp) is enough for a high and heterocyst specific expression of hupSL. This is highly interesting because it indicates that the information that determines heterocyst specific gene expression might be confined to this short sequence or in the downstream untranslated leader sequence. PMID:19284581

Characterization of the hupSL promoter activity in Nostoc punctiforme ATCC 29133

Directory of Open Access Journals (Sweden)

Lindberg Pia

2009-03-01

Full Text Available Abstract Background In cyanobacteria three enzymes are directly involved in the hydrogen metabolism; a nitrogenase that produces molecular hydrogen, H2, as a by-product of nitrogen fixation, an uptake hydrogenase that recaptures H2 and oxidize it, and a bidirectional hydrogenase that can both oxidize and produce H2.Nostoc punctiforme ATCC 29133 is a filamentous dinitrogen fixing cyanobacterium containing a nitrogenase and an uptake hydrogenase but no bidirectional hydrogenase. Generally, little is known about the transcriptional regulation of the cyanobacterial uptake hydrogenases. In this study gel shift assays showed that NtcA has a specific affinity to a region of the hupSL promoter containing a predicted NtcA binding site. The predicted NtcA binding site is centred at 258.5 bp upstream the transcription start point (tsp. To further investigate the hupSL promoter, truncated versions of the hupSL promoter were fused to either gfp or luxAB, encoding the reporter proteins Green Fluorescent Protein and Luciferase, respectively. Results Interestingly, all hupsSL promoter deletion constructs showed heterocyst specific expression. Unexpectedly the shortest promoter fragment, a fragment covering 57 bp upstream and 258 bp downstream the tsp, exhibited the highest promoter activity. Deletion of the NtcA binding site neither affected the expression to any larger extent nor the heterocyst specificity. Conclusion Obtained data suggest that the hupSL promoter in N. punctiforme is not strictly dependent on the upstream NtcA cis element and that the shortest promoter fragment (-57 to tsp is enough for a high and heterocyst specific expression of hupSL. This is highly interesting because it indicates that the information that determines heterocyst specific gene expression might be confined to this short sequence or in the downstream untranslated leader sequence.

Control Theoretic Modeling and Generated Flow Patterns of a Fish-Tail Robot

Science.gov (United States)

Massey, Brian; Morgansen, Kristi; Dabiri, Dana

2003-11-01

Many real-world engineering problems involve understanding and manipulating fluid flows. One of the challenges to further progress in the area of active flow control is the lack of appropriate models that are amenable to control-theoretic studies and algorithm design and also incorporate reasonably realistic fluid dynamic effects. We focus here on modeling and model-verification of bio-inspired actuators (fish-fin type structures) used to control fluid dynamic artifacts that will affect speed, agility, and stealth of Underwater Autonomous Vehicles (UAVs). Vehicles using fish-tail type systems are more maneuverable, can turn in much shorter and more constrained spaces, have lower drag, are quieter and potentially more efficient than those using propellers. We will present control-theoretic models for a simple prototype coupled fluid and mechanical actuator where fluid effects are crudely modeled by assuming only lift, drag, and added mass, while neglecting boundary effects. These models will be tested with different control input parameters on an experimental fish-tail robot with the resulting flow captured with DPIV. Relations between the model, the control function choices, the obtained thrust and drag, and the corresponding flow patterns will be presented and discussed.

A model of phone call intervention in sensitizing the change of dietary pattern

Directory of Open Access Journals (Sweden)

Eliane Corrêa Chaves

2010-06-01

Full Text Available Objective: To propose a model of phone call intervention for changing dietary patterns and to assess its effectiveness. Method: A study carried out at the Health Promotion School of Medicine, University of São Paulo, with 27 subjects, 3-5 phone calls contacts per user, by means of which were given orientations and interventions on the principles of Cognitive Behavioral Therapy and the Transtheoretical Model on healthy eating. We analyzed the variables weight and body mass index, dietary patterns and overall stage of motivation to change. The data were submitted to analysis of variance with repeated measures at different stages of evaluation: pre-contact, 3rd and 5th phone calls. Results: After intervention, users showed a change in eating behavior in the third contact, and change occurred in weight and BMI in one patient. All findings were not statistically significant. There was improvement in the motivation to acquire new eating habits, also not significant. Conclusion: There was a slight change in feeding behavior, the motivation to change improved for all participants, without, however, have been effective in this type of approach.

Dorsoventral patterning by the Chordin-BMP pathway: a unified model from a pattern-formation perspective for Drosophila, vertebrates, sea urchins and Nematostella.

Science.gov (United States)

Meinhardt, Hans

2015-09-01

Conserved from Cnidarians to vertebrates, the dorsoventral (DV) axis is patterned by the Chordin-BMP pathway. However, the functions of the pathway's components are very different in different phyla. By modeling it is shown that many observations can be integrated by the assumption that BMP, acting as an inhibitory component in more ancestral systems, became a necessary and activating component for the generation of a secondary and antipodal-located signaling center. The different realizations seen in vertebrates, Drosophila, sea urchins and Nematostella allow reconstruction of a chain of modifications during evolution. BMP-signaling is proposed to be based on a pattern-forming reaction of the activator-depleted substrate type in which BMP-signaling acts via pSmad as the local self-enhancing component and the depletion of the highly mobile BMP-Chordin complex as the long-ranging antagonistic component. Due to the rapid removal of the BMP/Chordin complex during BMP-signaling, an oriented transport and "shuttling" results, although only ordinary diffusion is involved. The system can be self-organizing, allowing organizer formation even from near homogeneous initial situations. Organizers may regenerate after removal. Although connected with some losses of self-regulation, for large embryos as in amphibians, the employment of maternal determinants is an efficient strategy to make sure that only a single organizer of each type is generated. The generation of dorsoventral positional information along a long-extended anteroposterior (AP) axis cannot be achieved directly by a single patch-like organizer. Nature found different solutions for this task. Corresponding models provide a rationale for the well-known reversal in the dorsoventral patterning between vertebrates and insects. Copyright © 2015 Elsevier Inc. All rights reserved.

Biochemical changes induced by fungicides in nitrogen fixing Nostoc sp.

Science.gov (United States)

Deviram, G V N S; Pant, Gaurav; Prasuna, R Gyana

2013-01-01

The present study indicates the effect of fungicides (approved by WHO) and their behavior on nitrogen fixer of rice eco system Nostoc sp. Application of plant protecting chemicals at recommended levels braced up the growth of blue green algae thereby enhancing heterocyst formation and nitrogenase activity. Nostoc sp demoed varying degrees of sensitivity to fungicides. Biomass yield, protein, carbohydrate content reduced after 3pg/mL concentration. Heterocyst damage was observed from 4μg/mL, Proline content increased with increase in fungicide concentration, utmost yellowing of the culture started from 4μg/mL. The decreasing order of the toxicity to Nostoc sp with fungicides was Mancozeb> Ediphenphos> Carbendazim> Hexaconazole.

