TOPTRAC: Topical Trajectory Pattern Mining
Kim, Younghoon; Han, Jiawei; Yuan, Cangzhou
2015-01-01
With the increasing use of GPS-enabled mobile phones, geo-tagging, which refers to adding GPS information to media such as micro-blogging messages or photos, has seen a surge in popularity recently. This enables us to not only browse information based on locations, but also discover patterns in the location-based behaviors of users. Many techniques have been developed to find the patterns of people's movements using GPS data, but latent topics in text messages posted with local contexts have not been utilized effectively. In this paper, we present a latent topic-based clustering algorithm to discover patterns in the trajectories of geo-tagged text messages. We propose a novel probabilistic model to capture the semantic regions where people post messages with a coherent topic as well as the patterns of movement between the semantic regions. Based on the model, we develop an efficient inference algorithm to calculate model parameters. By exploiting the estimated model, we next devise a clustering algorithm to find the significant movement patterns that appear frequently in data. Our experiments on real-life data sets show that the proposed algorithm finds diverse and interesting trajectory patterns and identifies the semantic regions in a finer granularity than the traditional geographical clustering methods. PMID:26709365
Diversity of chimera-like patterns from a model of 2D arrays of neurons with nonlocal coupling
NASA Astrophysics Data System (ADS)
Tian, Chang-Hai; Zhang, Xi-Yun; Wang, Zhen-Hua; Liu, Zong-Hua
2017-06-01
Chimera states have been studied in 1D arrays, and a variety of different chimera states have been found using different models. Research has recently been extended to 2D arrays but only to phase models of them. Here, we extend it to a nonphase model of 2D arrays of neurons and focus on the influence of nonlocal coupling. Using extensive numerical simulations, we find, surprisingly, that this system can show most types of previously observed chimera states, in contrast to previous models, where only one or a few types of chimera states can be observed in each model. We also find that this model can show some special chimera-like patterns such as gridding and multicolumn patterns, which were previously observed only in phase models. Further, we present an effective approach, i.e., removing some of the coupling links, to generate heterogeneous coupling, which results in diverse chimera-like patterns and even induces transformations from one chimera-like pattern to another.
Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity
Beck, Cornelia; Neumann, Heiko
2011-01-01
Background The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour. PMID:21814543
Repetition Is the Feature Behind the Attentional Bias for Recognizing Threatening Patterns.
Shabbir, Maryam; Zon, Adelynn M Y; Thuppil, Vivek
2018-01-01
Animals attend to what is relevant in order to behave in an effective manner and succeed in their environments. In several nonhuman species, there is an evolved bias for attending to patterns indicative of threats in the natural environment such as dangerous animals. Because skins of many dangerous animals are typically repetitive, we propose that repetition is the key feature enabling recognition of evolutionarily important threats. The current study consists of two experiments where we measured participants' reactions to pictures of male and female models wearing clothing of various repeating (leopard skin, snakeskin, and floral print) and nonrepeating (camouflage, shiny, and plain) patterns. In Experiment 1, when models wearing patterns were presented side by side with total fixation duration as the measure, the repeating floral pattern was the most provocative, with total fixation duration significantly longer than all other patterns. Leopard and snakeskin patterns had total fixation durations that were significantly longer than the plain pattern. In Experiment 2, we employed a visual-search task where participants were required to find models wearing the various patterns in a setting of a crowded airport terminal. Participants detected leopard skin pattern and repetitive floral pattern significantly faster than two of the nonpatterned clothing styles. Our experimental findings support the hypothesis that repetition of specific visual features might facilitate target detection, especially those characterizing evolutionary important threats. Our findings that intricate, but nonthreatening repeating patterns can have similar attention-grabbing properties to animal skin patterns have important implications for the fashion industry and wildlife trade.
Combinatorial Histone Acetylation Patterns Are Generated by Motif-Specific Reactions.
Blasi, Thomas; Feller, Christian; Feigelman, Justin; Hasenauer, Jan; Imhof, Axel; Theis, Fabian J; Becker, Peter B; Marr, Carsten
2016-01-27
Post-translational modifications (PTMs) are pivotal to cellular information processing, but how combinatorial PTM patterns ("motifs") are set remains elusive. We develop a computational framework, which we provide as open source code, to investigate the design principles generating the combinatorial acetylation patterns on histone H4 in Drosophila melanogaster. We find that models assuming purely unspecific or lysine site-specific acetylation rates were insufficient to explain the experimentally determined motif abundances. Rather, these abundances were best described by an ensemble of models with acetylation rates that were specific to motifs. The model ensemble converged upon four acetylation pathways; we validated three of these using independent data from a systematic enzyme depletion study. Our findings suggest that histone acetylation patterns originate through specific pathways involving motif-specific acetylation activity. Copyright © 2016 Elsevier Inc. All rights reserved.
FraudMiner: A Novel Credit Card Fraud Detection Model Based on Frequent Itemset Mining
Seeja, K. R.; Zareapoor, Masoumeh
2014-01-01
This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers. PMID:25302317
FraudMiner: a novel credit card fraud detection model based on frequent itemset mining.
Seeja, K R; Zareapoor, Masoumeh
2014-01-01
This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers.
A phenological mid-domain effect in flowering diversity.
Morales, Manuel A; Dodge, Gary J; Inouye, David W
2005-01-01
In this paper, we test the mid-domain hypothesis as an explanation for observed patterns of flowering diversity in two sub-alpine communities of insect-pollinated plants. Observed species richness patterns showed an early-season increase in richness, a mid-season peak, and a late-season decrease. We show that a "mid-domain" null model can qualitatively match this pattern of flowering species richness, with R(2) values typically greater than 60%. We find significant or marginally significant departures from expected patterns of diversity for only 3 out of 12 year-site combinations. On the other hand, we do find a consistent pattern of departure when comparing observed versus null-model predicted flowering diversity averaged across years. Our results therefore support the hypothesis that ecological factors shape patterns of flowering phenology, but that the strength or nature of these environmental forcings may differ between years or the two habitats we studied, or may depend on species-specific characteristics of these plant communities. We conclude that mid-domain null models provide an important baseline from which to test departure of expected patterns of flowering diversity across temporal domains. Geometric constraints should be included first in the list of factors that drive seasonal patterns of flowering diversity.
Cascading Walks Model for Human Mobility Patterns
Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong
2015-01-01
Background 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. Methodology/Principal Findings 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. Conclusions/Significance 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. PMID:25860140
Campana, Lorenzo; Breitbeck, Robert; Bauer-Kreuz, Regula; Buck, Ursula
2016-05-01
This study evaluated the feasibility of documenting patterned injury using three dimensions and true colour photography without complex 3D surface documentation methods. This method is based on a generated 3D surface model using radiologic slice images (CT) while the colour information is derived from photographs taken with commercially available cameras. The external patterned injuries were documented in 16 cases using digital photography as well as highly precise photogrammetry-supported 3D structured light scanning. The internal findings of these deceased were recorded using CT and MRI. For registration of the internal with the external data, two different types of radiographic markers were used and compared. The 3D surface model generated from CT slice images was linked with the photographs, and thereby digital true-colour 3D models of the patterned injuries could be created (Image projection onto CT/IprojeCT). In addition, these external models were merged with the models of the somatic interior. We demonstrated that 3D documentation and visualization of external injury findings by integration of digital photography in CT/MRI data sets is suitable for the 3D documentation of individual patterned injuries to a body. Nevertheless, this documentation method is not a substitution for photogrammetry and surface scanning, especially when the entire bodily surface is to be recorded in three dimensions including all external findings, and when precise data is required for comparing highly detailed injury features with the injury-inflicting tool.
Unlearning of Mixed States in the Hopfield Model —Extensive Loading Case—
NASA Astrophysics Data System (ADS)
Hayashi, Kao; Hashimoto, Chinami; Kimoto, Tomoyuki; Uezu, Tatsuya
2018-05-01
We study the unlearning of mixed states in the Hopfield model for the extensive loading case. Firstly, we focus on case I, where several embedded patterns are correlated with each other, whereas the rest are uncorrelated. Secondly, we study case II, where patterns are divided into clusters in such a way that patterns in any cluster are correlated but those in two different clusters are not correlated. By using the replica method, we derive the saddle point equations for order parameters under the ansatz of replica symmetry. The same equations are also derived by self-consistent signal-to-noise analysis in case I. In both cases I and II, we find that when the correlation between patterns is large, the network loses its ability to retrieve the embedded patterns and, depending on the parameters, a confused memory, which is a mixed state and/or spin glass state, emerges. By unlearning the mixed state, the network acquires the ability to retrieve the embedded patterns again in some parameter regions. We find that to delete the mixed state and to retrieve the embedded patterns, the coefficient of unlearning should be chosen appropriately. We perform Markov chain Monte Carlo simulations and find that the simulation and theoretical results agree reasonably well, except for the spin glass solution in a parameter region due to the replica symmetry breaking. Furthermore, we find that the existence of many correlated clusters reduces the stabilities of both embedded patterns and mixed states.
Selecting climate simulations for impact studies based on multivariate patterns of climate change.
Mendlik, Thomas; Gobiet, Andreas
In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.
Branching Patterns and Stepped Leaders in an Electric-Circuit Model for Creeping Discharge
NASA Astrophysics Data System (ADS)
Hidetsugu Sakaguchi,; Sahim M. Kourkouss,
2010-06-01
We construct a two-dimensional electric circuit model for creeping discharge. Two types of discharge, surface corona and surface leader, are modeled by a two-step function of conductance. Branched patterns of surface leaders surrounded by the surface corona appear in numerical simulation. The fractal dimension of branched discharge patterns is calculated by changing voltage and capacitance. We find that surface leaders often grow stepwise in time, as is observed in lightning leaders of thunder.
Exploring the Complex Pattern of Information Spreading in Online Blog Communities
Pei, Sen; Muchnik, Lev; Tang, Shaoting; Zheng, Zhiming; Makse, Hernán A.
2015-01-01
Information spreading in online social communities has attracted tremendous attention due to its utmost practical values in applications. Despite that several individual-level diffusion data have been investigated, we still lack the detailed understanding of the spreading pattern of information. Here, by comparing information flows and social links in a blog community, we find that the diffusion processes are induced by three different spreading mechanisms: social spreading, self-promotion and broadcast. Although numerous previous studies have employed epidemic spreading models to simulate information diffusion, we observe that such models fail to reproduce the realistic diffusion pattern. In respect to users behaviors, strikingly, we find that most users would stick to one specific diffusion mechanism. Moreover, our observations indicate that the social spreading is not only crucial for the structure of diffusion trees, but also capable of inducing more subsequent individuals to acquire the information. Our findings suggest new directions for modeling of information diffusion in social systems, and could inform design of efficient propagation strategies based on users behaviors. PMID:25985081
Exploring the complex pattern of information spreading in online blog communities.
Pei, Sen; Muchnik, Lev; Tang, Shaoting; Zheng, Zhiming; Makse, Hernán A
2015-01-01
Information spreading in online social communities has attracted tremendous attention due to its utmost practical values in applications. Despite that several individual-level diffusion data have been investigated, we still lack the detailed understanding of the spreading pattern of information. Here, by comparing information flows and social links in a blog community, we find that the diffusion processes are induced by three different spreading mechanisms: social spreading, self-promotion and broadcast. Although numerous previous studies have employed epidemic spreading models to simulate information diffusion, we observe that such models fail to reproduce the realistic diffusion pattern. In respect to users behaviors, strikingly, we find that most users would stick to one specific diffusion mechanism. Moreover, our observations indicate that the social spreading is not only crucial for the structure of diffusion trees, but also capable of inducing more subsequent individuals to acquire the information. Our findings suggest new directions for modeling of information diffusion in social systems, and could inform design of efficient propagation strategies based on users behaviors.
Clustering change patterns using Fourier transformation with time-course gene expression data.
Kim, Jaehee
2011-01-01
To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.
Finding Major Patterns of Aging Process by Data Synchronization
NASA Astrophysics Data System (ADS)
Miyano, Takaya; Tsutsui, Takako
We developed a method for extracting feature patterns from multivariate data using a network of coupled phase oscillators subject to an analogue of the Kuramoto model for collective synchronization. Our method may be called data synchronization. We applied data synchronization to the care-needs-certification data, provided by Otsu City as a historical old city near Kyoto City, in the Japanese public long-term care insurance program to find the trend of the major patterns of the aging process for elderly people needing nursing care.
Finding gene clusters for a replicated time course study
2014-01-01
Background Finding genes that share similar expression patterns across samples is an important question that is frequently asked in high-throughput microarray studies. Traditional clustering algorithms such as K-means clustering and hierarchical clustering base gene clustering directly on the observed measurements and do not take into account the specific experimental design under which the microarray data were collected. A new model-based clustering method, the clustering of regression models method, takes into account the specific design of the microarray study and bases the clustering on how genes are related to sample covariates. It can find useful gene clusters for studies from complicated study designs such as replicated time course studies. Findings In this paper, we applied the clustering of regression models method to data from a time course study of yeast on two genotypes, wild type and YOX1 mutant, each with two technical replicates, and compared the clustering results with K-means clustering. We identified gene clusters that have similar expression patterns in wild type yeast, two of which were missed by K-means clustering. We further identified gene clusters whose expression patterns were changed in YOX1 mutant yeast compared to wild type yeast. Conclusions The clustering of regression models method can be a valuable tool for identifying genes that are coordinately transcribed by a common mechanism. PMID:24460656
Mechanism underlying the diverse collective behavior in the swarm oscillator model
NASA Astrophysics Data System (ADS)
Iwasa, Masatomo; Tanaka, Dan
2017-09-01
The swarm oscillator model describes the long-time behavior of interacting chemotactic particles, and it shows numerous types of macroscopic patterns. However, the reason why so many kinds of patterns emerge is not clear. In this study, we elucidate the mechanism underlying the diversity of the pattens by analyzing the model for two particles. Focusing on the behavior when the two particles are spatially close, we find that the dynamics is classified into eight types, which explain most of the observed 13 types of patterns.
Spatiotemporal Patterns in a Predator-Prey Model with Cross-Diffusion Effect
NASA Astrophysics Data System (ADS)
Sambath, M.; Balachandran, K.; Guin, L. N.
The present research deals with the emergence of spatiotemporal patterns of a two-dimensional (2D) continuous predator-prey system with cross-diffusion effect. First, we work out the critical lines of Hopf and Turing bifurcations of the current model system in a 2D spatial domain by means of bifurcation theory. More specifically, the exact Turing region is specified in a two-parameter space. In effect, by choosing the cross-diffusion coefficient as one of the momentous parameter, we demonstrate that the model system undergoes a sequence of spatiotemporal patterns in a homogeneous environment through diffusion-driven instability. Our results via numerical simulation authenticate that cross-diffusion be able to create stationary patterns which enrich the findings of pattern formation in an ecosystem.
NASA Astrophysics Data System (ADS)
Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.
2017-08-01
Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.
A Multiscale Survival Process for Modeling Human Activity Patterns.
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.
Universal predictability of mobility patterns in cities
Yan, Xiao-Yong; Zhao, Chen; Fan, Ying; Di, Zengru; Wang, Wen-Xu
2014-01-01
Despite the long history of modelling human mobility, we continue to lack a highly accurate approach with low data requirements for predicting mobility patterns in cities. Here, we present a population-weighted opportunities model without any adjustable parameters to capture the underlying driving force accounting for human mobility patterns at the city scale. We use various mobility data collected from a number of cities with different characteristics to demonstrate the predictive power of our model. We find that insofar as the spatial distribution of population is available, our model offers universal prediction of mobility patterns in good agreement with real observations, including distance distribution, destination travel constraints and flux. By contrast, the models that succeed in modelling mobility patterns in countries are not applicable in cities, which suggests that there is a diversity of human mobility at different spatial scales. Our model has potential applications in many fields relevant to mobility behaviour in cities, without relying on previous mobility measurements. PMID:25232053
Central Pattern Generation and the Motor Infrastructure for Suck, Respiration, and Speech
ERIC Educational Resources Information Center
Barlow, Steven M.; Estep, Meredith
2006-01-01
The objective of the current report is to review experimental findings on centrally patterned movements and sensory and descending modulation of central pattern generators (CPGs) in a variety of animal and human models. Special emphasis is directed toward speech production muscle systems, including the chest wall and orofacial complex during…
Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology
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
Cascading walks model for human mobility patterns.
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.
Applications of statistical physics and information theory to the analysis of DNA sequences
NASA Astrophysics Data System (ADS)
Grosse, Ivo
2000-10-01
DNA carries the genetic information of most living organisms, and the of genome projects is to uncover that genetic information. One basic task in the analysis of DNA sequences is the recognition of protein coding genes. Powerful computer programs for gene recognition have been developed, but most of them are based on statistical patterns that vary from species to species. In this thesis I address the question if there exist universal statistical patterns that are different in coding and noncoding DNA of all living species, regardless of their phylogenetic origin. In search for such species-independent patterns I study the mutual information function of genomic DNA sequences, and find that it shows persistent period-three oscillations. To understand the biological origin of the observed period-three oscillations, I compare the mutual information function of genomic DNA sequences to the mutual information function of stochastic model sequences. I find that the pseudo-exon model is able to reproduce the mutual information function of genomic DNA sequences. Moreover, I find that a generalization of the pseudo-exon model can connect the existence and the functional form of long-range correlations to the presence and the length distributions of coding and noncoding regions. Based on these theoretical studies I am able to find an information-theoretical quantity, the average mutual information (AMI), whose probability distributions are significantly different in coding and noncoding DNA, while they are almost identical in all studied species. These findings show that there exist universal statistical patterns that are different in coding and noncoding DNA of all studied species, and they suggest that the AMI may be used to identify genes in different living species, irrespective of their taxonomic origin.
Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics.
Takaguchi, Taro; Masuda, Naoki; Holme, Petter
2013-01-01
Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.
Bursts of Vertex Activation and Epidemics in Evolving Networks
Rocha, Luis E. C.; Blondel, Vincent D.
2013-01-01
The dynamic nature of contact patterns creates diverse temporal structures. In particular, empirical studies have shown that contact patterns follow heterogeneous inter-event time intervals, meaning that periods of high activity are followed by long periods of inactivity. To investigate the impact of these heterogeneities in the spread of infection from a theoretical perspective, we propose a stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event intervals, and may leave and enter the system. We study how these properties affect the prevalence of an infection and estimate , the number of secondary infections of an infectious individual in a completely susceptible population, by modeling simulated infections (SI and SIR) that co-evolve with the network structure. We find that heterogeneous contact patterns cause earlier and larger epidemics in the SIR model in comparison to homogeneous scenarios for a vast range of parameter values, while smaller epidemics may happen in some combinations of parameters. In the case of SI and heterogeneous patterns, the epidemics develop faster in the earlier stages followed by a slowdown in the asymptotic limit. For increasing vertex turnover rates, heterogeneous patterns generally cause higher prevalence in comparison to homogeneous scenarios with the same average inter-event interval. We find that is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability. PMID:23555211
Transducer model produces facilitation from opposite-sign flanks
NASA Technical Reports Server (NTRS)
Solomon, J. A.; Watson, A. B.; Morgan, M. J.
1999-01-01
Small spots, lines and Gabor patterns can be easier to detect when they are superimposed upon similar spots, lines and Gabor patterns. Traditionally, such facilitation has been understood to be a consequence of nonlinear contrast transduction. Facilitation has also been reported to arise from non-overlapping patterns with opposite sign. We point out that this result does not preclude the traditional explanation for superimposed targets. Moreover, we find that facilitation from opposite-sign flanks is weaker than facilitation from same-sign flanks. Simulations with a transducer model produce opposite-sign facilitation.
New activity pattern in human interactive dynamics
NASA Astrophysics Data System (ADS)
Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni
2015-09-01
We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.
Rejecting probability summation for radial frequency patterns, not so Quick!
Baldwin, Alex S; Schmidtmann, Gunnar; Kingdom, Frederick A A; Hess, Robert F
2016-05-01
Radial frequency (RF) patterns are used to assess how the visual system processes shape. They are thought to be detected globally. This is supported by studies that have found summation for RF patterns to be greater than what is possible if the parts were being independently detected and performance only then improved with an increasing number of cycles by probability summation between them. However, the model of probability summation employed in these previous studies was based on High Threshold Theory (HTT), rather than Signal Detection Theory (SDT). We conducted rating scale experiments to investigate the receiver operating characteristics. We find these are of the curved form predicted by SDT, rather than the straight lines predicted by HTT. This means that to test probability summation we must use a model based on SDT. We conducted a set of summation experiments finding that thresholds decrease as the number of modulated cycles increases at approximately the same rate as previously found. As this could be consistent with either additive or probability summation, we performed maximum-likelihood fitting of a set of summation models (Matlab code provided in our Supplementary material) and assessed the fits using cross validation. We find we are not able to distinguish whether the responses to the parts of an RF pattern are combined by additive or probability summation, because the predictions are too similar. We present similar results for summation between separate RF patterns, suggesting that the summation process there may be the same as that within a single RF. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Anderegg, L. D.; Berner, L. T.; Badgley, G.; Hillerislambers, J.; Law, B. E.
2017-12-01
Functional traits could facilitate ecological prediction by provide scale-free tools for modeling ecosystem function. Yet much of their utility lies in three key assumptions: 1) that global patterns of trait covariation are the result of universal trade-offs independent of taxonomic scale, so empirical trait-trait relationships can be used to constrain vegetation models 2) that traits respond predictably to environmental gradients and can therefore be reliably quantified to parameterize models and 3) that well sampled traits influence productivity. We use an extensive dataset of within-species leaf trait variation in North American conifers combined with global leaf trait datasets to test these assumptions. We examine traits central to the `leaf economics spectrum', and quantify patterns of trait variation at multiple taxonomic scales. We also test whether site environment explains geographic trait variation within conifers, and ask whether foliar traits explain geographic variation in relative growth rates. We find that most leaf traits vary primarily between rather than within species globally, but that a large fraction of within-PFT trait variation is within-species. We also find that some leaf economics spectrum relationships differ in sign within versus between species, particularly the relationship between leaf lifespan and LMA. In conifers, we find weak and inconsistent relationships between site environment and leaf traits, making it difficult capture within-species leaf trait variation for regional model parameterization. Finally, we find limited relationships between tree relative growth rate and any foliar trait other than leaf lifespan, with leaf traits jointly explaining 42% of within-species growth variation but environmental factors explaining 77% of variation. We suggest that additional traits, particularly whole plant allometry/allocation traits may be better than leaf traits for improving vegetation model performance at smaller taxonomic and spatial scales.
An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data
Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos
2015-01-01
This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800
Predicting perturbation patterns from the topology of biological networks.
Santolini, Marc; Barabási, Albert-László
2018-06-20
High-throughput technologies, offering an unprecedented wealth of quantitative data underlying the makeup of living systems, are changing biology. Notably, the systematic mapping of the relationships between biochemical entities has fueled the rapid development of network biology, offering a suitable framework to describe disease phenotypes and predict potential drug targets. However, our ability to develop accurate dynamical models remains limited, due in part to the limited knowledge of the kinetic parameters underlying these interactions. Here, we explore the degree to which we can make reasonably accurate predictions in the absence of the kinetic parameters. We find that simple dynamically agnostic models are sufficient to recover the strength and sign of the biochemical perturbation patterns observed in 87 biological models for which the underlying kinetics are known. Surprisingly, a simple distance-based model achieves 65% accuracy. We show that this predictive power is robust to topological and kinetic parameter perturbations, and we identify key network properties that can increase up to 80% the recovery rate of the true perturbation patterns. We validate our approach using experimental data on the chemotactic pathway in bacteria, finding that a network model of perturbation spreading predicts with ∼80% accuracy the directionality of gene expression and phenotype changes in knock-out and overproduction experiments. These findings show that the steady advances in mapping out the topology of biochemical interaction networks opens avenues for accurate perturbation spread modeling, with direct implications for medicine and drug development.
Understanding human activity patterns based on space-time-semantics
NASA Astrophysics Data System (ADS)
Huang, Wei; Li, Songnian
2016-11-01
Understanding human activity patterns plays a key role in various applications in an urban environment, such as transportation planning and traffic forecasting, urban planning, public health and safety, and emergency response. Most existing studies in modeling human activity patterns mainly focus on spatiotemporal dimensions, which lacks consideration of underlying semantic context. In fact, what people do and discuss at some places, inferring what is happening at the places, cannot be simple neglected because it is the root of human mobility patterns. We believe that the geo-tagged semantic context, representing what individuals do and discuss at a place and a specific time, drives a formation of specific human activity pattern. In this paper, we aim to model human activity patterns not only based on space and time but also with consideration of associated semantics, and attempt to prove a hypothesis that similar mobility patterns may have different motivations. We develop a spatiotemporal-semantic model to quantitatively express human activity patterns based on topic models, leading to an analysis of space, time and semantics. A case study is conducted using Twitter data in Toronto based on our model. Through computing the similarities between users in terms of spatiotemporal pattern, semantic pattern and spatiotemporal-semantic pattern, we find that only a small number of users (2.72%) have very similar activity patterns, while the majority (87.14%) show different activity patterns (i.e., similar spatiotemporal patterns and different semantic patterns, similar semantic patterns and different spatiotemporal patterns, or different in both). The population of users that has very similar activity patterns is decreased by 56.41% after incorporating semantic information in the corresponding spatiotemporal patterns, which can quantitatively prove the hypothesis.
NASA Astrophysics Data System (ADS)
Owolabi, Kolade M.; Atangana, Abdon
2018-02-01
This paper primarily focused on the question of how population diffusion can affect the formation of the spatial patterns in the spatial fraction predator-prey system by Turing mechanisms. Our numerical findings assert that modeling by fractional reaction-diffusion equations should be considered as an appropriate tool for studying the fundamental mechanisms of complex spatiotemporal dynamics. We observe that pure Hopf instability gives rise to the formation of spiral patterns in 2D and pure Turing instability destroys the spiral pattern and results to the formation of chaotic or spatiotemporal spatial patterns. Existence and permanence of the species is also guaranteed with the 3D simulations at some instances of time for subdiffusive and superdiffusive scenarios.
Spatio-temporal patterns of bacteria caused by collective motion
NASA Astrophysics Data System (ADS)
Kitsunezaki, So
2006-04-01
In incubation experiments on bacterial colonies of Proteus mirabilis, collective motion of bacteria is found to generate macroscopic turbulent patterns on the surface of agar media. We propose a mathematical model to describe the time evolution of the positional and directional distributions of motile bacteria in such systems, and investigate this model both numerically and analytically. It is shown that as the average density of bacteria increases, nonuniform swarming patterns emerge from a uniform stationary state. For a sufficient large density, we find that spiral patterns are caused by interactions between the local bacteria densities and the rotational mode of the collective motion. Unidirectional spiral patterns similar to those observed in experiments appear in the case in which the equilibrium directional distribution is asymmetric.
Detailed temporal structure of communication networks in groups of songbirds.
Stowell, Dan; Gill, Lisa; Clayton, David
2016-06-01
Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch (Taeniopygia guttata) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that 'kernels' reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual. © 2016 The Authors.
Non-Gaussian distributions of melodic intervals in music: The Lévy-stable approximation
NASA Astrophysics Data System (ADS)
Niklasson, Gunnar A.; Niklasson, Maria H.
2015-11-01
The analysis of structural patterns in music is of interest in order to increase our fundamental understanding of music, as well as for devising algorithms for computer-generated music, so called algorithmic composition. Musical melodies can be analyzed in terms of a “music walk” between the pitches of successive tones in a notescript, in analogy with the “random walk” model commonly used in physics. We find that the distribution of melodic intervals between tones can be approximated with a Lévy-stable distribution. Since music also exibits self-affine scaling, we propose that the “music walk” should be modelled as a Lévy motion. We find that the Lévy motion model captures basic structural patterns in classical as well as in folk music.
Namboodiri, Vijay Mohan K; Levy, Joshua M; Mihalas, Stefan; Sims, David W; Hussain Shuler, Marshall G
2016-08-02
Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.
A mechanism for pattern formation in dynamic populations by the effect of gregarious instinct
NASA Astrophysics Data System (ADS)
Mangioni, Sergio E.
2012-01-01
We introduced the gregarious instinct by means of a novel strategy that considers the average effect of the attractive forces between individuals within a given population. We watched how pattern formation can be explained by the effect of aggregation depending on conditions on food and / or mortality. We propose a model that describes the corresponding dynamic and by a linear stability analysis of homogeneous solutions and can identify and interpret the region of parameters where these patterns are stable. Then we test numerically these preliminary results and find stable patterns as solutions. Finally, we developed a simplified model allowing us to understand in greater detail the processes involved.
Pattern statistics on Markov chains and sensitivity to parameter estimation
Nuel, Grégory
2006-01-01
Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). Results: In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of σ, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. Conclusion: We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation. PMID:17044916
Pattern statistics on Markov chains and sensitivity to parameter estimation.
Nuel, Grégory
2006-10-17
In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of sigma, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation.
Emergent Vortex Patterns in Systems of Self-Propelled, Chiral Particles
NASA Astrophysics Data System (ADS)
Huber, Lorenz; Denk, Jonas; Reithmann, Emanuel; Frey, Erwin
Self-organization of FtsZ polymers is vital for Z-ring assembly during bacterial cell division, and has been studied using reconstituted in vitro model systems. Employing Brownian dynamics simulations and a Boltzmann approach, we model FtsZ polymers as active particles moving along chiral circular paths. With both theoretical approaches we find self-organization into vortex structures and characterize different states in parameter states. Our work demonstrates that these patterns are robust and are generic for active chiral matter. Moreover, we show that the dynamics at the onset of pattern formation is described by a generalized complex Ginzburg-Landau equation.
Application of a clustering-remote sensing method in analyzing security patterns
NASA Astrophysics Data System (ADS)
López-Caloca, Alejandra; Martínez-Viveros, Elvia; Chapela-Castañares, José Ignacio
2009-04-01
In Mexican academic and government circles, research on criminal spatial behavior has been neglected. Only recently has there been an interest in criminal data geo-reference. However, more sophisticated spatial analyses models are needed to disclose spatial patterns of crime and pinpoint their changes overtime. The main use of these models lies in supporting policy making and strategic intelligence. In this paper we present a model for finding patterns associated with crime. It is based on a fuzzy logic algorithm which finds the best fit within cluster numbers and shapes of groupings. We describe the methodology for building the model and its validation. The model was applied to annual data for types of felonies from 2005 to 2006 in the Mexican city of Hermosillo. The results are visualized as a standard deviational ellipse computed for the points identified to be a "cluster". These areas indicate a high to low demand for public security, and they were cross-related to urban structure analyzed by SPOT images and statistical data such as population, poverty levels, urbanization, and available services. The fusion of the model results with other geospatial data allows detecting obstacles and opportunities for crime commission in specific high risk zones and guide police activities and criminal investigations.
Self-Assembly of Human Serum Albumin: A Simplex Phenomenon
Thakur, Garima; Prashanthi, Kovur; Jiang, Keren; Thundat, Thomas
2017-01-01
Spontaneous self-assemblies of biomolecules can generate geometrical patterns. Our findings provide an insight into the mechanism of self-assembled ring pattern generation by human serum albumin (HSA). The self-assembly is a process guided by kinetic and thermodynamic parameters. The generated protein ring patterns display a behavior which is geometrically related to a n-simplex model and is explained through thermodynamics and chemical kinetics. PMID:28930179
Finding Services for an Open Architecture: A Review of Existing Applications and Programs in PEO C4I
2011-01-01
2004) Two key SOA success factors listed were as follows: 1. Shared Services Strategy: Existence of a strategy to identify overlapping business and...model Architectural pattern 22 Finding Services for an Open Architecture or eliminating redundancies and overlaps through use of shared services 2...Funding Model: Existence of an IT funding model aligned with and supportive of a shared services strategy. (Sun Micro- systems, 2004) Become Data
Cellular pattern formation by SCRAMBLED, a leucine-rich repeat receptor-like kinase in Arabidopsis.
Kwak, Su-Hwan; Schiefelbein, John
2008-02-01
The appropriate specification of distinct cell types is important for generating the proper tissues and bodies of multicellular organisms. In the root epidermis of Arabidopsis, cell fate determination is accomplished by a transcriptional regulatory circuit that is influenced by positional signaling. A leucine-rich repeat receptor-like kinase, SCRAMBLED (SCM), has been shown to be responsible for the position-dependent aspect of this epidermal pattern. In a recent report, we find that SCM affects the transcriptional regulatory network by down-regulating the WEREWOLF (WER) MYB gene expression in a set of epidermal cells located in a specific position. We also find that SCM and the SCM-related SRF1 and SRF3 are not required for embryonic epidermal patterning and that SRF1 and SRF3 do not act redundantly with SCM. This suggests that distinct positional signaling mechanisms exist for embryonic and post-embryonic epidermal patterning. In this addendum, we discuss the implications of our recent findings and extend our working model for epidermal cell pattering.
Cellular pattern formation by SCRAMBLED, a leucine-rich repeat receptor-like kinase in Arabidopsis
Kwak, Su-Hwan
2008-01-01
The appropriate specification of distinct cell types is important for generating the proper tissues and bodies of multicellular organisms. In the root epidermis of Arabidopsis, cell fate determination is accomplished by a transcriptional regulatory circuit that is influenced by positional signaling. A leucine-rich repeat receptor-like kinase, SCRAMBLED (SCM), has been shown to be responsible for the position-dependent aspect of this epidermal pattern. In a recent report, we find that SCM affects the transcriptional regulatory network by down-regulating the WEREWOLF (WER) MYB gene expression in a set of epidermal cells located in a specific position. We also find that SCM and the SCM-related SRF1 and SRF3 are not required for embryonic epidermal patterning and that SRF1 and SRF3 do not act redundantly with SCM. This suggests that distinct positional signaling mechanisms exist for embryonic and post-embryonic epidermal patterning. In this addendum, we discuss the implications of our recent findings and extend our working model for epidermal cell pattering. PMID:19704725
Narrative and the Origins of Discourse: Patterns of Discourse in Stories around the World
ERIC Educational Resources Information Center
Rose, David
2005-01-01
This paper summarises findings of discourse analyses of traditional stories from eleven language phyla around the world. The aim is a preliminary exploration of relationships amongst diverse languages in patterns of discourse, using a systemic functional language model. Several techniques were developed for managing and displaying the analyses,…
Neural activity in the hippocampus during conflict resolution.
Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo
2013-01-15
This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.
Exploring the patterns and evolution of self-organized urban street networks through modeling
NASA Astrophysics Data System (ADS)
Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan
2013-03-01
As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.
Pattern formation in a model for mountain pine beetle dispersal: linking model predictions to data.
Strohm, S; Tyson, R C; Powell, J A
2013-10-01
Pattern formation occurs in a wide range of biological systems. This pattern formation can occur in mathematical models because of diffusion-driven instability or due to the interaction between reaction, diffusion, and chemotaxis. In this paper, we investigate the spatial pattern formation of attack clusters in a system for Mountain Pine Beetle. The pattern formation (aggregation) of the Mountain Pine Beetle in order to attack susceptible trees is crucial for their survival and reproduction. We use a reaction-diffusion equation with chemotaxis to model the interaction between Mountain Pine Beetle, Mountain Pine Beetle pheromones, and susceptible trees. Mathematical analysis is utilized to discover the spacing in-between beetle attacks on the susceptible landscape. The model predictions are verified by analysing aerial detection survey data of Mountain Pine Beetle Attack from the Sawtooth National Recreation Area. We find that the distance between Mountain Pine Beetle attack clusters predicted by our model closely corresponds to the observed attack data in the Sawtooth National Recreation Area. These results clarify the spatial mechanisms controlling the transition from incipient to epidemic populations and may lead to control measures which protect forests from Mountain Pine Beetle outbreak.
Patterns of Activity in A Global Model of A Solar Active Region
NASA Technical Reports Server (NTRS)
Bradshaw, S. J.; Viall, N. M.
2016-01-01
In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (1) Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. (2) Shorter coronal loops in the core cool more quickly than longer loops at the periphery. (3) All channel pairs show zero time lag when the line of sight passes through coronal loop footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating across active regions. (5) Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.
Altered Connectivity and Action Model Formation in Autism Is Autism
Mostofsky, Stewart H.; Ewen, Joshua B.
2014-01-01
Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others’ actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function. PMID:21467306
EXAMINING TATOOINE: ATMOSPHERIC MODELS OF NEPTUNE-LIKE CIRCUMBINARY PLANETS
DOE Office of Scientific and Technical Information (OSTI.GOV)
May, E. M.; Rauscher, E.
2016-08-01
Circumbinary planets experience a time-varying irradiation pattern as they orbit their two host stars. In this work, we present the first detailed study of the atmospheric effects of this irradiation pattern on known and hypothetical gaseous circumbinary planets. Using both a one-dimensional energy balance model (EBM) and a three-dimensional general circulation model (GCM), we look at the temperature differences between circumbinary planets and their equivalent single-star cases in order to determine the nature of the atmospheres of these planets. We find that for circumbinary planets on stable orbits around their host stars, temperature differences are on average no more thanmore » 1.0% in the most extreme cases. Based on detailed modeling with the GCM, we find that these temperature differences are not large enough to excite circulation differences between the two cases. We conclude that gaseous circumbinary planets can be treated as their equivalent single-star case in future atmospheric modeling efforts.« less
Implications of tristability in pattern-forming ecosystems
NASA Astrophysics Data System (ADS)
Zelnik, Yuval R.; Gandhi, Punit; Knobloch, Edgar; Meron, Ehud
2018-03-01
Many ecosystems show both self-organized spatial patterns and multistability of possible states. The combination of these two phenomena in different forms has a significant impact on the behavior of ecosystems in changing environments. One notable case is connected to tristability of two distinct uniform states together with patterned states, which has recently been found in model studies of dryland ecosystems. Using a simple model, we determine the extent of tristability in parameter space, explore its effects on the system dynamics, and consider its implications for state transitions or regime shifts. We analyze the bifurcation structure of model solutions that describe uniform states, periodic patterns, and hybrid states between the former two. We map out the parameter space where these states exist, and note how the different states interact with each other. We further focus on two special implications with ecological significance, breakdown of the snaking range and complex fronts. We find that the organization of the hybrid states within a homoclinic snaking structure breaks down as it meets a Maxwell point where simple fronts are stationary. We also discover a new series of complex fronts between the uniform states, each with its own velocity. We conclude with a brief discussion of the significance of these findings for the dynamics of regime shifts and their potential control.
Namboodiri, Vijay Mohan K.; Levy, Joshua M.; Mihalas, Stefan; Sims, David W.; Hussain Shuler, Marshall G.
2016-01-01
Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers. PMID:27385831
A model-based exploration of the role of pattern generating circuits during locomotor adaptation.
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.
Staton-Tindall, Michele; Oser, Carrie B.; Duvall, Jamieson L.; Havens, Jennifer R.; Webster, J. Matthew; Leukefeld, Carl; Booth, Brenda M.
2017-01-01
This study describes gender-specific patterns of drug use among active rural stimulant users and examines religiosity and spirituality as factors that may be related to stimulant use among males and females. The study includes a sample of 225 active rural stimulant users from Kentucky who were recruited using respondent driven sampling and completed face-to-face interviews. Findings suggest gender specific patterns among active rural stimulant users, with females reporting more amphetamine use. In addition, bivariate findings indicate that there is an inverse relationship between spirituality, religiosity, and stimulant use (specifically methamphetamine and amphetamine use), particularly for males. However, when further examining this relationship in multivariate models controlling for age and race, few significant findings were noted for spirituality and religiosity in predicting gender-specific stimulant use patterns. These findings suggest that treatment interventions that incorporate spirituality and religiosity should not only be gender specific, but should also target clients differentially. Findings on the degree of reported spirituality and religiosity also suggest that religious and/or faithbased organizations could be utilized for drug use interventions for rural stimulant users. PMID:29104311
Torsion sensing based on patterned piezoelectric beams
NASA Astrophysics Data System (ADS)
Cha, Youngsu; You, Hangil
2018-03-01
In this study, we investigated the sensing characteristics of piezoelectric beams under torsional loads. We used partially patterned piezoelectric beams to sense torsion. In particular, the piezoelectric patches are located symmetrically with respect to the line of the shear center of the beam. The patterned piezoelectric beam is modeled as a slender beam, and its electrical responses are obtained by piezoelectric electromechanical equations. To validate the modeling framework, experiments are performed using a setup that forces pure torsional deformation. Three different geometric configurations of the patterned piezoelectric layer are used for the experiments. The frequency and amplitude of the forced torsional load are systematically varied in order to study the behavior of the piezoelectric sensor. Experimental results demonstrate that two voltage outputs of the piezoelectric beam are approximately out of phase with identical amplitude. Moreover, the length of the piezoelectric layers has a significant influence on the sensing properties. Our theoretical predictions using the model support the experimental findings.
Predicting spiral wave patterns from cell properties in a model of biological self-organization.
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.
Predicting spiral wave patterns from cell properties in a model of biological self-organization
NASA Astrophysics Data System (ADS)
Geberth, Daniel; Hütt, Marc-Thorsten
2008-09-01
In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.
A Bayesian Dose-finding Design for Oncology Clinical Trials of Combinational Biological Agents
Cai, Chunyan; Yuan, Ying; Ji, Yuan
2013-01-01
Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which efficacy and toxicity monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a dose-finding design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. PMID:24511160
The amazing evolutionary dynamics of non-linear optical systems with feedback
NASA Astrophysics Data System (ADS)
Yaroslavsky, Leonid
2013-09-01
Optical systems with feedback are, generally, non-linear dynamic systems. As such, they exhibit evolutionary behavior. In the paper we present results of experimental investigation of evolutionary dynamics of several models of such systems. The models are modifications of the famous mathematical "Game of Life". The modifications are two-fold: "Game of Life" rules are made stochastic and mutual influence of cells is made spatially non-uniform. A number of new phenomena in the evolutionary dynamics of the models are revealed: - "Ordering of chaos". Formation, from seed patterns, of stable maze-like patterns with chaotic "dislocations" that resemble natural patterns, such as skin patterns of some animals and fishes, see shell, fingerprints, magnetic domain patterns and alike, which one can frequently find in the nature. These patterns and their fragments exhibit a remarkable capability of unlimited growth. - "Self-controlled growth" of chaotic "live" formations into "communities" bounded, depending on the model, by a square, hexagon or octagon, until they reach a certain critical size, after which the growth stops. - "Eternal life in a bounded space" of "communities" after reaching a certain size and shape. - "Coherent shrinkage" of "mature", after reaching a certain size, "communities" into one of stable or oscillating patterns preserving in this process isomorphism of their bounding shapes until the very end.