Models for positional signalling, the threefold subdivision of segments and the pigmentation pattern of molluscs.

Science.gov (United States)

Meinhardt, H

1984-11-01

Models of biological pattern formation are discussed. The regulatory features expected from the models are compared to those observed experimentally. It will be shown that: (i) Stable gradients appropriate to supply positional information can be produced by local autocatalysis and long-range inhibition. (ii) Spatially ordered sequences of differentiated cell states can emerge if these cell states mutually activate each other on long range but exclude each other locally. Segmentation results from the repetition of three such cell states, S, A and P (and not of only two, as is usually assumed). With a repetition of three states, each segment has a defined polarity. The confrontation of P cells and S cells lead to the formation of a segment border (...P/SAP/SAP/S...) while the A-P confrontation is a prerequisite for appendage formation. Mutations of Drosophila affecting larval segmentation are discussed in terms of this model. (iii) The two models for the generation of sequences of structures in space (positional information including interpretation versus mutual activation) lead to different predictions with respect to intercalary regeneration. This allows a distinction between the two models on the basis of experiments. (iv) The pigmentation patterns of certain molluscs emerge from a coupled oscillation of cells (that is, a lateral inhibition in time, instead of space). The oblique lines result from a chain of triggering events.

Statistical Methods for Detecting and Modeling General Patterns and Relationships in Lifetime Data

Energy Technology Data Exchange (ETDEWEB)

Kvaloey, Jan Terje

1999-04-01

In this thesis, the author tries to develop methods of detecting and modeling general patterns and relationships in lifetime data. Tests with power against nonmonotonic trends and nonmonotonic co variate effects are considered, and nonparametric regression methods which allow estimation of fairly general nonlinear relationships are studied. Practical uses of some of the methods are illustrated although in a medical rather than engineering or technological context.

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

Science.gov (United States)

Parto, Sahar; Lartillot, Nicolas

2017-06-23

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

Cohesive zone modelling of wafer bonding and fracture: effect of patterning and toughness variations

Science.gov (United States)

Kubair, D. V.; Spearing, S. M.

2006-03-01

Direct wafer bonding has increasingly become popular in the manufacture of microelectromechanical systems and semiconductor microelectronics components. The success of the bonding process is controlled by variables such as wafer flatness and surface preparation. In order to understand the effects of these variables, spontaneous planar crack propagation simulations were performed using the spectral scheme in conjunction with a cohesive zone model. The fracture-toughness on the bond interface is varied to simulate the effect of surface roughness (nanotopography) and patterning. Our analysis indicated that the energetics of crack propagation is sensitive to the local surface property variations. The patterned wafers are tougher (well bonded) than the unpatterned ones of the same average fracture-toughness.

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

Science.gov (United States)

Fernández, Alfonso; Najafi, Mohammad Reza; Durand, Michael; Mark, Bryan G.; Moritz, Mark; Jung, Hahn Chul; Neal, Jeffrey; Shastry, Apoorva; Laborde, Sarah; Phang, Sui Chian; Hamilton, Ian M.; Xiao, Ningchuan

2016-08-01

Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km2, compared to peak inundation greater than 6000 km2. Predicted discharge downstream of the floodplain matched measurements (Nash-Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic

Effect of training the communication skills with cognitive-behavioral model to drug dependent couples on communication patterns and recurrent relapse

Directory of Open Access Journals (Sweden)

M. Rahbarian

2016-12-01

Full Text Available Background: One of the main challenges in methadone maintenance treatment is relapse and lack of sustainability on treatment. Therefore, considering the effective factors in this regard and reducing it through psychological interventions as an adjunct to medication is necessary. Objective: The current study aimed to determine the effectiveness of communication skill training based on cognitive-behavioral model on communication patterns and recurrent relapse in drug dependent couples. Methods: This study was a quasi-experimental intervention with pretest-posttest and control group in 2013 which carried on 40 couple referred to public addiction treatment center of Qazvin city. These people had troubled communication patterns and were selected using convenience sampling and were divided into two groups of intervention and control, randomly. Two groups were assessed by relapse prediction scale (RPS and structured clinical interview for DSM (SCID-I for men and communication pattern questionnaire (CPQ for couples in pre and post-test. Intervention group received 9 two hours sessions of communication skill training based on cognitive-behavioral model. Data were analyzed using Levin and Box tests and multivariate analysis of covariance (MANCOVA. Findings: The difference between the intervention and control groups in the constructive communication pattern with 51% (p<0/05, in mutual avoidance pattern with 61% (p<0/0001 and in the demand / withdraw pattern with 45% (p<0/05 was statistically significant. Also, the difference between the two groups in the rate of relapse with 64% (p<0/0001 was statistically significant. Conclusion: According to the findings it seems group training of communication skill based on cognitive-behavioral model can improve the communication patterns in drug-dependent couples, as well as prevents relapse in men.

A Buffer Model Account of Behavioral and ERP Patterns in the Von Restorff Paradigm

Directory of Open Access Journals (Sweden)

Siri-Maria Kamp

2016-06-01

Full Text Available We combined a mechanistic model of episodic encoding with theories on the functional significance of two event-related potential (ERP components to develop an integrated account for the Von Restorff effect, which refers to the enhanced recall probability for an item that deviates in some feature from other items in its study list. The buffer model of Lehman and Malmberg (2009, 2013 can account for this effect such that items encountered during encoding enter an episodic buffer where they are actively rehearsed. When a deviant item is encountered, in order to re-allocate encoding resources towards this item the buffer is emptied from its prior content, a process labeled “compartmentalization”. Based on theories on their functional significance, the P300 component of the ERP may co-occur with this hypothesized compartmentalization process, while the frontal slow wave may index rehearsal. We derived predictions from this integrated model for output patterns in free recall, systematic variance in ERP components, as well as associations between the two types of measures in a dataset of 45 participants who studied and freely recalled lists of the Von Restorff type. Our major predictions were confirmed and the behavioral and physiological results were consistent with the predictions derived from the model. These findings demonstrate that constraining mechanistic models of episodic memory with brain activity patterns and generating predictions for relationships between brain activity and behavior can lead to novel insights into the relationship between the brain, the mind, and behavior.

Patterns in natural systems

NARCIS (Netherlands)

Sewalt, L.

2016-01-01

In the thesis, `Patterns in natural systems’ the formation and evolution of patterns as solutions of several partial differential systems are studied. These mathematical systems model three different biological and ecological processes. First, the way that plankton concentrates in the water column,

Continental rift architecture and patterns of magma migration: a dynamic analysis based on centrifuge models.

NARCIS (Netherlands)

Corti, G.; Bonini, M.; Sokoutis, D.; Innocenti, F.; Manetti, P.; Cloetingh, S.A.P.L.; Mulugeta, G.

2004-01-01

Small-scale centrifuge models were used to investigate the role of continental rift structure in controlling patterns of magma migration and emplacement. Experiments considered the reactivation of weakness zones in the lower crust and the presence of magma at Moho depths. Results suggest that

Zebrafish: an exciting model for investigating the spatio-temporal pattern of enteric nervous system development.

LENUS (Irish Health Repository)

Doodnath, Reshma

2012-02-01

AIM: Recently, the zebrafish (Danio rerio) has been shown to be an excellent model for human paediatric research. Advantages over other models include its small size, externally visually accessible development and ease of experimental manipulation. The enteric nervous system (ENS) consists of neurons and enteric glia. Glial cells permit cell bodies and processes of neurons to be arranged and maintained in a proper spatial arrangement, and are essential in the maintenance of basic physiological functions of neurons. Glial fibrillary acidic protein (GFAP) is expressed in astrocytes, but also expressed outside of the central nervous system. The aim of this study was to investigate the spatio-temporal pattern of GFAP expression in developing zebrafish ENS from 24 h post-fertilization (hpf), using transgenic fish that express green fluorescent protein (GFP). METHODS: Zebrafish embryos were collected from transgenic GFP Tg(GFAP:GFP)(mi2001) adult zebrafish from 24 to 120 hpf, fixed and processed for whole mount immunohistochemistry. Antibodies to Phox2b were used to identify enteric neurons. Specimens were mounted on slides and imaging was performed using a fluorescent laser confocal microscope. RESULTS: GFAP:GFP labelling outside the spinal cord was identified in embryos from 48 hpf. The patterning was intracellular and consisted of elongated profiles that appeared to migrate away from the spinal cord into the periphery. At 72 and 96 hpf, GFAP:GFP was expressed dorsally and ventrally to the intestinal tract. At 120 hpf, GFAP:GFP was expressed throughout the intestinal wall, and clusters of enteric neurons were identified using Phox2b immunofluorescence along the pathway of GFAP:GFP positive processes, indicative of a migratory pathway of ENS precursors from the spinal cord into the intestine. CONCLUSION: The pattern of migration of GFAP:GFP expressing cells outside the spinal cord suggests an organized, early developing migratory pathway to the ENS. This shows for the

Workflow patterns the definitive guide

CERN Document Server

Russell, Nick; ter Hofstede, Arthur H M

2016-01-01

The study of business processes has emerged as a highly effective approach to coordinating an organization's complex service- and knowledge-based activities. The growing field of business process management (BPM) focuses on methods and tools for designing, enacting, and analyzing business processes. This volume offers a definitive guide to the use of patterns, which synthesize the wide range of approaches to modeling business processes. It provides a unique and comprehensive introduction to the well-known workflow patterns collection -- recurrent, generic constructs describing common business process modeling and execution scenarios, presented in the form of problem-solution dialectics. The underlying principles of the patterns approach ensure that they are independent of any specific enabling technology, representational formalism, or modeling approach, and thus broadly applicable across the business process modeling and business process technology domains. The authors, drawing on extensive research done by...

Objective measurement of intraocular forward light scatter using Hartmann-Shack spot patterns from clinical aberrometers. Model-eye and human-eye study.

Science.gov (United States)

Cerviño, Alejandro; Bansal, Dheeraj; Hosking, Sarah L; Montés-Micó, Robert

2008-07-01

To apply software-based image-analysis tools to objectively determine intraocular scatter determined from clinically derived Hartmann-Shack patterns. Aston Academy of Life Sciences, Aston University, Birmingham, United Kingdom, and Department of Optics, University of Valencia, Valencia, Spain. Purpose-designed image-analysis software was used to quantify scatter from centroid patterns obtained using a clinical Hartmann-Shack analyzer (WASCA, Zeiss/Meditec). Three scatter values, as the maximum standard deviation within a lenslet for all lenslets in the pattern, were obtained in 6 model eyes and 10 human eyes. In the model-eye sample, patterns were obtained in 4 sessions: 2 without realigning between measurements, 1 with realignment, and 1 with an angular shift of 6 degrees from the instrument axis. Three measurements were made in the human eyes with the C-Quant straylight meter (Oculus) to obtain psychometric and objective measures of retinal straylight. Analysis of variance, intraclass correlation coefficients, coefficient of repeatability (CoR), and correlations were used to determine intrasession and intersession repeatability and the relationship between measures. No significant differences were found between the sessions in the model eye (P=.234). The mean CoR was less than 10% in all model- and human-eye sessions. After incomplete patterns were removed, good correlation was achieved between psychometric and objective scatter measurements despite the small sample size (n=6; r=-0.831; P=.040). The methodology was repeatable in model and human eyes, strong against realignment and misalignment, and sensitive. Clinical application would benefit from effective use of the sensor's dynamic range.

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

Science.gov (United States)

Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Agent-based modelling of shifting cultivation field patterns, Vietnam

DEFF Research Database (Denmark)

Jepsen, Martin Rudbeck; Leisz, S.; Rasmussen, K.

2006-01-01

Shifting cultivation in the Nghe An Province of Vietnam's Northern Mountain Region produces a characteristic land-cover pattern of small and larger fields. The pattern is the result of farmers cultivating either individually or in spatially clustered groups. Using spatially explicit agent...

The ultimate intrinsic signal-to-noise ratio of loop- and dipole-like current patterns in a realistic human head model.

Science.gov (United States)

Pfrommer, Andreas; Henning, Anke

2018-03-13

The ultimate intrinsic signal-to-noise ratio (UISNR) represents an upper bound for the achievable SNR of any receive coil. To reach this threshold a complete basis set of equivalent surface currents is required. This study systematically investigated to what extent either loop- or dipole-like current patterns are able to reach the UISNR threshold in a realistic human head model between 1.5 T and 11.7 T. Based on this analysis, we derived guidelines for coil designers to choose the best array element at a given field strength. Moreover, we present ideal current patterns yielding the UISNR in a realistic body model. We distributed generic current patterns on a cylindrical and helmet-shaped surface around a realistic human head model. We excited electromagnetic fields in the human head by using eigenfunctions of the spherical and cylindrical Helmholtz operator. The electromagnetic field problem was solved by a fast volume integral equation solver. At 7 T and above, adding curl-free current patterns to divergence-free current patterns substantially increased the SNR in the human head (locally >20%). This was true for the helmet-shaped and the cylindrical surface. On the cylindrical surface, dipole-like current patterns had high SNR performance in central regions at ultra-high field strength. The UISNR increased superlinearly with B0 in most parts of the cerebrum but only sublinearly in the periphery of the human head. The combination of loop and dipole elements could enhance the SNR performance in the human head at ultra-high field strength. © 2018 International Society for Magnetic Resonance in Medicine.