Proposal of diagnostic process model for computer based diagnosis.
Matsumura, Yasushi; Takeda, Toshihiro; Manabe, Shiro; Saito, Hirokazu; Teramoto, Kei; Kuwata, Shigeki; Mihara, Naoki
2012-01-01
We aim at making a diagnosis support system that can be put to practical use. We proposed a diagnostic process model based on simple knowledge which can be gleaned from textbooks. We defined clinical finding (CF) as a general concept for patient's symptom or findings etc., whose value is expressed by Boolean. We call the combination of several CFs a "CF pattern", and a set of CF patterns with concomitant diseases "case base". We consider diagnosis as a process of searching an instance from the case base whose CF pattern is concomitant with that of a patient. The diseases which have the same CF pattern are candidates for diagnosis. Then we select a CF which is present in part of the candidates and check whether it is present or absent in the patient in order to narrow down the candidates. Because the case base does not exist in reality, the probability of CF pattern is calculated by the product of CF occurrence rate assuming that occurrence of CF is independent. Therefore the knowledge required for diagnosis is frequency of disease under sex and age group and CF-disease relation (CF and its occurrence rate in the disease). By processing these two types of knowledge, diagnosis can be made.
Reply to comments by Riley and Dunlop on He et al. (2015)
Bence, James R.; Madenjian, Charles P.; He, Ji X.; Fielder, David G.; Pothoven, Steven A.; Dobiesz, Norine E.; Johnson, James E.; Ebener, Mark P.; Cottrill, R. Adam; Mohr, Lloyd C.; Koproski, Scott R.
2016-01-01
He et al. (2015) described piscivory patterns in the main basin of Lake Huron 1984-2010, during which there was also a pattern of stepwise declines in the abundance of dominant prey fish species. The approach of He et al. (2015) was to couple age-structured stock assessment and fish bioenergetics models to estimate prey fish consumption, and to compare these patterns with prey fish biomass from a bottom trawl survey. Riley and Dunlop (2015) were highly critical of the methods and conclusions reached by He et al. (2015). They claimed that we incorrectly interpreted the bottom trawl survey data, and did not account for uncertainty. We respond to these and other criticisms below, which we find do not undermine our findings.
DEM study of granular flow around blocks attached to inclined walls
NASA Astrophysics Data System (ADS)
Samsu, Joel; Zhou, Zongyan; Pinson, David; Chew, Sheng
2017-06-01
Damage due to intense particle-wall contact in industrial applications can cause severe problems in industries such as mineral processing, mining and metallurgy. Studying the flow dynamics and forces on containing walls can provide valuable feedback for equipment design and optimising operations to prolong the equipment lifetime. Therefore, solids flow-wall interaction phenomena, i.e. induced wall stress and particle flow patterns should be well understood. In this work, discrete element method (DEM) is used to study steady state granular flow in a gravity-fed hopper like geometry with blocks attached to an inclined wall. The effects of different geometries, e.g. different wall angles and spacing between blocks are studied by means of a 3D DEM slot model with periodic boundary conditions. The findings of this work include (i) flow analysis in terms of flow patterns and particle velocities, (ii) force distributions within the model geometry, and (iii) wall stress vs. model height diagrams. The model enables easy transfer of the key findings to other industrial applications handling granular materials.
The (Conditional) Resource Dilution Model: State- and Community-Level Modifications.
Gibbs, Benjamin G; Workman, Joseph; Downey, Douglas B
2016-06-01
One of the most consistent patterns in the social sciences is the relationship between sibship size and educational outcomes: those with fewer siblings outperform those with many. The resource dilution (RD) model emphasizes the increasing division of parental resources within the nuclear family as the number of children grows, yet it fails to account for instances when the relationship between sibship size and education is often weak or even positive. To reconcile, we introduce a conditional resource dilution (CRD) model to acknowledge that nonparental investments might aid in children's development and condition the effect of siblings. We revisit the General Social Surveys (1972-2010) and find support for a CRD approach: the relationship between sibship size and educational attainment has declined during the first half of the twentieth century, and this relationship varies across religious groups. Findings suggest that state and community resources can offset the impact of resource dilution-a more sociological interpretation of sibship size patterns than that of the traditional RD model.
NASA Astrophysics Data System (ADS)
van der Ent, R.; Van Beek, R.; Sutanudjaja, E.; Wang-Erlandsson, L.; Hessels, T.; Bastiaanssen, W.; Bierkens, M. F.
2017-12-01
The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. Root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.
NASA Astrophysics Data System (ADS)
van der Ent, Ruud; van Beek, Rens; Sutanudjaja, Edwin; Wang-Erlandsson, Lan; Hessels, Tim; Bastiaanssen, Wim; Bierkens, Marc
2017-04-01
The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. For root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.
Influence of urban pattern on inundation flow in floodplains of lowland rivers.
Bruwier, M; Mustafa, A; Aliaga, D G; Archambeau, P; Erpicum, S; Nishida, G; Zhang, X; Pirotton, M; Teller, J; Dewals, B
2018-05-01
The objective of this paper is to investigate the respective influence of various urban pattern characteristics on inundation flow. A set of 2000 synthetic urban patterns were generated using an urban procedural model providing locations and shapes of streets and buildings over a square domain of 1×1km 2 . Steady two-dimensional hydraulic computations were performed over the 2000 urban patterns with identical hydraulic boundary conditions. To run such a large amount of simulations, the computational efficiency of the hydraulic model was improved by using an anisotropic porosity model. This model computes on relatively coarse computational cells, but preserves information from the detailed topographic data through porosity parameters. Relationships between urban characteristics and the computed inundation water depths have been based on multiple linear regressions. Finally, a simple mechanistic model based on two district-scale porosity parameters, combining several urban characteristics, is shown to capture satisfactorily the influence of urban characteristics on inundation water depths. The findings of this study give guidelines for more flood-resilient urban planning. Copyright © 2017 Elsevier B.V. All rights reserved.
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.
Reconceptualizing the classification of PNAS articles
Airoldi, Edoardo M.; Erosheva, Elena A.; Fienberg, Stephen E.; Joutard, Cyrille; Love, Tanzy; Shringarpure, Suyash
2010-01-01
PNAS article classification is rooted in long-standing disciplinary divisions that do not necessarily reflect the structure of modern scientific research. We reevaluate that structure using latent pattern models from statistical machine learning, also known as mixed-membership models, that identify semantic structure in co-occurrence of words in the abstracts and references. Our findings suggest that the latent dimensionality of patterns underlying PNAS research articles in the Biological Sciences is only slightly larger than the number of categories currently in use, but it differs substantially in the content of the categories. Further, the number of articles that are listed under multiple categories is only a small fraction of what it should be. These findings together with the sensitivity analyses suggest ways to reconceptualize the organization of papers published in PNAS. PMID:21078953
NASA Astrophysics Data System (ADS)
Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.
2017-02-01
Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.
Clustering of change patterns using Fourier coefficients.
Kim, Jaehee; Kim, Haseong
2008-01-15
To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a time period because biologically related gene groups can share the same change patterns. Many clustering algorithms have been proposed to group observation data. However, because of the complexity of the underlying functions there have not been many studies on grouping data based on change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. The sample Fourier coefficients not only provide information about the underlying functions, but also reduce the dimension. In addition, as their limiting distribution is a multivariate normal, a model-based clustering method incorporating statistical properties would be appropriate. This work is aimed at discovering gene groups with similar change patterns that share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. The model-based method is advantageous over other methods in our proposed model because the sample Fourier coefficients asymptotically follow the multivariate normal distribution. Change patterns are automatically estimated with the Fourier representation in our model. Our model was tested in simulations and on real gene data sets. The simulation results showed that the model-based clustering method with the sample Fourier coefficients has a lower clustering error rate than K-means clustering. Even when the number of repeated time points was small, the same results were obtained. We also applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns. The R program is available upon the request.
Sentence-Based Attentional Mechanisms in Word Learning: Evidence from a Computational Model
Alishahi, Afra; Fazly, Afsaneh; Koehne, Judith; Crocker, Matthew W.
2012-01-01
When looking for the referents of novel nouns, adults and young children are sensitive to cross-situational statistics (Yu and Smith, 2007; Smith and Yu, 2008). In addition, the linguistic context that a word appears in has been shown to act as a powerful attention mechanism for guiding sentence processing and word learning (Landau and Gleitman, 1985; Altmann and Kamide, 1999; Kako and Trueswell, 2000). Koehne and Crocker (2010, 2011) investigate the interaction between cross-situational evidence and guidance from the sentential context in an adult language learning scenario. Their studies reveal that these learning mechanisms interact in a complex manner: they can be used in a complementary way when context helps reduce referential uncertainty; they influence word learning about equally strongly when cross-situational and contextual evidence are in conflict; and contextual cues block aspects of cross-situational learning when both mechanisms are independently applicable. To address this complex pattern of findings, we present a probabilistic computational model of word learning which extends a previous cross-situational model (Fazly et al., 2010) with an attention mechanism based on sentential cues. Our model uses a framework that seamlessly combines the two sources of evidence in order to study their emerging pattern of interaction during the process of word learning. Simulations of the experiments of (Koehne and Crocker, 2010, 2011) reveal an overall pattern of results that are in line with their findings. Importantly, we demonstrate that our model does not need to explicitly assign priority to either source of evidence in order to produce these results: learning patterns emerge as a result of a probabilistic interaction between the two clue types. Moreover, using a computational model allows us to examine the developmental trajectory of the differential roles of cross-situational and sentential cues in word learning. PMID:22783211
Coupling human mobility and social ties.
Toole, Jameson L; Herrera-Yaqüe, Carlos; Schneider, Christian M; González, Marta C
2015-04-06
Studies using massive, passively collected data from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion and organizational dynamics. More recently, these data have come tagged with geographical information, enabling studies of human mobility patterns and the science of cities. We combine these two pursuits and uncover reproducible mobility patterns among social contacts. First, we introduce measures of mobility similarity and predictability and measure them for populations of users in three large urban areas. We find individuals' visitations patterns are far more similar to and predictable by social contacts than strangers and that these measures are positively correlated with tie strength. Unsupervised clustering of hourly variations in mobility similarity identifies three categories of social ties and suggests geography is an important feature to contextualize social relationships. We find that the composition of a user's ego network in terms of the type of contacts they keep is correlated with mobility behaviour. Finally, we extend a popular mobility model to include movement choices based on social contacts and compare its ability to reproduce empirical measurements with two additional models of mobility. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Dawson, Samantha J.; Chivers, Meredith L.
2016-01-01
Research across groups and methods consistently finds a gender difference in patterns of specificity of genital response; however, empirically supported mechanisms to explain this difference are lacking. The information-processing model of sexual arousal posits that automatic and controlled cognitive processes are requisite for the generation of sexual responses. Androphilic women’s gender-nonspecific response patterns may be the result of sexually-relevant cues that are common to both preferred and nonpreferred genders capturing attention and initiating an automatic sexual response, whereas men’s attentional system may be biased towards the detection and response to sexually-preferred cues only. In the present study, we used eye tracking to assess visual attention to sexually-preferred and nonpreferred cues in a sample of androphilic women and gynephilic men. Results support predictions from the information-processing model regarding gendered processing of sexual stimuli in men and women. Men’s initial attention patterns were gender-specific, whereas women’s were nonspecific. In contrast, both men and women exhibited gender-specific patterns of controlled attention, although this effect was stronger among men. Finally, measures of attention and self-reported attraction were positively related in both men and women. These findings are discussed in the context of the information-processing model and evolutionary mechanisms that may have evolved to promote gendered attentional systems. PMID:27088358
The neural dynamics of task context in free recall.
Polyn, Sean M; Kragel, James E; Morton, Neal W; McCluey, Joshua D; Cohen, Zachary D
2012-03-01
Multivariate pattern analysis (MVPA) is a powerful tool for relating theories of cognitive function to the neural dynamics observed while people engage in cognitive tasks. Here, we use the Context Maintenance and Retrieval model of free recall (CMR; Polyn et al., 2009a) to interpret variability in the strength of task-specific patterns of distributed neural activity as participants study and recall lists of words. The CMR model describes how temporal and source-related (here, encoding task) information combine in a contextual representation that is responsible for guiding memory search. Each studied word in the free-recall paradigm is associated with one of two encoding tasks (size and animacy) that have distinct neural representations during encoding. We find evidence for the context retrieval hypothesis central to the CMR model: Task-specific patterns of neural activity are reactivated during memory search, as the participant recalls an item previously associated with a particular task. Furthermore, we find that the fidelity of these task representations during study is related to task-shifting, the serial position of the studied item, and variability in the magnitude of the recency effect across participants. The CMR model suggests that these effects may be related to a central parameter of the model that controls the rate that an internal contextual representation integrates information from the surrounding environment. Copyright © 2011 Elsevier Ltd. All rights reserved.
Sarker, Hillol; Tyburski, Matthew; Rahman, Md. Mahbubur; Hovsepian, Karen; Sharmin, Moushumi; Epstein, David H.; Preston, Kenzie L.; Furr-Holden, C. Debra; Milam, Adam; Nahum-Shani, Inbal; al’Absi, Mustafa; Kumar, Santosh
2016-01-01
Management of daily stress can be greatly improved by delivering sensor-triggered just-in-time interventions (JITIs) on mobile devices. The success of such JITIs critically depends on being able to mine the time series of noisy sensor data to find the most opportune moments. In this paper, we propose a time series pattern mining method to detect significant stress episodes in a time series of discontinuous and rapidly varying stress data. We apply our model to 4 weeks of physiological, GPS, and activity data collected from 38 users in their natural environment to discover patterns of stress in real-life. We find that the duration of a prior stress episode predicts the duration of the next stress episode and stress in mornings and evenings is lower than during the day. We then analyze the relationship between stress and objectively rated disorder in the surrounding neighborhood and develop a model to predict stressful episodes. PMID:28058409
NASA Astrophysics Data System (ADS)
Kaplan, D. A.; Casey, S. T.; Cohen, M. J.; Acharya, S.; Jawitz, J. W.
2016-12-01
A century of hydrologic modification has altered the physical and biological drivers of landscape processes in the Everglades (Florida, USA). Restoring the ridge-slough patterned landscape, a dominant feature of the historical system, is a priority, but requires an understanding of pattern genesis and degradation mechanisms. Physical experiments to evaluate alternative pattern formation mechanisms are limited by the long time scales of peat accumulation and loss, necessitating model-based comparisons, where support for a particular mechanism is based on model replication of extant patterning and trajectories of degradation. However, multiple mechanisms yield patch elongation in the direction of historical flow (a central feature of ridge-slough patterning), limiting the utility of that characteristic for discriminating among alternatives. Using data from vegetation maps, we investigated the statistical features of ridge-slough spatial patterning (ridge density, patch perimeter, elongation, patch-size distributions, and spatial periodicity) to establish more rigorous criteria for evaluating model performance and to inform controls on pattern variation across the contemporary system. Two independent analyses (2-D periodograms and patch size distributions) provide strong evidence against regular patterning, with the landscape exhibiting neither a characteristic wavelength nor a characteristic patch size, both of which are expected under conditions that produce regular patterns. Rather, landscape properties suggest robust scale-free patterning, indicating genesis from the coupled effects of local facilitation and a global negative feedback operating uniformly at the landscape-scale. This finding challenges widespread invocation of scale-dependent negative feedbacks for explaining ridge-slough pattern origins. These results help discern among genesis mechanisms and provide an improved statistical description of the landscape that can be used to compare among model outputs, as well as to assess the success of future restoration projects.
Modelling survival: exposure pattern, species sensitivity and uncertainty.
Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G
2016-07-06
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.
Modelling survival: exposure pattern, species sensitivity and uncertainty
NASA Astrophysics Data System (ADS)
Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I.; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B.; van den Brink, Paul J.; Veltman, Karin; Vogel, Sören; Zimmer, Elke I.; Preuss, Thomas G.
2016-07-01
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.
Chung, Sukhoon; Rhee, Hyunsill; Suh, Yongmoo
2010-01-01
Objectives This study sought to find answers to the following questions: 1) Can we predict whether a patient will revisit a healthcare center? 2) Can we anticipate diseases of patients who revisit the center? Methods For the first question, we applied 5 classification algorithms (decision tree, artificial neural network, logistic regression, Bayesian networks, and Naïve Bayes) and the stacking-bagging method for building classification models. To solve the second question, we performed sequential pattern analysis. Results We determined: 1) In general, the most influential variables which impact whether a patient of a public healthcare center will revisit it or not are personal burden, insurance bill, period of prescription, age, systolic pressure, name of disease, and postal code. 2) The best plain classification model is dependent on the dataset. 3) Based on average of classification accuracy, the proposed stacking-bagging method outperformed all traditional classification models and our sequential pattern analysis revealed 16 sequential patterns. Conclusions Classification models and sequential patterns can help public healthcare centers plan and implement healthcare service programs and businesses that are more appropriate to local residents, encouraging them to revisit public health centers. PMID:21818426
Anatomy of news consumption on Facebook.
Schmidt, Ana Lucía; Zollo, Fabiana; Del Vicario, Michela; Bessi, Alessandro; Scala, Antonio; Caldarelli, Guido; Stanley, H Eugene; Quattrociocchi, Walter
2017-03-21
The advent of social media and microblogging platforms has radically changed the way we consume information and form opinions. In this paper, we explore the anatomy of the information space on Facebook by characterizing on a global scale the news consumption patterns of 376 million users over a time span of 6 y (January 2010 to December 2015). We find that users tend to focus on a limited set of pages, producing a sharp community structure among news outlets. We also find that the preferences of users and news providers differ. By tracking how Facebook pages "like" each other and examining their geolocation, we find that news providers are more geographically confined than users. We devise a simple model of selective exposure that reproduces the observed connectivity patterns.
Simple versus complex models of trait evolution and stasis as a response to environmental change
NASA Astrophysics Data System (ADS)
Hunt, Gene; Hopkins, Melanie J.; Lidgard, Scott
2015-04-01
Previous analyses of evolutionary patterns, or modes, in fossil lineages have focused overwhelmingly on three simple models: stasis, random walks, and directional evolution. Here we use likelihood methods to fit an expanded set of evolutionary models to a large compilation of ancestor-descendant series of populations from the fossil record. In addition to the standard three models, we assess more complex models with punctuations and shifts from one evolutionary mode to another. As in previous studies, we find that stasis is common in the fossil record, as is a strict version of stasis that entails no real evolutionary changes. Incidence of directional evolution is relatively low (13%), but higher than in previous studies because our analytical approach can more sensitively detect noisy trends. Complex evolutionary models are often favored, overwhelmingly so for sequences comprising many samples. This finding is consistent with evolutionary dynamics that are, in reality, more complex than any of the models we consider. Furthermore, the timing of shifts in evolutionary dynamics varies among traits measured from the same series. Finally, we use our empirical collection of evolutionary sequences and a long and highly resolved proxy for global climate to inform simulations in which traits adaptively track temperature changes over time. When realistically calibrated, we find that this simple model can reproduce important aspects of our paleontological results. We conclude that observed paleontological patterns, including the prevalence of stasis, need not be inconsistent with adaptive evolution, even in the face of unstable physical environments.
ERIC Educational Resources Information Center
Montemurro, Theodore J.
The behavior patterns of 6 handicapped children and 14 nonhandicapped children were recorded during participation in a model developmental-interactive based curriculum for preschool children. Interactions were recorded using the Coping Analysis Schedule for Educational Settings. Among findings were the following: the consistently high occurrence…
Fraver, Shawn; D'Amato, Anthony W.; Bradford, John B.; Jonsson, Bengt Gunnar; Jönsson, Mari; Esseen, Per-Anders
2013-01-01
Question: What factors best characterize tree competitive environments in this structurally diverse old-growth forest, and do these factors vary spatially within and among stands? Location: Old-growth Picea abies forest of boreal Sweden. Methods: Using long-term, mapped permanent plot data augmented with dendrochronological analyses, we evaluated the effect of neighbourhood competition on focal tree growth by means of standard competition indices, each modified to include various metrics of trees size, neighbour mortality weighting (for neighbours that died during the inventory period), and within-neighbourhood tree clustering. Candidate models were evaluated using mixed-model linear regression analyses, with mean basal area increment as the response variable. We then analysed stand-level spatial patterns of competition indices and growth rates (via kriging) to determine if the relationship between these patterns could further elucidate factors influencing tree growth. Results: Inter-tree competition clearly affected growth rates, with crown volume being the size metric most strongly influencing the neighbourhood competitive environment. Including neighbour tree mortality weightings in models only slightly improved descriptions of competitive interactions. Although the within-neighbourhood clustering index did not improve model predictions, competition intensity was influenced by the underlying stand-level tree spatial arrangement: stand-level clustering locally intensified competition and reduced tree growth, whereas in the absence of such clustering, inter-tree competition played a lesser role in constraining tree growth. Conclusions: Our findings demonstrate that competition continues to influence forest processes and structures in an old-growth system that has not experienced major disturbances for at least two centuries. The finding that the underlying tree spatial pattern influenced the competitive environment suggests caution in interpreting traditional tree competition studies, in which tree spatial patterning is typically not taken into account. Our findings highlight the importance of forest structure – particularly the spatial arrangement of trees – in regulating inter-tree competition and growth in structurally diverse forests, and they provide insight into the causes and consequences of heterogeneity in this old-growth system.
Heterogeneity in Trajectories of Child Maltreatment Severity: A Two-Part Growth Mixture Model
Yampolskaya, Svetlana; Greenbaum, Paul E.; Brown, C. Hendricks; Armstrong, Mary I.
2016-01-01
This study examined the trajectories of maltreatment severity and substantiation over a 24-month period among children (N = 82,396) with repeated maltreatment reports. Findings revealed two different longitudinal patterns. The first pattern, Elevated Severity, showed a higher level of maltreatment during the initial incident and increased maltreatment severity during subsequent incidents but the substantiation rates for this class decreased over time. The second pattern, Lowered Severity, showed a much lower level of severity, but the likelihood of substantiation increased over time. The Elevated Severity class was comprised of children with an elevated risk profile due to both individual and contextual risk factors including older age, female gender, caregivers’ substance use problems, and a higher number of previous maltreatment reports. Implications of the findings are discussed. PMID:26300381
Trojano, L; Balbi, P; Russo, G; Elefante, R
1994-05-01
We present a 2-year verbal and nonverbal follow-up of a crossed aphasic patient. The patient had suffered from widespread ischemic damage in the area of right middle cerebral artery, with a parieto-temporal lesion. Three months postonset he showed classical Wernicke's aphasia associated with oral, limb and constructional apraxia and left hemineglect. However, follow-up findings showed a complex, dynamic pattern entirely consistent with cognitive models of language and nonlanguage abilities. Current models of functional brain lateralizations could not satisfactorily account for such longitudinal, fine-grain observations.
Street, Nichola; Forsythe, Alexandra M; Reilly, Ronan; Taylor, Richard; Helmy, Mai S
2016-01-01
Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics.
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 extended HR increasing as monitoring duration increased (median peak core and extended HR 0.650 and 9.520ha, respectively). These findings are likely driven by multiple factors that have not been further investigated within this study. Different roaming patterns suggest heterogeneous contact rates between dogs in this population. These findings will be incorporated into disease-spread modelling to more realistically represent roaming patterns and improve model predictions. Copyright © 2017 Elsevier B.V. All rights reserved.
Bisous model-Detecting filamentary patterns in point processes
NASA Astrophysics Data System (ADS)
Tempel, E.; Stoica, R. S.; Kipper, R.; Saar, E.
2016-07-01
The cosmic web is a highly complex geometrical pattern, with galaxy clusters at the intersection of filaments and filaments at the intersection of walls. Identifying and describing the filamentary network is not a trivial task due to the overwhelming complexity of the structure, its connectivity and the intrinsic hierarchical nature. To detect and quantify galactic filaments we use the Bisous model, which is a marked point process built to model multi-dimensional patterns. The Bisous filament finder works directly with the galaxy distribution data and the model intrinsically takes into account the connectivity of the filamentary network. The Bisous model generates the visit map (the probability to find a filament at a given point) together with the filament orientation field. Using these two fields, we can extract filament spines from the data. Together with this paper we publish the computer code for the Bisous model that is made available in GitHub. The Bisous filament finder has been successfully used in several cosmological applications and further development of the model will allow to detect the filamentary network also in photometric redshift surveys, using the full redshift posterior. We also want to encourage the astro-statistical community to use the model and to connect it with all other existing methods for filamentary pattern detection and characterisation.
Dynamic sensory cues shape song structure in Drosophila
NASA Astrophysics Data System (ADS)
Coen, Philip; Clemens, Jan; Weinstein, Andrew J.; Pacheco, Diego A.; Deng, Yi; Murthy, Mala
2014-03-01
The generation of acoustic communication signals is widespread across the animal kingdom, and males of many species, including Drosophilidae, produce patterned courtship songs to increase their chance of success with a female. For some animals, song structure can vary considerably from one rendition to the next; neural noise within pattern generating circuits is widely assumed to be the primary source of such variability, and statistical models that incorporate neural noise are successful at reproducing the full variation present in natural songs. In direct contrast, here we demonstrate that much of the pattern variability in Drosophila courtship song can be explained by taking into account the dynamic sensory experience of the male. In particular, using a quantitative behavioural assay combined with computational modelling, we find that males use fast modulations in visual and self-motion signals to pattern their songs, a relationship that we show is evolutionarily conserved. Using neural circuit manipulations, we also identify the pathways involved in song patterning choices and show that females are sensitive to song features. Our data not only demonstrate that Drosophila song production is not a fixed action pattern, but establish Drosophila as a valuable new model for studies of rapid decision-making under both social and naturalistic conditions.
A Bayesian Model of Category-Specific Emotional Brain Responses
Wager, Tor D.; Kang, Jian; Johnson, Timothy D.; Nichols, Thomas E.; Satpute, Ajay B.; Barrett, Lisa Feldman
2015-01-01
Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories—fear, anger, disgust, sadness, or happiness—is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches. PMID:25853490
Quantification of Operational Risk Using A Data Mining
NASA Technical Reports Server (NTRS)
Perera, J. Sebastian
1999-01-01
What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process
More rain, more drought: will the forests thrive or die?
Sally Duncan
1999-01-01
Global warming: Is it real or not? Ron Neilson, PNW Research Station bioclimatologist, has been studying the phenomena for about 25 years. He also is the lead author on one of three models in the world designed to track climate-driven vegetation change patterns on the planet.Neilson's findings, featured in this issue of "Science Findings," may...
Maximum entropy production allows a simple representation of heterogeneity in semiarid ecosystems.
Schymanski, Stanislaus J; Kleidon, Axel; Stieglitz, Marc; Narula, Jatin
2010-05-12
Feedbacks between water use, biomass and infiltration capacity in semiarid ecosystems have been shown to lead to the spontaneous formation of vegetation patterns in a simple model. The formation of patterns permits the maintenance of larger overall biomass at low rainfall rates compared with homogeneous vegetation. This results in a bias of models run at larger scales neglecting subgrid-scale variability. In the present study, we investigate the question whether subgrid-scale heterogeneity can be parameterized as the outcome of optimal partitioning between bare soil and vegetated area. We find that a two-box model reproduces the time-averaged biomass of the patterns emerging in a 100 x 100 grid model if the vegetated fraction is optimized for maximum entropy production (MEP). This suggests that the proposed optimality-based representation of subgrid-scale heterogeneity may be generally applicable to different systems and at different scales. The implications for our understanding of self-organized behaviour and its modelling are discussed.
What spatial scales are believable for climate model projections of sea surface temperature?
NASA Astrophysics Data System (ADS)
Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.
2014-09-01
Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.
Network based approaches reveal clustering in protein point patterns
NASA Astrophysics Data System (ADS)
Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang
2014-03-01
Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.
Lomsadze, Alexandre; Gemayel, Karl; Tang, Shiyuyun; Borodovsky, Mark
2018-05-17
In a conventional view of the prokaryotic genome organization, promoters precede operons and ribosome binding sites (RBSs) with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of precomputed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as noncanonical RBS patterns. To assess the accuracy of GeneMarkS-2, we used genes validated by COG (Clusters of Orthologous Groups) annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of ∼5000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts. © 2018 Lomsadze et al.; Published by Cold Spring Harbor Laboratory Press.
Mynard, Jonathan P; Smolich, Joseph J
2016-07-01
Coronary hemodynamics are known to be affected by intravascular and extravascular factors that vary regionally and transmurally between the perfusion territories of left and right coronary arteries. However, despite clinical evidence that left coronary arterial dominance portends greater cardiovascular risk, relatively little is known about the effects of left or right dominance on regional conduit arterial and microcirculatory blood flow patterns, particularly in the presence of systemic or pulmonary hypertension. We addressed this issue using a multiscale numerical model of the human coronary circulation situated in a closed-loop cardiovascular model. The coronary model represented left or right dominant anatomies and accounted for transmural and regional differences in vascular properties and extravascular compression. Regional coronary flow dynamics of the two anatomical variants were compared under normotensive conditions, raised systemic or pulmonary pressures with maintained flow demand, and after accounting for adaptations known to occur in acute and chronic hypertensive states. Key findings were that 1) right coronary arterial flow patterns were strongly influenced by dominance and systemic/pulmonary hypertension; 2) dominance had minor effects on left coronary arterial and all microvascular flow patterns (aside from mean circumflex flow); 3) although systemic hypertension favorably increased perfusion pressure, this benefit varied regionally and transmurally and was offset by increased left ventricular and septal flow demands; and 4) pulmonary hypertension had a substantial negative effect on right ventricular and septal flows, which was exacerbated by greater metabolic demands. These findings highlight the importance of interactions between coronary arterial dominance and hypertension in modulating coronary hemodynamics. Copyright © 2016 the American Physiological Society.
Trend time-series modeling and forecasting with neural networks.
Qi, Min; Zhang, G Peter
2008-05-01
Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.
Integrative modelling reveals mechanisms linking productivity and plant species richness.
Grace, James B; Anderson, T Michael; Seabloom, Eric W; Borer, Elizabeth T; Adler, Peter B; Harpole, W Stanley; Hautier, Yann; Hillebrand, Helmut; Lind, Eric M; Pärtel, Meelis; Bakker, Jonathan D; Buckley, Yvonne M; Crawley, Michael J; Damschen, Ellen I; Davies, Kendi F; Fay, Philip A; Firn, Jennifer; Gruner, Daniel S; Hector, Andy; Knops, Johannes M H; MacDougall, Andrew S; Melbourne, Brett A; Morgan, John W; Orrock, John L; Prober, Suzanne M; Smith, Melinda D
2016-01-21
How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.
The role of the SCRAMBLED receptor-like kinase in patterning the Arabidopsis root epidermis.
Kwak, Su-Hwan; Schiefelbein, John
2007-02-01
Cell-type patterning in the Arabidopsis root epidermis is achieved by a network of transcription factors and influenced by a position-dependent mechanism. The SCRAMBLED receptor-like kinase is required for the normal pattern to arise, but its precise role is not understood. Here we describe genetic and molecular studies to define the spatial and temporal role of SCM in epidermal patterning and its relationship to the transcriptional network. Our results suggest that SCM helps unspecified epidermal cells interpret their position in relation to the underlying cortical cells and establish distinct cell identities. Furthermore, SCM loss-of-function and overexpression analyses suggest that SCM influences cell fate through its negative transcriptional regulation of the WEREWOLF MYB gene in epidermal cells at the H position. We also find that SCM function is specifically required for patterning the post-embryonic root epidermis and not for the analogous epidermal cell-type patterning during embryogenesis or hypocotyl development. In addition, we show that two closely related SCM-like genes in Arabidopsis (SRF1 and SRF3) are not required alone or together with SCM for proper epidermal patterning. These findings help define the developmental and mechanistic role of SCM and suggest a new model for its action in root epidermal cell patterning.
Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.
de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca
2018-05-01
Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.
Thermodynamic Modeling of Donor Splice Site Recognition in pre-mRNA
NASA Astrophysics Data System (ADS)
Aalberts, Daniel P.; Garland, Jeffrey A.
2004-03-01
When eukaryotic genes are edited by the spliceosome, the first step in intron recognition is the binding of a U1 snRNA with the donor (5') splice site. We model this interaction thermodynamically to identify splice sites. Applied to a set of 65 annotated genes, our Finding with Binding method achieves a significant separation between real and false sites. Analyzing binding patterns allows us to discard a large number of decoy sites. Our results improve statistics-based methods for donor site recognition, demonstrating the promise of physical modeling to find functional elements in the genome.
Thermodynamic modeling of donor splice site recognition in pre-mRNA
NASA Astrophysics Data System (ADS)
Garland, Jeffrey A.; Aalberts, Daniel P.
2004-04-01
When eukaryotic genes are edited by the spliceosome, the first step in intron recognition is the binding of a U1 small nuclear RNA with the donor ( 5' ) splice site. We model this interaction thermodynamically to identify splice sites. Applied to a set of 65 annotated genes, our “finding with binding” method achieves a significant separation between real and false sites. Analyzing binding patterns allows us to discard a large number of decoy sites. Our results improve statistics-based methods for donor site recognition, demonstrating the promise of physical modeling to find functional elements in the genome.
Training Spiking Neural Models Using Artificial Bee Colony
Vazquez, Roberto A.; Garro, Beatriz A.
2015-01-01
Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644
Active Curved Polymers Form Vortex Patterns on Membranes.
Denk, Jonas; Huber, Lorenz; Reithmann, Emanuel; Frey, Erwin
2016-04-29
Recent in vitro experiments with FtsZ polymers show self-organization into different dynamic patterns, including structures reminiscent of the bacterial Z ring. We model FtsZ polymers as active particles moving along chiral, circular paths by Brownian dynamics simulations and a Boltzmann approach. Our two conceptually different methods point to a generic phase behavior. At intermediate particle densities, we find self-organization into vortex structures including closed rings. Moreover, we show that the dynamics at the onset of pattern formation is described by a generalized complex Ginzburg-Landau equation.
Synonym set extraction from the biomedical literature by lexical pattern discovery.
McCrae, John; Collier, Nigel
2008-03-24
Although there are a large number of thesauri for the biomedical domain many of them lack coverage in terms and their variant forms. Automatic thesaurus construction based on patterns was first suggested by Hearst 1, but it is still not clear how to automatically construct such patterns for different semantic relations and domains. In particular it is not certain which patterns are useful for capturing synonymy. The assumption of extant resources such as parsers is also a limiting factor for many languages, so it is desirable to find patterns that do not use syntactical analysis. Finally to give a more consistent and applicable result it is desirable to use these patterns to form synonym sets in a sound way. We present a method that automatically generates regular expression patterns by expanding seed patterns in a heuristic search and then develops a feature vector based on the occurrence of term pairs in each developed pattern. This allows for a binary classifications of term pairs as synonymous or non-synonymous. We then model this result as a probability graph to find synonym sets, which is equivalent to the well-studied problem of finding an optimal set cover. We achieved 73.2% precision and 29.7% recall by our method, out-performing hand-made resources such as MeSH and Wikipedia. We conclude that automatic methods can play a practical role in developing new thesauri or expanding on existing ones, and this can be done with only a small amount of training data and no need for resources such as parsers. We also concluded that the accuracy can be improved by grouping into synonym sets.
Representing Practice: Practice Models, Patterns, Bundles
ERIC Educational Resources Information Center
Falconer, Isobel; Finlay, Janet; Fincher, Sally
2011-01-01
This article critiques learning design as a representation for sharing and developing practice, based on synthesis of three projects. Starting with the findings of the Mod4L Models of Practice project, it argues that the technical origins of learning design, and the consequent focus on structure and sequence, limit its usefulness for sharing…
An overview of the neuron ring model
NASA Technical Reports Server (NTRS)
Taber, Rod
1991-01-01
The Neuron Ring model employs an avalanche structure with two important distinctions at the neuron level. Each neuron has two memory latches; one traps maximum neuronal activation during pattern presentation, and the other records the time of latch content change. The latches filter short term memory. In the process, they preserve length 1 snapshots of activation theory history. The model finds utility in pattern classification. Its synaptic weights are first conditioned with sample spectra. The model then receives a test or unknown signal. The objective is to identify the sample closest to the test signal. Class decision follows complete presentation of the test data. The decision maker relies exclusively on the latch contents. Presented here is an overview of the Neuron Ring at the seminar level.
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.
Exploring Entrainment Patterns of Human Emotion in Social Media
Luo, Chuan; Zhang, Zhu
2016-01-01
Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace. PMID:26953692
Exploring Entrainment Patterns of Human Emotion in Social Media.
He, Saike; Zheng, Xiaolong; Zeng, Daniel; Luo, Chuan; Zhang, Zhu
2016-01-01
Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace.
Anatomy of news consumption on Facebook
Schmidt, Ana Lucía; Del Vicario, Michela; Quattrociocchi, Walter
2017-01-01
The advent of social media and microblogging platforms has radically changed the way we consume information and form opinions. In this paper, we explore the anatomy of the information space on Facebook by characterizing on a global scale the news consumption patterns of 376 million users over a time span of 6 y (January 2010 to December 2015). We find that users tend to focus on a limited set of pages, producing a sharp community structure among news outlets. We also find that the preferences of users and news providers differ. By tracking how Facebook pages “like” each other and examining their geolocation, we find that news providers are more geographically confined than users. We devise a simple model of selective exposure that reproduces the observed connectivity patterns. PMID:28265082
Colón-Ramos, Uriyoán; Racette, Susan B.; Ganiban, Jody; Nguyen, Thuy G.; Kocak, Mehmet; Carroll, Kecia N.; Völgyi, Eszter; Tylavsky, Frances A.
2015-01-01
Despite increased interest in promoting nutrition during pregnancy, the association between maternal dietary patterns and birth outcomes has been equivocal. We examined maternal dietary patterns during pregnancy as a determinant of offspring’s birth weight-for-length (WLZ), weight-for-age (WAZ), length-for-age (LAZ), and head circumference (HCZ) Z-scores in Southern United States (n = 1151). Maternal diet during pregnancy was assessed by seven dietary patterns. Multivariable linear regression models described the association of WLZ, WAZ, LAZ, and HCZ with diet patterns controlling for other maternal and child characteristics. In bivariate analyses, WAZ and HCZ were significantly lower for processed and processed-Southern compared to healthy dietary patterns, whereas LAZ was significantly higher for these patterns. In the multivariate models, mothers who consumed a healthy-processed dietary pattern had children with significantly higher HCZ compared to the ones who consumed a healthy dietary pattern (HCZ β: 0.36; p = 0.019). No other dietary pattern was significantly associated with any of the birth outcomes. Instead, the major outcome determinants were: African American race, pre-pregnancy BMI, and gestational weight gain. These findings justify further investigation about socio-environmental and genetic factors related to race and birth outcomes in this population. PMID:25690420
Effects of developmental variability on the dynamics and self-organization of cell populations
NASA Astrophysics Data System (ADS)
Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard
2017-11-01
We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.
Long-Term Memory Stabilized by Noise-Induced Rehearsal
Wei, Yi
2014-01-01
Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507
Oh, Won-Jong; Gu, Chenghua
2013-10-16
Nerves and vessels often run parallel to one another, a phenomenon that reflects their functional interdependency. Previous studies have suggested that neurovascular congruency in planar tissues such as skin is established through a "one-patterns-the-other" model, in which either the nervous system or the vascular system precedes developmentally and then instructs the other system to form using its established architecture as a template. Here, we find that, in tissues with complex three-dimensional structures such as the mouse whisker system, neurovascular congruency does not follow the previous model but rather is established via a mechanism in which nerves and vessels are patterned independently. Given the diversity of neurovascular structures in different tissues, guidance signals emanating from a central organizer in the specific target tissue may act as an important mechanism to establish neurovascular congruency patterns that facilitate unique target tissue function. Copyright © 2013 Elsevier Inc. All rights reserved.
Selective memory generalization by spatial patterning of protein synthesis
O’Donnell, Cian; Sejnowski, Terrence J.
2014-01-01
Summary Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings we proposed a novel two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. PMID:24742462
Selective memory generalization by spatial patterning of protein synthesis.
O'Donnell, Cian; Sejnowski, Terrence J
2014-04-16
Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.
Fang, Jing; Demic, Selver; Cheng, Sen
2018-01-01
Major depressive disorder (MDD) is associated with an impairment of episodic memory, but the mechanisms underlying this deficit remain unclear. Animal models of MDD find impaired adult neurogenesis (AN) in the dentate gyrus (DG), and AN in DG has been suggested to play a critical role in reducing the interference between overlapping memories through pattern separation. Here, we study the effect of reduced AN in MDD on the accuracy of episodic memory using computational modeling. We focus on how memory is affected when periods with a normal rate of AN (asymptomatic states) alternate with periods with a low rate (depressive episodes), which has never been studied before. Also, unlike previous models of adult neurogenesis, which consider memories as static patterns, we model episodic memory as sequences of neural activity patterns. In our model, AN adds additional random components to the memory patterns, which results in the decorrelation of similar patterns. Consistent with previous studies, higher rates of AN lead to higher memory accuracy in our model, which implies that memories stored in the depressive state are impaired. Intriguingly, our model makes the novel prediction that memories stored in an earlier asymptomatic state are also impaired by a later depressive episode. This retrograde effect exacerbates with increased duration of the depressive episode. Finally, pattern separation at the sensory processing stage does not improve, but rather worsens, the accuracy of episodic memory retrieval, suggesting an explanation for why AN is found in brain areas serving memory rather than sensory function. In conclusion, while cognitive retrieval biases might contribute to episodic memory deficits in MDD, our model suggests a mechanistic explanation that affects all episodic memories, regardless of emotional relevance. PMID:29879169
Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation
Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.; ...
2017-01-31
Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less
Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.
Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less
Fang, Jing; Demic, Selver; Cheng, Sen
2018-01-01
Major depressive disorder (MDD) is associated with an impairment of episodic memory, but the mechanisms underlying this deficit remain unclear. Animal models of MDD find impaired adult neurogenesis (AN) in the dentate gyrus (DG), and AN in DG has been suggested to play a critical role in reducing the interference between overlapping memories through pattern separation. Here, we study the effect of reduced AN in MDD on the accuracy of episodic memory using computational modeling. We focus on how memory is affected when periods with a normal rate of AN (asymptomatic states) alternate with periods with a low rate (depressive episodes), which has never been studied before. Also, unlike previous models of adult neurogenesis, which consider memories as static patterns, we model episodic memory as sequences of neural activity patterns. In our model, AN adds additional random components to the memory patterns, which results in the decorrelation of similar patterns. Consistent with previous studies, higher rates of AN lead to higher memory accuracy in our model, which implies that memories stored in the depressive state are impaired. Intriguingly, our model makes the novel prediction that memories stored in an earlier asymptomatic state are also impaired by a later depressive episode. This retrograde effect exacerbates with increased duration of the depressive episode. Finally, pattern separation at the sensory processing stage does not improve, but rather worsens, the accuracy of episodic memory retrieval, suggesting an explanation for why AN is found in brain areas serving memory rather than sensory function. In conclusion, while cognitive retrieval biases might contribute to episodic memory deficits in MDD, our model suggests a mechanistic explanation that affects all episodic memories, regardless of emotional relevance.
Cancer Modeling: From Optimal Cell Renewal to Immunotherapy
NASA Astrophysics Data System (ADS)
Alvarado Alvarado, Cesar Leonardo
Cancer is a disease caused by mutations in normal cells. According to the National Cancer Institute, in 2016, an estimated 1.6 million people were diagnosed and approximately 0.5 million people died from the disease in the United States. There are many factors that shape cancer at the cellular and organismal level, including genetic, immunological, and environmental components. In this thesis, we show how mathematical modeling can be used to provide insight into some of the key mechanisms underlying cancer dynamics. First, we use mathematical modeling to investigate optimal homeostatic cell renewal in tissues such as the small intestine with an emphasis on division patterns and tissue architecture. We find that the division patterns that delay the accumulation of mutations are strictly associated with the population sizes of the tissue. In particular, patterns with long chains of differentiation delay the time to observe a second-hit mutant, which is important given that for many cancers two mutations are enough to initiate a tumor. We also investigated homeostatic cell renewal under a selective pressure and find that hierarchically organized tissues act as suppressors of selection; we find that an architecture with a small number of stem cells and larger pools of transit amplifying cells and mature differentiated cells, together with long chains of differentiation, form a robust evolutionary strategy to delay the time to observe a second-hit mutant when mutations acquire a fitness advantage or disadvantage. We also formulate a model of the immune response to cancer in the presence of costimulatory and inhibitory signals. We demonstrate that the coordination of such signals is crucial to initiate an effective immune response, and while immunotherapy has become a promising cancer treatment over the past decade, these results offer some explanations for why it can fail.
NASA Technical Reports Server (NTRS)
Hendrickson, J. R. (Principal Investigator)
1973-01-01
The author has identified the following significant results. Results of studies of the oceanography of the northern Gulf of California (Mexico) are reported. A remote, instrumented buoy measuring and telemetering oceanographic data by ERTS-1 satellite was designed, constructed, deployed, and tested. Regular cruises by a research ship on a pattern of 47 oceanographic stations collected data which are analyzed and referenced to analysis of ERTS-1 satellite imagery. A thermal dynamic model of current patterns in the northern Gulf of California is proposed. Findings are examined in relation to the model.
Ramachandran, Sohini; Deshpande, Omkar; Roseman, Charles C.; Rosenberg, Noah A.; Feldman, Marcus W.; Cavalli-Sforza, L. Luca
2005-01-01
Equilibrium models of isolation by distance predict an increase in genetic differentiation with geographic distance. Here we find a linear relationship between genetic and geographic distance in a worldwide sample of human populations, with major deviations from the fitted line explicable by admixture or extreme isolation. A close relationship is shown to exist between the correlation of geographic distance and genetic differentiation (as measured by FST) and the geographic pattern of heterozygosity across populations. Considering a worldwide set of geographic locations as possible sources of the human expansion, we find that heterozygosities in the globally distributed populations of the data set are best explained by an expansion originating in Africa and that no geographic origin outside of Africa accounts as well for the observed patterns of genetic diversity. Although the relationship between FST and geographic distance has been interpreted in the past as the result of an equilibrium model of drift and dispersal, simulation shows that the geographic pattern of heterozygosities in this data set is consistent with a model of a serial founder effect starting at a single origin. Given this serial-founder scenario, the relationship between genetic and geographic distance allows us to derive bounds for the effects of drift and natural selection on human genetic variation. PMID:16243969
NASA Astrophysics Data System (ADS)
Wang, Yizhou; Zhang, Huiping; Zheng, Dewen; von Dassow, Wesley; Zhang, Zhuqi; Yu, Jingxing; Pang, Jianzhang
2017-05-01
In order to test the hypothesis that the stationary nature of the Yarlung Tsangpo Gorge is tectonically controlled, the rock uplift pattern in the southeast Tibetan Plateau and the critical condition to sustain a stable knickpoint must be derived. Via slope-area analysis and the integral approach, we first quantify the pattern of channel steepness in southeast Tibet and find that the steepness index shows higher values around the gorge but lower values toward the inner land and the mountain front. Such a pattern of channel steepness indicates that the active rock uplift is restricted in the zone just around the Yarlung Tsangpo Gorge. Then, we derive a general knickpoint migration model that accounts for spatially variant rock uplift rates. From the model, a critical condition for maintaining a stable knickpoint is concluded that the difference of incision rates in the downstream and upstream reaches of the knickpoint should match that of rock uplift. Employing a stream-power river incision model, we calculate the incision rate in the gorge and find a higher correspondence with differential rock uplift rates in the downstream and upstream reaches of the knickpoint. Therefore, we favor tectonic control as the primary mechanism to explain the stability of the knickpoint within the Yarlung Tsangpo Gorge.
Pine invasions in treeless environments: dispersal overruns microsite heterogeneity.
Pauchard, Aníbal; Escudero, Adrián; García, Rafael A; de la Cruz, Marcelino; Langdon, Bárbara; Cavieres, Lohengrin A; Esquivel, Jocelyn
2016-01-01
Understanding biological invasions patterns and mechanisms is highly needed for forecasting and managing these processes and their negative impacts. At small scales, ecological processes driving plant invasions are expected to produce a spatially explicit pattern driven by propagule pressure and local ground heterogeneity. Our aim was to determine the interplay between the intensity of seed rain, using distance to a mature plantation as a proxy, and microsite heterogeneity in the spreading of Pinus contorta in the treeless Patagonian steppe. Three one-hectare plots were located under different degrees of P. contorta invasion (Coyhaique Alto, 45° 30'S and 71° 42'W). We fitted three types of inhomogeneous Poisson models to each pine plot in an attempt for describing the observed pattern as accurately as possible: the "dispersal" models, "local ground heterogeneity" models, and "combined" models, using both types of covariates. To include the temporal axis in the invasion process, we analyzed both the pattern of young and old recruits and also of all recruits together. As hypothesized, the spatial patterns of recruited pines showed coarse scale heterogeneity. Early pine invasion spatial patterns in our Patagonian steppe site is not different from expectations of inhomogeneous Poisson processes taking into consideration a linear and negative dependency of pine recruit intensity on the distance to afforestations. Models including ground-cover predictors were able to describe the point pattern process only in a couple of cases but never better than dispersal models. This finding concurs with the idea that early invasions depend more on seed pressure than on the biotic and abiotic relationships seed and seedlings establish at the microsite scale. Our results show that without a timely and active management, P. contorta will invade the Patagonian steppe independently of the local ground-cover conditions.
Coalescent patterns for chromosomal inversions in divergent populations
Guerrero, Rafael F.; Rousset, François; Kirkpatrick, Mark
2012-01-01
Chromosomal inversions allow genetic divergence of locally adapted populations by reducing recombination between chromosomes with different arrangements. Divergence between populations (or hybridization between species) is expected to leave signatures in the neutral genetic diversity of the inverted region. Quantitative expectations for these patterns, however, have not been obtained. Here, we develop coalescent models of neutral sites linked to an inversion polymorphism in two locally adapted populations. We consider two scenarios of local adaptation: selection on the inversion breakpoints and selection on alleles inside the inversion. We find that ancient inversion polymorphisms cause genetic diversity to depart dramatically from neutral expectations. Other situations, however, lead to patterns that may be difficult to detect; important determinants are the age of the inversion and the rate of gene flux between arrangements. We also study inversions under genetic drift, finding that they produce patterns similar to locally adapted inversions of intermediate age. Our results are consistent with empirical observations, and provide the foundation for quantitative analyses of the roles that inversions have played in speciation. PMID:22201172
Modeling the Underlying Dynamics of the Spread of Crime
McMillon, David; Simon, Carl P.; Morenoff, Jeffrey
2014-01-01
The spread of crime is a complex, dynamic process that calls for a systems level approach. Here, we build and analyze a series of dynamical systems models of the spread of crime, imprisonment and recidivism, using only abstract transition parameters. To find the general patterns among these parameters—patterns that are independent of the underlying particulars—we compute analytic expressions for the equilibria and for the tipping points between high-crime and low-crime equilibria in these models. We use these expressions to examine, in particular, the effects of longer prison terms and of increased incarceration rates on the prevalence of crime, with a follow-up analysis on the effects of a Three-Strike Policy. PMID:24694545
Spatial effects in discrete generation population models.
Carrillo, C; Fife, P
2005-02-01
A framework is developed for constructing a large class of discrete generation, continuous space models of evolving single species populations and finding their bifurcating patterned spatial distributions. Our models involve, in separate stages, the spatial redistribution (through movement laws) and local regulation of the population; and the fundamental properties of these events in a homogeneous environment are found. Emphasis is placed on the interaction of migrating individuals with the existing population through conspecific attraction (or repulsion), as well as on random dispersion. The nature of the competition of these two effects in a linearized scenario is clarified. The bifurcation of stationary spatially patterned population distributions is studied, with special attention given to the role played by that competition.
Combinatorics of the Breakage-Fusion-Bridge Mechanism
Bafna, Vineet
2012-01-01
Abstract The breakage-fusion-bridge (BFB) mechanism was proposed over seven decades ago and is a source of genomic variability and gene amplification in cancer. Here we formally model and analyze the BFB mechanism, to our knowledge the first time this has been undertaken. We show that BFB can be modeled as successive inverted prefix duplications of a string. Using this model, we show that BFB can achieve a surprisingly broad range of amplification patterns. We find that a sequence of BFB operations can be found that nearly fits most patterns of copy number increases along a chromosome. We conclude that this limits the usefulness of methods like array CGH for detecting BFB. PMID:22506505
NASA Technical Reports Server (NTRS)
Jones, D. H.
1985-01-01
A new flexible model of pilot instrument scanning behavior is presented which assumes that the pilot uses a set of deterministic scanning patterns on the pilot's perception of error in the state of the aircraft, and the pilot's knowledge of the interactive nature of the aircraft's systems. Statistical analyses revealed that a three stage Markov process composed of the pilot's three predicted lookpoints (LP), occurring 1/30, 2/30, and 3/30 of a second prior to each LP, accurately modelled the scanning behavior of 14 commercial airline pilots while flying steep turn maneuvers in a Boeing 737 flight simulator. The modelled scanning data for each pilot were not statistically different from the observed scanning data in comparisons of mean dwell time, entropy, and entropy rate. These findings represent the first direct evidence that pilots are using deterministic scanning patterns during instrument flight. The results are interpreted as direct support for the error dependent model and suggestions are made for further research that could allow for identification of the specific scanning patterns suggested by the model.
A gene network model accounting for development and evolution of mammalian teeth
Salazar-Ciudad, Isaac; Jernvall, Jukka
2002-01-01
Generation of morphological diversity remains a challenge for evolutionary biologists because it is unclear how an ultimately finite number of genes involved in initial pattern formation integrates with morphogenesis. Ideally, models used to search for the simplest developmental principles on how genes produce form should account for both developmental process and evolutionary change. Here we present a model reproducing the morphology of mammalian teeth by integrating experimental data on gene interactions and growth into a morphodynamic mechanism in which developing morphology has a causal role in patterning. The model predicts the course of tooth-shape development in different mammalian species and also reproduces key transitions in evolution. Furthermore, we reproduce the known expression patterns of several genes involved in tooth development and their dynamics over developmental time. Large morphological effects frequently can be achieved by small changes, according to this model, and similar morphologies can be produced by different changes. This finding may be consistent with why predicting the morphological outcomes of molecular experiments is challenging. Nevertheless, models incorporating morphology and gene activity show promise for linking genotypes to phenotypes. PMID:12048258
Bars and spirals in tidal interactions with an ensemble of galaxy mass models
NASA Astrophysics Data System (ADS)
Pettitt, Alex R.; Wadsley, J. W.
2018-03-01
We present simulations of the gaseous and stellar material in several different galaxy mass models under the influence of different tidal fly-bys to assess the changes in their bar and spiral morphology. Five different mass models are chosen to represent the variety of rotation curves seen in nature. We find a multitude of different spiral and bar structures can be created, with their properties dependent on the strength of the interaction. We calculate pattern speeds, spiral wind-up rates, bar lengths, and angular momentum exchange to quantify the changes in disc morphology in each scenario. The wind-up rates of the tidal spirals follow the 2:1 resonance very closely for the flat and dark matter-dominated rotation curves, whereas the more baryon-dominated curves tend to wind-up faster, influenced by their inner bars. Clear spurs are seen in most of the tidal spirals, most noticeable in the flat rotation curve models. Bars formed both in isolation and interactions agree well with those seen in real galaxies, with a mixture of `fast' and `slow' rotators. We find no strong correlation between bar length or pattern speed and the interaction strength. Bar formation is, however, accelerated/induced in four out of five of our models. We close by briefly comparing the morphology of our models to real galaxies, easily finding analogues for nearly all simulations presenter here, showing passages of small companions can easily reproduce an ensemble of observed morphologies.
Statistically significant relational data mining :
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann
This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publicationsmore » that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.« less
Modelling survival: exposure pattern, species sensitivity and uncertainty
Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I.; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B.; Van den Brink, Paul J.; Veltman, Karin; Vogel, Sören; Zimmer, Elke I.; Preuss, Thomas G.
2016-01-01
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans. PMID:27381500
Frustration in Condensed Matter and Protein Folding
NASA Astrophysics Data System (ADS)
Lorelli, S.; Cabot, A.; Sundarprasad, N.; Boekema, C.
Using computer modeling we study frustration in condensed matter and protein folding. Frustration is due to random and/or competing interactions. One definition of frustration is the sum of squares of the differences between actual and expected distances between characters. If this sum is non-zero, then the system is said to have frustration. A simulation tracks the movement of characters to lower their frustration. Our research is conducted on frustration as a function of temperature using a logarithmic scale. At absolute zero, the relaxation for frustration is a power function for randomly assigned patterns or an exponential function for regular patterns like Thomson figures. These findings have implications for protein folding; we attempt to apply our frustration modeling to protein folding and dynamics. We use coding in Python to simulate different ways a protein can fold. An algorithm is being developed to find the lowest frustration (and thus energy) states possible. Research supported by SJSU & AFC.
Do, Catherine; Xing, Zhuo; Yu, Y Eugene; Tycko, Benjamin
2017-01-01
An important line of postgenomic research seeks to understand how genetic factors can influence epigenetic patterning. Here we review epigenetic effects of chromosomal aneuploidies, focusing on findings in Down syndrome (DS, trisomy 21). Recent work in human DS and mouse models has shown that the extra chromosome 21 acts in trans to produce epigenetic changes, including differential CpG methylation (DS-DM), in specific sets of downstream target genes, mostly on other chromosomes. Mechanistic hypotheses emerging from these data include roles of chromosome 21-linked methylation pathway genes (DNMT3L and others) and transcription factor genes (RUNX1, OLIG2, GABPA, ERG and ETS2) in shaping the patterns of DS-DM. The findings may have broader implications for trans-acting epigenetic effects of chromosomal and subchromosomal aneuploidies in other human developmental and neuropsychiatric disorders, and in cancers. PMID:27911079
Modelling human mobility patterns using photographic data shared online.
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.
Modelling human mobility patterns using photographic data shared online
Barchiesi, Daniele; Preis, Tobias; Bishop, Steven; Moat, Helen Susannah
2015-01-01
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. PMID:26361545
Sul, Bora; Oppito, Zachary; Jayasekera, Shehan; Vanger, Brian; Zeller, Amy; Morris, Michael; Ruppert, Kai; Altes, Talissa; Rakesh, Vineet; Day, Steven; Robinson, Risa; Reifman, Jaques; Wallqvist, Anders
2018-05-01
Computational models are useful for understanding respiratory physiology. Crucial to such models are the boundary conditions specifying the flow conditions at truncated airway branches (terminal flow rates). However, most studies make assumptions about these values, which are difficult to obtain in vivo. We developed a computational fluid dynamics (CFD) model of airflows for steady expiration to investigate how terminal flows affect airflow patterns in respiratory airways. First, we measured in vitro airflow patterns in a physical airway model, using particle image velocimetry (PIV). The measured and computed airflow patterns agreed well, validating our CFD model. Next, we used the lobar flow fractions from a healthy or chronic obstructive pulmonary disease (COPD) subject as constraints to derive different terminal flow rates (i.e., three healthy and one COPD) and computed the corresponding airflow patterns in the same geometry. To assess airflow sensitivity to the boundary conditions, we used the correlation coefficient of the shape similarity (R) and the root-mean-square of the velocity magnitude difference (Drms) between two velocity contours. Airflow patterns in the central airways were similar across healthy conditions (minimum R, 0.80) despite variations in terminal flow rates but markedly different for COPD (minimum R, 0.26; maximum Drms, ten times that of healthy cases). In contrast, those in the upper airway were similar for all cases. Our findings quantify how variability in terminal and lobar flows contributes to airflow patterns in respiratory airways. They highlight the importance of using lobar flow fractions to examine physiologically relevant airflow characteristics.
Howard, Mary F; Poeppel, David
2010-11-01
Speech stimuli give rise to neural activity in the listener that can be observed as waveforms using magnetoencephalography. Although waveforms vary greatly from trial to trial due to activity unrelated to the stimulus, it has been demonstrated that spoken sentences can be discriminated based on theta-band (3-7 Hz) phase patterns in single-trial response waveforms. Furthermore, manipulations of the speech signal envelope and fine structure that reduced intelligibility were found to produce correlated reductions in discrimination performance, suggesting a relationship between theta-band phase patterns and speech comprehension. This study investigates the nature of this relationship, hypothesizing that theta-band phase patterns primarily reflect cortical processing of low-frequency (<40 Hz) modulations present in the acoustic signal and required for intelligibility, rather than processing exclusively related to comprehension (e.g., lexical, syntactic, semantic). Using stimuli that are quite similar to normal spoken sentences in terms of low-frequency modulation characteristics but are unintelligible (i.e., their time-inverted counterparts), we find that discrimination performance based on theta-band phase patterns is equal for both types of stimuli. Consistent with earlier findings, we also observe that whereas theta-band phase patterns differ across stimuli, power patterns do not. We use a simulation model of the single-trial response to spoken sentence stimuli to demonstrate that phase-locked responses to low-frequency modulations of the acoustic signal can account not only for the phase but also for the power results. The simulation offers insight into the interpretation of the empirical results with respect to phase-resetting and power-enhancement models of the evoked response.
Transcranial Electrical Neuromodulation Based on the Reciprocity Principle
Fernández-Corazza, Mariano; Turovets, Sergei; Luu, Phan; Anderson, Erik; Tucker, Don
2016-01-01
A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints. PMID:27303311
Transcranial Electrical Neuromodulation Based on the Reciprocity Principle.
Fernández-Corazza, Mariano; Turovets, Sergei; Luu, Phan; Anderson, Erik; Tucker, Don
2016-01-01
A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.
Analysis of noise-induced temporal correlations in neuronal spike sequences
NASA Astrophysics Data System (ADS)
Reinoso, José A.; Torrent, M. C.; Masoller, Cristina
2016-11-01
We investigate temporal correlations in sequences of noise-induced neuronal spikes, using a symbolic method of time-series analysis. We focus on the sequence of time-intervals between consecutive spikes (inter-spike-intervals, ISIs). The analysis method, known as ordinal analysis, transforms the ISI sequence into a sequence of ordinal patterns (OPs), which are defined in terms of the relative ordering of consecutive ISIs. The ISI sequences are obtained from extensive simulations of two neuron models (FitzHugh-Nagumo, FHN, and integrate-and-fire, IF), with correlated noise. We find that, as the noise strength increases, temporal order gradually emerges, revealed by the existence of more frequent ordinal patterns in the ISI sequence. While in the FHN model the most frequent OP depends on the noise strength, in the IF model it is independent of the noise strength. In both models, the correlation time of the noise affects the OP probabilities but does not modify the most probable pattern.
Spiral and never-settling patterns in active systems
NASA Astrophysics Data System (ADS)
Yang, X.; Marenduzzo, D.; Marchetti, M. C.
2014-01-01
We present a combined numerical and analytical study of pattern formation in an active system where particles align, possess a density-dependent motility, and are subject to a logistic reaction. The model can describe suspensions of reproducing bacteria, as well as polymerizing actomyosin gels in vitro or in vivo. In the disordered phase, we find that motility suppression and growth compete to yield stable or blinking patterns, which, when dense enough, acquire internal orientational ordering to give asters or spirals. We predict these may be observed within chemotactic aggregates in bacterial fluids. In the ordered phase, the reaction term leads to previously unobserved never-settling patterns which can provide a simple framework to understand the formation of motile and spiral patterns in intracellular actin systems.
Effect of diastolic flow patterns on the function of the left ventricle
NASA Astrophysics Data System (ADS)
Seo, Jung Hee; Mittal, Rajat
2013-11-01
Direct numerical simulations are used to study the effect of intraventricular flow patterns on the pumping efficiency and the blood mixing and transport characteristics of the left ventricle. The simulations employ a geometric model of the left ventricle which is derived from contrast computed tomography. A variety of diastolic flow conditions are generated for a fixed ejection fraction in order to delineate the effect of flow patterns on ventricular performance. The simulations indicate that the effect of intraventricular blood flow pattern on the pumping power is physiologically insignificant. However, diastolic flow patterns have a noticeable effect on the blood mixing as well as the residence time of blood cells in the ventricle. The implications of these findings on ventricular function are discussed.
Network Sampling and Classification:An Investigation of Network Model Representations
Airoldi, Edoardo M.; Bai, Xue; Carley, Kathleen M.
2011-01-01
Methods for generating a random sample of networks with desired properties are important tools for the analysis of social, biological, and information networks. Algorithm-based approaches to sampling networks have received a great deal of attention in recent literature. Most of these algorithms are based on simple intuitions that associate the full features of connectivity patterns with specific values of only one or two network metrics. Substantive conclusions are crucially dependent on this association holding true. However, the extent to which this simple intuition holds true is not yet known. In this paper, we examine the association between the connectivity patterns that a network sampling algorithm aims to generate and the connectivity patterns of the generated networks, measured by an existing set of popular network metrics. We find that different network sampling algorithms can yield networks with similar connectivity patterns. We also find that the alternative algorithms for the same connectivity pattern can yield networks with different connectivity patterns. We argue that conclusions based on simulated network studies must focus on the full features of the connectivity patterns of a network instead of on the limited set of network metrics for a specific network type. This fact has important implications for network data analysis: for instance, implications related to the way significance is currently assessed. PMID:21666773
Kim, Jung-Sun; Afari, Maxwell E; Ha, Jinyong; Tellez, Armando; Milewski, Krzysztof; Conditt, Gerard; Cheng, Yanping; Hua Yi, Geng; Kaluza, Greg L; Granada, Juan F
2014-03-01
Although optical coherence tomography (OCT) is capable to detect microscopic peri-strut changes that seem to be related to neointimal inhibition and healing, its ability to characterize these components is still limited. In this study, we aimed to compare different OCT morphological characteristics with different in-stent neointimal tissue types analysed by histology. A total of 69 stents (39 drug eluting and 30 bare metal stents) were implanted in coronary arteries of 27 swine. By OCT, neointimal type was classified as homogeneous, heterogeneous, or layered according to its pattern of backscatter and optical intensity. The resulting optical patterns were correlated with several histological findings [external elastic lamina (EEL) disruption, fibrin deposition, circumferential rim of peri-strut inflammatory cell infiltration, and fibrous connective deposition] in every single cross-section (CS) analysed. A total of 197 matched OCT and histological CS were analysed. The heterogeneous (0.44 ± 0.21 mm) and layered (0.65 ± 0.16 mm) patterns had a significantly higher degree of neointimal thickness compared with the homogeneous pattern (0.25 ± 0.16 mm, P < 0.001). Fibrous connective tissue deposition was more frequently present in the homogeneous pattern (71.6%, P < 0.001), whereas significant fibrin deposits were more commonly seen in the heterogeneous pattern (56.9%, P = 0.007). Peri-strut inflammation was less frequently found in the homogeneous pattern (19.8%, P < 0.001) in comparison with the layered (73.9%) or heterogeneous patterns (43.1%). The presence of EEL rupture was also more commonly seen in layered (73.9%) and heterogeneous (46.6%) patterns than in the homogeneous pattern (22.4%, P < 0.001). The optical characteristics of neointimal formation seen in OCT properly correlated with the presence of several histological findings involved in stent healing. The biological implications of these findings in clinical outcomes require further investigation.
Impact of the basic state and MJO representation on MJO Pacific teleconnections in GCMs
NASA Astrophysics Data System (ADS)
Henderson, S. A.; Maloney, E. D.; Son, S. W.
2017-12-01
Teleconnection patterns induced by the Madden-Julian Oscillation (MJO) are known to significantly alter extratropical weather and climate patterns. However, accurate MJO representation has been difficult for many General Circulation Models (GCMs). Furthermore, many GCMs contain large basic state biases. These issues present challenges to the simulation of MJO teleconnections and, in turn, their associated extratropical impacts. This study examines the impacts of basic state quality and MJO representation on the quality of MJO teleconnection patterns in GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Results suggest that GCMs assessed to have a good MJO but with large basic state biases have similarly low skill in reproducing MJO teleconnections as GCMs with poor MJO representation. In the good MJO models examined, poor teleconnection quality is associated with large errors in the zonal extent of the Pacific subtropical jet. Whereas the horizontal structure of MJO heating in the Indo-Pacific region is found to have modest impacts on the teleconnection patterns, results suggest that MJO heating east of the dateline can alter the teleconnection pattern characteristics over North America. These findings suggest that in order to accurately simulate the MJO teleconnection patterns and associated extratropical impacts, both the MJO and the basic state must be well represented.
Collective iteration behavior for online social networks
NASA Astrophysics Data System (ADS)
Liu, Jian-Guo; Li, Ren-De; Guo, Qiang; Zhang, Yi-Cheng
2018-06-01
Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users' online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the ego network. The empirical results show that there are robust social signatures of interactions no matter how friends change over time, which indicates that a stable commutation pattern exists in online communication. By comparing a random null model, we find the that commutation pattern is heterogeneous between ego and alters. Furthermore, in order to regenerate the pattern of the social signature, we present a preferential interaction model, which assumes that new users intend to look for the old users with strong ties while old users have tendency to interact with new friends. The experimental results show that the presented model can reproduce the heterogeneity of social signature by adjusting 2 parameters, the number of communicating targets m and the max number of interactions n, for Facebook users, m = n = 5, for Wiki users, m = 2 and n = 8. This work helps in deeply understanding the regularity of social signature.
Pattern uniformity control in integrated structures
NASA Astrophysics Data System (ADS)
Kobayashi, Shinji; Okada, Soichiro; Shimura, Satoru; Nafus, Kathleen; Fonseca, Carlos; Biesemans, Serge; Enomoto, Masashi
2017-03-01
In our previous paper dealing with multi-patterning, we proposed a new indicator to quantify the quality of final wafer pattern transfer, called interactive pattern fidelity error (IPFE). It detects patterning failures resulting from any source of variation in creating integrated patterns. IPFE is a function of overlay and edge placement error (EPE) of all layers comprising the final pattern (i.e. lower and upper layers). In this paper, we extend the use cases with Via in additional to the bridge case (Block on Spacer). We propose an IPFE budget and CD budget using simple geometric and statistical models with analysis of a variance (ANOVA). In addition, we validate the model with experimental data. From the experimental results, improvements in overlay, local-CDU (LCDU) of contact hole (CH) or pillar patterns (especially, stochastic pattern noise (SPN)) and pitch walking are all critical to meet budget requirements. We also provide a special note about the importance of the line length used in analyzing LWR. We find that IPFE and CD budget requirements are consistent to the table of the ITRS's technical requirement. Therefore the IPFE concept can be adopted for a variety of integrated structures comprising digital logic circuits. Finally, we suggest how to use IPFE for yield management and optimization requirements for each process.
NASA Astrophysics Data System (ADS)
Yang, Zhangcan; Lively, Michael A.; Allain, Jean Paul
2015-02-01
The production of self-organized nanostructures by ion beam sputtering has been of keen interest to researchers for many decades. Despite numerous experimental and theoretical efforts to understand ion-induced nanostructures, there are still many basic questions open to discussion, such as the role of erosion or curvature-dependent sputtering. In this work, a hybrid MD/kMC (molecular dynamics/kinetic Monte Carlo) multiscale atomistic model is developed to investigate these knowledge gaps, and its predictive ability is validated across the experimental parameter space. This model uses crater functions, which were obtained from MD simulations, to model the prompt mass redistribution due to single-ion impacts. Defect migration, which is missing from previous models that use crater functions, is treated by a kMC Arrhenius method. Using this model, a systematic study was performed for silicon bombarded by Ar+ ions of various energies (100 eV, 250 eV, 500 eV, 700 eV, and 1000 eV) at incidence angles of 0∘ to 80∘. The simulation results were compared with experimental findings, showing good agreement in many aspects of surface evolution, such as the phase diagram. The underestimation of the ripple wavelength by the simulations suggests that surface diffusion is not the main smoothening mechanism for ion-induced pattern formation. Furthermore, the simulated results were compared with moment-description continuum theory and found to give better results, as the simulation did not suffer from the same mathematical inconsistencies as the continuum model. The key finding was that redistributive effects are dominant in the formation of flat surfaces and parallel-mode ripples, but erosive effects are dominant at high angles when perpendicular-mode ripples are formed. Ion irradiation with simultaneous sample rotation was also simulated, resulting in arrays of square-ordered dots. The patterns obtained from sample rotation were strongly correlated to the rotation speed and to the pattern types formed without sample rotation, and a critical value of about 5 rpm was found between disordered ripples and square-ordered dots. Finally, simulations of dual-beam sputtering were performed, with the resulting patterns determined by the flux ratio of the two beams and the pattern types resulting from single-beam sputtering under the same conditions.
Probabilistic projections of 21st century climate change over Northern Eurasia
NASA Astrophysics Data System (ADS)
Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang
2013-12-01
We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.
NASA Astrophysics Data System (ADS)
Meng, Yu; Hanson, Sandra L.
Both race and sex continue to be factors that stratify entry into science education and occupations in the United States. Asian-Americans (men and women) have experienced considerable success in the sciences and have earned the label of "model minority." The complexities and patterns involved in this success remain elusive. We use several concepts coming out of the status attainment framework and a multicultural gender perspective to explore the way in which race and sex come together to influence choices of science major and degree. Our sample consists of Asian-American and white students in the National Educational Longitudinal Study. Findings suggest that being male and being Asian-American are both associated with higher chances of pursuing majors and degrees in science. The male advantage is greater than the Asian-American advantage. Findings also suggest that race and sex interact in the science decision. For example, race differences (with an Asian-American advantage) in choice of science major are significant for women but not men. Sex differences (with a male advantage) in choice of science major are significant in the white, but not the Asian-American sample. A different set of race and sex patterns is revealed in the science degree models. Processes associated with family socioeconomic status and student characteristics help to explain race and sex patterns. Findings suggest that when Asian-American youths have closer ties to the Asian culture, they are more likely to choose science majors and degrees. Implications for policy, practice, and research in science education are discussed.
Physics Constrained Stochastic-Statistical Models for Extended Range Environmental Prediction
2014-09-30
pressure ( SLP ), respectively]. A major finding of this work, illustrated in Figure 1, is that the North Pacific patterns identified in [1] are part of...Figure II 1. Reconstruction of sea ice concentration, SST, and SLP anomalies in the arctic using NLSA reemergence modes during an active phase of...to reemerge. The geostrophic winds associated with the annular SLP pattern in the right-hand column are cold Northerlies (warm Southerlies) in the
Blur Clarified: A review and Synthesis of Blur Discrimination
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Ahumada, Albert J.
2011-01-01
Blur is an important attribute of human spatial vision, and sensitivity to blur has been the subject of considerable experimental research and theoretical modeling. Often these models have invoked specialized concepts or mechanisms, such as intrinsic blur, multiple channels, or blur estimation units. In this paper we review the several experimental studies of blur discrimination and find they are in broad empirical agreement. But contrary to previous modeling efforts, we find that the essential features of blur discrimination are fully accounted for by a visible contrast energy model (ViCE), in which two spatial patterns are distinguished when the integrated difference between their masked local contrast energy responses reaches a threshold value.
Diversity of multilayer networks and its impact on collaborating epidemics
NASA Astrophysics Data System (ADS)
Min, Yong; Hu, Jiaren; Wang, Weihong; Ge, Ying; Chang, Jie; Jin, Xiaogang
2014-12-01
Interacting epidemics on diverse multilayer networks are increasingly important in modeling and analyzing the diffusion processes of real complex systems. A viral agent spreading on one layer of a multilayer network can interact with its counterparts by promoting (cooperative interaction), suppressing (competitive interaction), or inducing (collaborating interaction) its diffusion on other layers. Collaborating interaction displays different patterns: (i) random collaboration, where intralayer or interlayer induction has the same probability; (ii) concentrating collaboration, where consecutive intralayer induction is guaranteed with a probability of 1; and (iii) cascading collaboration, where consecutive intralayer induction is banned with a probability of 0. In this paper, we develop a top-bottom framework that uses only two distributions, the overlaid degree distribution and edge-type distribution, to model collaborating epidemics on multilayer networks. We then state the response of three collaborating patterns to structural diversity (evenness and difference of network layers). For viral agents with small transmissibility, we find that random collaboration is more effective in networks with higher diversity (high evenness and difference), while the concentrating pattern is more suitable in uneven networks. Interestingly, the cascading pattern requires a network with moderate difference and high evenness, and the moderately uneven coupling of multiple network layers can effectively increase robustness to resist cascading failure. With large transmissibility, however, we find that all collaborating patterns are more effective in high-diversity networks. Our work provides a systemic analysis of collaborating epidemics on multilayer networks. The results enhance our understanding of biotic and informative diffusion through multiple vectors.
Fumanelli, Laura; Ajelli, Marco; Manfredi, Piero; Vespignani, Alessandro; Merler, Stefano
2012-01-01
Social contact patterns among individuals encode the transmission route of infectious diseases and are a key ingredient in the realistic characterization and modeling of epidemics. Unfortunately, the gathering of high quality experimental data on contact patterns in human populations is a very difficult task even at the coarse level of mixing patterns among age groups. Here we propose an alternative route to the estimation of mixing patterns that relies on the construction of virtual populations parametrized with highly detailed census and demographic data. We present the modeling of the population of 26 European countries and the generation of the corresponding synthetic contact matrices among the population age groups. The method is validated by a detailed comparison with the matrices obtained in six European countries by the most extensive survey study on mixing patterns. The methodology presented here allows a large scale comparison of mixing patterns in Europe, highlighting general common features as well as country-specific differences. We find clear relations between epidemiologically relevant quantities (reproduction number and attack rate) and socio-demographic characteristics of the populations, such as the average age of the population and the duration of primary school cycle. This study provides a numerical approach for the generation of human mixing patterns that can be used to improve the accuracy of mathematical models in the absence of specific experimental data. PMID:23028275
Domingues, Carla P.; Nolasco, Rita; Dubert, Jesus; Queiroga, Henrique
2012-01-01
Background Predicting the spatial and temporal patterns of marine larval dispersal and supply is a challenging task due to the small size of the larvae and the variability of oceanographic processes. Addressing this problem requires the use of novel approaches capable of capturing the inherent variability in the mechanisms involved. Methodology/Principal Findings In this study we test whether dispersal and connectivity patterns generated from a bio-physical model of larval dispersal of the crab Carcinus maenas, along the west coast of the Iberian Peninsula, can predict the highly variable daily pattern of wind-driven larval supply to an estuary observed during the peak reproductive season (March–June) in 2006 and 2007. Cross-correlations between observed and predicted supply were significant (p<0.05) and strong, ranging from 0.34 to 0.81 at time lags of −6 to +5 d. Importantly, the model correctly predicted observed cross-shelf distributions (Pearson r = 0.82, p<0.001, and r = 0.79, p<0.01, in 2006 and 2007) and indicated that all supply events were comprised of larvae that had been retained within the inner shelf; larvae transported to the outer shelf and beyond never recruited. Estimated average dispersal distances ranged from 57 to 198 km and were only marginally affected by mortality. Conclusions/Significance The high degree of predicted demographic connectivity over relatively large geographic scales is consistent with the lack of genetic structuring in C. maenas along the Iberian Peninsula. These findings indicate that the dynamic nature of larval dispersal can be captured by mechanistic biophysical models, which can be used to provide meaningful predictions of the patterns and causes of fine-scale variability in larval supply to marine populations. PMID:22558225
Park, Young Il
2016-01-01
BACKGROUND/OBJECTIVES This research analyzes the effects of the food choices of industrial workers according to their sugar intake pattern on their job satisfaction through the construction of a model on the relationship between sugar intake pattern and job satisfaction. SUBJECTS/METHODS Surveys were collected from May to July 2015. A statistical analysis of the 775 surveys from Kyungsangnam-do was conducted using SPSS13.0 for Windows and SEM was performed using the AMOS 5.0 statistics package. RESULTS The reliability of the data was confirmed by an exploratory factor analysis through a Cronbach's alpha coefficient, and the measurement model was proven to be appropriate by a confirmatory factor analysis in conjunction with AMOS. The results of factor analysis on food choice, sugar intake pattern and job satisfaction were categorized into five categories. The reliability of these findings was supported by a Cronbach's alpha coefficient of 0.6 and higher for all factors except confection (0.516) and dairy products (0.570). The multicollinearity results did not indicate a problem between the variables since the highest correlation coefficient was 0.494 (P < 0.01). In an attempt to study the sugar intake pattern in accordance with the food choices and job satisfaction of industrial workers, a structural equation model was constructed and analyzed. CONCLUSIONS All tests confirmed that the model satisfied the recommended levels for the goodness of fit index, and thus, the overall research model was proven to be appropriate. PMID:27478555
Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences.
Kovanen, Lauri; Kaski, Kimmo; Kertész, János; Saramäki, Jari
2013-11-05
Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals' attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter's hypothesis to temporal networks.
Temporal motifs reveal homophily, gender-specific patterns, and group talk in call sequences
Kovanen, Lauri; Kaski, Kimmo; Kertész, János; Saramäki, Jari
2013-01-01
Recent studies on electronic communication records have shown that human communication has complex temporal structure. We study how communication patterns that involve multiple individuals are affected by attributes such as sex and age. To this end, we represent the communication records as a colored temporal network where node color is used to represent individuals’ attributes, and identify patterns known as temporal motifs. We then construct a null model for the occurrence of temporal motifs that takes into account the interaction frequencies and connectivity between nodes of different colors. This null model allows us to detect significant patterns in call sequences that cannot be observed in a static network that uses interaction frequencies as link weights. We find sex-related differences in communication patterns in a large dataset of mobile phone records and show the existence of temporal homophily, the tendency of similar individuals to participate in communication patterns beyond what would be expected on the basis of their average interaction frequencies. We also show that temporal patterns differ between dense and sparse neighborhoods in the network. Because also this result is independent of interaction frequencies, it can be seen as an extension of Granovetter’s hypothesis to temporal networks. PMID:24145424
The role of organo-mineral interactions on the capacity of soils to store carbon
NASA Astrophysics Data System (ADS)
Georgiou, K.; Abramoff, R. Z.; Riley, W. J.; Torn, M. S.
2017-12-01
Observed patterns of soil organic carbon (SOC) content across geochemical regimes are signatures of process and provide opportunities to understand the underlying decomposition and stabilization mechanisms that can guide their representation in models. The type of sorption equation used in soil decomposition models has large implications for both SOC stock and its temperature sensitivity. Here we compared different model formulations of SOC sorption to mineral surfaces, motivated by the myriad of chemical associations between organic and mineral surfaces, and used laboratory and field incubations to inform model parameters. We explored linear, Langmuir, and Freundlich adsorption models, where the latter emerges from heterogeneous compositions of substrate and surface components. We show the effect of model representations on predicted trends of SOC as a function of mineralogy and discuss the role of soil C saturation on emergent patterns. Specifically, our results highlight that the response of mineral-associated (`protected') SOC to changes in plant C inputs depends greatly on the C saturation deficit of the soil and thus, the representation of organo-mineral interactions in models can lead to nonlinear steady-state responses in protected SOC. We also find that, consistent with field experiments, the trend in protected SOC and mineral C saturation capacity is linear, but, interestingly, the slope depends on the degree of C saturation. We contend that this latter finding is an important consideration for field studies that did not find a universal slope and interpreted this as an inability of mineralogy to explain observed patterns. Our results also suggest that warming affects this slope, with higher temperatures causing a decrease in the amount of protected C for a given saturation capacity and C input rate. This means that more C inputs will be needed to keep the same amount of protected C at higher temperatures. Organo-mineral interactions play a key role in governing soil C stabilization and long-term storage, and thus, improving their representation for inclusion in Earth system models is crucial for understanding and predicting feedbacks under global change.