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

Science.gov (United States)

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 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 decision tree model was greater than that of the line discriminant model (0.765 vs 0.629, P Decision tree models constructed using functions of R2* values may facilitate the prediction of renal pathological patterns.

Modeling activity patterns of wildlife using time-series analysis.

Science.gov (United States)

Zhang, Jindong; Hull, Vanessa; Ouyang, Zhiyun; He, Liang; Connor, Thomas; Yang, Hongbo; Huang, Jinyan; Zhou, Shiqiang; Zhang, Zejun; Zhou, Caiquan; Zhang, Hemin; Liu, Jianguo

2017-04-01

The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency-based time-series analysis, with high-resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda ( Ailuropoda melanoleuca ). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda's mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24-hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high-resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.

Symmetry breaking patterns of the 3-3-1 model at finite temperature

Energy Technology Data Exchange (ETDEWEB)

Borges, J.S. [Universidade do Estado do Rio de Janeiro, Departamento de Fisica de Altas Energias, Rio de Janeiro, RJ (Brazil); Ramos, Rudnei O. [Universidade do Estado do Rio de Janeiro, Departamento de Fisica Teorica, Rio de Janeiro, RJ (Brazil)

2016-06-15

We consider the minimal version of an extension of the standard electroweak model based on the SU(3){sub c} x SU(3){sub L} x U(1){sub X} gauge symmetry (the 3-3-1 model). We analyze the most general potential constructed from three scalars in the triplet representation of SU(3){sub L}, whose neutral components develop nonzero vacuum expectation values, giving mass for all the model's massive particles. For different choices of parameters, we obtain the particle spectrum for the two symmetry breaking scales: one where the SU(3){sub L} x U(1){sub X} group is broken down to SU(2){sub L} x U(1){sub Y} and a lower scale similar to the standard model one. Within the considerations used, we show that the model encodes two first-order phase transitions, respecting the pattern of symmetry restoration. The last transition, corresponding to the standard electroweak one, is found to be very weak first-order, most likely turning second-order or a crossover in practice. However, the first transition in this model can be strongly first-order, which might happen at a temperature not too high above the second one. We determine the respective critical temperatures for symmetry restoration for the model. (orig.)

Pore network modeling of drainage process in patterned porous media: a quasi-static study

KAUST Repository

Zhang, Tao

2015-04-17

This work represents a preliminary investigation on the role of wettability conditions on the flow of a two-phase system in porous media. Since such effects have been lumped implicitly in relative permeability-saturation and capillary pressure-saturation relationships, it is quite challenging to isolate its effects explicitly in real porous media applications. However, within the framework of pore network models, it is easy to highlight the effects of wettability conditions on the transport of two-phase systems. We employ quasi-static investigation in which the system undergo slow movement based on slight increment of the imposed pressure. Several numerical experiments of the drainage process are conducted to displace a wetting fluid with a non-wetting one. In all these experiments the network is assigned different scenarios of various wettability patterns. The aim is to show that the drainage process is very much affected by the imposed pattern of wettability. The wettability conditions are imposed by assigning the value of contact angle to each pore throat according to predefined patterns.

Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam

NARCIS (Netherlands)

Castella, J.C.; Verburg, P.H.

2007-01-01

The tools and methods developed by different scientific communities to simulate the dynamics of land use have emphasised either processes or patterns of changes. Agent-based models (ABM) belong to the former category while many spatially explicit simulation models belong to the latter. These two

Workflow User Interfaces Patterns

Directory of Open Access Journals (Sweden)

Jean Vanderdonckt

2012-03-01

Full Text Available Este trabajo presenta una colección de patrones de diseño de interfaces de usuario para sistemas de información para el flujo de trabajo; la colección incluye cuarenta y tres patrones clasificados en siete categorías identificados a partir de la lógica del ciclo de vida de la tarea sobre la base de la oferta y la asignación de tareas a los responsables de realizarlas (i. e. recursos humanos durante el flujo de trabajo. Cada patrón de la interfaz de usuario de flujo de trabajo (WUIP, por sus siglas en inglés se caracteriza por las propiedades expresadas en el lenguaje PLML para expresar patrones y complementado por otros atributos y modelos que se adjuntan a dicho modelo: la interfaz de usuario abstracta y el modelo de tareas correspondiente. Estos modelos se especifican en un lenguaje de descripción de interfaces de usuario. Todos los WUIPs se almacenan en una biblioteca y se pueden recuperar a través de un editor de flujo de trabajo que vincula a cada patrón de asignación de trabajo a su WUIP correspondiente.A collection of user interface design patterns for workflow information systems is presented that contains forty three resource patterns classified in seven categories. These categories and their corresponding patterns have been logically identified from the task life cycle based on offering and allocation operations. Each Workflow User Interface Pattern (WUIP is characterized by properties expressed in the PLML markup language for expressing patterns and augmented by additional attributes and models attached to the pattern: the abstract user interface and the corresponding task model. These models are specified in a User Interface Description Language. All WUIPs are stored in a library and can be retrieved within a workflow editor that links each workflow pattern to its corresponding WUIP, thus giving rise to a user interface for each workflow pattern.

Point-Mass Model for Nano-Patterning Using Dip-Pen Nanolithography (DPN

Directory of Open Access Journals (Sweden)

Seok-Won Kang

2011-04-01

Full Text Available Micro-cantilevers are frequently used as scanning probes and sensors in micro-electromechanical systems (MEMS. Usually micro-cantilever based sensors operate by detecting changes in cantilever vibration modes (e.g., bending or torsional vibration frequency or surface stresses - when a target analyte is adsorbed on the surface. The catalyst for chemical reactions (i.e., for a specific analyte can be deposited on micro-cantilevers by using Dip-Pen Nanolithography (DPN technique. In this study, we simulate the vibration mode in nano-patterning processes by using a Point-Mass Model (or Lumped Parameter Model. The results from the simulations are used to derive the stability of writing and reading mode for a particular driving frequency during the DPN process. In addition, we analyze the sensitivity of the tip-sample interaction forces in fluid (ink solution by utilizing the Derjaguin-Muller-Toporov (DMT contact theory.

Tidal-induced large-scale regular bed form patterns in a three-dimensional shallow water model

NARCIS (Netherlands)

Hulscher, Suzanne J.M.H.