Layout optimization of DRAM cells using rigorous simulation model for NTD
NASA Astrophysics Data System (ADS)
Jeon, Jinhyuck; Kim, Shinyoung; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Kuechler, Bernd; Zimmermann, Rainer; Muelders, Thomas; Klostermann, Ulrich; Schmoeller, Thomas; Do, Mun-hoe; Choi, Jung-Hoe
2014-03-01
DRAM chip space is mainly determined by the size of the memory cell array patterns which consist of periodic memory cell features and edges of the periodic array. Resolution Enhancement Techniques (RET) are used to optimize the periodic pattern process performance. Computational Lithography such as source mask optimization (SMO) to find the optimal off axis illumination and optical proximity correction (OPC) combined with model based SRAF placement are applied to print patterns on target. For 20nm Memory Cell optimization we see challenges that demand additional tool competence for layout optimization. The first challenge is a memory core pattern of brick-wall type with a k1 of 0.28, so it allows only two spectral beams to interfere. We will show how to analytically derive the only valid geometrically limited source. Another consequence of two-beam interference limitation is a "super stable" core pattern, with the advantage of high depth of focus (DoF) but also low sensitivity to proximity corrections or changes of contact aspect ratio. This makes an array edge correction very difficult. The edge can be the most critical pattern since it forms the transition from the very stable regime of periodic patterns to non-periodic periphery, so it combines the most critical pitch and highest susceptibility to defocus. Above challenge makes the layout correction to a complex optimization task demanding a layout optimization that finds a solution with optimal process stability taking into account DoF, exposure dose latitude (EL), mask error enhancement factor (MEEF) and mask manufacturability constraints. This can only be achieved by simultaneously considering all criteria while placing and sizing SRAFs and main mask features. The second challenge is the use of a negative tone development (NTD) type resist, which has a strong resist effect and is difficult to characterize experimentally due to negative resist profile taper angles that perturb CD at bottom characterization by scanning electron microscope (SEM) measurements. High resist impact and difficult model data acquisition demand for a simulation model that hat is capable of extrapolating reliably beyond its calibration dataset. We use rigorous simulation models to provide that predictive performance. We have discussed the need of a rigorous mask optimization process for DRAM contact cell layout yielding mask layouts that are optimal in process performance, mask manufacturability and accuracy. In this paper, we have shown the step by step process from analytical illumination source derivation, a NTD and application tailored model calibration to layout optimization such as OPC and SRAF placement. Finally the work has been verified with simulation and experimental results on wafer.
Koelle, Katia; Rasmussen, David A
2015-01-01
Recent phylogenetic analyses indicate that RNA virus populations carry a significant deleterious mutation load. This mutation load has the potential to shape patterns of adaptive evolution via genetic linkage to beneficial mutations. Here, we examine the effect of deleterious mutations on patterns of influenza A subtype H3N2's antigenic evolution in humans. By first analyzing simple models of influenza that incorporate a mutation load, we show that deleterious mutations, as expected, act to slow the virus's rate of antigenic evolution, while making it more punctuated in nature. These models further predict three distinct molecular pathways by which antigenic cluster transitions occur, and we find phylogenetic patterns consistent with each of these pathways in influenza virus sequences. Simulations of a more complex phylodynamic model further indicate that antigenic mutations act in concert with deleterious mutations to reproduce influenza's spindly hemagglutinin phylogeny, co-circulation of antigenic variants, and high annual attack rates. DOI: http://dx.doi.org/10.7554/eLife.07361.001 PMID:26371556
The potential of air-sea interactions for improving summertime North Atlantic seasonal forecasts
NASA Astrophysics Data System (ADS)
Ossó, Albert; Shaffrey, Len; Dong, Buwen; Sutton, Rowan
2017-04-01
Delivering skillful summertime seasonal forecasts of the Northern Hemisphere (NH) mid-latitude climate is a key unresolved issue for the climate science community. Current climate models have some skill in forecasting the wintertime NH mid-latitude circulation but very limited skill during summertime. To explore the potential predictability of the summertime climate we analyze lagged correlation patterns between the SSTs and summer atmospheric circulation in the North Atlantic both in observations and climate model outputs. We find observational evidence in the ERA-Interim (1979-2015) reanalysis and the HadSLP2 and HadISST data of an SST pattern forced by late winter atmospheric circulation persisting from winter to early summer that excites an anticyclonic summer SLP anomaly west of the British Isles. We show that the atmospheric response is driven through the action of turbulent heat fluxes and changes on the background baroclinicity. The lagged atmospheric response to the SSTs could be exploited for summertime predictability over Western Europe. We find a statistical significant correlation of over 0.6 between April-May North Atlantic SSTs and the June-August North Atlantic SLP anomaly. The previous findings are further explored using 120 years of coupled ocean-atmosphere HadGEM3-GC2 model simulation. The climate model qualitatively reproduces the observed spatial relationship between the late winter and spring SSTs and summertime circulation, although the correlations are substantially weaker than observed.
Modeling the Effects of Perceptual Load: Saliency, Competitive Interactions, and Top-Down Biases.
Neokleous, Kleanthis; Shimi, Andria; Avraamides, Marios N
2016-01-01
A computational model of visual selective attention has been implemented to account for experimental findings on the Perceptual Load Theory (PLT) of attention. The model was designed based on existing neurophysiological findings on attentional processes with the objective to offer an explicit and biologically plausible formulation of PLT. Simulation results verified that the proposed model is capable of capturing the basic pattern of results that support the PLT as well as findings that are considered contradictory to the theory. Importantly, the model is able to reproduce the behavioral results from a dilution experiment, providing thus a way to reconcile PLT with the competing Dilution account. Overall, the model presents a novel account for explaining PLT effects on the basis of the low-level competitive interactions among neurons that represent visual input and the top-down signals that modulate neural activity. The implications of the model concerning the debate on the locus of selective attention as well as the origins of distractor interference in visual displays of varying load are discussed.
Experimental verification of electrostatic boundary conditions in gate-patterned quantum devices
NASA Astrophysics Data System (ADS)
Hou, H.; Chung, Y.; Rughoobur, G.; Hsiao, T. K.; Nasir, A.; Flewitt, A. J.; Griffiths, J. P.; Farrer, I.; Ritchie, D. A.; Ford, C. J. B.
2018-06-01
In a model of a gate-patterned quantum device, it is important to choose the correct electrostatic boundary conditions (BCs) in order to match experiment. In this study, we model gated-patterned devices in doped and undoped GaAs heterostructures for a variety of BCs. The best match is obtained for an unconstrained surface between the gates, with a dielectric region above it and a frozen layer of surface charge, together with a very deep back boundary. Experimentally, we find a ∼0.2 V offset in pinch-off characteristics of 1D channels in a doped heterostructure before and after etching off a ZnO overlayer, as predicted by the model. Also, we observe a clear quantised current driven by a surface acoustic wave through a lateral induced n-i-n junction in an undoped heterostructure. In the model, the ability to pump electrons in this type of device is highly sensitive to the back BC. Using the improved boundary conditions, it is straightforward to model quantum devices quite accurately using standard software.
Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns
NASA Astrophysics Data System (ADS)
Aoyagi, Toshio; Nomura, Masaki
1999-08-01
Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.
Hiramura, Hidetoshi; Shono, Masahiro; Tanaka, Nao; Nagata, Toshiaki; Kitamura, Toshinori
2008-01-01
The present study examines the effects of stressful life events, depression, and depressogenic cognitive patterns on suicidal ideation in 500 Japanese undergraduate students. The above factors were assessed at baseline (T1) and two weeks later (T3). At T1, structural equation modeling confirmed that (1) cognitive patterns and depression, but not stressful life events, influence suicidal ideation, and (2) cognitive patterns also influence suicidal ideation through depression. These findings were confirmed in a longitudinal analysis. The results suggest that the effects of stressful life events on suicidal ideation are indirect and are mediated by depressogenic cognitive styles and depressed mood.
NASA Astrophysics Data System (ADS)
Cooke, M. L.; Fattaruso, L.; Dorsey, R. J.; Housen, B. A.
2015-12-01
Between ~1.5 and 1.1 Ma, the southern San Andreas fault system underwent a major reorganization that included initiation of the San Jacinto fault and termination of slip on the extensional West Salton detachment fault. The southern San Andreas fault itself has also evolved since this time, with several shifts in activity among fault strands within San Gorgonio Pass. We use three-dimensional mechanical Boundary Element Method models to investigate the impact of these changes to the fault network on deformation patterns. A series of snapshot models of the succession of active fault geometries explore the role of fault interaction and tectonic loading in abandonment of the West Salton detachment fault, initiation of the San Jacinto fault, and shifts in activity of the San Andreas fault. Interpreted changes to uplift patterns are well matched by model results. These results support the idea that growth of the San Jacinto fault led to increased uplift rates in the San Gabriel Mountains and decreased uplift rates in the San Bernardino Mountains. Comparison of model results for vertical axis rotation to data from paleomagnetic studies reveals a good match to local rotation patterns in the Mecca Hills and Borrego Badlands. We explore the mechanical efficiency at each step in the evolution, and find an overall trend toward increased efficiency through time. Strain energy density patterns are used to identify regions of off-fault deformation and potential incipient faulting. These patterns support the notion of north-to-south propagation of the San Jacinto fault during its initiation. The results of the present-day model are compared with microseismicity focal mechanisms to provide additional insight into the patterns of off-fault deformation within the southern San Andreas fault system.
Mechanisms underlying different onset patterns of focal seizures
Trevelyan, Andrew J; Valentin, Antonio; Alarcon, Gonzalo
2017-01-01
Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types—low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the “healthy” surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome. PMID:28472032
Evaluating Arctic warming mechanisms in CMIP5 models
NASA Astrophysics Data System (ADS)
Franzke, Christian L. E.; Lee, Sukyoung; Feldstein, Steven B.
2017-05-01
Arctic warming is one of the most striking signals of global warming. The Arctic is one of the fastest warming regions on Earth and constitutes, thus, a good test bed to evaluate the ability of climate models to reproduce the physics and dynamics involved in Arctic warming. Different physical and dynamical mechanisms have been proposed to explain Arctic amplification. These mechanisms include the surface albedo feedback and poleward sensible and latent heat transport processes. During the winter season when Arctic amplification is most pronounced, the first mechanism relies on an enhancement in upward surface heat flux, while the second mechanism does not. In these mechanisms, it has been proposed that downward infrared radiation (IR) plays a role to a varying degree. Here, we show that the current generation of CMIP5 climate models all reproduce Arctic warming and there are high pattern correlations—typically greater than 0.9—between the surface air temperature (SAT) trend and the downward IR trend. However, we find that there are two groups of CMIP5 models: one with small pattern correlations between the Arctic SAT trend and the surface vertical heat flux trend (Group 1), and the other with large correlations (Group 2) between the same two variables. The Group 1 models exhibit higher pattern correlations between Arctic SAT and 500 hPa geopotential height trends, than do the Group 2 models. These findings suggest that Arctic warming in Group 1 models is more closely related to changes in the large-scale atmospheric circulation, whereas in Group 2, the albedo feedback effect plays a more important role. Interestingly, while Group 1 models have a warm or weak bias in their Arctic SAT, Group 2 models show large cold biases. This stark difference in model bias leads us to hypothesize that for a given model, the dominant Arctic warming mechanism and trend may be dependent on the bias of the model mean state.
Azimuthal anisotropy of the Pacific region
NASA Astrophysics Data System (ADS)
Maggi, Alessia; Debayle, Eric; Priestley, Keith; Barruol, Guilhem
2006-10-01
Azimuthal anisotropy is the dependence of local seismic properties on the azimuth of propagation. We present the azimuthally anisotropic component of a 3D SV velocity model for the Pacific Ocean, derived from the waveform modeling of over 56,000 multi-mode Rayleigh waves followed by a simultaneous inversion for isotropic and azimuthally anisotropic vsv structure. The isotropic vsv model is discussed in a previous paper (A. Maggi, E. Debayle, K. Priestley, G. Barruol, Multi-mode surface waveform tomography of the Pacific Ocean: a close look at the lithospheric cooling signature, Geophys. J. Int. 166 (3) (2006). doi:10.1111/j.1365-246x.2006.03037.x). The azimuthal anisotropy we find is consistent with the lattice preferred orientation model (LPO): the hypothesis of anisotropy generation in the Earth's mantle by preferential alignment of anisotropic crystals in response to the shear strains induced by mantle flow. At lithospheric depths we find good agreement between fast azimuthal anisotropy orientations and ridge spreading directions recorded by sea-floor magnetic anomalies. At asthenospheric depths we find a strong correlation between fast azimuthal anisotropy orientations and the directions of current plate motions. We observe perturbations in the pattern of seismic anisotropy close to Pacific hot-spots that are consistent with the predictions of numerical models of LPO generation in plume-disturbed plate motion-driven mantle flow. These observations suggest that perturbations in the patterns of azimuthal anisotropy may provide indirect evidence for plume-like upwelling in the mantle.
Street, Nichola; Forsythe, Alexandra M.; Reilly, Ronan; Taylor, Richard; Helmy, Mai S.
2016-01-01
Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics. PMID:27252634
Jansen, Dorine YM; Abadi, Fitsum; Harebottle, Doug; Altwegg, Res
2014-01-01
Among birds, northern temperate species generally have larger clutches, shorter development periods and lower adult survival than similarly-sized southern and tropical species. Even though this global pattern is well accepted, the driving mechanism is still not fully understood. The main theories are founded on the differing environmental seasonality of these zones (higher seasonality in the North). These patterns arise in cross-species comparisons, but we hypothesized that the same patterns should arise among populations within a species if different types of seasonality select for different life histories. Few studies have examined this. We estimated survival of an azonal habitat specialist, the African reed warbler, across the environmentally diverse African subcontinent, and related survival to latitude and to the seasonality of the different environments of their breeding habitats. Data (1998–2010) collected through a public ringing scheme were analyzed with hierarchical capture-mark-recapture models to determine resident adult survival and its spatial variance across sixteen vegetation units spread across four biomes. The models were defined as state-space multi-state models to account for transience and implemented in a Bayesian framework. We did not find a latitudinal trend in survival or a clear link between seasonality and survival. Spatial variation in survival was substantial across the sixteen sites (spatial standard deviation of the logit mean survival: 0.70, 95% credible interval (CRI): 0.33–1.27). Mean site survival ranged from 0.49 (95% CRI: 0.18–0.80) to 0.83 (95% CRI: 0.62–0.97) with an overall mean of 0.67 (95% CRI: 0.47–0.85). A hierarchical modeling approach enabled us to estimate spatial variation in survival of the African reed warbler across the African subcontinent from sparse data. Although we could not confirm the global pattern of higher survival in less seasonal environments, our findings from a poorly studied region contribute to the study of life-history strategies. PMID:24772268
Pattern formation with proportionate growth
NASA Astrophysics Data System (ADS)
Dhar, Deepak
It is a common observation that as baby animals grow, different body parts grow approximately at same rate. This property, called proportionate growth is remarkable in that it is not encountered easily outside biology. The models of growth that have been studied in Physics so far, e.g diffusion -limited aggregation, surface deposition, growth of crystals from melt etc. involve only growth at the surface, with the inner structure remaining frozen. Interestingly, patterns formed in growing sandpiles provide a very wide variety of patterns that show proportionate growth. One finds patterns with different features, with sharply defined boundaries. In particular, even with very simple rules, one can produce patterns that show striking resemblance to those seen in nature. We can characterize the asymptotic pattern exactly in some special cases. I will discuss in particular the patterns grown on noisy backgrounds. Supported by J. C. Bose fellowship from DST (India).
Instabilities and spatiotemporal patterns behind predator invasions with nonlocal prey competition.
Merchant, Sandra M; Nagata, Wayne
2011-12-01
We study the influence of nonlocal intraspecies prey competition on the spatiotemporal patterns arising behind predator invasions in two oscillatory reaction-diffusion integro-differential models. We use three common types of integral kernels as well as develop a caricature system, to describe the influence of the standard deviation and kurtosis of the kernel function on the patterns observed. We find that nonlocal competition can destabilize the spatially homogeneous state behind the invasion and lead to the formation of complex spatiotemporal patterns, including stationary spatially periodic patterns, wave trains and irregular spatiotemporal oscillations. In addition, the caricature system illustrates how large standard deviation and low kurtosis facilitate the formation of these spatiotemporal patterns. This suggests that nonlocal competition may be an important mechanism underlying spatial pattern formation, particularly in systems where the competition between individuals varies over space in a platykurtic manner. Copyright © 2011 Elsevier Inc. All rights reserved.
Stevens, Jeffrey R; Marewski, Julian N; Schooler, Lael J; Gilby, Ian C
2016-08-01
In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees ( Pan troglodytes ) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.
Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans
Marewski, Julian N.; Schooler, Lael J.; Gilby, Ian C.
2016-01-01
In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition. PMID:27853606
Empirical Profiles of Alcohol and Marijuana Use, Drugged Driving, and Risk Perceptions.
Arterberry, Brooke J; Treloar, Hayley; McCarthy, Denis M
2017-11-01
The present study sought to inform models of risk for drugged driving through empirically identifying patterns of marijuana use, alcohol use, and related driving behaviors. Perceived dangerousness and consequences of drugged driving were evaluated as putative influences on risk patterns. We used latent profile analysis of survey responses from 897 college students to identify patterns of substance use and drugged driving. We tested the hypotheses that low perceived danger and low perceived likelihood of negative consequences of drugged driving would identify individuals with higher-risk patterns. Findings from the latent profile analysis indicated that a four-profile model provided the best model fit. Low-level engagers had low rates of substance use and drugged driving. Alcohol-centric engagers had higher rates of alcohol use but low rates of marijuana/simultaneous use and low rates of driving after substance use. Concurrent engagers had higher rates of marijuana and alcohol use, simultaneous use, and related driving behaviors, but marijuana-centric/simultaneous engagers had the highest rates of marijuana use, co-use, and related driving behaviors. Those with higher perceived danger of driving while high were more likely to be in the low-level, alcohol-centric, or concurrent engagers' profiles; individuals with higher perceived likelihood of consequences of driving while high were more likely to be in the low-level engagers group. Findings suggested that college students' perceived dangerousness of driving after using marijuana had greater influence on drugged driving behaviors than alcohol-related driving risk perceptions. These results support targeting marijuana-impaired driving risk perceptions in young adult intervention programs.
A fast process development flow by applying design technology co-optimization
NASA Astrophysics Data System (ADS)
Chen, Yi-Chieh; Yeh, Shin-Shing; Ou, Tsong-Hua; Lin, Hung-Yu; Mai, Yung-Ching; Lin, Lawrence; Lai, Jun-Cheng; Lai, Ya Chieh; Xu, Wei; Hurat, Philippe
2017-03-01
Beyond 40 nm technology node, the pattern weak points and hotspot types increase dramatically. The typical patterns for lithography verification suffers huge turn-around-time (TAT) to handle the design complexity. Therefore, in order to speed up process development and increase pattern variety, accurate design guideline and realistic design combinations are required. This paper presented a flow for creating a cell-based layout, a lite realistic design, to early identify problematic patterns which will negatively affect the yield. A new random layout generating method, Design Technology Co-Optimization Pattern Generator (DTCO-PG), is reported in this paper to create cell-based design. DTCO-PG also includes how to characterize the randomness and fuzziness, so that it is able to build up the machine learning scheme which model could be trained by previous results, and then it generates patterns never seen in a lite design. This methodology not only increases pattern diversity but also finds out potential hotspot preliminarily. This paper also demonstrates an integrated flow from DTCO pattern generation to layout modification. Optical Proximity Correction, OPC and lithographic simulation is then applied to DTCO-PG design database to detect hotspots and then hotspots or weak points can be automatically fixed through the procedure or handled manually. This flow benefits the process evolution to have a faster development cycle time, more complexity pattern design, higher probability to find out potential hotspots in early stage, and a more holistic yield ramping operation.
Transionospheric Propagation of VLF Transmitter Signals
NASA Astrophysics Data System (ADS)
Cohen, M.; Inan, U. S.; Lehtinen, N. G.
2012-12-01
Ground based Very Low Frequency (VLF, 3-30 kHz) radio transmitters may play a significant role in precipitation of inner belt (L<2.5) energetic Van Allen electrons. Initial analyses of the total contribution of VLF transmitters utilized models of transionospheric propagation, but some recent studies have suggested that those models may overestimate (by 20-100 dB) the VLF energy reaching the magnetosphere. One possible cause of this discrepancy was suggested to be conversion of wave energy into electrostatic modes in the D, E, and F regions, from ionospheric density irregularities, either natural or generated by the transmitter heating itself. The DEMETER satellite built a six year history of continuous and global survey mode data which, when combined, yields detailed pictures of the radiation pattern from many transmitters into space at 680 km, with 25 km resolution, and clear features like the interference pattern on the ground mapped upwards. With both E and B survey mode data, we can also directly approximate the total power injected into the magnetosphere from each transmitter, separately for day and night, as well as the power arriving at the conjugate region. We find no detectable variation of signal intensity with geomagnetic conditions. We find evidence of transmitter heating affecting the transionospheric propagation of other transmitters. We find that the power reaching the conjugate region is a large fraction of the power injected above the transmitter. We then employ a full wave model to simulate VLF transmitter transionospheric propagation, calculating the electromagnetic fields and power flux injected into the magnetosphere. Although the model does not include ionospheric irregularities, the radiation pattern largely matches the observed one, and the total power calculated is within 6 dB of observations for every transmitter, both day and night, and across a range of low to middle latitudes and transmitter powers. We thus conclude that the effect of ionospheric irregularities on VLF wave injection into the radiation belts may be small, if present at all.The nighttime radiation pattern of NWC at 700 km altitude, derived by averaging 6 years of DEMETER survey mode data.
ERIC Educational Resources Information Center
Celentin, Paola
2007-01-01
In this article we discuss findings from a case-study related to the distance education of teachers of Italian as a second/foreign language. This case-study has examined interactions among teachers during their discussions in a web-forum exploiting the model of content analysis proposed in the "Practical Inquiry Model" by Garrison, Anderson, and…
Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory
Xue, Gui; Love, Bradley C.; Preston, Alison R.; Poldrack, Russell A.
2014-01-01
Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. PMID:24872552
Data-driven Modelling for decision making under uncertainty
NASA Astrophysics Data System (ADS)
Angria S, Layla; Dwi Sari, Yunita; Zarlis, Muhammad; Tulus
2018-01-01
The rise of the issues with the uncertainty of decision making has become a very warm conversation in operation research. Many models have been presented, one of which is with data-driven modelling (DDM). The purpose of this paper is to extract and recognize patterns in data, and find the best model in decision-making problem under uncertainty by using data-driven modeling approach with linear programming, linear and nonlinear differential equation, bayesian approach. Model criteria tested to determine the smallest error, and it will be the best model that can be used.
Eom, Dae Seok; Inoue, Shinya; Patterson, Larissa B; Gordon, Tiffany N; Slingwine, Rebecca; Kondo, Shigeru; Watanabe, Masakatsu; Parichy, David M
2012-01-01
The zebrafish adult pigment pattern has emerged as a useful model for understanding the development and evolution of adult form as well as pattern-forming mechanisms more generally. In this species, a series of horizontal melanophore stripes arises during the larval-to-adult transformation, but the genetic and cellular bases for stripe formation remain largely unknown. Here, we show that the seurat mutant phenotype, consisting of an irregular spotted pattern, arises from lesions in the gene encoding Immunoglobulin superfamily member 11 (Igsf11). We find that Igsf11 is expressed by melanophores and their precursors, and we demonstrate by cell transplantation and genetic rescue that igsf11 functions autonomously to this lineage in promoting adult stripe development. Further analyses of cell behaviors in vitro, in vivo, and in explant cultures ex vivo demonstrate that Igsf11 mediates adhesive interactions and that mutants for igsf11 exhibit defects in both the migration and survival of melanophores and their precursors. These findings identify the first in vivo requirements for igsf11 as well as the first instance of an immunoglobulin superfamily member functioning in pigment cell development and patterning. Our results provide new insights into adult pigment pattern morphogenesis and how cellular interactions mediate pattern formation.
Patterson, Larissa B.; Gordon, Tiffany N.; Slingwine, Rebecca; Kondo, Shigeru; Watanabe, Masakatsu; Parichy, David M.
2012-01-01
The zebrafish adult pigment pattern has emerged as a useful model for understanding the development and evolution of adult form as well as pattern-forming mechanisms more generally. In this species, a series of horizontal melanophore stripes arises during the larval-to-adult transformation, but the genetic and cellular bases for stripe formation remain largely unknown. Here, we show that the seurat mutant phenotype, consisting of an irregular spotted pattern, arises from lesions in the gene encoding Immunoglobulin superfamily member 11 (Igsf11). We find that Igsf11 is expressed by melanophores and their precursors, and we demonstrate by cell transplantation and genetic rescue that igsf11 functions autonomously to this lineage in promoting adult stripe development. Further analyses of cell behaviors in vitro, in vivo, and in explant cultures ex vivo demonstrate that Igsf11 mediates adhesive interactions and that mutants for igsf11 exhibit defects in both the migration and survival of melanophores and their precursors. These findings identify the first in vivo requirements for igsf11 as well as the first instance of an immunoglobulin superfamily member functioning in pigment cell development and patterning. Our results provide new insights into adult pigment pattern morphogenesis and how cellular interactions mediate pattern formation. PMID:22916035
Healthy Eating Strategies in the Workplace
Quintiliani, Lisa; Poulsen, Signe; Sorensen, Glorian
2013-01-01
Purpose There is a clear link between dietary behavior and a range of chronic diseases, and overweight and obesity constitute an indirect risk in relation to these diseases. The worksite is a central venue for influencing dietary behavior. The purpose of this paper is to provide an overview of workplace influences on worker dietary patterns. Design/methodology/approach The paper reviews the evidence of the effectiveness of dietary health promotion, and provides a brief overview of appropriate theoretical frameworks to guide intervention design and evaluation. The findings are illustrated through research examples. Findings Through case studies and published research, it is found that workplace dietary interventions are generally effective, especially fruit and vegetable interventions. There is less consistent evidence on the long term effectiveness of workplace weight management interventions, underscoring the need for further research in this area. This paper also reports evidence that changes in the work environment, including through health and safety programs, may contribute to enhancing the effectiveness of workplace health promotion, including dietary interventions. Organizational factors such as work schedule may also influence dietary patterns. The social ecological model, the social contextual model and political process approach are presented as exemplar conceptual models that may be useful when designing or assessing the effects of workplace health promotion. Originality/value Using the worksite as setting for influencing health by influencing dietary patterns holds considerable promise and may be instrumental in reducing workers’ risk of chronic diseases. PMID:23935706
Role of alveolar topology on acinar flows and convective mixing.
Hofemeier, Philipp; Sznitman, Josué
2014-06-01
Due to experimental challenges, computational simulations are often sought to quantify inhaled aerosol transport in the pulmonary acinus. Commonly, these are performed using generic alveolar topologies, including spheres, toroids, and polyhedra, to mimic the complex acinar morphology. Yet, local acinar flows and ensuing particle transport are anticipated to be influenced by the specific morphological structures. We have assessed a range of acinar models under self-similar breathing conditions with respect to alveolar flow patterns, convective flow mixing, and deposition of fine particles (1.3 μm diameter). By tracking passive tracers over cumulative breathing cycles, we find that irreversible flow mixing correlates with the location and strength of the recirculating vortex inside the cavity. Such effects are strongest in proximal acinar generations where the ratio of alveolar to ductal flow rates is low and interalveolar disparities are most apparent. Our results for multi-alveolated acinar ducts highlight that fine 1 μm inhaled particles subject to alveolar flows are sensitive to the alveolar topology, underlining interalveolar disparities in particle deposition patterns. Despite the simplicity of the acinar models investigated, our findings suggest that alveolar topologies influence more significantly local flow patterns and deposition sites of fine particles for upper generations emphasizing the importance of the selected acinar model. In distal acinar generations, however, the alveolar geometry primarily needs to mimic the space-filling alveolar arrangement dictated by lung morphology.
A latent transition model of the effects of a teen dating violence prevention initiative.
Williams, Jason; Miller, Shari; Cutbush, Stacey; Gibbs, Deborah; Clinton-Sherrod, Monique; Jones, Sarah
2015-02-01
Patterns of physical and psychological teen dating violence (TDV) perpetration, victimization, and related behaviors were examined with data from the evaluation of the Start Strong: Building Healthy Teen Relationships initiative, a dating violence primary prevention program targeting middle school students. Latent class and latent transition models were used to estimate distinct patterns of TDV and related behaviors of bullying and sexual harassment in seventh grade students at baseline and to estimate transition probabilities from one pattern of behavior to another at the 1-year follow-up. Intervention effects were estimated by conditioning transitions on exposure to Start Strong. Latent class analyses suggested four classes best captured patterns of these interrelated behaviors. Classes were characterized by elevated perpetration and victimization on most behaviors (the multiproblem class), bullying perpetration/victimization and sexual harassment victimization (the bully-harassment victimization class), bullying perpetration/victimization and psychological TDV victimization (bully-psychological victimization), and experience of bully victimization (bully victimization). Latent transition models indicated greater stability of class membership in the comparison group. Intervention students were less likely to transition to the most problematic pattern and more likely to transition to the least problem class. Although Start Strong has not been found to significantly change TDV, alternative evaluation models may find important differences. Latent transition analysis models suggest positive intervention impact, especially for the transitions at the most and the least positive end of the spectrum. Copyright © 2015. Published by Elsevier Inc.
Anatomical and spiral wave reentry in a simplified model for atrial electrophysiology.
Richter, Yvonne; Lind, Pedro G; Seemann, Gunnar; Maass, Philipp
2017-04-21
For modeling the propagation of action potentials in the human atria, various models have been developed in the past, which take into account in detail the influence of the numerous ionic currents flowing through the cell membrane. Aiming at a simplified description, the Bueno-Orovio-Cherry-Fenton (BOCF) model for electric wave propagation in the ventricle has been adapted recently to atrial physiology. Here, we study this adapted BOCF (aBOCF) model with respect to its capability to accurately generate spatio-temporal excitation patterns found in anatomical and spiral wave reentry. To this end, we compare results of the aBOCF model with the more detailed one proposed by Courtemanche, Ramirez and Nattel (CRN model). We find that characteristic features of the reentrant excitation patterns seen in the CRN model are well captured by the aBOCF model. This opens the possibility to study origins of atrial fibrillation based on a simplified but still reliable description. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mechanochemical Symmetry Breaking in Hydra Aggregates
Mercker, Moritz; Köthe, Alexandra; Marciniak-Czochra, Anna
2015-01-01
Tissue morphogenesis comprises the self-organized creation of various patterns and shapes. Although detailed underlying mechanisms are still elusive in many cases, an increasing amount of experimental data suggests that chemical morphogen and mechanical processes are strongly coupled. Here, we develop and test a minimal model of the axis-defining step (i.e., symmetry breaking) in aggregates of the Hydra polyp. Based on previous findings, we combine osmotically driven shape oscillations with tissue mechanics and morphogen dynamics. We show that the model incorporating a simple feedback loop between morphogen patterning and tissue stretch reproduces a wide range of experimental data. Finally, we compare different hypothetical morphogen patterning mechanisms (Turing, tissue-curvature, and self-organized criticality). Our results suggest the experimental investigation of bigger (i.e., multiple head) aggregates as a key step for a deeper understanding of mechanochemical symmetry breaking in Hydra. PMID:25954896
Inverse scattering approach to improving pattern recognition
NASA Astrophysics Data System (ADS)
Chapline, George; Fu, Chi-Yung
2005-05-01
The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the "wake-sleep" algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensory feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.
Inverse Scattering Approach to Improving Pattern Recognition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chapline, G; Fu, C
2005-02-15
The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the ''wake-sleep'' algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensorymore » feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.« less
Dynamos driven by weak thermal convection and heterogeneous outer boundary heat flux
NASA Astrophysics Data System (ADS)
Sahoo, Swarandeep; Sreenivasan, Binod; Amit, Hagay
2016-01-01
We use numerical dynamo models with heterogeneous core-mantle boundary (CMB) heat flux to show that lower mantle lateral thermal variability may help support a dynamo under weak thermal convection. In our reference models with homogeneous CMB heat flux, convection is either marginally supercritical or absent, always below the threshold for dynamo onset. We find that lateral CMB heat flux variations organize the flow in the core into patterns that favour the growth of an early magnetic field. Heat flux patterns symmetric about the equator produce non-reversing magnetic fields, whereas anti-symmetric patterns produce polarity reversals. Our results may explain the existence of the geodynamo prior to inner core nucleation under a tight energy budget. Furthermore, in order to sustain a strong geomagnetic field, the lower mantle thermal distribution was likely dominantly symmetric about the equator.
SST Patterns, Atmospheric Variability, and Inferred Sensitivities in the CMIP5 Model Archive
NASA Astrophysics Data System (ADS)
Marvel, K.; Pincus, R.; Schmidt, G. A.
2017-12-01
An emerging consensus suggests that global mean feedbacks to increasing temperature are not constant in time. If feedbacks become more positive in the future, the equilibrium climate sensitivity (ECS) inferred from recent observed global energy budget constraints is likely to be biased low. Time-varying feedbacks are largely tied to evolving sea-surface temperature patterns. In particular, recent anomalously cool conditions in the tropical Pacific may have triggered feedbacks that are not reproduced in equilibrium simulations where the tropical Pacific and Southern Ocean have had time to warm. Here, we use AMIP and CMIP5 historical simulations to explore the ECS that may be inferred over the recent historical period. We find that in all but one CMIP5 model, the feedbacks triggered by observed SST patterns are significantly less positive than those arising from historical simulations in which SST patterns are allowed to evolve unconstrained. However, there are substantial variations in feedbacks even when the SST pattern is held fixed, suggesting that atmospheric and land variability contribute to uncertainty in the estimates of ECS obtained from recent observations of the global energy budget.
NASA Astrophysics Data System (ADS)
Chen, Yi-Chieh; Li, Tsung-Han; Lin, Hung-Yu; Chen, Kao-Tun; Wu, Chun-Sheng; Lai, Ya-Chieh; Hurat, Philippe
2018-03-01
Along with process improvement and integrated circuit (IC) design complexity increased, failure rate caused by optical getting higher in the semiconductor manufacture. In order to enhance chip quality, optical proximity correction (OPC) plays an indispensable rule in the manufacture industry. However, OPC, includes model creation, correction, simulation and verification, is a bottleneck from design to manufacture due to the multiple iterations and advanced physical behavior description in math. Thus, this paper presented a pattern-based design technology co-optimization (PB-DTCO) flow in cooperation with OPC to find out patterns which will negatively affect the yield and fixed it automatically in advance to reduce the run-time in OPC operation. PB-DTCO flow can generate plenty of test patterns for model creation and yield gaining, classify candidate patterns systematically and furthermore build up bank includes pairs of match and optimization patterns quickly. Those banks can be used for hotspot fixing, layout optimization and also be referenced for the next technology node. Therefore, the combination of PB-DTCO flow with OPC not only benefits for reducing the time-to-market but also flexible and can be easily adapted to diversity OPC flow.
2015-01-01
The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities. PMID:26569608
Kostrubiec, Viviane; Dumas, Guillaume; Zanone, Pier-Giorgio; Kelso, J A Scott
2015-01-01
The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities.
Motion patterns in acupuncture needle manipulation.
Seo, Yoonjeong; Lee, In-Seon; Jung, Won-Mo; Ryu, Ho-Sun; Lim, Jinwoong; Ryu, Yeon-Hee; Kang, Jung-Won; Chae, Younbyoung
2014-10-01
In clinical practice, acupuncture manipulation is highly individualised for each practitioner. Before we establish a standard for acupuncture manipulation, it is important to understand completely the manifestations of acupuncture manipulation in the actual clinic. To examine motion patterns during acupuncture manipulation, we generated a fitted model of practitioners' motion patterns and evaluated their consistencies in acupuncture manipulation. Using a motion sensor, we obtained real-time motion data from eight experienced practitioners while they conducted acupuncture manipulation using their own techniques. We calculated the average amplitude and duration of a sampled motion unit for each practitioner and, after normalisation, we generated a true regression curve of motion patterns for each practitioner using a generalised additive mixed modelling (GAMM). We observed significant differences in rotation amplitude and duration in motion samples among practitioners. GAMM showed marked variations in average regression curves of motion patterns among practitioners but there was strong consistency in motion parameters for individual practitioners. The fitted regression model showed that the true regression curve accounted for an average of 50.2% of variance in the motion pattern for each practitioner. Our findings suggest that there is great inter-individual variability between practitioners, but remarkable intra-individual consistency within each practitioner. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Pattern separation in the hippocampus: distinct circuits under different conditions.
Kassab, Randa; Alexandre, Frédéric
2018-04-11
Pattern separation is a fundamental hippocampal process thought to be critical for distinguishing similar episodic memories, and has long been recognized as a natural function of the dentate gyrus (DG), supporting autoassociative learning in CA3. Understanding how neural circuits within the DG-CA3 network mediate this process has received much interest, yet the exact mechanisms behind remain elusive. Here, we argue for the case that sparse coding is necessary but not sufficient to ensure efficient separation and, alternatively, propose a possible interaction of distinct circuits which, nevertheless, act in synergy to produce a unitary function of pattern separation. The proposed circuits involve different functional granule-cell populations, a primary population mediates sparsification and provides recurrent excitation to the other populations which are related to additional pattern separation mechanisms with higher degrees of robustness against interference in CA3. A variety of top-down and bottom-up factors, such as motivation, emotion, and pattern similarity, control the selection of circuitry depending on circumstances. According to this framework, a computational model is implemented and tested against model variants in a series of numerical simulations and biological experiments. The results demonstrate that the model combines fast learning, robust pattern separation and high storage capacity. It also accounts for the controversy around the involvement of the DG during memory recall, explains other puzzling findings, and makes predictions that can inform future investigations.
Menstrual Bleeding Patterns Among Regularly Menstruating Women
Dasharathy, Sonya S.; Mumford, Sunni L.; Pollack, Anna Z.; Perkins, Neil J.; Mattison, Donald R.; Wactawski-Wende, Jean; Schisterman, Enrique F.
2012-01-01
Menstrual bleeding patterns are considered relevant indicators of reproductive health, though few studies have evaluated patterns among regularly menstruating premenopausal women. The authors evaluated self-reported bleeding patterns, incidence of spotting, and associations with reproductive hormones among 201 women in the BioCycle Study (2005–2007) with 2 consecutive cycles. Bleeding patterns were assessed by using daily questionnaires and pictograms. Marginal structural models were used to evaluate associations between endogenous hormone concentrations and subsequent total reported blood loss and bleeding length by weighted linear mixed-effects models and weighted parametric survival analysis models. Women bled for a median of 5 days (standard deviation: 1.5) during menstruation, with heavier bleeding during the first 3 days. Only 4.8% of women experienced midcycle bleeding. Increased levels of follicle-stimulating hormone (β = 0.20, 95% confidence interval: 0.13, 0.27) and progesterone (β = 0.06, 95% confidence interval: 0.03, 0.09) throughout the cycle were associated with heavier menstrual bleeding, and higher follicle-stimulating hormone levels were associated with longer menses. Bleeding duration and volume were reduced after anovulatory compared with ovulatory cycles (geometric mean blood loss: 29.6 vs. 47.2 mL; P = 0.07). Study findings suggest that detailed characterizations of bleeding patterns may provide more insight than previously thought as noninvasive markers for endocrine status in a given cycle. PMID:22350580
Long-term memory stabilized by noise-induced rehearsal.
Wei, Yi; Koulakov, Alexei A
2014-11-19
Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. Copyright © 2014 the authors 0270-6474/14/3415804-12$15.00/0.
Neutral Community Dynamics and the Evolution of Species Interactions.
Coelho, Marco Túlio P; Rangel, Thiago F
2018-04-01
A contemporary goal in ecology is to determine the ecological and evolutionary processes that generate recurring structural patterns in mutualistic networks. One of the great challenges is testing the capacity of neutral processes to replicate observed patterns in ecological networks, since the original formulation of the neutral theory lacks trophic interactions. Here, we develop a stochastic-simulation neutral model adding trophic interactions to the neutral theory of biodiversity. Without invoking ecological differences among individuals of different species, and assuming that ecological interactions emerge randomly, we demonstrate that a spatially explicit multitrophic neutral model is able to capture the recurrent structural patterns of mutualistic networks (i.e., degree distribution, connectance, nestedness, and phylogenetic signal of species interactions). Nonrandom species distribution, caused by probabilistic events of migration and speciation, create nonrandom network patterns. These findings have broad implications for the interpretation of niche-based processes as drivers of ecological networks, as well as for the integration of network structures with demographic stochasticity.
Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data
Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong
2014-01-01
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips. PMID:24465849
Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.
Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong
2014-01-01
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.
Simulating the role of visual selective attention during the development of perceptual completion
Schlesinger, Matthew; Amso, Dima; Johnson, Scott P.
2014-01-01
We recently proposed a multi-channel, image-filtering model for simulating the development of visual selective attention in young infants (Schlesinger, Amso & Johnson, 2007). The model not only captures the performance of 3-month-olds on a visual search task, but also implicates two cortical regions that may play a role in the development of visual selective attention. In the current simulation study, we used the same model to simulate 3-month-olds’ performance on a second measure, the perceptual unity task. Two parameters in the model – corresponding to areas in the occipital and parietal cortices – were systematically varied while the gaze patterns produced by the model were recorded and subsequently analyzed. Three key findings emerged from the simulation study. First, the model successfully replicated the performance of 3-month-olds on the unity perception task. Second, the model also helps to explain the improved performance of 2-month-olds when the size of the occluder in the unity perception task is reduced. Third, in contrast to our previous simulation results, variation in only one of the two cortical regions simulated (i.e. recurrent activity in posterior parietal cortex) resulted in a performance pattern that matched 3-month-olds. These findings provide additional support for our hypothesis that the development of perceptual completion in early infancy is promoted by progressive improvements in visual selective attention and oculomotor skill. PMID:23106728
Simulating the role of visual selective attention during the development of perceptual completion.
Schlesinger, Matthew; Amso, Dima; Johnson, Scott P
2012-11-01
We recently proposed a multi-channel, image-filtering model for simulating the development of visual selective attention in young infants (Schlesinger, Amso & Johnson, 2007). The model not only captures the performance of 3-month-olds on a visual search task, but also implicates two cortical regions that may play a role in the development of visual selective attention. In the current simulation study, we used the same model to simulate 3-month-olds' performance on a second measure, the perceptual unity task. Two parameters in the model - corresponding to areas in the occipital and parietal cortices - were systematically varied while the gaze patterns produced by the model were recorded and subsequently analyzed. Three key findings emerged from the simulation study. First, the model successfully replicated the performance of 3-month-olds on the unity perception task. Second, the model also helps to explain the improved performance of 2-month-olds when the size of the occluder in the unity perception task is reduced. Third, in contrast to our previous simulation results, variation in only one of the two cortical regions simulated (i.e. recurrent activity in posterior parietal cortex) resulted in a performance pattern that matched 3-month-olds. These findings provide additional support for our hypothesis that the development of perceptual completion in early infancy is promoted by progressive improvements in visual selective attention and oculomotor skill. © 2012 Blackwell Publishing Ltd.
van der Post, Daniel J; Semmann, Dirk
2011-10-01
Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or "recognize patterns" in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is "staying in patches". In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape.
Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*
Castruccio, Stefano; McInerney, David J.; Stein, Michael L.; ...
2014-02-24
The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO 2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as patternmore » scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. In conclusion, it may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.« less
Reconstructing Perceived and Retrieved Faces from Activity Patterns in Lateral Parietal Cortex.
Lee, Hongmi; Kuhl, Brice A
2016-06-01
Recent findings suggest that the contents of memory encoding and retrieval can be decoded from the angular gyrus (ANG), a subregion of posterior lateral parietal cortex. However, typical decoding approaches provide little insight into the nature of ANG content representations. Here, we tested whether complex, multidimensional stimuli (faces) could be reconstructed from ANG by predicting underlying face components from fMRI activity patterns in humans. Using an approach inspired by computer vision methods for face recognition, we applied principal component analysis to a large set of face images to generate eigenfaces. We then modeled relationships between eigenface values and patterns of fMRI activity. Activity patterns evoked by individual faces were then used to generate predicted eigenface values, which could be transformed into reconstructions of individual faces. We show that visually perceived faces were reliably reconstructed from activity patterns in occipitotemporal cortex and several lateral parietal subregions, including ANG. Subjective assessment of reconstructed faces revealed specific sources of information (e.g., affect and skin color) that were successfully reconstructed in ANG. Strikingly, we also found that a model trained on ANG activity patterns during face perception was able to successfully reconstruct an independent set of face images that were held in memory. Together, these findings provide compelling evidence that ANG forms complex, stimulus-specific representations that are reflected in activity patterns evoked during perception and remembering. Neuroimaging studies have consistently implicated lateral parietal cortex in episodic remembering, but the functional contributions of lateral parietal cortex to memory remain a topic of debate. Here, we used an innovative form of fMRI pattern analysis to test whether lateral parietal cortex actively represents the contents of memory. Using a large set of human face images, we first extracted latent face components (eigenfaces). We then used machine learning algorithms to predict face components from fMRI activity patterns and, ultimately, to reconstruct images of individual faces. We show that activity patterns in a subregion of lateral parietal cortex, the angular gyrus, supported successful reconstruction of perceived and remembered faces, confirming a role for this region in actively representing remembered content. Copyright © 2016 the authors 0270-6474/16/366069-14$15.00/0.
Self-esteem Is Mostly Stable Across Young Adulthood: Evidence from Latent STARTS Models.
Wagner, Jenny; Lüdtke, Oliver; Trautwein, Ulrich
2016-08-01
How stable is self-esteem? This long-standing debate has led to different conclusions across different areas of psychology. Longitudinal data and up-to-date statistical models have recently indicated that self-esteem has stable and autoregressive trait-like components and state-like components. We applied latent STARTS models with the goal of replicating previous findings in a longitudinal sample of young adults (N = 4,532; Mage = 19.60, SD = 0.85; 55% female). In addition, we applied multigroup models to extend previous findings on different patterns of stability for men versus women and for people with high versus low levels of depressive symptoms. We found evidence for the general pattern of a major proportion of stable and autoregressive trait variance and a smaller yet substantial amount of state variance in self-esteem across 10 years. Furthermore, multigroup models suggested substantial differences in the variance components: Females showed more state variability than males. Individuals with higher levels of depressive symptoms showed more state and less autoregressive trait variance in self-esteem. Results are discussed with respect to the ongoing trait-state debate and possible implications of the group differences that we found in the stability of self-esteem. © 2015 Wiley Periodicals, Inc.
Signatures of a staggered-flux phase in the t-J model with two holes on a 32-site lattice
NASA Astrophysics Data System (ADS)
Leung, P. W.
2000-09-01
We study the relevance of the staggered-flux phase in the t-J model using a system with two holes on a 32-site lattice with periodic boundary conditions. We find a staggered-flux pattern in the current-current correlation in the lowest energy d-wave state where there is mutual attraction between the holes. This staggered correlation decays faster with distance when the hole binding becomes stronger. This is in complete agreement with a recent study by Ivanov, Lee, and Wen [Phys. Rev. Lett. 84, 3958 (2000)] based on the SU(2) theory, and strongly suggests that the staggered-flux phase is a key ingredient in the t-J model. We further show that this staggered-flux pattern does not exist in a state where the holes repel each other. Correlations of the chirality operator S1.(S2×S3) show that the staggered pattern of the chirality is closely tied to the holes.
Aldwin, Carolyn M.; Molitor, Nuoo-Ting; Avron, Spiro; Levenson, Michael R.; Molitor, John; Igarashi, Heidi
2011-01-01
We examined long-term patterns of stressful life events (SLE) and their impact on mortality contrasting two theoretical models: allostatic load (linear relationship) and hormesis (inverted U relationship) in 1443 NAS men (aged 41–87 in 1985; M = 60.30, SD = 7.3) with at least two reports of SLEs over 18 years (total observations = 7,634). Using a zero-inflated Poisson growth mixture model, we identified four patterns of SLE trajectories, three showing linear decreases over time with low, medium, and high intercepts, respectively, and one an inverted U, peaking at age 70. Repeating the analysis omitting two health-related SLEs yielded only the first three linear patterns. Compared to the low-stress group, both the moderate and the high-stress groups showed excess mortality, controlling for demographics and health behavior habits, HRs = 1.42 and 1.37, ps <.01 and <.05. The relationship between stress trajectories and mortality was complex and not easily explained by either theoretical model. PMID:21961066
Geostatistical modeling of riparian forest microclimate and its implications for sampling
Eskelson, B.N.I.; Anderson, P.D.; Hagar, J.C.; Temesgen, H.
2011-01-01
Predictive models of microclimate under various site conditions in forested headwater stream - riparian areas are poorly developed, and sampling designs for characterizing underlying riparian microclimate gradients are sparse. We used riparian microclimate data collected at eight headwater streams in the Oregon Coast Range to compare ordinary kriging (OK), universal kriging (UK), and kriging with external drift (KED) for point prediction of mean maximum air temperature (Tair). Several topographic and forest structure characteristics were considered as site-specific parameters. Height above stream and distance to stream were the most important covariates in the KED models, which outperformed OK and UK in terms of root mean square error. Sample patterns were optimized based on the kriging variance and the weighted means of shortest distance criterion using the simulated annealing algorithm. The optimized sample patterns outperformed systematic sample patterns in terms of mean kriging variance mainly for small sample sizes. These findings suggest methods for increasing efficiency of microclimate monitoring in riparian areas.
NASA Astrophysics Data System (ADS)
Lindblad, P. A. B.; Kristen, H.
1996-09-01
We perform two-dimensional time dependent hydrodynamical simulations of the barred spiral galaxy NGC 1300. The input potential is divided into an axisymmetric part mainly derived from the observed rotation curve, and a perturbing part obtained from near infrared surface photometry of the bar and spiral structure. Self-gravitation of the gas is not taken into account in our modeling. A pure bar perturbed model is unable to reproduce the observations. It was found necessary to add a weak spiral potential to the perturbation, thus suggesting the presence of massive spiral arms in NGC 1300. We find two models, differing mainly in pattern speed, which are able to reproduce the essentials of NGC 1300. The high pattern speed model has {OMEGA}_p_=20km/s/kpc, corresponding to a corotation radius at R_CR_~104"=1.3R_bar_. Furthermore, the adopted rotation curve for this model supports one ILR at R_ILR_~26" and an OLR at R_OLR_~188". The low pattern speed model has {OMEGA}_p_=12km/s/kpc, corresponding to a corotation radius at R_ CR_~190"=2.4R_bar_. The adopted rotation curve for this model, which differs from the fast pattern speed model, supports one ILR at R_ILR_~25" and an OLR at R_OLR_~305". Morphological features, like spiral arms and offset dust lanes, are basically reproduced by both models. They are driven by orbit crowding effects across various resonances, leading to density enhancements. The general velocity structure, as described by HI data and optical long slit measurements, is fairly consistent with the model velocities.
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.
A subject-independent pattern-based Brain-Computer Interface
Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos, Cristián; Zamorano, Francisco; Aboitiz, Francisco; Birbaumer, Niels; Ruiz, Sergio
2015-01-01
While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders. PMID:26539089
NASA Astrophysics Data System (ADS)
Eliazar, Iddo
2017-09-01
This paper presents a general stochastic model for procrastination with respect to a deadline. The model establishes a universal procrastination pattern that follows an inverse power-law: if the time remaining to the deadline is r then the response is 1/rε , where ɛ is a positive exponent. The model further establishes that the exponent value ε =1 , which yields the harmonic response 1/r , stands out as special and distinguishable. The theoretical results of the model are shown to be in perfect accord with recent empirical findings.
Chimera patterns in the Kuramoto-Battogtokh model
NASA Astrophysics Data System (ADS)
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.
Using qualitative studies to improve the usability of an EMR.
Rose, Alan F; Schnipper, Jeffrey L; Park, Elyse R; Poon, Eric G; Li, Qi; Middleton, Blackford
2005-02-01
The adoption of electronic medical records (EMRs) and user satisfaction are closely associated with the system's usability. To improve the usability of a results management module of a widely deployed web-based EMR, we conducted two qualitative studies that included multiple focus group and field study sessions. Qualitative research can help focus attention on user tasks and goals and identify patterns of care that can be visualized through task modeling exercises. Findings from both studies raised issues with the amount and organization of information in the display, interference with workflow patterns of primary care physicians, and the availability of visual cues and feedback. We used the findings of these studies to recommend design changes to the user interface of the results management module.
Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms
NASA Astrophysics Data System (ADS)
Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.
2017-12-01
Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Strike-Slip Fault Patterns on Europa: Obliquity or Polar Wander?
NASA Technical Reports Server (NTRS)
Rhoden, Alyssa Rose; Hurford, Terry A.; Manga, Michael
2011-01-01
Variations in diurnal tidal stress due to Europa's eccentric orbit have been considered as the driver of strike-slip motion along pre-existing faults, but obliquity and physical libration have not been taken into account. The first objective of this work is to examine the effects of obliquity on the predicted global pattern of fault slip directions based on a tidal-tectonic formation model. Our second objective is to test the hypothesis that incorporating obliquity can reconcile theory and observations without requiring polar wander, which was previously invoked to explain the mismatch found between the slip directions of 192 faults on Europa and the global pattern predicted using the eccentricity-only model. We compute predictions for individual, observed faults at their current latitude, longitude, and azimuth with four different tidal models: eccentricity only, eccentricity plus obliquity, eccentricity plus physical libration, and a combination of all three effects. We then determine whether longitude migration, presumably due to non-synchronous rotation, is indicated in observed faults by repeating the comparisons with and without obliquity, this time also allowing longitude translation. We find that a tidal model including an obliquity of 1.2?, along with longitude migration, can predict the slip directions of all observed features in the survey. However, all but four faults can be fit with only 1? of obliquity so the value we find may represent the maximum departure from a lower time-averaged obliquity value. Adding physical libration to the obliquity model improves the accuracy of predictions at the current locations of the faults, but fails to predict the slip directions of six faults and requires additional degrees of freedom. The obliquity model with longitude migration is therefore our preferred model. Although the polar wander interpretation cannot be ruled out from these results alone, the obliquity model accounts for all observations with a value consistent with theoretical expectations and cycloid modeling.
Boumans, Iris J M M; de Boer, Imke J M; Hofstede, Gert Jan; Bokkers, Eddie A M
2018-07-01
Domesticated pigs, Sus scrofa, vary considerably in feeding, social interaction and growth patterns. This variation originates partly from genetic variation that affects physiological factors and partly from behavioural strategies (avoid or approach) in competitive food resource situations. Currently, it is unknown how variation in physiological factors and in behavioural strategies among animals contributes to variation in feeding, social interaction and growth patterns in animals. The aim of this study was to unravel causation of variation in these patterns among pigs. We used an agent-based model to explore the effects of physiological factors and behavioural strategies in pigs on variation in feeding, social interaction and growth patterns. Model results show that variation in feeding, social interaction and growth patterns are caused partly by chance, such as time effects and coincidence of conflicts. Furthermore, results show that seemingly contradictory empirical findings in literature can be explained by variation in pig characteristics (i.e. growth potential, positive feedback, dominance, and coping style). Growth potential mainly affected feeding and growth patterns, whereas positive feedback, dominance and coping style affected feeding patterns, social interaction patterns, as well as growth patterns. Variation in behavioural strategies among pigs can reduce aggression at group level, but also make some pigs more susceptible to social constraints inhibiting them from feeding when they want to, especially low-ranking pigs and pigs with a passive coping style. Variation in feeding patterns, such as feeding rate or meal frequency, can indicate social constraints. Feeding patterns, however, can say something different about social constraints at group versus individual level. A combination of feeding patterns, such as a decreased feed intake, an increased feeding rate, and an increased meal frequency might, therefore, be needed to measure social constraints at individual level. Copyright © 2018 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Weisburd, Stefi
1986-01-01
Reviews current ideas and research findings related to the flow patterns of mantle rocks. Highlights the components of the two-layer convection and whole-mantle models of mantle flow. Proposes that mantle flow is the key to understanding how the earth has cooled and chemically evolved. (ML)
Li, Jun; Tibshirani, Robert
2015-01-01
We discuss the identification of features that are associated with an outcome in RNA-Sequencing (RNA-Seq) and other sequencing-based comparative genomic experiments. RNA-Seq data takes the form of counts, so models based on the normal distribution are generally unsuitable. The problem is especially challenging because different sequencing experiments may generate quite different total numbers of reads, or ‘sequencing depths’. Existing methods for this problem are based on Poisson or negative binomial models: they are useful but can be heavily influenced by ‘outliers’ in the data. We introduce a simple, nonparametric method with resampling to account for the different sequencing depths. The new method is more robust than parametric methods. It can be applied to data with quantitative, survival, two-class or multiple-class outcomes. We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. PMID:22127579
Branching pattern in natural drainage network
NASA Astrophysics Data System (ADS)
Hooshyar, M.; Singh, A.; Wang, D.
2017-12-01
The formation and growth of river channels and their network evolution are governed by the erosional and depositional processes operating on the landscape due to movement of water. The branching structure of drainage network is an important feature related to the network topology and contain valuable information about the forming mechanisms of the landscape. We studied the branching patterns in natural drainage networks, extracted from 1 m Digital Elevation Models (DEMs) of 120 catchments with minimal human impacts across the United States. We showed that the junction angles have two distinct modes an the observed modes are physically explained as the optimal angles that result in minimum energy dissipation and are linked to the exponent characterizing slope-area curve. Our findings suggest that the flow regimes, debris-flow dominated or fluvial, have distinct characteristic angles which are functions of the scaling exponent of the slope-area curve. These findings enable us to understand the geomorphological signature of hydrological processes on drainage networks and develop more refined landscape evolution models.
Nurse staffing patterns and hospital efficiency in the United States.
Bloom, J R; Alexander, J A; Nuchols, B A
1997-01-01
The objective of this exploratory study was to assess the effects of four nurse staffing patterns on the efficiency of patient care delivery in the hospital: registered nurses (RNs) from temporary agencies; part-time career RNs; RN rich skill mix; and organizationally experienced RNs. Using Transaction Cost Analysis, four regression models were specified to consider the effect of these staffing plans on personnel and benefit costs and on non-personnel operating costs. A number of additional variables were also included in the models to control for the effect of other organization and environmental determinants of hospital costs. Use of career part-time RNs and experienced staff reduced both personnel and benefit costs, as well as total non-personnel operating costs, while the use of temporary agencies for RNs increased non-personnel operating costs. An RN rich skill mix was not related to either measure of hospital costs. These findings provide partial support of the theory. Implications of our findings for future research on hospital management are discussed.
Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus
Jehee, Janneke F. M.; Ballard, Dana H.
2009-01-01
Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain. PMID:19412529
NASA Astrophysics Data System (ADS)
Solomon, Susan; Ivy, Diane; Gupta, Mukund; Bandoro, Justin; Santer, Benjamin; Fu, Qiang; Lin, Pu; Garcia, Rolando R.; Kinnison, Doug; Mills, Michael
2017-08-01
Observed and modeled patterns of lower stratospheric seasonal trends in Antarctic ozone and temperature in the late 20th (1979-2000) and the early 21st (2000-2014) centuries are compared. Patterns of pre-2000 observed Antarctic ozone decreases and stratospheric cooling as a function of month and pressure are followed by opposite-signed (i.e., "mirrored") patterns of ozone increases and warming post-2000. An interactive chemistry-climate model forced by changes in anthropogenic ozone depleting substances produces broadly similar mirrored features. Statistical analysis of unforced model simulations (from long-term model control simulations of a few centuries up to 1000 years) suggests that internal and solar natural variability alone is unable to account for the pattern of observed ozone trend mirroring, implying that forcing is the dominant driver of this behavior. Radiative calculations indicate that ozone increases have contributed to Antarctic warming of the lower stratosphere over 2000-2014, but dynamical changes that are likely due to internal variability over this relatively short period also appear to be important. Overall, the results support the recent finding that the healing of the Antarctic ozone hole is underway and that coupling between dynamics, chemistry, and radiation is important for a full understanding of the causes of observed stratospheric temperature and ozone changes.
The unusual suspect: Land use is a key predictor of biodiversity patterns in the Iberian Peninsula
NASA Astrophysics Data System (ADS)
Martins, Inês Santos; Proença, Vânia; Pereira, Henrique Miguel
2014-11-01
Although land use change is a key driver of biodiversity change, related variables such as habitat area and habitat heterogeneity are seldom considered in modeling approaches at larger extents. To address this knowledge gap we tested the contribution of land use related variables to models describing richness patterns of amphibians, reptiles and passerines in the Iberian Peninsula. We analyzed the relationship between species richness and habitat heterogeneity at two spatial resolutions (i.e., 10 km × 10 km and 50 km × 50 km). Using both ordinary least square and simultaneous autoregressive models, we assessed the relative importance of land use variables, climate variables and topographic variables. We also compare the species-area relationship with a multi-habitat model, the countryside species-area relationship, to assess the role of the area of different types of habitats on species diversity across scales. The association between habitat heterogeneity and species richness varied with the taxa and spatial resolution. A positive relationship was detected for all taxa at a grain size of 10 km × 10 km, but only passerines responded at a grain size of 50 km × 50 km. Species richness patterns were well described by abiotic predictors, but habitat predictors also explained a considerable portion of the variation. Moreover, species richness patterns were better described by a multi-habitat species-area model, incorporating land use variables, than by the classic power model, which only includes area as the single explanatory variable. Our results suggest that the role of land use in shaping species richness patterns goes beyond the local scale and persists at larger spatial scales. These findings call for the need of integrating land use variables in models designed to assess species richness response to large scale environmental changes.
Pattern formation for NO+N H3 on Pt(100): Two-dimensional numerical results
NASA Astrophysics Data System (ADS)
Uecker, Hannes
2005-01-01
The Lombardo-Fink-Imbihl model of the NO+NH3 reaction on a Pt(100) surface consists of seven coupled ordinary differential equations (ODE) and shows stable relaxation oscillations with sharp transitions in the relevant temperature range. Here we study numerically the effect of coupling of these oscillators by surface diffusion in two dimensions. We find different types of patterns, in particular phase clusters and standing waves. In models of related surface reactions such clustered solutions are known to exist only under a global coupling through the gas phase. This global coupling is replaced here by relatively fast diffusion of two variables which are kinetically slaved in the ODE. We also compare our simulations with experimental results and discuss some shortcomings of the model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luo, Xi; Feng, Xueshang; Potgieter, Marius S.
Based on the reduced diffusion mechanism for producing Forbush decreases (Fds) in the heliosphere, we constructed a three-dimensional (3D) diffusion barrier, and by incorporating it into a stochastic differential equation (SDE) based time-dependent, cosmic-ray transport model, a 3D numerical model for simulating Fds is built and applied to a period of relatively quiet solar activity. This SDE model generally corroborates previous Fd simulations concerning the effects of the solar magnetic polarity, the tilt angle of the heliospheric current sheet (HCS), and cosmic-ray particle energy. Because the modulation processes in this 3D model are multi-directional, the barrier’s geometrical features affect themore » intensity profiles of Fds differently. We find that both the latitudinal and longitudinal extent of the barrier have relatively fewer effects on these profiles than its radial extent and the level of decreased diffusion inside the disturbance. We find, with the 3D approach, that the HCS rotational motion causes the relative location from the observation point to the HCS to vary, so that a periodic pattern appears in the cosmic-ray intensity at the observing location. Correspondingly, the magnitude and recovery time of an Fd change, and the recovering intensity profile contains oscillation as well. Investigating the Fd magnitude variation with heliocentric radial distance, we find that the magnitude decreases overall and, additionally, that the Fd magnitude exhibits an oscillating pattern as the radial distance increases, which coincides well with the wavy profile of the HCS under quiet solar modulation conditions.« less
Mueller, Christina J; White, Corey N; Kuchinke, Lars
2017-11-27
The goal of this study was to replicate findings of diffusion model parameters capturing emotion effects in a lexical decision task and investigating whether these findings extend to other tasks of implicit emotion processing. Additionally, we were interested in the stability of diffusion model parameters across emotional stimuli and tasks for individual subjects. Responses to words in a lexical decision task were compared with responses to faces in a gender categorization task for stimuli of the emotion categories: happy, neutral and fear. Main effects of emotion as well as stability of emerging response style patterns as evident in diffusion model parameters across these tasks were analyzed. Based on earlier findings, drift rates were assumed to be more similar in response to stimuli of the same emotion category compared to stimuli of a different emotion category. Results showed that emotion effects of the tasks differed with a processing advantage for happy followed by neutral and fear-related words in the lexical decision task and a processing advantage for neutral followed by happy and fearful faces in the gender categorization task. Both emotion effects were captured in estimated drift rate parameters-and in case of the lexical decision task also in the non-decision time parameters. A principal component analysis showed that contrary to our hypothesis drift rates were more similar within a specific task context than within a specific emotion category. Individual response patterns of subjects across tasks were evident in significant correlations regarding diffusion model parameters including response styles, non-decision times and information accumulation.
NASA Astrophysics Data System (ADS)
Miller, S. M.; Andrews, A. E.; Benmergui, J. S.; Commane, R.; Dlugokencky, E. J.; Janssens-Maenhout, G.; Melton, J. R.; Michalak, A. M.; Sweeney, C.; Worthy, D. E. J.
2015-12-01
Existing estimates of methane fluxes from wetlands differ in both magnitude and distribution across North America. We discuss seven different bottom-up methane estimates in the context of atmospheric methane data collected across the US and Canada. In the first component of this study, we explore whether the observation network can even detect a methane pattern from wetlands. We find that the observation network can identify a methane pattern from Canadian wetlands but not reliably from US wetlands. Over Canada, the network can even identify spatial patterns at multi-provence scales. Over the US, by contrast, anthropogenic emissions and modeling errors obscure atmospheric patterns from wetland fluxes. In the second component of the study, we then use these observations to reconcile disagreements in the magnitude, seasonal cycle, and spatial distribution of existing estimates. Most existing estimates predict fluxes that are too large with a seasonal cycle that is too narrow. A model known as LPJ-Bern has a spatial distribution most consistent with atmospheric observations. By contrast, a spatially-constant model outperforms the distribution of most existing flux estimates across Canada. The results presented here provide several pathways to reduce disagreements among existing wetland flux estimates across North America.
NASA Astrophysics Data System (ADS)
Avelino, P. P.; Bazeia, D.; Losano, L.; Menezes, J.; de Oliveira, B. F.
2018-02-01
Stochastic simulations of cyclic three-species spatial predator-prey models are usually performed in square lattices with nearest-neighbour interactions starting from random initial conditions. In this letter we describe the results of off-lattice Lotka-Volterra stochastic simulations, showing that the emergence of spiral patterns does occur for sufficiently high values of the (conserved) total density of individuals. We also investigate the dynamics in our simulations, finding an empirical relation characterizing the dependence of the characteristic peak frequency and amplitude on the total density. Finally, we study the impact of the total density on the extinction probability, showing how a low population density may jeopardize biodiversity.
Regular Patterns in Cerebellar Purkinje Cell Simple Spike Trains
Shin, Soon-Lim; Hoebeek, Freek E.; Schonewille, Martijn; De Zeeuw, Chris I.; Aertsen, Ad; De Schutter, Erik
2007-01-01
Background Cerebellar Purkinje cells (PC) in vivo are commonly reported to generate irregular spike trains, documented by high coefficients of variation of interspike-intervals (ISI). In strong contrast, they fire very regularly in the in vitro slice preparation. We studied the nature of this difference in firing properties by focusing on short-term variability and its dependence on behavioral state. Methodology/Principal Findings Using an analysis based on CV2 values, we could isolate precise regular spiking patterns, lasting up to hundreds of milliseconds, in PC simple spike trains recorded in both anesthetized and awake rodents. Regular spike patterns, defined by low variability of successive ISIs, comprised over half of the spikes, showed a wide range of mean ISIs, and were affected by behavioral state and tactile stimulation. Interestingly, regular patterns often coincided in nearby Purkinje cells without precise synchronization of individual spikes. Regular patterns exclusively appeared during the up state of the PC membrane potential, while single ISIs occurred both during up and down states. Possible functional consequences of regular spike patterns were investigated by modeling the synaptic conductance in neurons of the deep cerebellar nuclei (DCN). Simulations showed that these regular patterns caused epochs of relatively constant synaptic conductance in DCN neurons. Conclusions/Significance Our findings indicate that the apparent irregularity in cerebellar PC simple spike trains in vivo is most likely caused by mixing of different regular spike patterns, separated by single long intervals, over time. We propose that PCs may signal information, at least in part, in regular spike patterns to downstream DCN neurons. PMID:17534435
Abundance patterns of evolved stars with Hipparcos parallaxes and ages based on the APOGEE data base
NASA Astrophysics Data System (ADS)
Jia, Y. P.; Chen, Y. Q.; Zhao, G.; Bari, M. A.; Zhao, J. K.; Tan, K. F.
2018-01-01
We investigate the abundance patterns for four groups of stars at evolutionary phases from sub-giant to red clump (RC) and trace the chemical evolution of the disc by taking 21 individual elemental abundances from APOGEE and ages from evolutionary models with the aid of Hipparcos distances. We find that the abundances of six elements (Si, S, K, Ca, Mn and Ni) are similar from the sub-giant phase to the RC phase. In particular, we find that a group of stars with low [C/N] ratios, mainly from the second sequence of RC stars, show that there is a difference in the transfer efficiency of the C-N-O cycle between the main and the secondary RC sequences. We also compare the abundance patterns of C-N, Mg-Al and Na-O with giant stars in globular clusters from APOGEE and find that field stars follow similar patterns as M107, a metal-rich globular cluster with [M/H] ∼- 1.0, which shows that the self-enrichment mechanism represented by strong C-N, Mg-Al and Na-O anti-correlations may not be important as the metallicity reaches [M/H] > -1.0 dex. Based on the abundances of above-mentioned six elements and [Fe/H], we investigate age versus abundance relations and find some old super-metal-rich stars in our sample. Their properties of old age and being rich in metal are evidence for stellar migration. The age versus metallicity relations in low-[α/M] bins show unexpectedly positive slopes. We propose that the fresh metal-poor gas infalling on to the Galactic disc may be the precursor for this unexpected finding.
Bhatt, Jay P.; Manish, Kumar; Pandit, Maharaj K.
2012-01-01
Background Studying diversity and distribution patterns of species along elevational gradients and understanding drivers behind these patterns is central to macroecology and conservation biology. A number of studies on biogeographic gradients are available for terrestrial ecosystems, but freshwater ecosystems remain largely neglected. In particular, we know very little about the species richness gradients and their drivers in the Himalaya, a global biodiversity hotspot. Methodology/Principal Findings We collated taxonomic and distribution data of fish species from 16 freshwater Himalayan rivers and carried out empirical studies on environmental drivers and fish diversity and distribution in the Teesta river (Eastern Himalaya). We examined patterns of fish species richness along the Himalayan elevational gradients (50–3800 m) and sought to understand the drivers behind the emerging patterns. We used generalized linear models (GLM) and generalized additive models (GAM) to examine the richness patterns; GLM was used to investigate relationship between fish species richness and various environmental variables. Regression modelling involved stepwise procedures, including elimination of collinear variables, best model selection, based on the least Akaike’s information criterion (AIC) and the highest percentage of deviance explained (D2). This maiden study on the Himalayan fishes revealed that total and non-endemic fish species richness monotonously decrease with increasing elevation, while endemics peaked around mid elevations (700–1500 m). The best explanatory model (synthetic model) indicated that water discharge is the best predictor of fish species richness patterns in the Himalayan rivers. Conclusions/Significance This study, carried out along one of the longest bioclimatic elevation gradients of the world, lends support to Rapoport’s elevational rule as opposed to mid domain effect hypothesis. We propose a species-discharge model and contradict species-area model in predicting fish species richness. We suggest that drivers of richness gradients in terrestrial and aquatic ecosystems are likely to be different. These studies are crucial in context of the impacts of unprecedented on-going river regulation on fish diversity and distribution in the Himalaya. PMID:23029444
Pattern sampling for etch model calibration
NASA Astrophysics Data System (ADS)
Weisbuch, François; Lutich, Andrey; Schatz, Jirka
2017-06-01
Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels as well as the choice of calibration patterns is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels -"internal, external, curvature, Gaussian, z_profile" - designed to capture the finest details of the resist contours and represent precisely any etch bias. By evaluating the etch kernels on various structures it is possible to map their etch signatures in a multi-dimensional space and analyze them to find an optimal sampling of structures to train an etch model. The method was specifically applied to a contact layer containing many different geometries and was used to successfully select appropriate calibration structures. The proposed kernels evaluated on these structures were combined to train an etch model significantly better than the standard one. We also illustrate the usage of the specific kernel "z_profile" which adds a third dimension to the description of the resist profile.
Automated real time constant-specificity surveillance for disease outbreaks.
Wieland, Shannon C; Brownstein, John S; Berger, Bonnie; Mandl, Kenneth D
2007-06-13
For real time surveillance, detection of abnormal disease patterns is based on a difference between patterns observed, and those predicted by models of historical data. The usefulness of outbreak detection strategies depends on their specificity; the false alarm rate affects the interpretation of alarms. We evaluate the specificity of five traditional models: autoregressive, Serfling, trimmed seasonal, wavelet-based, and generalized linear. We apply each to 12 years of emergency department visits for respiratory infection syndromes at a pediatric hospital, finding that the specificity of the five models was almost always a non-constant function of the day of the week, month, and year of the study (p < 0.05). We develop an outbreak detection method, called the expectation-variance model, based on generalized additive modeling to achieve a constant specificity by accounting for not only the expected number of visits, but also the variance of the number of visits. The expectation-variance model achieves constant specificity on all three time scales, as well as earlier detection and improved sensitivity compared to traditional methods in most circumstances. Modeling the variance of visit patterns enables real-time detection with known, constant specificity at all times. With constant specificity, public health practitioners can better interpret the alarms and better evaluate the cost-effectiveness of surveillance systems.
A Bayesian Joint Model of Menstrual Cycle Length and Fecundity
Lum, Kirsten J.; Sundaram, Rajeshwari; Louis, Germaine M. Buck; Louis, Thomas A.
2015-01-01
Summary Menstrual cycle length (MCL) has been shown to play an important role in couple fecundity, which is the biologic capacity for reproduction irrespective of pregnancy intentions. However, a comprehensive assessment of its role requires a fecundity model that accounts for male and female attributes and the couple’s intercourse pattern relative to the ovulation day. To this end, we employ a Bayesian joint model for MCL and pregnancy. MCLs follow a scale multiplied (accelerated) mixture model with Gaussian and Gumbel components; the pregnancy model includes MCL as a covariate and computes the cycle-specific probability of pregnancy in a menstrual cycle conditional on the pattern of intercourse and no previous fertilization. Day-specific fertilization probability is modeled using natural, cubic splines. We analyze data from the Longitudinal Investigation of Fertility and the Environment Study (the LIFE Study), a couple based prospective pregnancy study, and find a statistically significant quadratic relation between fecundity and menstrual cycle length, after adjustment for intercourse pattern and other attributes, including male semen quality, both partner’s age, and active smoking status (determined by baseline cotinine level 100ng/mL). We compare results to those produced by a more basic model and show the advantages of a more comprehensive approach. PMID:26295923
Latash, M L; Gottlieb, G L
1991-09-01
The model for isotonic movements introduced in the preceding article in this issue is used to account for isometric contractions. Isotonic movements and isometric contractions are analyzed as consequences of one motor program acting under different peripheral conditions. Differences in isotonic and isometric EMG patterns are analyzed theoretically. Computer simulation of the EMG patterns was performed both with and without the inclusion of possible effects of reciprocal inhibition. A series of experiments was performed to test the model. The subjects made fast isotonic movements that were unexpectedly blocked at the very beginning in some of the trials. The observed differences in the EMG patterns between blocked and unblocked trials corresponded to the model's predictions. The results suggest that these differences are due to the action of a tonic stretch reflex rather than to preprogrammed reactions. The experimental and simulation findings, and also the data from the literature, are discussed in the framework of the model and the dual-strategy hypothesis. They support the hypothesis that the motor control system uses one of a few standardized subprograms, specifying a small number of parameters to match a specific task.
Effect of the mitral valve on diastolic flow patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seo, Jung Hee; Vedula, Vijay; Mittal, Rajat, E-mail: mittal@jhu.edu
2014-12-15
The leaflets of the mitral valve interact with the mitral jet and significantly impact diastolic flow patterns, but the effect of mitral valve morphology and kinematics on diastolic flow and its implications for left ventricular function have not been clearly delineated. In the present study, we employ computational hemodynamic simulations to understand the effect of mitral valve leaflets on diastolic flow. A computational model of the left ventricle is constructed based on a high-resolution contrast computed-tomography scan, and a physiological inspired model of the mitral valve leaflets is synthesized from morphological and echocardiographic data. Simulations are performed with a diodemore » type valve model as well as the physiological mitral valve model in order to delineate the effect of mitral-valve leaflets on the intraventricular flow. The study suggests that a normal physiological mitral valve promotes the formation of a circulatory (or “looped”) flow pattern in the ventricle. The mitral valve leaflets also increase the strength of the apical flow, thereby enhancing apical washout and mixing of ventricular blood. The implications of these findings on ventricular function as well as ventricular flow models are discussed.« less
NASA Astrophysics Data System (ADS)
Dong, Haibin
2017-04-01
In this paper, a model is established to find the optimal shape, size and merging pattern of the toll plaza. The main work is how to take the aspects such as the accident prevention, throughput and cost into consideration to make the model of the toll plaza optimal. By analyzing the match of the number of tollbooths (B) and travel lanes (L) considering safety and cost, the optimal toll plaza model is established when the traffic flow is given.
Lerner, Itamar; Shriki, Oren
2014-01-01
For the last four decades, semantic priming—the facilitation in recognition of a target word when it follows the presentation of a semantically related prime word—has been a central topic in research of human cognitive processing. Studies have drawn a complex picture of findings which demonstrated the sensitivity of this priming effect to a unique combination of variables, including, but not limited to, the type of relatedness between primes and targets, the prime-target Stimulus Onset Asynchrony (SOA), the relatedness proportion (RP) in the stimuli list and the specific task subjects are required to perform. Automatic processes depending on the activation patterns of semantic representations in memory and controlled strategies adapted by individuals when attempting to maximize their recognition performance have both been implicated in contributing to the results. Lately, we have published a new model of semantic priming that addresses the majority of these findings within one conceptual framework. In our model, semantic memory is depicted as an attractor neural network in which stochastic transitions from one stored pattern to another are continually taking place due to synaptic depression mechanisms. We have shown how such transitions, in combination with a reinforcement-learning rule that adjusts their pace, resemble the classic automatic and controlled processes involved in semantic priming and account for a great number of the findings in the literature. Here, we review the core findings of our model and present new simulations that show how similar principles of parameter-adjustments could account for additional data not addressed in our previous studies, such as the relation between expectancy and inhibition in priming, target frequency and target degradation effects. Finally, we describe two human experiments that validate several key predictions of the model. PMID:24795670
Simple Rules Govern the Patterns of Arctic Sea Ice Melt Ponds
NASA Astrophysics Data System (ADS)
Popović, Predrag; Cael, B. B.; Silber, Mary; Abbot, Dorian S.
2018-04-01
Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverage fraction, are chosen by comparing, between the model and the aerial photographs of the ponds, two correlation functions which determine the typical pond size and their connectedness. Using these parameters, the void model robustly reproduces the ponds' area-perimeter and area-abundance relationships over more than 6 orders of magnitude. By analyzing the correlation functions of ponds on several dates, we also find that the pond scale and the connectedness are surprisingly constant across different years and ice types. Moreover, we find that ponds resemble percolation clusters near the percolation threshold. These results demonstrate that the geometry and abundance of Arctic melt ponds can be simply described, which can be exploited in future models of Arctic melt ponds that would improve predictions of the response of sea ice to Arctic warming.
Simple Rules Govern the Patterns of Arctic Sea Ice Melt Ponds.
Popović, Predrag; Cael, B B; Silber, Mary; Abbot, Dorian S
2018-04-06
Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverage fraction, are chosen by comparing, between the model and the aerial photographs of the ponds, two correlation functions which determine the typical pond size and their connectedness. Using these parameters, the void model robustly reproduces the ponds' area-perimeter and area-abundance relationships over more than 6 orders of magnitude. By analyzing the correlation functions of ponds on several dates, we also find that the pond scale and the connectedness are surprisingly constant across different years and ice types. Moreover, we find that ponds resemble percolation clusters near the percolation threshold. These results demonstrate that the geometry and abundance of Arctic melt ponds can be simply described, which can be exploited in future models of Arctic melt ponds that would improve predictions of the response of sea ice to Arctic warming.
Modeling the Effects of Perceptual Load: Saliency, Competitive Interactions, and Top-Down Biases
Neokleous, Kleanthis; Shimi, Andria; Avraamides, Marios N.
2016-01-01
A computational model of visual selective attention has been implemented to account for experimental findings on the Perceptual Load Theory (PLT) of attention. The model was designed based on existing neurophysiological findings on attentional processes with the objective to offer an explicit and biologically plausible formulation of PLT. Simulation results verified that the proposed model is capable of capturing the basic pattern of results that support the PLT as well as findings that are considered contradictory to the theory. Importantly, the model is able to reproduce the behavioral results from a dilution experiment, providing thus a way to reconcile PLT with the competing Dilution account. Overall, the model presents a novel account for explaining PLT effects on the basis of the low-level competitive interactions among neurons that represent visual input and the top-down signals that modulate neural activity. The implications of the model concerning the debate on the locus of selective attention as well as the origins of distractor interference in visual displays of varying load are discussed. PMID:26858668
Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data
Wu, Lun; Zhi, Ye; Sui, Zhengwei; Liu, Yu
2014-01-01
Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data. PMID:24824892
The predictability of consumer visitation patterns
NASA Astrophysics Data System (ADS)
Krumme, Coco; Llorente, Alejandro; Cebrian, Manuel; Pentland, Alex ("Sandy"); Moro, Esteban
2013-04-01
We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. Yet while aggregate behavior is largely predictable, the interleaving of shopping events introduces important stochastic elements at short time scales. These short- and long-scale patterns suggest a theoretical upper bound on predictability, and describe the accuracy of a Markov model in predicting a person's next location. We incorporate population-level transition probabilities in the predictive models, and find that in many cases these improve accuracy. While our results point to the elusiveness of precise predictions about where a person will go next, they suggest the existence, at large time-scales, of regularities across the population.
The predictability of consumer visitation patterns
Krumme, Coco; Llorente, Alejandro; Cebrian, Manuel; Pentland, Alex ("Sandy"); Moro, Esteban
2013-01-01
We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. Yet while aggregate behavior is largely predictable, the interleaving of shopping events introduces important stochastic elements at short time scales. These short- and long-scale patterns suggest a theoretical upper bound on predictability, and describe the accuracy of a Markov model in predicting a person's next location. We incorporate population-level transition probabilities in the predictive models, and find that in many cases these improve accuracy. While our results point to the elusiveness of precise predictions about where a person will go next, they suggest the existence, at large time-scales, of regularities across the population. PMID:23598917
ERIC Educational Resources Information Center
Stewart, Sunita Mahtani; Bond, Michael Harris; Deeds, Osvelia; Chung, Siu Fung
1999-01-01
Investigated value priorities and autonomy expectations in 59 pairs of Caucasian and 66 pairs of Asian teenagers and their mothers in Hong Kong. Findings support models that predict persistent family interdependence despite adoption of many individualist values in modernizing collectivist cultures. (SLD)
Process Mining Online Assessment Data
ERIC Educational Resources Information Center
Pechenizkiy, Mykola; Trcka, Nikola; Vasilyeva, Ekaterina; van der Aalst, Wil; De Bra, Paul
2009-01-01
Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated through the use of different information systems. The results of data mining can be used for getting a better understanding of the underlying educational processes, for…
Between-Site Differences in the Scale of Dispersal and Gene Flow in Red Oak
Moran, Emily V.; Clark, James S.