1996-01-01

The three-dimensional model presented in this paper is used to study how tidal currents form wave-like bottom patterns. Inclusion of vertical flow structure turns out to be necessary to describe the formation, or absence, of all known large-scale regular bottom features. The tide and topography are

Implementing gait pattern control and transition for legged locomotion

International Nuclear Information System (INIS)

Yang, Zhijun; Karamanoglu, Mehmet; Rocha, Marlon V; França, Felipe M G; Lima, Priscila M V

2014-01-01

In this work, a generalised central pattern generator (CPG) model is formulated to generate a full range of gait patterns for a hexapod insect. To this end, a recurrent neuronal network module, as the building block for rhythmic patterns, is proposed to extend the concept of oscillatory building blocks (OBB) for constructing a CPG model. The model is able to make transitions between different gait patterns by simply adjusting one model parameter. Simulation results are further presented to show the effectiveness and performance of the CPG network

The contribution of a central pattern generator in a reflex-based neuromuscular model

Science.gov (United States)

Dzeladini, Florin; van den Kieboom, Jesse; Ijspeert, Auke

2014-01-01

Although the concept of central pattern generators (CPGs) controlling locomotion in vertebrates is widely accepted, the presence of specialized CPGs in human locomotion is still a matter of debate. An interesting numerical model developed in the 90s’ demonstrated the important role CPGs could play in human locomotion, both in terms of stability against perturbations, and in terms of speed control. Recently, a reflex-based neuro-musculo-skeletal model has been proposed, showing a level of stability to perturbations similar to the previous model, without any CPG components. Although exhibiting striking similarities with human gaits, the lack of CPG makes the control of speed/step length in the model difficult. In this paper, we hypothesize that a CPG component will offer a meaningful way of controlling the locomotion speed. After introducing the CPG component in the reflex model, and taking advantage of the resulting properties, a simple model for gait modulation is presented. The results highlight the advantages of a CPG as feedforward component in terms of gait modulation. PMID:25018712

The Contribution of a Central Pattern Generator in a Reflex-Based Neuromuscular Model

Directory of Open Access Journals (Sweden)

Florin eDzeladini

2014-06-01

Full Text Available Although the concept of central pattern generators (CPGs controlling locomotion in vertebrates is widely accepted, the presence of specialized CPGs in human locomotion is still a matter of debate. An interesting numerical model developed in the 90s' demonstrated the important role CPGs could play in human locomotion, both in terms of stability against perturbations, and in terms of speed control. Recently, a reflex-based neuro-musculo-skeletal model has been proposed, showing a level of stability to perturbations similar to the previous model, without any CPG components. Although exhibiting striking similarities with human gaits, the lack of CPG makes the control of speed/step length in the model difficult. In this paper, we hypothesize that a CPG component will offer a meaningful way of controlling the locomotion speed. After introducing the CPG component in the reflex model, and taking advantage of the resulting properties, a simple model for gait modulation is presented.The results highlight the advantages that a feedforward component can have in terms of gait modulation.

Patterns of breast cancer mortality trends in Europe.

Science.gov (United States)

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.

SESAM – a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

DEFF Research Database (Denmark)

Guisan, Antoine; Rahbek, Carsten

2011-01-01

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts...

Turing patterns and biological explanation

DEFF Research Database (Denmark)

Serban, Maria

2017-01-01

, promoting theory exploration, and acting as constitutive parts of empirically adequate explanations of naturally occurring phenomena, such as biological pattern formation. Focusing on the roles that minimal model explanations play in science motivates the adoption of a broader diachronic view of scientific......Turing patterns are a class of minimal mathematical models that have been used to discover and conceptualize certain abstract features of early biological development. This paper examines a range of these minimal models in order to articulate and elaborate a philosophical analysis...

An ice flow modeling perspective on bedrock adjustment patterns of the Greenland ice sheet

Directory of Open Access Journals (Sweden)

M. Olaizola

2012-11-01

Full Text Available Since the launch in 2002 of the Gravity Recovery and Climate Experiment (GRACE satellites, several estimates of the mass balance of the Greenland ice sheet (GrIS have been produced. To obtain ice mass changes, the GRACE data need to be corrected for the effect of deformation changes of the Earth's crust. Recently, a new method has been proposed where ice mass changes and bedrock changes are simultaneously solved. Results show bedrock subsidence over almost the entirety of Greenland in combination with ice mass loss which is only half of the currently standing estimates. This subsidence can be an elastic response, but it may however also be a delayed response to past changes. In this study we test whether these subsidence patterns are consistent with ice dynamical modeling results. We use a 3-D ice sheet–bedrock model with a surface mass balance forcing based on a mass balance gradient approach to study the pattern and magnitude of bedrock changes in Greenland. Different mass balance forcings are used. Simulations since the Last Glacial Maximum yield a bedrock delay with respect to the mass balance forcing of nearly 3000 yr and an average uplift at present of 0.3 mm yr⁻¹. The spatial pattern of bedrock changes shows a small central subsidence as well as more intense uplift in the south. These results are not compatible with the gravity based reconstructions showing a subsidence with a maximum in central Greenland, thereby questioning whether the claim of halving of the ice mass change is justified.

Modelling human mobility patterns using photographic data shared online.

Science.gov (United States)

Barchiesi, Daniele; Preis, Tobias; Bishop, Steven; Moat, Helen Susannah

2015-08-01

Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns.

Knowledge fusion: An approach to time series model selection followed by pattern recognition

International Nuclear Information System (INIS)

Bleasdale, S.A.; Burr, T.L.; Scovel, J.C.; Strittmatter, R.B.

1996-03-01

This report describes work done during FY 95 that was sponsored by the Department of Energy, Office of Nonproliferation and National Security, Knowledge Fusion Project. The project team selected satellite sensor data to use as the one main example for the application of its analysis algorithms. The specific sensor-fusion problem has many generic features, which make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series that define a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. An accompanying report (Ref 1) describes the implementation and application of this 2-step process for separating events from unusual background and applies a suite of forecasting methods followed by a suite of pattern recognition methods. This report goes into more detail about one of the forecasting methods and one of the pattern recognition methods and is applied to the same kind of satellite-sensor data that is described in Ref. 1

Pattern activation/recognition theory of mind.

Science.gov (United States)

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.

MADS-box gene evolution - structure and transcription patterns

DEFF Research Database (Denmark)

Johansen, Bo; Pedersen, Louise Buchholt; Skipper, Martin

2002-01-01

Mads-box genes, ABC model, Evolution, Phylogeny, Transcription patterns, Gene structure, Conserved motifs......Mads-box genes, ABC model, Evolution, Phylogeny, Transcription patterns, Gene structure, Conserved motifs...

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

Science.gov (United States)

Reuter, H.; Jopp, F.; Blanco-Moreno, J. M.; Damgaard, C.; Matsinos, Y.; DeAngelis, D.L.