2012-01-01
Background Nut-bearing trees, including oaks (Quercus spp.), are considered to be highly dispersal limited, leading to concerns about their ability to colonize new sites or migrate in response to climate change. However, estimating seed dispersal is challenging in species that are secondarily dispersed by animals, and differences in disperser abundance or behavior could lead to large spatio-temporal variation in dispersal ability. Parentage and dispersal analyses combining genetic and ecological data provide accurate estimates of current dispersal, while spatial genetic structure (SGS) can shed light on past patterns of dispersal and establishment. Methodology and Principal Findings In this study, we estimate seed and pollen dispersal and parentage for two mixed-species red oak populations using a hierarchical Bayesian approach. We compare these results to those of a genetic ML parentage model. We also test whether observed patterns of SGS in three size cohorts are consistent with known site history and current dispersal patterns. We find that, while pollen dispersal is extensive at both sites, the scale of seed dispersal differs substantially. Parentage results differ between models due to additional data included in Bayesian model and differing genotyping error assumptions, but both indicate between-site dispersal differences. Patterns of SGS in large adults, small adults, and seedlings are consistent with known site history (farmed vs. selectively harvested), and with long-term differences in seed dispersal. This difference is consistent with predator/disperser satiation due to higher acorn production at the low-dispersal site. While this site-to-site variation results in substantial differences in asymptotic spread rates, dispersal for both sites is substantially lower than required to track latitudinal temperature shifts. Conclusions Animal-dispersed trees can exhibit considerable spatial variation in seed dispersal, although patterns may be surprisingly constant over time. However, even under favorable conditions, migration in heavy-seeded species is likely to lag contemporary climate change. PMID:22563504
Shaping Neuronal Network Activity by Presynaptic Mechanisms
Ashery, Uri
2015-01-01
Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048
Catchment heterogeneity controls emergent archetype concentration-discharge relationships
NASA Astrophysics Data System (ADS)
Musolff, A.; Fleckenstein, J. H.; Rao, P. S.; Jawitz, J. W.
2017-12-01
Relationships between in-stream dissolved solute concentrations (C) and discharge (Q) are often-used indicators of catchment-scale processes and their interference with human activities. Here we analyze observational C-Q relationships from 61 catchments and 8 different solutes across a wide range of land-uses and discharge regimes. This analysis is combined with a parsimonious stochastic modeling approach to test how C-Q relationships arise from spatial heterogeneity in catchment solute sources coupled with different timescales of biogeochemical reactions. The observational data exhibit archetypical dilution, enrichment, and constant C-Q patterns. Moreover, with land-use intensification we find decreasing C variability relative to Q variability (chemostatic export regime). Our model indicates that the dominant driver of emergent C-Q patterns was structured heterogeneity of solute sources implemented as correlation of source concentration to travel time. Regardless of the C-Q pattern, with decreasing source heterogeneity we consistently find lower variability in C than in Q and a dominance of chemostatic export regimes. Here, the variance in exported loads is determined primarily by variance of Q. We conclude that efforts to improve stream water quality and ecological integrity in intensely managed catchments should lead away from landscape homogenization by introducing structured source heterogeneity. References: Musolff, A., J. H. Fleckenstein, P. S. C. Rao, and J. W. Jawitz (2017), Emergent archetype patterns of coupled hydrologic and biogeochemical responses in catchments, Geophys. Res. Lett., 44(9), 4143-4151, doi: 10.1002/2017GL072630.
A GRAPH PARTITIONING APPROACH TO PREDICTING PATTERNS IN LATERAL INHIBITION SYSTEMS
RUFINO FERREIRA, ANA S.; ARCAK, MURAT
2017-01-01
We analyze spatial patterns on networks of cells where adjacent cells inhibit each other through contact signaling. We represent the network as a graph where each vertex represents the dynamics of identical individual cells and where graph edges represent cell-to-cell signaling. To predict steady-state patterns we find equitable partitions of the graph vertices and assign them into disjoint classes. We then use results from monotone systems theory to prove the existence of patterns that are structured in such a way that all the cells in the same class have the same final fate. To study the stability properties of these patterns, we rely on the graph partition to perform a block decomposition of the system. Then, to guarantee stability, we provide a small-gain type criterion that depends on the input-output properties of each cell in the reduced system. Finally, we discuss pattern formation in stochastic models. With the help of a modal decomposition we show that noise can enhance the parameter region where patterning occurs. PMID:29225552
NASA Astrophysics Data System (ADS)
Fattaruso, Laura A.; Cooke, Michele L.; Dorsey, Rebecca J.; Housen, Bernard A.
2016-12-01
Between 1.5 and 1.1 Ma, the southern San Andreas fault system underwent a major reorganization that included initiation of the San Jacinto fault zone and termination of slip on the extensional West Salton detachment fault. The southern San Andreas fault itself has also evolved since this time, with several shifts in activity among fault strands within San Gorgonio Pass. We use three-dimensional mechanical Boundary Element Method models to investigate the impact of these changes to the fault network on deformation patterns. A series of snapshot models of the succession of active fault geometries explore the role of fault interaction and tectonic loading in abandonment of the West Salton detachment fault, initiation of the San Jacinto fault zone, and shifts in activity of the San Andreas fault. Interpreted changes to uplift patterns are well matched by model results. These results support the idea that initiation and growth of the San Jacinto fault zone led to increased uplift rates in the San Gabriel Mountains and decreased uplift rates in the San Bernardino Mountains. Comparison of model results for vertical-axis rotation to data from paleomagnetic studies reveals a good match to local rotation patterns in the Mecca Hills and Borrego Badlands. We explore the mechanical efficiency at each step in the modeled fault evolution, and find an overall trend toward increased efficiency through time. Strain energy density patterns are used to identify regions of incipient faulting, and support the notion of north-to-south propagation of the San Jacinto fault during its initiation.
Friendship Group Composition and Juvenile Institutional Misconduct.
Reid, Shannon E
2017-02-01
The present study examines both the patterns of friendship networks and how these network characteristics relate to the risk factors of institutional misconduct for incarcerated youth. Using friendship networks collected from males incarcerated with California's Division of Juvenile Justice (DJJ), latent profile analysis was utilized to create homogeneous groups of friendship patterns based on alter attributes and network structure. The incarcerated youth provided 144 egocentric networks reporting 558 social network relationships. Latent profile analysis identified three network profiles: expected group (67%), new breed group (20%), and model citizen group (13%). The three network profiles were integrated into a multiple group analysis framework to examine the relative influence of individual-level risk factors on their rate of institutional misconduct. The analysis finds variation in predictors of institutional misconduct across profile types. These findings suggest that the close friendships of incarcerated youth are patterned across the individual characteristics of the youth's friends and that the friendship network can act as a moderator for individual risk factors for institutional misconduct.
Fractal scaling in bottlenose dolphin (Tursiops truncatus) echolocation: A case study
NASA Astrophysics Data System (ADS)
Perisho, Shaun T.; Kelty-Stephen, Damian G.; Hajnal, Alen; Houser, Dorian; Kuczaj, Stan A., II
2016-02-01
Fractal scaling patterns, which entail a power-law relationship between magnitude of fluctuations in a variable and the scale at which the variable is measured, have been found in many aspects of human behavior. These findings have led to advances in behavioral models (e.g. providing empirical support for cascade-driven theories of cognition) and have had practical medical applications (e.g. providing new methods for early diagnosis of medical conditions). In the present paper, fractal analysis is used to investigate whether similar fractal scaling patterns exist in inter-click interval and peak-peak amplitude measurements of bottlenose dolphin click trains. Several echolocation recordings taken from two male bottlenose dolphins were analyzed using Detrended Fluctuation Analysis and Higuchi's (1988) method for determination of fractal dimension. Both animals were found to exhibit fractal scaling patterns near what is consistent with persistent long range correlations. These findings suggest that recent advances in human cognition and medicine may have important parallel applications to echolocation as well.
A formal approach to the analysis of clinical computer-interpretable guideline modeling languages.
Grando, M Adela; Glasspool, David; Fox, John
2012-01-01
To develop proof strategies to formally study the expressiveness of workflow-based languages, and to investigate their applicability to clinical computer-interpretable guideline (CIG) modeling languages. We propose two strategies for studying the expressiveness of workflow-based languages based on a standard set of workflow patterns expressed as Petri nets (PNs) and notions of congruence and bisimilarity from process calculus. Proof that a PN-based pattern P can be expressed in a language L can be carried out semi-automatically. Proof that a language L cannot provide the behavior specified by a PNP requires proof by exhaustion based on analysis of cases and cannot be performed automatically. The proof strategies are generic but we exemplify their use with a particular CIG modeling language, PROforma. To illustrate the method we evaluate the expressiveness of PROforma against three standard workflow patterns and compare our results with a previous similar but informal comparison. We show that the two proof strategies are effective in evaluating a CIG modeling language against standard workflow patterns. We find that using the proposed formal techniques we obtain different results to a comparable previously published but less formal study. We discuss the utility of these analyses as the basis for principled extensions to CIG modeling languages. Additionally we explain how the same proof strategies can be reused to prove the satisfaction of patterns expressed in the declarative language CIGDec. The proof strategies we propose are useful tools for analysing the expressiveness of CIG modeling languages. This study provides good evidence of the benefits of applying formal methods of proof over semi-formal ones. Copyright © 2011 Elsevier B.V. All rights reserved.
Spatial pattern enhances ecosystem functioning in an African savanna.
Pringle, Robert M; Doak, Daniel F; Brody, Alison K; Jocqué, Rudy; Palmer, Todd M
2010-05-25
The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity). Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity): insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced). This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.
Quantifying patterns of research interest evolution
NASA Astrophysics Data System (ADS)
Jia, Tao; Wang, Dashun; Szymanski, Boleslaw
Changing and shifting research interest is an integral part of a scientific career. Despite extensive investigations of various factors that influence a scientist's choice of research topics, quantitative assessments of mechanisms that give rise to macroscopic patterns characterizing research interest evolution of individual scientists remain limited. Here we perform a large-scale analysis of extensive publication records, finding that research interest change follows a reproducible pattern characterized by an exponential distribution. We identify three fundamental features responsible for the observed exponential distribution, which arise from a subtle interplay between exploitation and exploration in research interest evolution. We develop a random walk based model, which adequately reproduces our empirical observations. Our study presents one of the first quantitative analyses of macroscopic patterns governing research interest change, documenting a high degree of regularity underlying scientific research and individual careers.
Robotic reactions: delay-induced patterns in autonomous vehicle systems.
Orosz, Gábor; Moehlis, Jeff; Bullo, Francesco
2010-02-01
Fundamental design principles are presented for vehicle systems governed by autonomous cruise control devices. By analyzing the corresponding delay differential equations, it is shown that for any car-following model short-wavelength oscillations can appear due to robotic reaction times, and that there are tradeoffs between the time delay and the control gains. The analytical findings are demonstrated on an optimal velocity model using numerical continuation and numerical simulation.
Robotic reactions: Delay-induced patterns in autonomous vehicle systems
NASA Astrophysics Data System (ADS)
Orosz, Gábor; Moehlis, Jeff; Bullo, Francesco
2010-02-01
Fundamental design principles are presented for vehicle systems governed by autonomous cruise control devices. By analyzing the corresponding delay differential equations, it is shown that for any car-following model short-wavelength oscillations can appear due to robotic reaction times, and that there are tradeoffs between the time delay and the control gains. The analytical findings are demonstrated on an optimal velocity model using numerical continuation and numerical simulation.
A Study of Early Afterdepolarizations in a Model for Human Ventricular Tissue
Vandersickel, Nele; Kazbanov, Ivan V.; Nuitermans, Anita; Weise, Louis D.; Pandit, Rahul; Panfilov, Alexander V.
2014-01-01
Sudden cardiac death is often caused by cardiac arrhythmias. Recently, special attention has been given to a certain arrhythmogenic condition, the long-QT syndrome, which occurs as a result of genetic mutations or drug toxicity. The underlying mechanisms of arrhythmias, caused by the long-QT syndrome, are not fully understood. However, arrhythmias are often connected to special excitations of cardiac cells, called early afterdepolarizations (EADs), which are depolarizations during the repolarizing phase of the action potential. So far, EADs have been studied mainly in isolated cardiac cells. However, the question on how EADs at the single-cell level can result in fibrillation at the tissue level, especially in human cell models, has not been widely studied yet. In this paper, we study wave patterns that result from single-cell EAD dynamics in a mathematical model for human ventricular cardiac tissue. We induce EADs by modeling experimental conditions which have been shown to evoke EADs at a single-cell level: by an increase of L-type Ca currents and a decrease of the delayed rectifier potassium currents. We show that, at the tissue level and depending on these parameters, three types of abnormal wave patterns emerge. We classify them into two types of spiral fibrillation and one type of oscillatory dynamics. Moreover, we find that the emergent wave patterns can be driven by calcium or sodium currents and we find phase waves in the oscillatory excitation regime. From our simulations we predict that arrhythmias caused by EADs can occur during normal wave propagation and do not require tissue heterogeneities. Experimental verification of our results is possible for experiments at the cell-culture level, where EADs can be induced by an increase of the L-type calcium conductance and by the application of I blockers, and the properties of the emergent patterns can be studied by optical mapping of the voltage and calcium. PMID:24427289
A dynamic game-theoretic model of parental care.
Mcnamara, J M; Székely, T; Webb, J N; Houston, A I
2000-08-21
We present a model in which members of a mated pair decide whether to care for their offspring or desert them. There is a breeding season of finite length during which it is possible to produce and raise several batches of offspring. On deserting its offspring, an individual can search for a new mate. The probability of finding a mate depends on the number of individuals of each sex that are searching, which in turn depends upon the previous care and desertion decisions of all population members. We find the evolutionarily stable pattern of care over the breeding season. The feedback between behaviour and mating opportunity can result in a pattern of stable oscillations between different forms of care over the breeding season. Oscillations can also arise because the best thing for an individual to do at a particular time in the season depends on future behaviour of all population members. In the baseline model, a pair splits up after a breeding attempt, even if they both care for the offspring. In a version of the model in which a pair stays together if they both care, the feedback between behaviour and mating opportunity can lead to more than one evolutionarily stable form of care. Copyright 2000 Academic Press.
Global neural pattern similarity as a common basis for categorization and recognition memory.
Davis, Tyler; Xue, Gui; Love, Bradley C; Preston, Alison R; Poldrack, Russell A
2014-05-28
Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. Copyright © 2014 the authors 0270-6474/14/347472-13$15.00/0.
A two-step patterning process increases the robustness of periodic patterning in the fly eye.
Gavish, Avishai; Barkai, Naama
2016-06-01
Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities ('noise') inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this 'noisy' environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations ('noise') in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.
Managing Human Resources in a Multinational Context
ERIC Educational Resources Information Center
Sumetzberger, Walter
2005-01-01
Purpose: To develop more sensitivity for different patterns of human resource management in multinational companies. Design/methodology/approach: Systemic approach; the concepts and models are based on the evaluation of consulting projects in the field of human resource management. Findings: A concept of four typical varieties of human resource…
Learning Management System with Prediction Model and Course-Content Recommendation Module
ERIC Educational Resources Information Center
Evale, Digna S.
2017-01-01
Aim/Purpose: This study is an attempt to enhance the existing learning management systems today through the integration of technology, particularly with educational data mining and recommendation systems. Background: It utilized five-year historical data to find patterns for predicting student performance in Java Programming to generate…
Do Non-Economic Quality of Life Factors Drive Immigration?
ERIC Educational Resources Information Center
Pacheco, Gail Anne; Rossouw, Stephanie; Lewer, Joshua
2013-01-01
This paper contributes to the immigration literature by generating two unique non-economic quality of life (QOL) indices and testing their role on recent migration patterns. Applying the generated QOL indices in conjunction with four independent welfare measures to an augmented gravity model of immigration, this paper finds an insignificant…
Elucidating the role of recovery experiences in the job demands-resources model.
Moreno-Jiménez, Bernardo; Rodríguez-Muñoz, Alfredo; Sanz-Vergel, Ana Isabel; Garrosa, Eva
2012-07-01
Based on the Job Demands-Resources (JD-R) model, the current study examined the moderating role of recovery experiences (i.e., psychological detachment from work, relaxation, mastery experiences, and control over leisure time) on the relationship between one job demand (i.e., role conflict) and work- and health-related outcomes. Results from our sample of 990 employees from Spain showed that psychological detachment from work and relaxation buffered the negative impact of role conflict on some of the proposed outcomes. Contrary to our expectations, we did not find significant results for mastery and control regarding moderating effects. Overall, findings suggest a differential pattern of the recovery experiences in the health impairment process proposed by the JD-R model.
Costly bilingualism model in a population with one zealot
NASA Astrophysics Data System (ADS)
Hong, Hyunsuk; Son, Seung-Woo
2013-08-01
We consider a costly bilingualism model in which one can take two strategies in parallel. We investigate how a single zealot triggers the cascading behavior and how the compatibility of the two strategies affects when interacting patterns change. First, the role of the interaction range in the cascading is studied by increasing the range from local to global. We find that people sometimes do not favor taking the superior strategy even though its payoff is higher than that of the inferior one. This is found to be caused by the local interactions rather than the global ones. Applying this model to social networks, we find that the location of the zealot is also important for larger cascading in heterogeneous networks.
Costly bilingualism model in a population with one zealot.
Hong, Hyunsuk; Son, Seung-Woo
2013-08-01
We consider a costly bilingualism model in which one can take two strategies in parallel. We investigate how a single zealot triggers the cascading behavior and how the compatibility of the two strategies affects when interacting patterns change. First, the role of the interaction range in the cascading is studied by increasing the range from local to global. We find that people sometimes do not favor taking the superior strategy even though its payoff is higher than that of the inferior one. This is found to be caused by the local interactions rather than the global ones. Applying this model to social networks, we find that the location of the zealot is also important for larger cascading in heterogeneous networks.
Predicting recreational fishing use of offshore petroleum platforms in the Central Gulf of Mexico
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gordon, W.R. Jr.
1987-01-01
This study is based on the premise that properly sited artificial reefs for optimal human recreational use, a predictive model based upon the marine travel patterns and behavior of marine recreational fishermen, is needed. This research used data gathered from a previous study that addressed the recreational fishing use of offshore oil and gas structures (Ditton and Auyong 1984); on-site data were also collected. The primary research objective was to generate a predictive model that can be applied to artificial-reef development efforts elsewhere. This study investigated the recreational-user patterns of selected petroleum platforms structures in the Central Gulf of Mexico.more » The petroleum structures offshore from the Louisiana coastline provide a unique research tool. Although intended to facilitate the exploration and recovery of hydrocarbons, petroleum platforms also serve as defacto artificial reefs, providing habitat for numerous species of fish and other marine life. Petroleum platforms were found to be the principal fishing destinations within the study area. On-site findings reveal that marine recreational fishermen were as mobile on water, as they are on land. On-site findings were used to assist in the development of a predictive model.« less
A lattice model for influenza spreading.
Liccardo, Antonella; Fierro, Annalisa
2013-01-01
We construct a stochastic SIR model for influenza spreading on a D-dimensional lattice, which represents the dynamic contact network of individuals. An age distributed population is placed on the lattice and moves on it. The displacement from a site to a nearest neighbor empty site, allows individuals to change the number and identities of their contacts. The dynamics on the lattice is governed by an attractive interaction between individuals belonging to the same age-class. The parameters, which regulate the pattern dynamics, are fixed fitting the data on the age-dependent daily contact numbers, furnished by the Polymod survey. A simple SIR transmission model with a nearest neighbors interaction and some very basic adaptive mobility restrictions complete the model. The model is validated against the age-distributed Italian epidemiological data for the influenza A(H1N1) during the [Formula: see text] season, with sensible predictions for the epidemiological parameters. For an appropriate topology of the lattice, we find that, whenever the accordance between the contact patterns of the model and the Polymod data is satisfactory, there is a good agreement between the numerical and the experimental epidemiological data. This result shows how rich is the information encoded in the average contact patterns of individuals, with respect to the analysis of the epidemic spreading of an infectious disease.
Simple rules govern the patterns of Arctic sea ice melt ponds
NASA Astrophysics Data System (ADS)
Popovic, P.; Cael, B. B.; Abbot, D. S.; Silber, M.
2017-12-01
Climate change, amplified in the far north, has led to a rapid sea ice decline in recent years. Melt ponds that form on the surface of Arctic sea ice in the summer significantly lower the ice albedo, thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback. However, currently it is unclear how to model this intricate geometry. Here we show that an extremely simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The model has only two parameters, circle scale and the fraction of the surface covered by voids, and we choose them by comparing the model to pond images. Using these parameters the void model robustly reproduces all of the examined pond features such as the ponds' area-perimeter relationship and the area-abundance relationship over nearly 7 orders of magnitude. By analyzing airborne photographs of sea ice, we also find that the typical pond scale is surprisingly constant across different years, regions, and ice types. These results demonstrate that the geometric and abundance patterns of Arctic melt ponds can be simply described, and can guide future models of Arctic melt ponds to improve predictions of how sea ice will respond to Arctic warming.
Hadač, Otto; Kohout, Martin; Havlica, Jaromír; Schreiber, Igor
2015-03-07
A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.
Observational evidence of European summer weather patterns predictable from spring
NASA Astrophysics Data System (ADS)
Ossó, Albert; Sutton, Rowan; Shaffrey, Len; Dong, Buwen
2018-01-01
Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications. However, seasonal dynamical model forecasts for European summers have very little skill, particularly for rainfall. It has not been clear whether this low skill reflects inherent unpredictability of summer weather or, alternatively, is a consequence of weaknesses in current forecast systems. Here we analyze atmosphere and ocean observations and identify evidence that a specific pattern of summertime atmospheric circulation––the summer East Atlantic (SEA) pattern––is predictable from the previous spring. An index of North Atlantic sea-surface temperatures in March–April can predict the SEA pattern in July–August with a cross-validated correlation skill above 0.6. Our analyses show that the sea-surface temperatures influence atmospheric circulation and the position of the jet stream over the North Atlantic. The SEA pattern has a particularly strong influence on rainfall in the British Isles, which we find can also be predicted months ahead with a significant skill of 0.56. Our results have immediate application to empirical forecasts of summer rainfall for the United Kingdom, Ireland, and northern France and also suggest that current dynamical model forecast systems have large potential for improvement.
Geomorphological analysis of boulders and polygons on Martian periglacial patterned ground terrains
NASA Astrophysics Data System (ADS)
Orloff, Travis C.
Images from the High Resolution Imaging Science Experiment Camera onboard the Mars Reconnaisance Orbiter show the surface in higher detail than previously capable. I look at a landscape on Mars called permafrost patterned ground which covers ˜10 million square kilometers of the surface at high latitudes (>50°). Using the new high resolution images available we objectively characterize permafrost patterned ground terrains as an alternative to observational surveys which while detailed suffer from subjective bias. I take two dimensional Fourier transforms of individual images of Martian permafrost patterned ground to find the scale most representative of the terrain. This scale acts as a proxy for the size of the polygons themselves. Then I look at the distribution of spectral scales in the northern hemisphere between 50-70° and find correlations to previous studies and with the extent of ground ice in the surface. The high resolution images also show boulders clustering with respect to the underlying pattern. I make the first detailed observations of these clustered boulders and use crater counting to place constraints on the time it takes for boulders to cluster. Finally, I present a potential mechanism for the process that clusters the boulders that takes the specifics of the Martian environment to account. Boulders lying on the surface get trapped in seasonal CO2 frost while ice in the near surface contracts in the winter. The CO2 frost sublimates in spring/summer allowing the boulders to move when the near surface ice expands in summer. Repeated iterations lead to boulders that cluster in the polygon edges. Using a thermal model of the subsurface with Mars conditions and an elastic model of a polygon I show boulders could move as much as ˜0.1mm per year in the present day.
Contrasting species and functional beta diversity in montane ant assemblages.
Bishop, Tom R; Robertson, Mark P; van Rensburg, Berndt J; Parr, Catherine L
2015-09-01
Beta diversity describes the variation in species composition between sites and can be used to infer why different species occupy different parts of the globe. It can be viewed in a number of ways. First, it can be partitioned into two distinct patterns: turnover and nestedness. Second, it can be investigated from either a species identity or a functional-trait point of view. We aim to document for the first time how these two aspects of beta diversity vary in response to a large environmental gradient. Maloti-Drakensberg Mountains, southern Africa. We sampled ant assemblages along an extensive elevational gradient (900-3000 m a.s.l.) twice yearly for 7 years, and collected functional-trait information related to the species' dietary and habitat-structure preferences. We used recently developed methods to partition species and functional beta diversity into their turnover and nestedness components. A series of null models were used to test whether the observed beta diversity patterns differed from random expectations. Species beta diversity was driven by turnover, but functional beta diversity was composed of both turnover and nestedness patterns at different parts of the gradient. Null models revealed that deterministic processes were likely to be responsible for the species patterns but that the functional changes were indistinguishable from stochasticity. Different ant species are found with increasing elevation, but they tend to represent an increasingly nested subset of the available functional strategies. This finding is unique and narrows down the list of possible factors that control ant existence across elevation. We conclude that diet and habitat preferences have little role in structuring ant assemblages in montane environments and that some other factor must be driving the non-random patterns of species turnover. This finding also highlights the importance of distinguishing between different kinds of beta diversity.
Zubrick, Stephen R.; Taylor, Catherine L.; Christensen, Daniel
2015-01-01
Aims Oral language is the foundation of literacy. Naturally, policies and practices to promote children’s literacy begin in early childhood and have a strong focus on developing children’s oral language, especially for children with known risk factors for low language ability. The underlying assumption is that children’s progress along the oral to literate continuum is stable and predictable, such that low language ability foretells low literacy ability. This study investigated patterns and predictors of children’s oral language and literacy abilities at 4, 6, 8 and 10 years. The study sample comprised 2,316 to 2,792 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Six developmental patterns were observed, a stable middle-high pattern, a stable low pattern, an improving pattern, a declining pattern, a fluctuating low pattern, and a fluctuating middle-high pattern. Most children (69%) fit a stable middle-high pattern. By contrast, less than 1% of children fit a stable low pattern. These results challenged the view that children’s progress along the oral to literate continuum is stable and predictable. Findings Multivariate logistic regression was used to investigate risks for low literacy ability at 10 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. Predictors were modelled as risk variables with the lowest level of risk as the reference category. In the multivariate model, substantial risks for low literacy ability at 10 years, in order of descending magnitude, were: low school readiness, Aboriginal and/or Torres Strait Islander status and low language ability at 8 years. Moderate risks were high temperamental reactivity, low language ability at 4 years, and low language ability at 6 years. The following risk factors were not statistically significant in the multivariate model: Low maternal consistency, low family income, health care card, child not read to at home, maternal smoking, maternal education, family structure, temperamental persistence, and socio-economic area disadvantage. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude did not do particularly well in predicting low literacy ability at 10 years. PMID:26352436
Yan, Bei; A, Ji-Ye; Hao, Hai-Ping; Wang, Guang-Ji; Liu, Lin-Sheng; Zha, Wei-Bin; Zhang, Ying; Gu, Sheng-Hua
2011-08-01
In order to explore the scientific connotation of "Fangzhengduiying (formula corresponding to pattern types)", "Qiyinliangxuzheng (Qi and Yin deficiency pattern)" of myocardial ischemia rat model and GC-TOF/MS based metabonomic method were used for comparing the effects of Sheng-mai injection, Salvia injection and propranolol in the present study. After data processing and pattern recognition, Sheng-mai injection showed better efficacy than the other two drugs in accordance with not only visual observation from PLS-DA scores plots but also the number of abnormal endogenous compounds restored to the normal level. Further studies showed that Sheng-mai injection could normalize the level of plasma endothelin-1, the index related to cardiovascular diseases and sleep disorders, which verified the results of metabonomics. Finally, the regulated metabolites and related metabolic pathways were analyzed, and it was supposed that the effects of Sheng-mai injection involved in the alternation of energy metabolism, lipid metabolism, amino acids metabolism, and so on. These findings provided scientific evidence to Shengmai "Fang" used for "Qi and Yin deficiency pattern" correspondingly, indicating that metabonomics has great potential in traditional Chinese medical research, which provides a novel approach and way to modernization of traditional Chinese medicine.
NASA Astrophysics Data System (ADS)
Iida, Michihira; Maeno, Tsuyoshi; Wang, Jianqing; Fujiwara, Osamu
Electromagnetic disturbances in vehicle-mounted radios are mainly caused by conducted noise currents flowing through wiring-harnesses from vehicle-mounted printed circuit boards (PCBs) with common slitting ground patterns. To suppress these kinds of noise currents, we previously measured them for simple two-layer PCBs with two parallel signal traces and slitting or non-slitting ground patterns, and then investigated by the FDTD simulation the reduction characteristics of the FM-band cross-talk noise levels between two parallel signal traces on six simple PCB models having different slitting ground or different divided ground patterns parallel to the traces. As a result, we found that the contributory factor for the FM-band cross-talk reduction is the reduction of mutual inductance between the two parallel traces, and also the noise currents from PCBs can rather be suppressed even if the size of the return ground becomes small. In this study, to investigate this finding, we further simulated the frequency characteristics of cross-talk reduction for additional six simple PCB models with different dividing dimensions ground patterns parallel to the traces, which revealed an interesting phenomenon that cross-talk reduction characteristics do not always decrease with increasing the width between the divided ground patterns.
Polarization models of filamentary molecular clouds.
NASA Astrophysics Data System (ADS)
Carlqvist, P.; Kristen, H.
1997-08-01
We study numerically the linear polarization and extinction of light from background stars in three types of models of elongated molecular clouds by following the development of the Stokes parameters. The clouds are assumed to be of cylindrical shape and penetrated by a helical magnetic field {vec}(B). In the first two models we study only the relative magnitude of the polarization assuming that the polarization is proportional to Bmu^, where primarily μ=2. Provided there is no background/foreground polarization present we find from the cylindrically symmetric Model I that the angle of polarization has a bimodal character with the polarization being either parallel with or perpendicular to the axis of the filament. For some magnetic-field geometries both angles may exist in one and the same filament. It is concluded that it is not a straightforward task to find the magnetic-field-line pattern from the polarization pattern. If a background/foreground polarization exists or, as in Model II, the filament is not cylindrically symmetric, the bimodal character of the angle of polarization is lost. By means of Model III we have, using semi-empirical methods based on the Davis-Greenstein mechanism, estimated the absolute degree of polarization in the filamentary molecular cloud L204. It is found that the polarization produced by the model is much less than the polarization observed. We therefore conclude that most of the polarization measured in the L204 cloud is not produced in the cloud itself but is constituted by a large-scale background/foreground polarization.
Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics
NASA Astrophysics Data System (ADS)
Saeedi, Sara
2018-06-01
With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving mechanism of urbanization and provide decision-making support for urban management.
Visual Attention Patterns of Women with Androphilic and Gynephilic Sexual Attractions.
Dawson, Samantha J; Fretz, Katherine M; Chivers, Meredith L
2017-01-01
Women who report exclusive sexual attractions to men (i.e., androphilia) exhibit gender-nonspecific patterns of sexual response-similar magnitude of genital response to both male and female targets. Interestingly, women reporting any degree of attraction to women (i.e., gynephilia) show significantly greater sexual responses to stimuli depicting female targets compared to male targets. At present, the mechanism(s) underlying these patterns are unknown. According to the information processing model (IPM), attentional processing of sexual cues initiates sexual responding; thus, attention to sexual cues may be one mechanism to explain the observed within-gender differences in specificity findings among women. The purpose of the present study was to examine patterns of initial and controlled visual attention among women with varying sexual attractions. We used eye tracking to assess visual attention to sexually preferred and nonpreferred cues in a sample of 164 women who differed in their degree of androphilia and gynephilia. We found that both exclusively and predominantly androphilic women showed gender-nonspecific patterns of initial attention. In contrast, ambiphilic (i.e., concurrent androphilia and gynephilia) and predominantly/exclusively gynephilic women oriented more quickly toward female targets. Controlled attention patterns mirrored patterns of self-reported sexual attractions for three of these four groups of women, such that gender-specific patterns of visual attention were found for androphilic and gynephilic women. Ambiphilic women looked significantly longer at female targets compared to male targets. These findings support predictions from the IPM and suggest that both initial and controlled attention to sexual cues may be mechanisms contributing to within-gender variation in sexual responding.
Habitat-based constraints on food web structure and parasite life cycles.
Rossiter, Wayne; Sukhdeo, Michael V K
2014-04-01
Habitat is frequently implicated as a powerful determinant of community structure and species distributions, but few studies explicitly evaluate the relationship between habitat-based patterns of species' distributions and the presence or absence of trophic interactions. The complex (multi-host) life cycles of parasites are directly affected by these factors, but almost no data exist on the role of habitat in constraining parasite-host interactions at the community level. In this study the relationship(s) between species abundances, distributions and trophic interactions (including parasitism) were evaluated in the context of habitat structure (classic geomorphic designations of pools, riffles and runs) in a riverine community (Raritan River, Hunterdon County, NJ, USA). We report 121 taxa collected over a 2-year period, and compare the observed food web patterns to null model expectations. The results show that top predators are constrained to particular habitat types, and that species' distributions are biased towards pool habitats. However, our null model (which incorporates cascade model assumptions) accurately predicts the observed patterns of trophic interactions. Thus, habitat strongly dictates species distributions, and patterns of trophic interactions arise as a consequence of these distributions. Additionally, we find that hosts utilized in parasite life cycles are more overlapping in their distributions, and this pattern is more pronounced among those involved in trophic transmission. We conclude that habitat structure may be a strong predictor of parasite transmission routes, particularly within communities that occupy heterogeneous habitats.
The importance of topographically corrected null models for analyzing ecological point processes.
McDowall, Philip; Lynch, Heather J
2017-07-01
Analyses of point process patterns and related techniques (e.g., MaxEnt) make use of the expected number of occurrences per unit area and second-order statistics based on the distance between occurrences. Ecologists working with point process data often assume that points exist on a two-dimensional x-y plane or within a three-dimensional volume, when in fact many observed point patterns are generated on a two-dimensional surface existing within three-dimensional space. For many surfaces, however, such as the topography of landscapes, the projection from the surface to the x-y plane preserves neither area nor distance. As such, when these point patterns are implicitly projected to and analyzed in the x-y plane, our expectations of the point pattern's statistical properties may not be met. When used in hypothesis testing, we find that the failure to account for the topography of the generating surface may bias statistical tests that incorrectly identify clustering and, furthermore, may bias coefficients in inhomogeneous point process models that incorporate slope as a covariate. We demonstrate the circumstances under which this bias is significant, and present simple methods that allow point processes to be simulated with corrections for topography. These point patterns can then be used to generate "topographically corrected" null models against which observed point processes can be compared. © 2017 by the Ecological Society of America.
Instability of the cored barotropic disc: the linear eigenvalue formulation
NASA Astrophysics Data System (ADS)
Polyachenko, E. V.
2018-05-01
Gaseous rotating razor-thin discs are a testing ground for theories of spiral structure that try to explain appearance and diversity of disc galaxy patterns. These patterns are believed to arise spontaneously under the action of gravitational instability, but calculations of its characteristics in the gas are mostly obscured. The paper suggests a new method for finding the spiral patterns based on an expansion of small amplitude perturbations over Lagrange polynomials in small radial elements. The final matrix equation is extracted from the original hydrodynamical equations without the use of an approximate theory and has a form of the linear algebraic eigenvalue problem. The method is applied to a galactic model with the cored exponential density profile.
Stochastic feeding dynamics arise from the need for information and energy.
Scholz, Monika; Dinner, Aaron R; Levine, Erel; Biron, David
2017-08-29
Animals regulate their food intake in response to the available level of food. Recent observations of feeding dynamics in small animals showed feeding patterns of bursts and pauses, but their function is unknown. Here, we present a data-driven decision-theoretical model of feeding in Caenorhabditis elegans Our central assumption is that food intake serves a dual purpose: to gather information about the external food level and to ingest food when the conditions are good. The model recapitulates experimentally observed feeding patterns. It naturally implements trade-offs between speed versus accuracy and exploration versus exploitation in responding to a dynamic environment. We find that the model predicts three distinct regimes in responding to a dynamical environment, with a transition region where animals respond stochastically to periodic signals. This stochastic response accounts for previously unexplained experimental data.
Regional Patterns of Stress Transfer in the Ablation Zone of the Western Greenland Ice Sheet
NASA Astrophysics Data System (ADS)
Andrews, L. C.; Hoffman, M. J.; Neumann, T.; Catania, G. A.; Luethi, M. P.; Hawley, R. L.
2016-12-01
Current understanding of the subglacial system indicates that the seasonal evolution of ice flow is strongly controlled by the gradual upstream progression of an inefficient - efficient transition within the subglacial hydrologic system followed by the reduction of melt and a downstream collapse of the efficient system. Using a spatiotemporally dense network of GPS-derived surface velocities from the Pâkitsoq Region of the western Greenland Ice Sheet, we find that this pattern of subglacial development is complicated by heterogeneous bed topography, resulting in complex patterns of ice flow. Following low elevation melt onset, early melt season strain rate anomalies are dominated by regional extension, which then gives way to spatially expansive compression. However, once daily minimum ice velocities fall below the observed winter background velocities, an alternating spatial pattern of extension and compression prevails. This pattern of strain rate anomalies is correlated with changing basal topography and differences in the magnitude of diurnal surface ice speeds. Along subglacial ridges, diurnal variability in ice speed is large, suggestive of a mature, efficient subglacial system. In regions of subglacial lows, diurnal variability in ice velocity is relatively low, likely associated with a less developed efficient subglacial system. The observed pattern suggests that borehole observations and modeling results demonstrating the importance of longitudinal stress transfer at a single field location are likely widely applicable in our study area and other regions of the Greenland Ice Sheet with highly variable bed topography. Further, the complex pattern of ice flow and evidence of spatially extensive longitudinal stress transfer add to the body of work indicating that the bed character plays an important role in the development of the subglacial system; closely matching diurnal ice velocity patterns with subglacial models may be difficult without coupling these models to high order ice flow models.
Crone, Julia Sophia; Lutkenhoff, Evan Scott; Bio, Branden Joseph; Laureys, Steven; Monti, Martin Max
2017-04-01
In recent years, a number of brain regions and connectivity patterns have been proposed to be crucial for loss and recovery of consciousness but have not been compared in detail. In a 3 T resting-state functional magnetic resonance imaging paradigm, we test the plausibility of these different neuronal models derived from theoretical and empirical knowledge. Specifically, we assess the fit of each model to the dynamic change in effective connectivity between specific cortical and subcortical regions at different consecutive levels of propofol-induced sedation by employing spectral dynamic causal modeling. Surprisingly, our findings indicate that proposed models of impaired consciousness do not fit the observed patterns of effective connectivity. Rather, the data show that loss of consciousness, at least in the context of propofol-induced sedation, is marked by a breakdown of corticopetal projections from the globus pallidus. Effective connectivity between the globus pallidus and the ventral posterior cingulate cortex, present during wakefulness, fades in the transition from lightly sedated to full loss of consciousness and returns gradually as consciousness recovers, thereby, demonstrating the dynamic shift in brain architecture of the posterior cingulate "hub" during changing states of consciousness. These findings highlight the functional role of a previously underappreciated direct pallido-cortical connectivity in supporting consciousness. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
A comparison of algorithms for inference and learning in probabilistic graphical models.
Frey, Brendan J; Jojic, Nebojsa
2005-09-01
Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.
Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.
2010-01-01
Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927
NASA Astrophysics Data System (ADS)
Jia, Xiaoliang; An, Haizhong; Sun, Xiaoqi; Huang, Xuan; Gao, Xiangyun
2016-04-01
The globalization and regionalization of crude oil trade inevitably give rise to the difference of crude oil prices. The understanding of the pattern of the crude oil prices' mutual propagation is essential for analyzing the development of global oil trade. Previous research has focused mainly on the fuzzy long- or short-term one-to-one propagation of bivariate oil prices, generally ignoring various patterns of periodical multivariate propagation. This study presents a wavelet-based network approach to help uncover the multipath propagation of multivariable crude oil prices in a joint time-frequency period. The weekly oil spot prices of the OPEC member states from June 1999 to March 2011 are adopted as the sample data. First, we used wavelet analysis to find different subseries based on an optimal decomposing scale to describe the periodical feature of the original oil price time series. Second, a complex network model was constructed based on an optimal threshold selection to describe the structural feature of multivariable oil prices. Third, Bayesian network analysis (BNA) was conducted to find the probability causal relationship based on periodical structural features to describe the various patterns of periodical multivariable propagation. Finally, the significance of the leading and intermediary oil prices is discussed. These findings are beneficial for the implementation of periodical target-oriented pricing policies and investment strategies.
Ma, Yuanxiao; Ma, Haijing; Chen, Xu; Ran, Guangming; Zhang, Xing
2017-07-01
People tend to respond to rejection and attack with aggression. The present research examined the modulation role of attachment patterns on provoked aggression following punishment and proposed an executive functioning account of attachment patterns' modulating influence based on the General Aggression Model. Attachment style was measured using the Experiences in Close Relationships inventory. Experiments 1a and b and 2 adopted a social rejection task and assessed subsequent unprovoked and provoked aggression with different attachment patterns. Moreover, Experiment 1b and 2 used a Stroop task to examine whether differences in provoked aggression by attachment patterns are due to the amount of executive functioning following social rejection, or after unprovoked punishment, or even before social rejection. Anxiously attached participants displayed significant more provoked aggression than securely and avoidantly attached participants in provoked aggression following unprovoked punishment in Experiments 1 and 2. Meanwhile, subsequent Stroop tests indicated anxiously attached participants experienced more executive functioning depletion after social rejection and unprovoked aggression. The present findings support the General Aggression Model and suggest that provoked aggression is predicted by attachment patterns in the context of social rejection; different provoked aggression may depend on the degree of executive functioning that individuals preserved in aggressive situations. The current study contributes to our understanding of the importance of the role of attachment patterns in modulating aggressive behavior accompanying unfair social encounters. © 2017 Wiley Periodicals, Inc.
Conserved and Divergent Molecular and Anatomic Features of Human and Mouse Nephron Patterning.
Lindström, Nils O; Tran, Tracy; Guo, Jinjin; Rutledge, Elisabeth; Parvez, Riana K; Thornton, Matthew E; Grubbs, Brendan; McMahon, Jill A; McMahon, Andrew P
2018-03-01
The nephron is the functional unit of the kidney, but the mechanism of nephron formation during human development is unclear. We conducted a detailed analysis of nephron development in humans and mice by immunolabeling, and we compared human and mouse nephron patterning to describe conserved and divergent features. We created protein localization maps that highlight the emerging patterns along the proximal-distal axis of the developing nephron and benchmark expectations for localization of functionally important transcription factors, which revealed unanticipated cellular diversity. Moreover, we identified a novel nephron subdomain marked by Wnt4 expression that we fate-mapped to the proximal mature nephron. Significant conservation was observed between human and mouse patterning. We also determined the time at which markers for mature nephron cell types first emerge-critical data for the renal organoid field. These findings have conceptual implications for the evolutionary processes driving the diversity of mammalian organ systems. Furthermore, these findings provide practical insights beyond those gained with mouse and rat models that will guide in vitro efforts to harness the developmental programs necessary to build human kidney structures. Copyright © 2018 by the American Society of Nephrology.
Two-state Markov-chain Poisson nature of individual cellphone call statistics
NASA Astrophysics Data System (ADS)
Jiang, Zhi-Qiang; Xie, Wen-Jie; Li, Ming-Xia; Zhou, Wei-Xing; Sornette, Didier
2016-07-01
Unfolding the burst patterns in human activities and social interactions is a very important issue especially for understanding the spreading of disease and information and the formation of groups and organizations. Here, we conduct an in-depth study of the temporal patterns of cellphone conversation activities of 73 339 anonymous cellphone users, whose inter-call durations are Weibull distributed. We find that the individual call events exhibit a pattern of bursts, that high activity periods are alternated with low activity periods. In both periods, the number of calls are exponentially distributed for individuals, but power-law distributed for the population. Together with the exponential distributions of inter-call durations within bursts and of the intervals between consecutive bursts, we demonstrate that the individual call activities are driven by two independent Poisson processes, which can be combined within a minimal model in terms of a two-state first-order Markov chain, giving significant fits for nearly half of the individuals. By measuring directly the distributions of call rates across the population, which exhibit power-law tails, we purport the existence of power-law distributions, via the ‘superposition of distributions’ mechanism. Our findings shed light on the origins of bursty patterns in other human activities.
Junier, Ivan; Boccard, Frédéric; Espéli, Olivier
2014-01-01
The mechanisms that control chromosome conformation and segregation in bacteria have not yet been elucidated. In Escherichia coli, the mere presence of an active process remains an open question. Here, we investigate the conformation and segregation pattern of the E. coli genome by performing numerical simulations on a polymer model of the chromosome. We analyze the roles of the intrinsic structuring of chromosomes and the forced localization of specific loci, which are observed in vivo. Specifically, we examine the segregation pattern of a chromosome that is divided into four structured macrodomains (MDs) and two non-structured regions. We find that strong osmotic-like organizational forces, which stem from the differential condensation levels of the chromosome regions, dictate the cellular disposition of the chromosome. Strikingly, the comparison of our in silico results with fluorescent imaging of the chromosome choreography in vivo reveals that in the presence of MDs the targeting of the origin and terminus regions to specific positions are sufficient to generate a segregation pattern that is indistinguishable from experimentally observed patterns. PMID:24194594
Perceptual learning in a non-human primate model of artificial vision
Killian, Nathaniel J.; Vurro, Milena; Keith, Sarah B.; Kyada, Margee J.; Pezaris, John S.
2016-01-01
Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation. PMID:27874058
NASA Astrophysics Data System (ADS)
Trout, Joseph; Manson, J. Russell; King, David; Decicco, Nicolas; Prince, Alyssa; di Mercurio, Alexis; Rios, Manual
2017-01-01
Wake Vortex Turbulence is the turbulence generated by an aircraft in flight. This turbulence is created by vortices at the tips of the wing that may decay slowly and persist for several minutes after creation. These vortices and turbulence are hazardous to other aircraft in the vicinity. The strength, formation and lifetime of the turbulence and vortices are effected by many things including the weather. Here we present the final results of the pilot project to investigation of low level wind fields generated by the Weather Research and Forecasting Model and an analysis of historical data. The findings from the historical data and the data simulations were used as inputs for the computational fluid dynamics model (OpenFoam) to show that the vortices could be simulated using OpenFoam. Presented here are the updated results from a research grant, ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Stockton University and the FAA''.
Occurrence Frequencies of Acoustic Patterns of Vocal Fry in American English Speakers.
Abdelli-Beruh, Nassima B; Drugman, Thomas; Red Owl, R H
2016-11-01
The goal of this study was to analyze the occurrence frequencies of three individual acoustic patterns (A, B, C) and of vocal fry overall (A + B + C) as a function of gender, word position in the sentence (Not Last Word vs. Last Word), and sentence length (number of words in a sentence). This is an experimental design. Twenty-five male and 29 female American English (AE) speakers read the Grandfather Passage. The recordings were processed by a Matlab toolbox designed for the analysis and detection of creaky segments, automatically identified using the Kane-Drugman algorithm. The experiment produced subsamples of outcomes, three that reflect a single, discrete acoustic pattern (A, B, or C) and the fourth that reflects the occurrence frequency counts of Vocal Fry Overall without regard to any specific pattern. Zero-truncated Poisson regression analyses were conducted with Gender and Word Position as predictors and Sentence Length as a covariate. The results of the present study showed that the occurrence frequencies of the three acoustic patterns and vocal fry overall (A + B + C) are greatest at the end of sentences but are unaffected by sentence length. The findings also reveal that AE female speakers exhibit Pattern C significantly more frequently than Pattern B, and the converse holds for AE male speakers. Future studies are needed to confirm such outcomes, assess the perceptual salience of these acoustic patterns, and determine the physiological correlates of these acoustic patterns. The findings have implications for the design of new excitation models of vocal fry. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases
Mossong, Joël; Hens, Niel; Jit, Mark; Beutels, Philippe; Auranen, Kari; Mikolajczyk, Rafael; Massari, Marco; Salmaso, Stefania; Tomba, Gianpaolo Scalia; Wallinga, Jacco; Heijne, Janneke; Sadkowska-Todys, Malgorzata; Rosinska, Magdalena; Edmunds, W. John
2008-01-01
Background Mathematical modelling of infectious diseases transmitted by the respiratory or close-contact route (e.g., pandemic influenza) is increasingly being used to determine the impact of possible interventions. Although mixing patterns are known to be crucial determinants for model outcome, researchers often rely on a priori contact assumptions with little or no empirical basis. We conducted a population-based prospective survey of mixing patterns in eight European countries using a common paper-diary methodology. Methods and Findings 7,290 participants recorded characteristics of 97,904 contacts with different individuals during one day, including age, sex, location, duration, frequency, and occurrence of physical contact. We found that mixing patterns and contact characteristics were remarkably similar across different European countries. Contact patterns were highly assortative with age: schoolchildren and young adults in particular tended to mix with people of the same age. Contacts lasting at least one hour or occurring on a daily basis mostly involved physical contact, while short duration and infrequent contacts tended to be nonphysical. Contacts at home, school, or leisure were more likely to be physical than contacts at the workplace or while travelling. Preliminary modelling indicates that 5- to 19-year-olds are expected to suffer the highest incidence during the initial epidemic phase of an emerging infection transmitted through social contacts measured here when the population is completely susceptible. Conclusions To our knowledge, our study provides the first large-scale quantitative approach to contact patterns relevant for infections transmitted by the respiratory or close-contact route, and the results should lead to improved parameterisation of mathematical models used to design control strategies. PMID:18366252
Spiral and Rotor Patterns Produced by Fairy Ring Fungi
NASA Astrophysics Data System (ADS)
Karst, N.; Dralle, D.; Thompson, S. E.
2014-12-01
Soil fungi fill many essential ecological and biogeochemical roles, e.g. decomposing litter, redistributing nutrients, and promoting biodiversity. Fairy ring fungi offer a rare glimpse into the otherwise opaque spatiotemporal dynamics of soil fungal growth, because subsurface mycelial patterns can be inferred from observations at the soil's surface. These observations can be made directly when the fungi send up fruiting bodies (e.g., mushrooms and toadstools), or indirectly via the effect the fungi have on neighboring organisms. Grasses in particular often temporarily thrive on the nutrients liberated by the fungus, creating bands of rich, dark green turf at the edge of the fungal mat. To date, only annular (the "ring" in fairy ring) and arc patterns have been described in the literature. We report observations of novel spiral and rotor pattern formation in fairy ring fungi, as seen in publically available high-resolution aerial imagery of 22 sites across the continental United States. To explain these new behaviors, we first demonstrate that a well-known model describing fairy ring formation is equivalent to the Gray-Scott reaction-diffusion model, which is known to support a wide range of dynamical behaviors, including annular traveling waves, rotors, spirals, and stable spatial patterns including spots and stripes. Bifurcation analysis and numerical simulation are then used to define the region of parameter space that supports spiral and rotor formation. We find that this region is adjacent to one within which typical fairy rings develop. Model results suggest simple experimental procedures that could potentially induce traditional ring structures to exhibit rotor or spiral dynamics. Intriguingly, the Gray-Scott model predicts that these same procedures could be used to solicit even richer patterns, including spots and stripes, which have not yet been identified in the field.
Spiral and Rotor Patterns Produced by Fairy Ring Fungi
NASA Astrophysics Data System (ADS)
Karst, N.; Dralle, D.; Thompson, S. E.
2015-12-01
Soil fungi fill many essential ecological and biogeochemical roles, e.g. decomposing litter, redistributing nutrients, and promoting biodiversity. Fairy ring fungi offer a rare glimpse into the otherwise opaque spatiotemporal dynamics of soil fungal growth, because subsurface mycelial patterns can be inferred from observations at the soil's surface. These observations can be made directly when the fungi send up fruiting bodies (e.g., mushrooms and toadstools), or indirectly via the effect the fungi have on neighboring organisms. Grasses in particular often temporarily thrive on the nutrients liberated by the fungus, creating bands of rich, dark green turf at the edge of the fungal mat. To date, only annular (the "ring" in fairy ring) and arc patterns have been described in the literature. We report observations of novel spiral and rotor pattern formation in fairy ring fungi, as seen in publically available high-resolution aerial imagery of 22 sites across the continental United States. To explain these new behaviors, we first demonstrate that a well-known model describing fairy ring formation is equivalent to the Gray-Scott reaction-diffusion model, which is known to support a wide range of dynamical behaviors, including annular traveling waves, rotors, spirals, and stable spatial patterns including spots and stripes. Bifurcation analysis and numerical simulation are then used to define the region of parameter space that supports spiral and rotor formation. We find that this region is adjacent to one within which typical fairy rings develop. Model results suggest simple experimental procedures that could potentially induce traditional ring structures to exhibit rotor or spiral dynamics. Intriguingly, the Gray-Scott model predicts that these same procedures could be used to solicit even richer patterns, including spots and stripes, which have not yet been identified in the field.
North Atlantic sub-decadal variability in climate models
NASA Astrophysics Data System (ADS)
Reintges, Annika; Martin, Thomas; Latif, Mojib; Park, Wonsun
2017-04-01
The North Atlantic Oscillation (NAO) is the dominant variability mode for the winter climate of the North Atlantic sector. During a positive (negative) NAO phase, the sea level pressure (SLP) difference between the subtropical Azores high and the subpolar Icelandic low is anomalously strong (weak). This affects, for example, temperature, precipitation, wind, and surface heat flux over the North Atlantic, and over large parts of Europe. In observations we find enhanced sub-decadal variability of the NAO index that goes along with a dipolar sea surface temperature (SST) pattern. The corresponding SLP and SST patterns are reproduced in a control experiment of the Kiel Climate Model (KCM). Large-scale air-sea interaction is suggested to be essential for the North Atlantic sub-decadal variability in the KCM. The Atlantic Meridional Overturning Circulation (AMOC) plays a key role, setting the timescale of the variability by providing a delayed negative feedback to the NAO. The interplay of the NAO and the AMOC on the sub-decadal timescale is further investigated in the CMIP5 model ensemble. For example, the average CMIP5 model AMOC pattern associated with sub-decadal variability is characterized by a deep-reaching dipolar structure, similar to the KCM's sub-decadal AMOC variability pattern. The results suggest that dynamical air-sea interactions are crucial to generate enhanced sub-decadal variability in the North Atlantic climate.
Fat-tailed fluctuations in the size of organizations: the role of social influence.
Mondani, Hernan; Holme, Petter; Liljeros, Fredrik
2014-01-01
Organizational growth processes have consistently been shown to exhibit a fatter-than-Gaussian growth-rate distribution in a variety of settings. Long periods of relatively small changes are interrupted by sudden changes in all size scales. This kind of extreme events can have important consequences for the development of biological and socio-economic systems. Existing models do not derive this aggregated pattern from agent actions at the micro level. We develop an agent-based simulation model on a social network. We take our departure in a model by a Schwarzkopf et al. on a scale-free network. We reproduce the fat-tailed pattern out of internal dynamics alone, and also find that it is robust with respect to network topology. Thus, the social network and the local interactions are a prerequisite for generating the pattern, but not the network topology itself. We further extend the model with a parameter δ that weights the relative fraction of an individual's neighbours belonging to a given organization, representing a contextual aspect of social influence. In the lower limit of this parameter, the fraction is irrelevant and choice of organization is random. In the upper limit of the parameter, the largest fraction quickly dominates, leading to a winner-takes-all situation. We recover the real pattern as an intermediate case between these two extremes.
A feature illustration and application of azimuthal P receiver function patterns
NASA Astrophysics Data System (ADS)
Eckhardt, C.; Rabbel, W.
2009-12-01
Based on a synthetic catalog of thirty azimuthal patterns of P receiver functions for crustal structures down to thirty km depth we have summarized and illustrated the most important azimuthal features. We have constructed five model classes encompassing (an-)isotropic horizontal and dipping layers. The model classes were initialized by in situ observations of three deep reflection seismic profiles (DEKORP) of varying high reflective zones and a spiral shaped foliation scheme of an upper crustal bore hole out of the German Continental Deep Drilling Program (KTB). Up to fourteen azimuthal features were extracted out of the synthetic patterns and could be grouped into an already known fundamental part, a multiple part and into an extension part. Each feature was rated by a specific grade A, B, C to inform about the type of its initialization ((an-) isotropy and/or layer dipping). We have evaluated the fourteen features on the synthetic patterns to apply a hierarchical classification. From the classification of the model objects we found that nearly eighty percent of the models are well explained by the fundamental part. The hierarchical order of the model objects can be used as a template to screen real observed azimuthal patterns to find a starting model for a forward modeling or an inversion procedure. For one station of the German Regional Seismic Network (GRSN) we have evaluated the features and screened them through the template. A forward simulation of the azimuthal pattern, using the modified first found model explanation out of the hierarchical order for station MOX, leads to a good coincidence between the real and the simulated pattern. The final 1D model could be divided into an upper crustal part (8 km deep) with an axis of symmetry tilt of 55° and 20°NW trend (direction of axis tilt) and a lower crustal part (24 km thickness) with an axis of symmetry of increasing tilt from 55° to 85° and a trend orientation of 20°SE. For the simulation we have assumed 8 and 7 percent of negative P+S anisotropy for hexagonal symmetry of the upper and lower crust, respectively. From the synthetic and the real observations it is evident that additional boundaries beside the Moho discontinuity are merely detectable for certain circumstances in an azimuthal resolution and will be blinded out in the traditional radial stack.
The anisotropic signal of topotaxy during phase transitions in D″
NASA Astrophysics Data System (ADS)
Walker, Andrew M.; Dobson, David P.; Wookey, James; Nowacki, Andy; Forte, Alessandro M.
2018-03-01
While observations and modelling of seismic anisotropy in the lowermost mantle offers the possibility of imaging mantle flow close to the core-mantle boundary, current models do not explain all observations. Here, we seek to explain a long-wavelength pattern of shear wave anisotropy observed in anisotropic tomography where vertically polarised shear waves travel faster than horizontally polarised shear waves in the central Pacific and under Africa but this pattern is reversed elsewhere. In particular, we test an explanation derived from experiments on analogues, which suggest that texture may be inherited during phase transitions between bridgmanite (perovskite structured MgSiO3) and post-perovskite, and that such texture inheritance may yield the long-wavelength pattern of anisotropy. We find that models that include this effect correlate better with tomographic models than those that assume deformation due to a single phase in the lowermost mantle, supporting the idea that texture inheritance is an important factor in understanding lowermost mantle anisotropy. It is possible that anisotropy could be used to map the post-perovskite stability field in the lowermost mantle, and thus place constraints on the temperature structure above the core-mantle boundary.
A simple model for research interest evolution patterns
NASA Astrophysics Data System (ADS)
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.
Glimm, Tilmann; Zhang, Jianying; Shen, Yun-Qiu; Newman, Stuart A
2012-03-01
We investigate a reaction-diffusion system consisting of an activator and an inhibitor in a two-dimensional domain. There is a morphogen gradient in the domain. The production of the activator depends on the concentration of the morphogen. Mathematically, this leads to reaction-diffusion equations with explicitly space-dependent terms. It is well known that in the absence of an external morphogen, the system can produce either spots or stripes via the Turing bifurcation. We derive first-order expansions for the possible patterns in the presence of an external morphogen and show how both stripes and spots are affected. This work generalizes previous one-dimensional results to two dimensions. Specifically, we consider the quasi-one-dimensional case of a thin rectangular domain and the case of a square domain. We apply the results to a model of skeletal pattern formation in vertebrate limbs. In the framework of reaction-diffusion models, our results suggest a simple explanation for some recent experimental findings in the mouse limb which are much harder to explain in positional-information-type models.
Turing-like structures in a functional model of cortical spreading depression
NASA Astrophysics Data System (ADS)
Verisokin, A. Yu.; Verveyko, D. V.; Postnov, D. E.
2017-12-01
Cortical spreading depression (CSD) along with migraine waves and spreading depolarization events with stroke or injures are the front-line examples of extreme physiological behaviors of the brain cortex which manifest themselves via the onset and spreading of localized areas of neuronal hyperactivity followed by their depression. While much is known about the physiological pathways involved, the dynamical mechanisms of the formation and evolution of complex spatiotemporal patterns during CSD are still poorly understood, in spite of the number of modeling studies that have been already performed. Recently we have proposed a relatively simple mathematical model of cortical spreading depression which counts the effects of neurovascular coupling and cerebral blood flow redistribution during CSD. In the present study, we address the main dynamical consequences of newly included pathways, namely, the changes in the formation and propagation speed of the CSD front and the pattern formation features in two dimensions. Our most notable finding is that the combination of vascular-mediated spatial coupling with local regulatory mechanisms results in the formation of stationary Turing-like patterns during a CSD event.
Wei, Ruihan; Parsons, Sean P; Huizinga, Jan D
2017-03-01
What is the central question of this study? What are the effects of interstitial cells of Cajal (ICC) network perturbations on intestinal pacemaker activity and motor patterns? What is the main finding and its importance? Two-dimensional modelling of the ICC pacemaker activity according to a phase model of weakly coupled oscillators showed that network properties (coupling strength between oscillators, frequency gradient and frequency noise) strongly influence pacemaker network activity and subsequent motor patterns. The model explains motor patterns observed in physiological conditions and provides predictions and testable hypotheses for effects of ICC loss and frequency modulation on the motor patterns. Interstitial cells of Cajal (ICC) are the pacemaker cells of gut motility and are associated with motility disorders. Interstitial cells of Cajal form a network, but the contributions of its network properties to gut physiology and dysfunction are poorly understood. We modelled an ICC network as a two-dimensional network of weakly coupled oscillators with a frequency gradient and showed changes over time in video and graphical formats. Model parameters were obtained from slow-wave-driven contraction patterns in the mouse intestine and pacemaker slow-wave activities from the cat intestine. Marked changes in propagating oscillation patterns (including changes from propagation to non-propagating) were observed by changing network parameters (coupling strength between oscillators, the frequency gradient and frequency noise), which affected synchronization, propagation velocity and occurrence of dislocations (termination of an oscillation). Complete uncoupling of a circumferential ring of oscillators caused the proximal and distal section to desynchronize, but complete synchronization was maintained with only a single oscillator connecting the sections with high enough coupling. The network of oscillators could withstand loss; even with 40% of oscillators lost randomly within the network, significant synchronization and anterograde propagation remained. A local increase in pacemaker frequency diminished anterograde propagation; the effects were strongly dependent on location, frequency gradient and coupling strength. In summary, the model puts forth the hypothesis that fundamental changes in oscillation patterns (ICC slow-wave activity or circular muscle contractions) can occur through physiological modulation of network properties. Strong evidence is provided to accept the ICC network as a system of coupled oscillators. © 2016 The Authors. Experimental Physiology © 2016 The Physiological Society.
Bioconvection in spatially extended domains
NASA Astrophysics Data System (ADS)
Karimi, A.; Paul, M. R.
2013-05-01
We numerically explore gyrotactic bioconvection in large spatially extended domains of finite depth using parameter values from available experiments with the unicellular alga Chlamydomonas nivalis. We numerically integrate the three-dimensional, time-dependent continuum model of Pedley [J. Fluid Mech.10.1017/S0022112088002393 195, 223 (1988)] using a high-order, parallel, spectral-element approach. We explore the long-time nonlinear patterns and dynamics found for layers with an aspect ratio of 10 over a range of Rayleigh numbers. Our results yield the pattern wavelength and pattern dynamics which we compare with available theory and experimental measurement. There is good agreement for the pattern wavelength at short times between numerics, experiment, and a linear stability analysis. At long times we find that the general sequence of patterns given by the nonlinear evolution of the governing equations correspond qualitatively to what has been described experimentally. However, at long times the patterns in numerics grow to larger wavelengths, in contrast to what is observed in experiment where the wavelength is found to decrease with time.
Structural salience and the nonaccidentality of a Gestalt.
Strother, Lars; Kubovy, Michael
2012-08-01
We perceive structure through a process of perceptual organization. Here we report a new perceptual organization phenomenon-the facilitation of visual grouping by global curvature. Observers viewed patterns that they perceived as organized into collections of curves. The patterns were perceptually ambiguous such that the perceived orientation of the patterns varied from trial to trial. When patterns were sufficiently dense and proximity was equated for the predominant perceptual alternatives, observers tended to perceive the organization with the greatest curvature. This effect is tantamount to visual grouping by maximal curvature and thus demonstrates an unprecedented effect of global structure on perceptual organization. We account for this result with a model that predicts the perceived organization of a pattern as function of its nonaccidentality, which we define as the probability that it could have occurred by chance. Our findings demonstrate a novel relationship between the geometry of a pattern and the visual salience of global structure. (c) 2012 APA, all rights reserved.
Stimulus exposure and gaze bias: a further test of the gaze cascade model.
Glaholt, Mackenzie G; Reingold, Eyal M
2009-04-01
We tested predictions derived from the gaze cascade model of preference decision making (Shimojo, Simion, Shimojo, & Scheier, 2003; Simion & Shimojo, 2006, 2007). In each trial, participants' eye movements were monitored while they performed an eight-alternative decision task in which four of the items in the array were preexposed prior to the trial. Replicating previous findings, we found a gaze bias toward the chosen item prior to the response. However, contrary to the prediction of the gaze cascade model, preexposure of stimuli decreased, rather than increased, the magnitude of the gaze bias in preference decisions. Furthermore, unlike the prediction of the model, preexposure did not affect the likelihood of an item being chosen, and the pattern of looking behavior in preference decisions and on a non preference control task was remarkably similar. Implications of the present findings in multistage models of decision making are discussed.
NASA Astrophysics Data System (ADS)
Palanivel, M.; Uthayakumar, R.
2015-07-01
This paper deals with an economic order quantity (EOQ) model for non-instantaneous deteriorating items with price and advertisement dependent demand pattern under the effect of inflation and time value of money over a finite planning horizon. In this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This paper aids the retailer in minimising the total inventory cost by finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented and the implications are discussed in detail.
An Investigation of Unified Memory Access Performance in CUDA
Landaverde, Raphael; Zhang, Tiansheng; Coskun, Ayse K.; Herbordt, Martin
2015-01-01
Managing memory between the CPU and GPU is a major challenge in GPU computing. A programming model, Unified Memory Access (UMA), has been recently introduced by Nvidia to simplify the complexities of memory management while claiming good overall performance. In this paper, we investigate this programming model and evaluate its performance and programming model simplifications based on our experimental results. We find that beyond on-demand data transfers to the CPU, the GPU is also able to request subsets of data it requires on demand. This feature allows UMA to outperform full data transfer methods for certain parallel applications and small data sizes. We also find, however, that for the majority of applications and memory access patterns, the performance overheads associated with UMA are significant, while the simplifications to the programming model restrict flexibility for adding future optimizations. PMID:26594668
Counting Necklaces and Other Patterns.
ERIC Educational Resources Information Center
Houghton, Chris
1990-01-01
A method for helping students to find formulas involving symmetry under various conditions is explained. Necklace symmetries, orbit counting, tetrahedra and cubes, relationship patterns, and finding patterns are discussed. (CW)
GEM-CEDAR Challenge: Poynting Flux at DMSP and Modeled Joule Heat
NASA Technical Reports Server (NTRS)
Rastaetter, Lutz; Shim, Ja Soon; Kuznetsova, Maria M.; Kilcommons, Liam M.; Knipp, Delores J.; Codrescu, Mihail; Fuller-Rowell, Tim; Emery, Barbara; Weimer, Daniel R.; Cosgrove, Russell;
2016-01-01
Poynting flux into the ionosphere measures the electromagnetic energy coming from the magnetosphere. This energy flux can vary greatly between quiet times and geomagnetic active times. As part of the Geospace Environment Modeling-coupling energetics and dynamics of atmospheric regions modeling challenge, physics-based models of the 3-D ionosphere and ionospheric electrodynamics solvers of magnetosphere models that specify Joule heat and empirical models specifying Poynting flux were run for six geomagnetic storm events of varying intensity. We compared model results with Poynting flux values along the DMSP-15 satellite track computed from ion drift meter and magnetic field observations. Although being a different quantity, Joule heat can in practice be correlated to incoming Poynting flux because the energy is dissipated primarily in high latitudes where Poynting flux is being deposited. Within the physics-based model group, we find mixed results with some models overestimating Joule heat and some models agreeing better with observed Poynting flux rates as integrated over auroral passes. In contrast, empirical models tend to underestimate integrated Poynting flux values. Modeled Joule heat or Poynting flux patterns often resemble the observed Poynting flux patterns on a large scale, but amplitudes can differ by a factor of 2 or larger due to the highly localized nature of observed Poynting flux deposition that is not captured by the models. In addition, the positioning of modeled patterns appear to be randomly shifted against the observed Poynting flux energy input. This study is the first to compare Poynting flux and Joule heat in a large variety of models of the ionosphere.
Toward robust phase-locking in Melibe swim central pattern generator models
NASA Astrophysics Data System (ADS)
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.
Immune networks: multitasking capabilities near saturation
NASA Astrophysics Data System (ADS)
Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.
2013-10-01
Pattern-diluted associative networks were recently introduced as models for the immune system, with nodes representing T-lymphocytes and stored patterns representing signalling protocols between T- and B-lymphocytes. It was shown earlier that in the regime of extreme pattern dilution, a system with NT T-lymphocytes can manage a number N_B={ {O}}(N_T^\\delta ) of B-lymphocytes simultaneously, with δ < 1. Here we study this model in the extensive load regime NB = αNT, with a high degree of pattern dilution, in agreement with immunological findings. We use graph theory and statistical mechanical analysis based on replica methods to show that in the finite-connectivity regime, where each T-lymphocyte interacts with a finite number of B-lymphocytes as NT → ∞, the T-lymphocytes can coordinate effective immune responses to an extensive number of distinct antigen invasions in parallel. As α increases, the system eventually undergoes a second order transition to a phase with clonal cross-talk interference, where the system’s performance degrades gracefully. Mathematically, the model is equivalent to a spin system on a finitely connected graph with many short loops, so one would expect the available analytical methods, which all assume locally tree-like graphs, to fail. Yet it turns out to be solvable. Our results are supported by numerical simulations.
Selective sweeps in growing microbial colonies
NASA Astrophysics Data System (ADS)
Korolev, Kirill S.; Müller, Melanie J. I.; Karahan, Nilay; Murray, Andrew W.; Hallatschek, Oskar; Nelson, David R.
2012-04-01
Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.
Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.
2011-01-01
Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710
Multiscale mobility networks and the spatial spreading of infectious diseases.
Balcan, Duygu; Colizza, Vittoria; Gonçalves, Bruno; Hu, Hao; Ramasco, José J; Vespignani, Alessandro
2009-12-22
Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. To study the interplay between short-scale commuting flows and long-range airline traffic in shaping the spatiotemporal pattern of a global epidemic we (i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms and (ii) integrate in a worldwide-structured metapopulation epidemic model a timescale-separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large-scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short-range mobility increases, however, the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multiscale framework.
Sindato, Calvin; Stevens, Kim B.; Karimuribo, Esron D.; Mboera, Leonard E. G.; Paweska, Janusz T.; Pfeiffer, Dirk U.
2016-01-01
Background Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Materials and Methods Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Principal Findings Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). Conclusion/Significance The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics. PMID:27654268
van der Post, Daniel J.; Semmann, Dirk
2011-01-01
Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571
Shen, Lu; Mickley, Loretta J
2017-03-07
We develop a statistical model to predict June-July-August (JJA) daily maximum 8-h average (MDA8) ozone concentrations in the eastern United States based on large-scale climate patterns during the previous spring. We find that anomalously high JJA ozone in the East is correlated with these springtime patterns: warm tropical Atlantic and cold northeast Pacific sea surface temperatures (SSTs), as well as positive sea level pressure (SLP) anomalies over Hawaii and negative SLP anomalies over the Atlantic and North America. We then develop a linear regression model to predict JJA MDA8 ozone from 1980 to 2013, using the identified SST and SLP patterns from the previous spring. The model explains ∼45% of the variability in JJA MDA8 ozone concentrations and ∼30% variability in the number of JJA ozone episodes (>70 ppbv) when averaged over the eastern United States. This seasonal predictability results from large-scale ocean-atmosphere interactions. Warm tropical Atlantic SSTs can trigger diabatic heating in the atmosphere and influence the extratropical climate through stationary wave propagation, leading to greater subsidence, less precipitation, and higher temperatures in the East, which increases surface ozone concentrations there. Cooler SSTs in the northeast Pacific are also associated with more summertime heatwaves and high ozone in the East. On average, models participating in the Atmospheric Model Intercomparison Project fail to capture the influence of this ocean-atmosphere interaction on temperatures in the eastern United States, implying that such models would have difficulty simulating the interannual variability of surface ozone in this region.
Modeling carbachol-induced hippocampal network synchronization using hidden Markov models
NASA Astrophysics Data System (ADS)
Dragomir, Andrei; Akay, Yasemin M.; Akay, Metin
2010-10-01
In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10-4) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.
Mickley, Loretta J.
2017-01-01
We develop a statistical model to predict June–July–August (JJA) daily maximum 8-h average (MDA8) ozone concentrations in the eastern United States based on large-scale climate patterns during the previous spring. We find that anomalously high JJA ozone in the East is correlated with these springtime patterns: warm tropical Atlantic and cold northeast Pacific sea surface temperatures (SSTs), as well as positive sea level pressure (SLP) anomalies over Hawaii and negative SLP anomalies over the Atlantic and North America. We then develop a linear regression model to predict JJA MDA8 ozone from 1980 to 2013, using the identified SST and SLP patterns from the previous spring. The model explains ∼45% of the variability in JJA MDA8 ozone concentrations and ∼30% variability in the number of JJA ozone episodes (>70 ppbv) when averaged over the eastern United States. This seasonal predictability results from large-scale ocean–atmosphere interactions. Warm tropical Atlantic SSTs can trigger diabatic heating in the atmosphere and influence the extratropical climate through stationary wave propagation, leading to greater subsidence, less precipitation, and higher temperatures in the East, which increases surface ozone concentrations there. Cooler SSTs in the northeast Pacific are also associated with more summertime heatwaves and high ozone in the East. On average, models participating in the Atmospheric Model Intercomparison Project fail to capture the influence of this ocean–atmosphere interaction on temperatures in the eastern United States, implying that such models would have difficulty simulating the interannual variability of surface ozone in this region. PMID:28223483
Chuk, Tim; Chan, Antoni B; Hsiao, Janet H
2017-12-01
The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.
Facebook Usage Patterns and School Attitudes
ERIC Educational Resources Information Center
Koles, Bernadett; Nagy, Peter
2012-01-01
Purpose: The purpose of this paper is to explore teenagers' and young adults' use of social networking sites (SNS), in light of certain personal, social and educational outcomes and attitudes. Design/methodology/approach: Data were gathered on the basis of surveys, and were analyzed through a series of multivariate models. Findings: It was found…
Information Seeking Behavior in Digital Image Collections: A Cognitive Approach
ERIC Educational Resources Information Center
Matusiak, Krystyna K.
2006-01-01
Presents the results of a qualitative study that focuses on search patterns of college students and community users interacting with a digital image collection. The study finds a distinct difference between the two groups of users and examines the role of mental models in information seeking behavior in digital libraries.
On wildfire complexity, simple models and environmental templates for fire size distributions
NASA Astrophysics Data System (ADS)
Boer, M. M.; Bradstock, R.; Gill, M.; Sadler, R.
2012-12-01
Vegetation fires affect some 370 Mha annually. At global and continental scales, fire activity follows predictable spatiotemporal patterns driven by gradients and seasonal fluctuations of primary productivity and evaporative demand that set constraints for fuel accumulation rates and fuel dryness, two key ingredients of fire. At regional scales, fires are also known to affect some landscapes more than others and within landscapes to occur preferentially in some sectors (e.g. wind-swept ridges) and rarely in others (e.g. wet gullies). Another common observation is that small fires occur relatively frequent yet collectively burn far less country than relatively infrequent large fires. These patterns of fire activity are well known to management agencies and consistent with their (informal) models of how the basic drivers and constraints of fire (i.e. fuels, ignitions, weather) vary in time and space across the landscape. The statistical behaviour of these landscape fire patterns has excited the (academic) research community by showing some consistency with that of complex dynamical systems poised at a phase transition. The common finding that the frequency-size distributions of actual fires follow power laws that resemble those produced by simple cellular models from statistical mechanics has been interpreted as evidence that flammable landscapes operate as self-organising systems with scale invariant fire size distributions emerging 'spontaneously' from simple rules of contagious fire spread and a strong feedback between fires and fuel patterns. In this paper we argue that the resemblance of simulated and actual fire size distributions is an example of equifinality, that is fires in model landscapes and actual landscapes may show similar statistical behaviour but this is reached by qualitatively different pathways or controlling mechanisms. We support this claim with two key findings regarding simulated fire spread mechanisms and fire-fuel feedbacks. Firstly, we demonstrate that the power law behaviour of fire size distributions in the widely used Drossel and Schwabl (1992) Forest Fire Model (FFM) is strictly conditional on simulating fire spread as a cell-to-cell contagion over a fixed distance; the invariant scaling of fire sizes breaks down under the slightest variation in that distance, suggesting that pattern formation in the FFM is irreconcilable with the reality of disparate rates and modes of fire spread observed in the field. Secondly, we review field evidence showing that fuel age effects on the probability of fire spread, a key assumption in simulation models like the FFM, do not generally apply across flammable environments. Finally, we explore alternative explanations for the formation of scale invariant fire sizes in real landscapes. Using observations from southern Australian forest regions we demonstrate that the spatiotemporal patterns of fuel dryness and magnitudes of fire driving weather events set strong environmental templates for regional fire size distributions.
Jarczok, Marc N; Aguilar-Raab, Corina; Koenig, Julian; Kaess, Michael; Borniger, Jeremy C; Nelson, Randy J; Hall, Martica; Ditzen, Beate; Thayer, Julian F; Fischer, Joachim E
2018-03-15
Successful regulation of emotional states is positively associated to mental health, while difficulties in regulating emotions are negatively associated to overall mental health and in particular associated with anxiety or depression symptoms. A key structure associated to socio-emotional regulatory processes is the central autonomic network. Activity in this structure is associated to vagal activity can be indexed noninvasively and simply by measures of peripheral cardiac autonomic modulations such as heart rate variability. Vagal activity exhibits a circadian variation pattern, with a maximum during nighttime. Depression is known to affect chronobiology. Also, depressive symptoms are known to be associated with decreased resting state vagal activity, but studies investigating the association between circadian variation pattern of vagal activity and depressive symptoms are scarce. We aim to examine these patterns in association to symptom severity of depression using chronobiologic methods. Data from the Manheim Industrial Cohort Studies (MICS) were used. A total of 3,030 predominantly healthy working adults underwent, among others, ambulatory 24-h hear rate-recordings, detailed health examination and online questionnaires and were available for this analysis. The root mean sum of successive differences (RMSSD) was used as an indicator of vagally mediated heart rate variability. Three individual-level cosine function parameters (MESOR, amplitude, acrophase) were estimated to quantify circadian variation pattern. Multivariate linear regression models including important covariates such as age, sex, and lifestyle factors as well as an interaction effect of sex with depressive symptoms were used to estimate the association of circadian variation pattern of vagal activity with depressive symptoms simultaneously. The analysis sample consisted of 20.2% females and an average age 41 with standard deviation of 11 years. Nonparametric bivariate analysis revealed significant MESOR and amplitude differences between the 90 th percentile split, but not on acrophase. Multivariate linear regression models estimated depressive symptoms to be negatively associated with the 24h mean (MESOR) and oscillation amplitude in men but positively associated in women. This pattern of findings indicates a blunted day-night rhythm of vagal activity in men with greater depressive symptoms as well as a moderation effect of sex in the association of CVP and depressive symptoms. This is the first study investigating circadian variation pattern by mild depressive symptoms in a large, rather healthy occupational sample. Depressive symptoms were associated with decreased circadian variation pattern of vagal activity in men but with increased circadian variation pattern in women. The possible underlying mechanism(s) are discussed using the neurovisceral integration model. These findings may have implications for the knowledge on etiology, diagnosis, course, and treatment of depressive symptoms and thus may be of significant public health relevance.
NASA Astrophysics Data System (ADS)
Bonilla Villarreal, Isaura Nathaly
While international academic and research collaborations are of great importance at this time, it is not easy to find researchers in the engineering field that publish in languages other than English. Because of this disconnect, there exists a need for a portal to find Who's Who in Engineering Education in the Americas. The objective of this thesis is to built an object-oriented architecture for this proposed portal. The Unified Modeling Language (UML) model developed in this thesis incorporates the basic structure of a social network for academic purposes. Reverse engineering of three social networks portals yielded important aspects of their structures that have been incorporated in the proposed UML model. Furthermore, the present work includes a pattern for academic social networks..
Lanham, Holly Jordan; Sittig, Dean F; Leykum, Luci K; Parchman, Michael L; Pugh, Jacqueline A; McDaniel, Reuben R
2014-01-01
Electronic health records (EHR) hold great promise for managing patient information in ways that improve healthcare delivery. Physicians differ, however, in their use of this health information technology (IT), and these differences are not well understood. The authors study the differences in individual physicians' EHR use patterns and identify perceptions of uncertainty as an important new variable in understanding EHR use. Qualitative study using semi-structured interviews and direct observation of physicians (n=28) working in a multispecialty outpatient care organization. We identified physicians' perceptions of uncertainty as an important variable in understanding differences in EHR use patterns. Drawing on theories from the medical and organizational literatures, we identified three categories of perceptions of uncertainty: reduction, absorption, and hybrid. We used an existing model of EHR use to categorize physician EHR use patterns as high, medium, and low based on degree of feature use, level of EHR-enabled communication, and frequency that EHR use patterns change. Physicians' perceptions of uncertainty were distinctly associated with their EHR use patterns. Uncertainty reductionists tended to exhibit high levels of EHR use, uncertainty absorbers tended to exhibit low levels of EHR use, and physicians demonstrating both perspectives of uncertainty (hybrids) tended to exhibit medium levels of EHR use. We find evidence linking physicians' perceptions of uncertainty with EHR use patterns. Study findings have implications for health IT research, practice, and policy, particularly in terms of impacting health IT design and implementation efforts in ways that consider differences in physicians' perceptions of uncertainty.
Formation and maintenance of nitrogen-fixing cell patterns in filamentous cyanobacteria.
Muñoz-García, Javier; Ares, Saúl
2016-05-31
Cyanobacteria forming one-dimensional filaments are paradigmatic model organisms of the transition between unicellular and multicellular living forms. Under nitrogen-limiting conditions, in filaments of the genus Anabaena, some cells differentiate into heterocysts, which lose the possibility to divide but are able to fix environmental nitrogen for the colony. These heterocysts form a quasiregular pattern in the filament, representing a prototype of patterning and morphogenesis in prokaryotes. Recent years have seen advances in the identification of the molecular mechanism regulating this pattern. We use these data to build a theory on heterocyst pattern formation, for which both genetic regulation and the effects of cell division and filament growth are key components. The theory is based on the interplay of three generic mechanisms: local autoactivation, early long-range inhibition, and late long-range inhibition. These mechanisms can be identified with the dynamics of hetR, patS, and hetN expression. Our theory reproduces quantitatively the experimental dynamics of pattern formation and maintenance for wild type and mutants. We find that hetN alone is not enough to play the role as the late inhibitory mechanism: a second mechanism, hypothetically the products of nitrogen fixation supplied by heterocysts, must also play a role in late long-range inhibition. The preponderance of even intervals between heterocysts arises naturally as a result of the interplay between the timescales of genetic regulation and cell division. We also find that a purely stochastic initiation of the pattern, without a two-stage process, is enough to reproduce experimental observations.