2010-01-01

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Nonlinear dynamics of pattern formation and pattern recognition in the rabbit olfactory bulb

Science.gov (United States)

Baird, Bill

1986-10-01

A mathematical model of the process of pattern recognition in the first olfactory sensory cortex of the rabbit is presented. It explains the formation and alteration of spatial patterns in neural activity observed experimentally during classical Pavlovian conditioning. On each inspiration of the animal, a surge of receptor input enters the olfactory bulb. EEG activity recorded at the surface of the bulb undergoes a transition from a low amplitude background state of temporal disorder to coherent oscillation. There is a distinctive spatial pattern of rms amplitude in this oscillation which changes reliably to a second pattern during each successful recognition by the animal of a conditioned stimulus odor. When a new odor is paired as conditioned stimulus, these patterns are replaced by new patterns that stabilize as the animal adapts to the new environment. I will argue that a unification of the theories of pattern formation and associative memory is required to account for these observations. This is achieved in a model of the bulb as a discrete excitable medium with spatially inhomogeneous coupling expressed by a connection matrix. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of competing unstable oscillatory modes. These may be created in the system by proper coupling and selectively evoked by specific classes of inputs. This allows a view of limit cycle attractors as “stored” fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

Capillarity Guided Patterning of Microliquids.

Science.gov (United States)

Kang, Myeongwoo; Park, Woohyun; Na, Sangcheol; Paik, Sang-Min; Lee, Hyunjae; Park, Jae Woo; Kim, Ho-Young; Jeon, Noo Li

2015-06-01

Soft lithography and other techniques have been developed to investigate biological and chemical phenomena as an alternative to photolithography-based patterning methods that have compatibility problems. Here, a simple approach for nonlithographic patterning of liquids and gels inside microchannels is described. Using a design that incorporates strategically placed microstructures inside the channel, microliquids or gels can be spontaneously trapped and patterned when the channel is drained. The ability to form microscale patterns inside microfluidic channels using simple fluid drain motion offers many advantages. This method is geometrically analyzed based on hydrodynamics and verified with simulation and experiments. Various materials (i.e., water, hydrogels, and other liquids) are successfully patterned with complex shapes that are isolated from each other. Multiple cell types are patterned within the gels. Capillarity guided patterning (CGP) is fast, simple, and robust. It is not limited by pattern shape, size, cell type, and material. In a simple three-step process, a 3D cancer model that mimics cell-cell and cell-extracellular matrix interactions is engineered. The simplicity and robustness of the CGP will be attractive for developing novel in vitro models of organ-on-a-chip and other biological experimental platforms amenable to long-term observation of dynamic events using advanced imaging and analytical techniques. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules.

Directory of Open Access Journals (Sweden)

Gregory R Johnson

2015-12-01

Full Text Available Characterizing the spatial distribution of proteins directly from microscopy images is a difficult problem with numerous applications in cell biology (e.g. identifying motor-related proteins and clinical research (e.g. identification of cancer biomarkers. Here we describe the design of a system that provides automated analysis of punctate protein patterns in microscope images, including quantification of their relationships to microtubules. We constructed the system using confocal immunofluorescence microscopy images from the Human Protein Atlas project for 11 punctate proteins in three cultured cell lines. These proteins have previously been characterized as being primarily located in punctate structures, but their images had all been annotated by visual examination as being simply "vesicular". We were able to show that these patterns could be distinguished from each other with high accuracy, and we were able to assign to one of these subclasses hundreds of proteins whose subcellular localization had not previously been well defined. In addition to providing these novel annotations, we built a generative approach to modeling of punctate distributions that captures the essential characteristics of the distinct patterns. Such models are expected to be valuable for representing and summarizing each pattern and for constructing systems biology simulations of cell behaviors.

Fringe pattern denoising using coherence-enhancing diffusion.

Science.gov (United States)

Wang, Haixia; Kemao, Qian; Gao, Wenjing; Lin, Feng; Seah, Hock Soon

2009-04-15

Electronic speckle pattern interferometry is one of the methods measuring the displacement on object surfaces in which fringe patterns need to be evaluated. Noise is one of the key problems affecting further processing and reducing measurement quality. We propose an application of coherence-enhancing diffusion to fringe-pattern denoising. It smoothes a fringe pattern along directions both parallel and perpendicular to fringe orientation with suitable diffusion speeds to more effectively reduce noise and improve fringe-pattern quality. It is a generalized work of Tang's et al.'s [Opt. Lett.33, 2179 (2008)] model that only smoothes a fringe pattern along fringe orientation. Since our model diffuses a fringe pattern with an additional direction, it is able to denoise low-density fringes as well as improve denoising effectiveness for high-density fringes. Theoretical analysis as well as simulation and experimental verifications are addressed.

Improving the Pattern Reproducibility of Multiple-Point-Based Prior Models Using Frequency Matching

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

2014-01-01

Some multiple-point-based sampling algorithms, such as the snesim algorithm, rely on sequential simulation. The conditional probability distributions that are used for the simulation are based on statistics of multiple-point data events obtained from a training image. During the simulation, data...... events with zero probability in the training image statistics may occur. This is handled by pruning the set of conditioning data until an event with non-zero probability is found. The resulting probability distribution sampled by such algorithms is a pruned mixture model. The pruning strategy leads...... to a probability distribution that lacks some of the information provided by the multiple-point statistics from the training image, which reduces the reproducibility of the training image patterns in the outcome realizations. When pruned mixture models are used as prior models for inverse problems, local re...

The seasonal dormancy pattern and germination of Matricaria maritima subsp. inodora (L. Dostal seeds in hydrotime model terms

Directory of Open Access Journals (Sweden)

Anna Bochenek

2011-01-01

Full Text Available Changes in hydrotime model parameters were determined in Matricaria maritima L. subsp. inodora seeds during burial in a field in order to describe the seasonal dormancy pattern. Seeds were exhumed at regular intervals over a year and incubated at different water potentials at 19°C. Germination time courses were analyzed to determine hydrotime population parameters. Values of ѱb(50, ѲH and σѱb varied each month. Mean base water potential values in seeds exhumed each month were related to precipitation over 20 days before their exhumation. Soil temperature could be a trend-controlling factor of this relationship. The seeds were in deep dormancy after remaining 80-90 days in soil below or above limit temperature 15°C. The application of the hydrotime model to describe and predict seasonal dormancy patterns of weed seed is promising, especially for species with a considerable diversification of life strategies and ecophysiological flexibility of diaspores. It could also suggest mechanisms of seasonal dormancy changes of seeds in natural conditions and provide a basis for their examination. One of advantages of the dormancy pattern description of weed seeds remaining in a soil bank by means of threshold models is its simplicity.

Pattern recognition model to estimate intergranular stress corrosion cracking (IGSCC) at crevices and pit sites of 304 SS in BWR environments

International Nuclear Information System (INIS)

Urquidi-Macdonald, Mirna

2004-01-01

Many publications have shown that crack growth rates (CGR) due to intergranular stress corrosion cracking (IGSCC) of metals is dependent on many parameters related to the manufacturing process of the steel and the environment to which the steel is exposed. Those parameters include, but are not restricted to, the concentration of chloride, fluoride, nitrates, and sulfates, pH, fluid velocity, electrochemical potential (ECP), electrolyte conductivity, stress and sensitization applied to the steel during its production and use. It is not well established how combinations of each of these parameters impact the CGR. Many different models and beliefs have been published, resulting in predictions that sometimes disagree with experimental observations. To some extent, the models are the closest to the nature of IGSCC, however, there is not a model that fully describes the entire range of observations, due to the difficulty of the problem. Among the models, the Fracture Environment Model, developed by Macdonald et al., is the most physico-chemical model, accounting for experimental observations in a wide range of environments or ECPs. In this work, we collected experimental data on BWR environments and designed a data mining pattern recognition model to learn from that data. The model was used to generate CGR estimations as a function of ECP on a BWR environment. The results of the predictive model were compared to the Fracture Environment Model predictions. The results from those two models are very close to the experimental observations of the area corresponding to creep and IGSCC controlled by diffusion. At more negative ECPs than the potential corresponding to creep, the pattern recognition predicts an increase of CGR with decreasing ECP, while the Fracture Environment Model predicts the opposite. The results of this comparison confirm that the pattern recognition model covers 3 phenomena: hydrogen embrittlement at very negative ECP, creep at intermediate ECP, and IGSCC

Pattern recognition model to estimate intergranular stress corrosion cracking (IGSCC) at crevices and pit sites of 304 SS in BWR environments

Energy Technology Data Exchange (ETDEWEB)

Urquidi-Macdonald, Mirna [Penn State University, 212 Earth-Engineering Science Building, University Park, PA 16801 (United States)

2004-07-01

Many publications have shown that crack growth rates (CGR) due to intergranular stress corrosion cracking (IGSCC) of metals is dependent on many parameters related to the manufacturing process of the steel and the environment to which the steel is exposed. Those parameters include, but are not restricted to, the concentration of chloride, fluoride, nitrates, and sulfates, pH, fluid velocity, electrochemical potential (ECP), electrolyte conductivity, stress and sensitization applied to the steel during its production and use. It is not well established how combinations of each of these parameters impact the CGR. Many different models and beliefs have been published, resulting in predictions that sometimes disagree with experimental observations. To some extent, the models are the closest to the nature of IGSCC, however, there is not a model that fully describes the entire range of observations, due to the difficulty of the problem. Among the models, the Fracture Environment Model, developed by Macdonald et al., is the most physico-chemical model, accounting for experimental observations in a wide range of environments or ECPs. In this work, we collected experimental data on BWR environments and designed a data mining pattern recognition model to learn from that data. The model was used to generate CGR estimations as a function of ECP on a BWR environment. The results of the predictive model were compared to the Fracture Environment Model predictions. The results from those two models are very close to the experimental observations of the area corresponding to creep and IGSCC controlled by diffusion. At more negative ECPs than the potential corresponding to creep, the pattern recognition predicts an increase of CGR with decreasing ECP, while the Fracture Environment Model predicts the opposite. The results of this comparison confirm that the pattern recognition model covers 3 phenomena: hydrogen embrittlement at very negative ECP, creep at intermediate ECP, and IGSCC

The cyanobacterium Mastigocladus fulfills the nitrogen demand of a terrestrial hot spring microbial mat.

Science.gov (United States)

Estrella Alcamán, María; Fernandez, Camila; Delgado, Antonio; Bergman, Birgitta; Díez, Beatriz

2015-10-01

Cyanobacteria from Subsection V (Stigonematales) are important components of microbial mats in non-acidic terrestrial hot springs. Despite their diazotrophic nature (N2 fixers), their impact on the nitrogen cycle in such extreme ecosystems remains unknown. Here, we surveyed the identity and activity of diazotrophic cyanobacteria in the neutral hot spring of Porcelana (Northern Patagonia, Chile) during 2009 and 2011-2013. We used 16S rRNA and the nifH gene to analyze the distribution and diversity of diazotrophic cyanobacteria. Our results demonstrate the dominance of the heterocystous genus Mastigocladus (Stigonematales) along the entire temperature gradient of the hot spring (69-38 °C). In situ nitrogenase activity (acetylene reduction), nitrogen fixation rates (cellular uptake of (15)N2) and nifH transcription levels in the microbial mats showed that nitrogen fixation and nifH mRNA expression were light-dependent. Nitrogen fixation activities were detected at temperatures ranging from 58 °C to 46 °C, with maximum daily rates of 600 nmol C2H4 cm(-2) per day and 94.1 nmol N cm(-2) per day. These activity patterns strongly suggest a heterocystous cyanobacterial origin and reveal a correlation between nitrogenase activity and nifH gene expression during diurnal cycles in thermal microbial mats. N and C fixation in the mats contributed ~3 g N m(-2) per year and 27 g C m(-2) per year, suggesting that these vital demands are fully met by the diazotrophic and photoautotrophic capacities of the cyanobacteria in the Porcelana hot spring.

Sleep patterning changes in a prenatal stress model of depression

DEFF Research Database (Denmark)

Sickmann, Helle Mark; Skoven, C; Bastlund, Jesper F

2018-01-01

/wakefulness behavior around the change from light-to-dark phase. Control and PNS Sprague-Dawley rats were implanted with electrodes for continuous monitoring of electroencephalic activity used to determine behavioral state. The distribution of slow-wave sleep (SWS), rapid eye movement sleep (REMS) and wakefulness......Clinical depression is accompanied by changes in sleep patterning, which is controlled in a circadian fashion. It is thus desirable that animal models of depression mirror such diurnally-specific state alterations, along with other behavioral and physiological changes. We previously found several...... changes in behavior indicative of a depression-like phenotype in offspring of rats subjected to repeated, variable prenatal stress (PNS), including increased locomotor activity during specific periods of the circadian cycle. We, therefore, investigated whether PNS rats also exhibit alterations in sleep...

High-frequency background modulation fringe patterns based on a fringe-wavelength geometry-constraint model for 3D surface-shape measurement.

Science.gov (United States)

Liu, Xinran; Kofman, Jonathan

2017-07-10

A new fringe projection method for surface-shape measurement was developed using four high-frequency phase-shifted background modulation fringe patterns. The pattern frequency is determined using a new fringe-wavelength geometry-constraint model that allows only two corresponding-point candidates in the measurement volume. The correct corresponding point is selected with high reliability using a binary pattern computed from intensity background encoded in the fringe patterns. Equations of geometry-constraint parameters permit parameter calculation prior to measurement, thus reducing measurement computational cost. Experiments demonstrated the ability of the method to perform 3D shape measurement for a surface with geometric discontinuity, and for spatially isolated objects.

The numerical model of the sediment distribution pattern at Lampulo National fisheries port

Science.gov (United States)

Irham, M.; Setiawan, I.

2018-01-01

The spatial distribution of sediment pattern was studied at Lampulo Fisheries Port, Krueng Aceh estuarial area, Banda Aceh. The research was conducted using the numerical model of wave-induced currents at shallow water area. The study aims to understand how waves and currents react to the pattern of sediment distribution around the beach structure in that region. The study demonstrated that the port pool area had no sedimentation and erosion occurred because the port was protected by the jetty as the breakwater to defend the incoming waves toward the pool. The protected pool created a weak current circulation to distribute the sediments. On the other hand, the sediments were heavily distributed along the beach due to the existence of longshore currents near the shoreline (outside the port pool area). Meanwhile, at the estuarial area, the incoming fresh water flow responded to the coastal shallow water currents, generating Eddy-like flow at the mouth of the river.

Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

Science.gov (United States)

Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

2014-10-01

Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

Occurrence of cyanobacteria (Richelia intracellularis)-diatom (Rhizosolenia hebetata) consortium in the Palk Bay, southeast coast of India

Digital Repository Service at National Institute of Oceanography (India)

Madhu, N.V.; Paul, M.; Ullas, N.; Ashwini, R.; Rehitha, T.V.

Symbiotic association of heterocystous cyanobacterium, Richelia intracellularis Schmidt with oceanic centric diatom, Rhizosolenia hebetata is reported from the Palk Bay, southeast coast of India. One to six trichomes of R. intracellularis were...

A model for size- and rotation-invariant pattern processing in the visual system.

Science.gov (United States)

Reitboeck, H J; Altmann, J

1984-01-01

The mapping of retinal space onto the striate cortex of some mammals can be approximated by a log-polar function. It has been proposed that this mapping is of functional importance for scale- and rotation-invariant pattern recognition in the visual system. An exact log-polar transform converts centered scaling and rotation into translations. A subsequent translation-invariant transform, such as the absolute value of the Fourier transform, thus generates overall size- and rotation-invariance. In our model, the translation-invariance is realized via the R-transform. This transform can be executed by simple neural networks, and it does not require the complex computations of the Fourier transform, used in Mellin-transform size-invariance models. The logarithmic space distortion and differentiation in the first processing stage of the model is realized via "Mexican hat" filters whose diameter increases linearly with eccentricity, similar to the characteristics of the receptive fields of retinal ganglion cells. Except for some special cases, the model can explain object recognition independent of size, orientation and position. Some general problems of Mellin-type size-invariance models-that also apply to our model-are discussed.

Revealing the Driving Forces of Mid-Cities Urban Growth Patterns Using Spatial Modeling: a Case Study of Los Ángeles, Chile

Directory of Open Access Journals (Sweden)

Mauricio I. Aguayo

2007-06-01

Full Text Available City growth and changes in land-use patterns cause various important social and environmental impacts. To understand the spatial and temporal dynamics of these processes, the factors that drive urban development must be identified and analyzed, especially those factors that can be used to predict future changes and their potential environmental effects. Our objectives were to quantify the relationship between urban growth and its driving forces and to predict the spatial growth pattern based on historical land-use changes for the city of Los Ángeles in central Chile. This involved the analysis of images from 1978, 1992, and 1998 and characterization of the spatial pattern of land-use change; the construction of digital coverage in GIS; the selection of predictive variables through univariate analysis; the construction of logistic regression models using growth vs. nongrowth for 1978-1992 as the dependent variable; and the prediction of the probability of land-use change by applying the regression model to the 1992-1998 period. To investigate the influence of spatial scale, we constructed several sets of models that contained (1 only distance variables, e.g., distance to highways; (2 only scale-dependent density variables, e.g., density of urban area within a 600-m radius; (3 both distance and density variables; and (4 both distance and density variables at several spatial scales. The environmental variables were included in all models. The combination of distance and density variables at several scales is required to appropriately capture the multiscale urban growth process. The best models correctly predict ~90% of the observed land-use changes for 1992-1998. The distance to access roads, densities of the urban road system and urbanized area at various scales, and soil type were the strongest predictors of the growth pattern. Other variables were less important or not significant in explaining the urban growth process. Our approach, which

The modelling of 2-D migration patterns of soluble waste in soils

International Nuclear Information System (INIS)

Villar, H.P.

1998-01-01

A novel approach to the modelling of two-dimensional migration patterns of soluble waste in soils is presented. This approach, albeit very simple and straightforward, was found to be powerful enough to simulate several aspects of the migration of conservative tracers in non-sorptive soils. In brief, the finite-difference technique is adopted for the solution of the two-dimensional advection-dispersion equation. Since the simulated data were to be verified against experimental data obtained through the use of radioactive tracers, the numerical model was modified to take into account the corresponding experimental aspects, with special regard to the attenuation of radiation through the soil mass. The introduction of this correcting factor rendered the simulation quite faithful to the experimental data, thus suggesting the feasibility of the proposed approach for the two-dimensional analysis of waste migration. (author)

A three-dimensional model for lubricant depletion under sliding condition on bit patterned media of hard disk drives

Science.gov (United States)

Wu, Lin

2018-05-01

In this paper, we model the depletion dynamics of the molecularly thin layer of lubricants on a bit patterned media disk of hard disk drives under a sliding air bearing head. The dominant physics and consequently, the lubricant depletion dynamics on a patterned disk are shown to be significantly different from the well-studied cases of a smooth disk. Our results indicate that the surface tension effect, which is negligible on a flat disk, apparently suppresses depletion by enforcing a bottleneck effect around the disk pattern peak regions to thwart the migration of lubricants. When the disjoining pressure is relatively small, it assists the depletion. But, when the disjoining pressure becomes dominant, the disjoining pressure resists depletion. Disk pattern orientation plays a critical role in the depletion process. The effect of disk pattern orientation on depletion originates from its complex interaction with other intermingled factors of external air shearing stress distribution and lubricant particle trajectory. Patterning a disk surface with nanostructures of high density, large height/pitch ratio, and particular orientation is demonstrated to be one efficient way to alleviate the formation of lubricant depletion tracks.

The stability and slow dynamics of spot patterns in the 2D Brusselator model: The effect of open systems and heterogeneities