Pattern Finding Skills of Pre-School Children
ERIC Educational Resources Information Center
Tarim, Kamuran
2017-01-01
This study investigates the pattern finding skills of pre-school children and the in-class pattern activities conducted by teachers. The research was designed as a descriptive survey study carried out with a total of 162 children aged 60-77 months from families with middle socio-economic status. The findings of the study revealed that the…
Effective robotic assistive pattern of treadmill training for spinal cord injury in a rat model
Zhao, Bo-Lun; Li, Wen-Tao; Zhou, Xiao-Hua; Wu, Su-Qian; Cao, Hong-Shi; Bao, Zhu-Ren; An, Li-Bin
2018-01-01
The purpose of the present study was to establish an effective robotic assistive stepping pattern of body-weight-supported treadmill training based on a rat spinal cord injury (SCI) model and assess the effect by comparing this with another frequently used assistive stepping pattern. The recorded stepping patterns of both hind limbs of trained intact rats were edited to establish a 30-sec playback normal rat stepping pattern (NRSP). Step features (step length, step height, step number and swing duration), BBB scores, latencies, and amplitudes of the transcranial electrical motor-evoked potentials (tceMEPs) and neurofilament 200 (NF200) expression in the spinal cord lesion area during and after 3 weeks of body-weight-supported treadmill training (BWSTT) were compared in rats with spinal contusion receiving NRSP assistance (NRSPA) and those that received manual assistance (MA). Hind limb stepping performance among rats receiving NRSPA during BWSTT was greater than that among rats receiving MA in terms of longer step length, taller step height, and longer swing duration. Furthermore a higher BBB score was also indicated. The rats in the NRSPA group achieved superior results in the tceMEPs assessment and greater NF200 expression in the spinal cord lesion area compared with the rats in the MA group. These findings suggest NRSPA was an effective assistive pattern of treadmill training compared with MA based on the rat SCI model and this approach could be used as a new platform for animal experiments for better understanding the mechanisms of SCI rehabilitation. PMID:29545846
The Kunming CalFit study: modeling dietary behavioral patterns using smartphone data.
Seto, Edmund; Hua, Jenna; Wu, Lemuel; Bestick, Aaron; Shia, Victor; Eom, Sue; Han, Jay; Wang, May; Li, Yan
2014-01-01
Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can facilitate various forms of user feedback for intervention studies. We describe our findings from a smartphone-based study, in which an Android-based application we developed called CalFit was used to collect information related to young adults' dietary behaviors. In addition to monitoring dietary patterns, we were interested in understanding contextual factors related to when and where an individual eats, as well as how their dietary intake relates to physical activity (which creates energy demand) and psychosocial stress. 12 participants were asked to use CalFit to record videos of their meals over two 1-week periods, which were translated into nutrient intake by trained dietitians. During this same period, triaxial accelerometry was used to assess each subject's energy expenditure, and GPS was used to record time-location patterns. Ecological momentary assessment was also used to prompt subjects to respond to questions on their phone about their psychological state. The GPS data were processed through a web service we developed called Foodscoremap that is based on the Google Places API to characterize food environments that subjects were exposed to, which may explain and influence dietary patterns. Furthermore, we describe a modeling framework that incorporates all of these information to dynamically infer behavioral patterns that may be used for future intervention studies.
2007-01-01
Background The usage of synonymous codons shows considerable variation among mammalian genes. How and why this usage is non-random are fundamental biological questions and remain controversial. It is also important to explore whether mammalian genes that are selectively expressed at different developmental stages bear different molecular features. Results In two models of mouse stem cell differentiation, we established correlations between codon usage and the patterns of gene expression. We found that the optimal codons exhibited variation (AT- or GC-ending codons) in different cell types within the developmental hierarchy. We also found that genes that were enriched (developmental-pivotal genes) or specifically expressed (developmental-specific genes) at different developmental stages had different patterns of codon usage and local genomic GC (GCg) content. Moreover, at the same developmental stage, developmental-specific genes generally used more GC-ending codons and had higher GCg content compared with developmental-pivotal genes. Further analyses suggest that the model of translational selection might be consistent with the developmental stage-related patterns of codon usage, especially for the AT-ending optimal codons. In addition, our data show that after human-mouse divergence, the influence of selective constraints is still detectable. Conclusion Our findings suggest that developmental stage-related patterns of gene expression are correlated with codon usage (GC3) and GCg content in stem cell hierarchies. Moreover, this paper provides evidence for the influence of natural selection at synonymous sites in the mouse genome and novel clues for linking the molecular features of genes to their patterns of expression during mammalian ontogenesis. PMID:17349061
Attempting to physically explain space-time correlation of extremes
NASA Astrophysics Data System (ADS)
Bernardara, Pietro; Gailhard, Joel
2010-05-01
Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.
NASA Astrophysics Data System (ADS)
Armour, K.
2017-12-01
Global energy budget observations have been widely used to constrain the effective, or instantaneous climate sensitivity (ICS), producing median estimates around 2°C (Otto et al. 2013; Lewis & Curry 2015). A key question is whether the comprehensive climate models used to project future warming are consistent with these energy budget estimates of ICS. Yet, performing such comparisons has proven challenging. Within models, values of ICS robustly vary over time, as surface temperature patterns evolve with transient warming, and are generally smaller than the values of equilibrium climate sensitivity (ECS). Naively comparing values of ECS in CMIP5 models (median of about 3.4°C) to observation-based values of ICS has led to the suggestion that models are overly sensitive. This apparent discrepancy can partially be resolved by (i) comparing observation-based values of ICS to model values of ICS relevant for historical warming (Armour 2017; Proistosescu & Huybers 2017); (ii) taking into account the "efficacies" of non-CO2 radiative forcing agents (Marvel et al. 2015); and (iii) accounting for the sparseness of historical temperature observations and differences in sea-surface temperature and near-surface air temperature over the oceans (Richardson et al. 2016). Another potential source of discrepancy is a mismatch between observed and simulated surface temperature patterns over recent decades, due to either natural variability or model deficiencies in simulating historical warming patterns. The nature of the mismatch is such that simulated patterns can lead to more positive radiative feedbacks (higher ICS) relative to those engendered by observed patterns. The magnitude of this effect has not yet been addressed. Here we outline an approach to perform fully commensurate comparisons of climate models with global energy budget observations that take all of the above effects into account. We find that when apples-to-apples comparisons are made, values of ICS in models are consistently in good agreement with values of ICS inferred from global energy budget constraints. This suggests that the current generation of coupled climate models are not overly sensitive. However, since global energy budget observations do not constrain ECS, it is less certain whether model ECS values are realistic.
Cobb, Alexander R; Hoyt, Alison M; Gandois, Laure; Eri, Jangarun; Dommain, René; Abu Salim, Kamariah; Kai, Fuu Ming; Haji Su'ut, Nur Salihah; Harvey, Charles F
2017-06-27
Tropical peatlands now emit hundreds of megatons of carbon dioxide per year because of human disruption of the feedbacks that link peat accumulation and groundwater hydrology. However, no quantitative theory has existed for how patterns of carbon storage and release accompanying growth and subsidence of tropical peatlands are affected by climate and disturbance. Using comprehensive data from a pristine peatland in Brunei Darussalam, we show how rainfall and groundwater flow determine a shape parameter (the Laplacian of the peat surface elevation) that specifies, under a given rainfall regime, the ultimate, stable morphology, and hence carbon storage, of a tropical peatland within a network of rivers or canals. We find that peatlands reach their ultimate shape first at the edges of peat domes where they are bounded by rivers, so that the rate of carbon uptake accompanying their growth is proportional to the area of the still-growing dome interior. We use this model to study how tropical peatland carbon storage and fluxes are controlled by changes in climate, sea level, and drainage networks. We find that fluctuations in net precipitation on timescales from hours to years can reduce long-term peat accumulation. Our mathematical and numerical models can be used to predict long-term effects of changes in temporal rainfall patterns and drainage networks on tropical peatland geomorphology and carbon storage.
Hoyt, Alison M.; Gandois, Laure; Eri, Jangarun; Dommain, René; Abu Salim, Kamariah; Kai, Fuu Ming; Haji Su’ut, Nur Salihah; Harvey, Charles F.
2017-01-01
Tropical peatlands now emit hundreds of megatons of carbon dioxide per year because of human disruption of the feedbacks that link peat accumulation and groundwater hydrology. However, no quantitative theory has existed for how patterns of carbon storage and release accompanying growth and subsidence of tropical peatlands are affected by climate and disturbance. Using comprehensive data from a pristine peatland in Brunei Darussalam, we show how rainfall and groundwater flow determine a shape parameter (the Laplacian of the peat surface elevation) that specifies, under a given rainfall regime, the ultimate, stable morphology, and hence carbon storage, of a tropical peatland within a network of rivers or canals. We find that peatlands reach their ultimate shape first at the edges of peat domes where they are bounded by rivers, so that the rate of carbon uptake accompanying their growth is proportional to the area of the still-growing dome interior. We use this model to study how tropical peatland carbon storage and fluxes are controlled by changes in climate, sea level, and drainage networks. We find that fluctuations in net precipitation on timescales from hours to years can reduce long-term peat accumulation. Our mathematical and numerical models can be used to predict long-term effects of changes in temporal rainfall patterns and drainage networks on tropical peatland geomorphology and carbon storage. PMID:28607068
Model of Tooth Morphogenesis Predicts Carabelli Cusp Expression, Size, and Symmetry in Humans
Hunter, John P.; Guatelli-Steinberg, Debbie; Weston, Theresia C.; Durner, Ryan; Betsinger, Tracy K.
2010-01-01
Background The patterning cascade model of tooth morphogenesis accounts for shape development through the interaction of a small number of genes. In the model, gene expression both directs development and is controlled by the shape of developing teeth. Enamel knots (zones of nonproliferating epithelium) mark the future sites of cusps. In order to form, a new enamel knot must escape the inhibitory fields surrounding other enamel knots before crown components become spatially fixed as morphogenesis ceases. Because cusp location on a fully formed tooth reflects enamel knot placement and tooth size is limited by the cessation of morphogenesis, the model predicts that cusp expression varies with intercusp spacing relative to tooth size. Although previous studies in humans have supported the model's implications, here we directly test the model's predictions for the expression, size, and symmetry of Carabelli cusp, a variation present in many human populations. Methodology/Principal Findings In a dental cast sample of upper first molars (M1s) (187 rights, 189 lefts, and 185 antimeric pairs), we measured tooth area and intercusp distances with a Hirox digital microscope. We assessed Carabelli expression quantitatively as an area in a subsample and qualitatively using two typological schemes in the full sample. As predicted, low relative intercusp distance is associated with Carabelli expression in both right and left samples using either qualitative or quantitative measures. Furthermore, asymmetry in Carabelli area is associated with asymmetry in relative intercusp spacing. Conclusions/Significance These findings support the model's predictions for Carabelli cusp expression both across and within individuals. By comparing right-left pairs of the same individual, our data show that small variations in developmental timing or spacing of enamel knots can influence cusp pattern independently of genotype. Our findings suggest that during evolution new cusps may first appear as a result of small changes in the spacing of enamel knots relative to crown size. PMID:20689576
Early Math Trajectories: Low-Income Children's Mathematics Knowledge From Ages 4 to 11.
Rittle-Johnson, Bethany; Fyfe, Emily R; Hofer, Kerry G; Farran, Dale C
2017-09-01
Early mathematics knowledge is a strong predictor of later academic achievement, but children from low-income families enter school with weak mathematics knowledge. An early math trajectories model is proposed and evaluated within a longitudinal study of 517 low-income American children from ages 4 to 11. This model includes a broad range of math topics, as well as potential pathways from preschool to middle grades mathematics achievement. In preschool, nonsymbolic quantity, counting, and patterning knowledge predicted fifth-grade mathematics achievement. By the end of first grade, symbolic mapping, calculation, and patterning knowledge were the important predictors. Furthermore, the first-grade predictors mediated the relation between preschool math knowledge and fifth-grade mathematics achievement. Findings support the early math trajectories model among low-income children. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.
Range expansion through fragmented landscapes under a variable climate
Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J
2013-01-01
Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124
Modelled drift patterns of fish larvae link coastal morphology to seabird colony distribution.
Sandvik, Hanno; Barrett, Robert T; Erikstad, Kjell Einar; Myksvoll, Mari S; Vikebø, Frode; Yoccoz, Nigel G; Anker-Nilssen, Tycho; Lorentsen, Svein-Håkon; Reiertsen, Tone K; Skarðhamar, Jofrid; Skern-Mauritzen, Mette; Systad, Geir Helge
2016-05-13
Colonial breeding is an evolutionary puzzle, as the benefits of breeding in high densities are still not fully explained. Although the dynamics of existing colonies are increasingly understood, few studies have addressed the initial formation of colonies, and empirical tests are rare. Using a high-resolution larval drift model, we here document that the distribution of seabird colonies along the Norwegian coast can be explained by variations in the availability and predictability of fish larvae. The modelled variability in concentration of fish larvae is, in turn, predicted by the topography of the continental shelf and coastline. The advection of fish larvae along the coast translates small-scale topographic characteristics into a macroecological pattern, viz. the spatial distribution of top-predator breeding sites. Our findings provide empirical corroboration of the hypothesis that seabird colonies are founded in locations that minimize travel distances between breeding and foraging locations, thereby enabling optimal foraging by central-place foragers.
Neuroendocrine and immune network re-modeling in chronic fatigue syndrome: an exploratory analysis.
Fuite, Jim; Vernon, Suzanne D; Broderick, Gordon
2008-12-01
This work investigates the significance of changes in association patterns linking indicators of neuroendocrine and immune activity in patients with chronic fatigue syndrome (CFS). Gene sets preferentially expressed in specific immune cell isolates were integrated with neuroendocrine data from a large population-based study. Co-expression patterns linking immune cell activity with hypothalamic-pituitary-adrenal (HPA), thyroidal (HPT) and gonadal (HPG) axis status were computed using mutual information criteria. Networks in control and CFS subjects were compared globally in terms of a weighted graph edit distance. Local re-modeling of node connectivity was quantified by node degree and eigenvector centrality measures. Results indicate statistically significant differences between CFS and control networks determined mainly by re-modeling around pituitary and thyroid nodes as well as an emergent immune sub-network. Findings align with known mechanisms of chronic inflammation and support possible immune-mediated loss of thyroid function in CFS exacerbated by blunted HPA axis responsiveness.
Taylor, Jeremy J; Grant, Kathryn E; Amrhein, Kelly; Carter, Jocelyn Smith; Farahmand, Farahnaz; Harrison, Aubrey; Thomas, Kina J; Carleton, Russell A; Lugo-Hernandez, Eduardo; Katz, Brian N
2014-12-01
The current study used confirmatory factor analysis (CFA) to compare the fit of 2 factor structures for the Children's Depression Inventory (CDI) in an urban community sample of low-income youth. Results suggest that the 6-factor model developed by Craighead and colleagues (1998) was a strong fit to the pattern of symptoms reported by low-income urban youth and was a superior fit with these data than the original 5-factor model of the CDI (Kovacs, 1992). Additionally, results indicated that all 6 factors from the Craighead model contributed to the measurement of depression, including School Problems and Externalizing Problems especially for older adolescents. This pattern of findings may reflect distinct contextual influences of urban poverty on the manifestation and measurement of depression in youth. (c) 2014 APA, all rights reserved.
The Sensitivity of the Crayfish Reward System to Mammalian Drugs of Abuse.
Shipley, Adam T; Imeh-Nathaniel, Adebobola; Orfanakos, Vasiliki B; Wormack, Leah N; Huber, Robert; Nathaniel, Thomas I
2017-01-01
The idea that addiction occurs when the brain is not able to differentiate whether specific reward circuits were triggered by adaptive natural rewards or falsely activated by addictive drugs exist in several models of drug addiction. The suitability of crayfish ( Orconectes rusticus ) for drug addiction research arises from developmental variation of growth, life span, reproduction, behavior and some quantitative traits, especially among isogenic mates reared in the same environment. This broad spectrum of traits makes it easier to analyze the effect of mammalian drugs of abuse in shaping behavioral phenotype. Moreover, the broad behavioral repertoire allows the investigation of self-reinforcing circuitries involving appetitive and exploratory motor behavior, while the step-wise alteration of the phenotype by metamorphosis allows accurate longitudinal analysis of different behavioral states. This paper reviews a series of recent experimental findings that evidence the suitability of crayfish as an invertebrate model system for the study of drug addiction. Results from these studies reveal that unconditioned exposure to mammalian drugs of abuse produces a variety of stereotyped behaviors. Moreover, if presented in the context of novelty, drugs directly stimulate exploration and appetitive motor patterns along with molecular processes for drug conditioned reward. Findings from these studies indicate the existence of drug sensitive circuitry in crayfish that facilitates exploratory behavior and appetitive motor patterns via increased incentive salience of environmental stimuli or by increasing exploratory motor patterns. This work demonstrates the potential of crayfish as a model system for research into the neural mechanisms of addiction, by contributing an evolutionary, comparative context to our understanding of natural reward as an important life-sustaining process.
Requirement for Jagged1-Notch2 signaling in patterning the bones of the mouse and human middle ear.
Teng, Camilla S; Yen, Hai-Yun; Barske, Lindsey; Smith, Bea; Llamas, Juan; Segil, Neil; Go, John; Sanchez-Lara, Pedro A; Maxson, Robert E; Crump, J Gage
2017-05-31
Whereas Jagged1-Notch2 signaling is known to pattern the sensorineural components of the inner ear, its role in middle ear development has been less clear. We previously reported a role for Jagged-Notch signaling in shaping skeletal elements derived from the first two pharyngeal arches of zebrafish. Here we show a conserved requirement for Jagged1-Notch2 signaling in patterning the stapes and incus middle ear bones derived from the equivalent pharyngeal arches of mammals. Mice lacking Jagged1 or Notch2 in neural crest-derived cells (NCCs) of the pharyngeal arches display a malformed stapes. Heterozygous Jagged1 knockout mice, a model for Alagille Syndrome (AGS), also display stapes and incus defects. We find that Jagged1-Notch2 signaling functions early to pattern the stapes cartilage template, with stapes malformations correlating with hearing loss across all frequencies. We observe similar stapes defects and hearing loss in one patient with heterozygous JAGGED1 loss, and a diversity of conductive and sensorineural hearing loss in nearly half of AGS patients, many of which carry JAGGED1 mutations. Our findings reveal deep conservation of Jagged1-Notch2 signaling in patterning the pharyngeal arches from fish to mouse to man, despite the very different functions of their skeletal derivatives in jaw support and sound transduction.
Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception.
Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil
2017-01-01
Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness.
NASA Astrophysics Data System (ADS)
Jiao, Yang; Lau, Timothy; Hatzikirou, Haralampos; Meyer-Hermann, Michael; Corbo, Joseph C.; Torquato, Salvatore
2014-02-01
Optimal spatial sampling of light rigorously requires that identical photoreceptors be arranged in perfectly regular arrays in two dimensions. Examples of such perfect arrays in nature include the compound eyes of insects and the nearly crystalline photoreceptor patterns of some fish and reptiles. Birds are highly visual animals with five different cone photoreceptor subtypes, yet their photoreceptor patterns are not perfectly regular. By analyzing the chicken cone photoreceptor system consisting of five different cell types using a variety of sensitive microstructural descriptors, we find that the disordered photoreceptor patterns are "hyperuniform" (exhibiting vanishing infinite-wavelength density fluctuations), a property that had heretofore been identified in a unique subset of physical systems, but had never been observed in any living organism. Remarkably, the patterns of both the total population and the individual cell types are simultaneously hyperuniform. We term such patterns "multihyperuniform" because multiple distinct subsets of the overall point pattern are themselves hyperuniform. We have devised a unique multiscale cell packing model in two dimensions that suggests that photoreceptor types interact with both short- and long-ranged repulsive forces and that the resultant competition between the types gives rise to the aforementioned singular spatial features characterizing the system, including multihyperuniformity. These findings suggest that a disordered hyperuniform pattern may represent the most uniform sampling arrangement attainable in the avian system, given intrinsic packing constraints within the photoreceptor epithelium. In addition, they show how fundamental physical constraints can change the course of a biological optimization process. Our results suggest that multihyperuniform disordered structures have implications for the design of materials with novel physical properties and therefore may represent a fruitful area for future research.
Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception
Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil
2017-01-01
Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171
Staunton, Kyran M; Robson, Simon K A; Burwell, Chris J; Reside, April E; Williams, Stephen E
2014-01-01
With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group's primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region.
Staunton, Kyran M.; Robson, Simon K. A.; Burwell, Chris J.; Reside, April E.; Williams, Stephen E.
2014-01-01
With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group’s primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region. PMID:24586362
Demand-Withdraw Patterns in Marital Conflict in the Home.
Papp, Lauren M; Kouros, Chrystyna D; Cummings, E Mark
2009-06-01
The present study extended laboratory-based findings of demand-withdraw communication into marital conflict in the home and further explored its linkages with spousal depression. U.S. couples (N = 116) provided diary reports of marital conflict and rated depressive symptoms. Hierarchical linear modeling results indicated that husband demand-wife withdraw and wife demand-husband withdraw occurred in the home at equal frequency, and both were more likely to occur when discussing topics that concerned the marital relationship. For both patterns, conflict initiator was positively linked to the demander role. Accounting for marital satisfaction, both demand-withdraw patterns predicted negative emotions and tactics during marital interactions and lower levels of conflict resolution. Spousal depression was linked to increased likelihood of husband demand-wife withdraw.
Star-Shaped Crack Pattern of Broken Windows
NASA Astrophysics Data System (ADS)
Vandenberghe, Nicolas; Vermorel, Romain; Villermaux, Emmanuel
2013-04-01
Broken thin brittle plates like windows and windshields are ubiquitous in our environment. When impacted locally, they typically present a pattern of cracks extending radially outward from the impact point. We study the variation of the pattern of cracks by performing controlled transverse impacts on brittle plates over a broad range of impact speed, plate thickness, and material properties, and we establish from experiments a global scaling law for the number of radial cracks incorporating all these parameters. A model based on Griffith’s theory of fracture combining bending elastic energy and fracture energy accounts for our observations. These findings indicate how the postmortem shape of broken samples are related to material properties and impact parameters, a procedure relevant to forensic science, archaeology, or astrophysics.
Nonlinear Dynamics, Noise and Cooperative Behavior in Affective Disorders
NASA Astrophysics Data System (ADS)
Huber, Martin
2001-03-01
Mood disorders tend to be recurrent and progressive and illness patterns typically evolve from isolated episodes at the beginning to more rapid, rhythmic and finally irregular "chaotic" mood patterns. This chararacteristic timecourse prompted the consideration of nonlinear dynamics as a way to describe and analyze course and disease states of mood disorders. Indeed, some evidences now exist indicating that low-dimensional dynamics underly the illness progression. To gain an understanding of prinicple mechanisms that might underly the course and disease patterns of mood disorders, we developed a phenomenological mathematical model for the disease course. In doing so, we made use of a neuronal analogy that exists between disease patterns and neuronal spike patterns and which is commonly referred to as the kindling model of mood disorders (Post, Am J of Psychiatry 1992,149:999-1010; Huber, Braun, Krieg, Biol Psychiatry 1999,46:256-262; Huber, Braun, Krieg, Biol Psychiatry 2000,47:634-642). Using a computational implementation of this approach we investigated the possible relevance of nonlinear dynamics for the disease course, the role of cooperative interactions between nonlinear and noisy dynamics as well as the effect of sensitization mechanisms between disease episodes and disease system. Our simulations show that a low-dimensional model can phenomenologically map the timecourse of mood disorders. From a functional perspective, the model indicates an important role for stochastic fluctuations which can amplify subthreshold states into disease states and can induce transitions to irregular rapidly changing disease patterns. Interesting dynamics are observed with respect to deterministically defined disease states and their dependence on noise intensity. Finally, our simulations show how sensitization effects quite naturally lead to a disease course which ends in irregular fluctuating disease patterns as observed in clinical data. Our findings indicate the usefulness of a computational approach as a way to understand and explain the complexity of temporal disease dynamics of mood disorders but also to procede to new experimental approaches for disease characterisation with the aim of better treatment options.
Horst, Fabian; Eekhoff, Alexander; Newell, Karl M; Schöllhorn, Wolfgang I
2017-01-01
Traditionally, gait analysis has been centered on the idea of average behavior and normality. On one hand, clinical diagnoses and therapeutic interventions typically assume that average gait patterns remain constant over time. On the other hand, it is well known that all our movements are accompanied by a certain amount of variability, which does not allow us to make two identical steps. The purpose of this study was to examine changes in the intra-individual gait patterns across different time-scales (i.e., tens-of-mins, tens-of-hours). Nine healthy subjects performed 15 gait trials at a self-selected speed on 6 sessions within one day (duration between two subsequent sessions from 10 to 90 mins). For each trial, time-continuous ground reaction forces and lower body joint angles were measured. A supervised learning model using a kernel-based discriminant regression was applied for classifying sessions within individual gait patterns. Discernable characteristics of intra-individual gait patterns could be distinguished between repeated sessions by classification rates of 67.8 ± 8.8% and 86.3 ± 7.9% for the six-session-classification of ground reaction forces and lower body joint angles, respectively. Furthermore, the one-on-one-classification showed that increasing classification rates go along with increasing time durations between two sessions and indicate that changes of gait patterns appear at different time-scales. Discernable characteristics between repeated sessions indicate continuous intrinsic changes in intra-individual gait patterns and suggest a predominant role of deterministic processes in human motor control and learning. Natural changes of gait patterns without any externally induced injury or intervention may reflect continuous adaptations of the motor system over several time-scales. Accordingly, the modelling of walking by means of average gait patterns that are assumed to be near constant over time needs to be reconsidered in the context of these findings, especially towards more individualized and situational diagnoses and therapy.
Miller, Jonas G.; Chocol, Caroline; Nuselovici, Jacob N.; Utendale, William T.; Simard, Melissa; Hastings, Paul D.
2014-01-01
This study examined the moderating effects of child temperament on the association between maternal socialization and 4–6-year-old children’s dynamic respiratory sinus arrhythmia (RSA) change in response to anger-themed emotional materials (N = 180). We used latent growth curve modeling to explore adaptive patterns of dynamic RSA change in response to anger. Greater change in RSA during anger-induction, characterized by more initial RSA suppression and a subsequent return to baseline, was related to children’s better regulation of aggression. For anger-themed materials, low levels of authoritarian parenting predicted more RSA suppression and recovery for more anger-prone children, whereas more authoritative parenting predicted more RSA suppression and recovery for less anger-prone children. These findings suggest that children’s adaptive patterns of dynamic RSA change can be characterized by latent growth curve modeling, and that these patterns may be differentially shaped by parent socialization experiences as a function of child temperament. PMID:23274169
NASA Astrophysics Data System (ADS)
Wamba, Etienne; Tchakoutio Nguetcho, Aurélien S.
2018-05-01
We use the time-dependent variational method to examine the formation of localized patterns in dynamically unstable anharmonic lattices with cubic-quintic nonlinearities and fourth-order dispersion. The governing equation is an extended nonlinear Schrödinger equation known for modified Frankel-Kontorova models of atomic lattices and here derived from an extended Bose-Hubbard model of bosonic lattices with local three-body interactions. In presence of modulated waves, we derive and investigate the ordinary differential equations for the time evolution of the amplitude and phase of dynamical perturbation. Through an effective potential, we find the modulationally unstable domains of the lattice and discuss the effect of the fourth-order dispersion in the dynamics. Direct numerical simulations are performed to support our analytical results, and a good agreement is found. Various types of localized patterns, including breathers and solitonic chirped-like pulses, form in the system as a result of interplay between the cubic-quintic nonlinearities and the second- and fourth-order dispersions.
Detection of quantum well induced single degenerate-transition-dipoles in ZnO nanorods.
Ghosh, Siddharth; Ghosh, Moumita; Seibt, Michael; Rao, G Mohan
2016-02-07
Quantifying and characterising atomic defects in nanocrystals is difficult and low-throughput using the existing methods such as high resolution transmission electron microscopy (HRTEM). In this article, using a defocused wide-field optical imaging technique, we demonstrate that a single ultrahigh-piezoelectric ZnO nanorod contains a single defect site. We model the observed dipole-emission patterns from optical imaging with a multi-dimensional dipole and find that the experimentally observed dipole pattern and model-calculated patterns are in excellent agreement. This agreement suggests the presence of vertically oriented degenerate-transition-dipoles in vertically aligned ZnO nanorods. The HRTEM of the ZnO nanorod shows the presence of a stacking fault, which generates a localised quantum well induced degenerate-transition-dipole. Finally, we elucidate that defocused wide-field imaging can be widely used to characterise defects in nanomaterials to answer many difficult questions concerning the performance of low-dimensional devices, such as in energy harvesting, advanced metal-oxide-semiconductor storage, and nanoelectromechanical and nanophotonic devices.
Phase transition of traveling waves in bacterial colony pattern
NASA Astrophysics Data System (ADS)
Wakano, Joe Yuichiro; Komoto, Atsushi; Yamaguchi, Yukio
2004-05-01
Depending on the growth condition, bacterial colonies can exhibit different morphologies. Many previous studies have used reaction diffusion equations to reproduce spatial patterns. They have revealed that nonlinear reaction term can produce diverse patterns as well as nonlinear diffusion coefficient. Typical reaction term consists of nutrient consumption, bacterial reproduction, and sporulation. Among them, the functional form of sporulation rate has not been biologically investigated. Here we report experimentally measured sporulation rate. Then, based on the result, a reaction diffusion model is proposed. One-dimensional simulation showed the existence of traveling wave solution. We study the wave form as a function of the initial nutrient concentration and find two distinct types of solution. Moreover, transition between them is very sharp, which is analogous to phase transition. The velocity of traveling wave also shows sharp transition in nonlinear diffusion model, which is consistent with the previous experimental result. The phenomenon can be explained by separatrix in reaction term dynamics. Results of two-dimensional simulation are also shown and discussed.
A Transactional Model of Sleep–Wake Regulation in Infants Born Preterm or Low Birthweight
Poehlmann, Julie
2009-01-01
Objective To test a transactional model of sleep–wake development in infants born preterm or low birthweight (PT LBW), which may inform clinical practice, interventions, and future research in this at risk population. Methods One hundred and twenty-eight mother–infant dyads participated from hospital discharge to 4 months postterm. Assessments of prematurity, infant sleep–wake patterns, maternal interaction quality, depression, feeding route, and sociodemographic factors were conducted. Results Path analyses revealed that maternal interactions directly related to infant sleep patterns and family sociodemographic risks related to less optimal parenting. In addition, bottle fed infants experienced fewer night wakings and more nighttime sleep. Conclusions Two potential pathways to sleep patterns in PT LBW infants were identified. The findings suggest directions for clinical work, such as supporting healthy infant sleep through parenting interventions or supporting interpersonal relations between parents and their PT LBW infants by encouraging more daytime naps. Additionally, clinicians should assess parents’ nighttime sleep concerns within the larger sociodemographic and feeding context. PMID:19098064
Miller, Jonas G; Chocol, Caroline; Nuselovici, Jacob N; Utendale, William T; Simard, Melissa; Hastings, Paul D
2013-02-01
This study examined the moderating effects of child temperament on the association between maternal socialization and 4-6-year-old children's dynamic respiratory sinus arrhythmia (RSA) change in response to anger-themed emotional materials (N=180). We used latent growth curve modeling to explore adaptive patterns of dynamic RSA change in response to anger. Greater change in RSA during anger-induction, characterized by more initial RSA suppression and a subsequent return to baseline, was related to children's better regulation of aggression. For anger-themed materials, low levels of authoritarian parenting predicted more RSA suppression and recovery for more anger-prone children, whereas more authoritative parenting predicted more RSA suppression and recovery for less anger-prone children. These findings suggest that children's adaptive patterns of dynamic RSA change can be characterized by latent growth curve modeling, and that these patterns may be differentially shaped by parent socialization experiences as a function of child temperament. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Cram, J. A.; Weber, T. S.; Leung, S.; Deutsch, C. A.
2016-02-01
New analyses of geochemical tracer data detect significant differences between ocean basins in the depth scale of particle remineralization, with deepest in high latitudes, shallowest in the subtropical gyres, and intermediate in the tropics. We evaluate the possible causes of this pattern using a mechanistic model of particle dynamics that includes microbial colonization, detachment, and degradation of sinking particles. The model represents the size structure of particles, the effects of mineral ballast (diagnosed from alkalinity and silicate distributions) and seawater temperature (which influences particle velocity and microbial metabolic rates). We find that diagnosed spatial patterns in particle flux profiles can be best reproduced through a combination of surface particle size distribution and temperature, which both favor low transfer efficiency in subtropical gyres, and high transfer efficiency in higher latitudes and intermediate tropical values. Particle mineral content is shown to significantly modulate these patterns, albeit with a high remaining uncertainty. Implications of these mechanisms for changes in biological carbon storage in a warmer ocean are examined.
Three tiers of genome evolution in reptiles
Organ, Chris L.; Moreno, Ricardo Godínez; Edwards, Scott V.
2008-01-01
Characterization of reptilian genomes is essential for understanding the overall diversity and evolution of amniote genomes, because reptiles, which include birds, constitute a major fraction of the amniote evolutionary tree. To better understand the evolution and diversity of genomic characteristics in Reptilia, we conducted comparative analyses of online sequence data from Alligator mississippiensis (alligator) and Sphenodon punctatus (tuatara) as well as genome size and karyological data from a wide range of reptilian species. At the whole-genome and chromosomal tiers of organization, we find that reptilian genome size distribution is consistent with a model of continuous gradual evolution while genomic compartmentalization, as manifested in the number of microchromosomes and macrochromosomes, appears to have undergone early rapid change. At the sequence level, the third genomic tier, we find that exon size in Alligator is distributed in a pattern matching that of exons in Gallus (chicken), especially in the 101—200 bp size class. A small spike in the fraction of exons in the 301 bp—1 kb size class is also observed for Alligator, but more so for Sphenodon. For introns, we find that members of Reptilia have a larger fraction of introns within the 101 bp–2 kb size class and a lower fraction of introns within the 5–30 kb size class than do mammals. These findings suggest that the mode of reptilian genome evolution varies across three hierarchical levels of the genome, a pattern consistent with a mosaic model of genomic evolution. PMID:21669810
Introducing etch kernels for efficient pattern sampling and etch bias prediction
NASA Astrophysics Data System (ADS)
Weisbuch, François; Lutich, Andrey; Schatz, Jirka
2018-01-01
Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.
NASA Astrophysics Data System (ADS)
Jung, Jongil; Hong, Ik-Seon; Cho, Eunjin; Yi, Yu
2016-03-01
Caves can serve as major outposts for future human exploration of the Moon and Mars. In addition, caves can protect people and electronic equipment from external hazards such as cosmic ray radiation and meteorites impacts and serve as a shelter. Numerous pit craters have been discovered on the Moon and Mars and are potential entrances to caves; the principal topographic features of pit craters are their visible internal floors and pits with vertical walls. We have devised two topographical models for investigating the relationship between the topographical characteristics and the inner void of pit craters. One of our models is a concave floor void model and the other is a convex floor tube model. For each model, optical photographs have been obtained under conditions similar to those in which optical photographs have been acquired for craters on the Moon and Mars. Brightness profiles were analyzed for determining the profile patterns of the void pit craters. The profile patterns were compared to the brightness profiles of Martian pit craters, because no good-quality images of lunar pit craters were available. In future studies, the model profile patterns will be compared to those of lunar pit craters, and the proposed method will likely become useful for finding lunar caves and consequently for planning lunar bases for manned lunar expeditions.
Menz, Hylton B; Lord, Stephen R; Fitzpatrick, Richard C
2007-02-01
Many falls in older people occur while walking, however the mechanisms responsible for gait instability are poorly understood. Therefore, the aim of this study was to develop a plausible model describing the relationships between impaired sensorimotor function, fear of falling and gait patterns in older people. Temporo-spatial gait parameters and acceleration patterns of the head and pelvis were obtained from 100 community-dwelling older people aged between 75 and 93 years while walking on an irregular walkway. A theoretical model was developed to explain the relationships between these variables, assuming that head stability is a primary output of the postural control system when walking. This model was then tested using structural equation modeling, a statistical technique which enables the testing of a set of regression equations simultaneously. The structural equation model indicated that: (i) reduced step length has a significant direct and indirect association with reduced head stability; (ii) impaired sensorimotor function is significantly associated with reduced head stability, but this effect is largely indirect, mediated by reduced step length, and; (iii) fear of falling is significantly associated with reduced step length, but has little direct influence on head stability. These findings provide useful insights into the possible mechanisms underlying gait characteristics and risk of falling in older people. Particularly important is the indication that fear-related step length shortening may be maladaptive.
NASA Astrophysics Data System (ADS)
Ewing, R. C.; Hayes, A. G.; McCormick, C.; Ballard, C.; Troy, S. A.
2012-04-01
Fields of bedform patterns persist across many orders of magnitude, from cm-scale sub-aqueous current ripples to km-scale aeolian dunes, and form with surprisingly little difference in expression despite a range of formative environments. Because of the remarkable similarity among bedform patterns, extracting information about climate and environment from these patterns is a challenge. For example, crestline orientation is not diagnostic of a particular flow regime; similar patterns form under many different flow configurations. On Titan, these challenges have played out with many attempts to reconcile dune crestline orientation with modeled and expected wind regimes. We propose that thinking about the time-scale of the change in dune orientation, rather than the orientation itself, can provide new insights on the long-term stability of the dune-field patterns and the formative wind regime. In this work, we apply the crestline re-orientation model developed by Werner and Kocurek [Geology, 1997] to the equatorial dune fields of Titan. We use Cassini Synthetic Aperture Radar images processed through a de-noising algorithm recently developed by Lucas et al. [LPSC, 2012] to measure variations in pattern parameters (crest spacing, crest length and defect density, which is the number of defect pairs per total crest length) both within and between Titan's dune fields to describe pattern maturity and identify areas where changes in dune orientation are likely to occur (or may already be occurring). Measured defect densities are similar to Earth's largest linear dune fields, such as the Namib Sand Sea and the Simpson Desert. We use measured defect densities in the Werner and Kocurek model to estimate crestline reorientation rates. We find reorientation timescales varying from ten to a hundred thousand times the average migration timescale (time to migrate a bedform one meter, ~1 Titan year according to Tokano (Aeolian Research, 2010)). Well-organized patterns have the longest reorientation time scales (~105 migration timescales), while the topographically or spatially isolated patches of dunes show the shortest reorientation times (~103 migration timescales). In addition, comparisons between spacing and defect density reveal that the well-organized patterns plot along an expected trend with Earth and Mars' largest, well-organized fields. Patterns on Earth and Mars that have been degraded and broken by environmental change fall off this trend and similarly, so do the isolated dune patterns on Titan fall suggesting changing environmental conditions such as wind regime and/or sediment availability have influenced the dunes on Titan. Crestline orientations in these areas suggest star and crescentic (barchans) morphologies in addition to linear dunes. Our results suggest that Titan's dunes may react to gross bedform transport averaged over orbital timescales, relaxing the requirement that a single modern wind regime is necessary to produce the observed well-organized dune patterns. We find signals of environmental change within the smallest patterns suggesting that the dunes may be recently reoriented or are reorienting to one component of a longer timescale wind regime with a duty cycle that persists over many seasonal cycles.
Morales, Knashawn H.; Kumanyika, Shiriki K.; Fassbender, Jennifer E.; Good, Jerene; Localio, A. Russell; Wadden, Thomas A.
2014-01-01
Objective Differentiating trajectories of weight change and identifying associated baseline predictors can provide insights for improving behavioral obesity treatment outcomes. Design and Methods Secondary, observational analyses using growth mixture models were conducted in pooled data for 604 black American, primarily female adults in three completed clinical trials. Covariates of identified patterns were evaluated. Results The best fitting model identified three patterns over 2 years: 1) mean weight loss of approximately 2 kg (n=519); 2) mean weight loss of approximately 3 kg at 1 year, followed by ~ 4 kg regain (n=61); and 3) mean weight loss of approximately 20 kg at 1 year followed by ~ 4 kg regain (n=24, with 23 from one study). In final multivariate analyses, higher BMI predicted having pattern 2 (OR[95% CI]) 1.10[1.03, 1.17]) or 3 (OR[95% CI] 1.42[1.25, 1.63]), and higher dietary fat score was predictive of a lower odds of having patterns 2 (OR[95% CI] 0.37[0.15, 0.94]) or 3 (OR[95% CI] 0.23[0.07, 0.79]). Conclusions Findings were consistent with moderate, clinically non-significant weight loss as the predominant pattern across all studies. Results underscore the need to develop novel and more carefully targeted and tailored approaches to facilitating weight loss in black American adults. PMID:25251464
Value increasing business model for e-hospital.
Null, Robert; Wei, June
2009-01-01
This paper developed a business value increasing model for electronic hospital (e-hospital) based on electronic value chain analysis. From this model, 58 hospital electronic business (e-business) solutions were developed. Additionally, this paper investigated the adoption patterns of these 58 e-business solutions within six US leading hospitals. The findings show that only 36 of 58 or 62% of the e-business solutions are fully or partially implemented within the six hospitals. Ultimately, the research results will be beneficial to managers and executives for accelerating e-business adoptions for e-hospital.
Mitchell, Christina M.; Beals, Janette; Whitesell, Nancy Rumbaugh
2008-01-01
Objective: We explored patterns of alcohol use among American Indian youths as well as concurrent predictors and developmental outcomes 6 years later. Method: This study used six semi-annual waves of data collected across 3 years from 861 American Indian youths, ages 14-20 initially, from two western tribes. Using a latent Markov model, we examined patterns of change in latent states of adolescent alcohol use in the past 6 months, combining these states of alcohol use into three latent statuses that described patterns of change across the 3 years: abstainers, inconsistent drinkers, and consistent drinkers. We then explored how the latent statuses differed, both initially and in young adulthood (ages 20-26). Results: Both alcohol use and nonuse were quite stable across time, although we also found evidence of change. Despite some rather troubling drinking patterns as teens, especially among consistent drinkers, most of the youths had achieved important tasks of young adulthood. But patterns of use during adolescence were related to greater levels of substance use in young adulthood. Conclusions: Latent Markov modeling provided a useful categorization of alcohol use that more finely differentiated those youths who would otherwise have been considered inconsistent drinkers. Findings also suggest that broad-based interventions during adolescence may not be the most important ones; instead, programs targeting later alcohol and other drug use may be a more strategic use of often limited resources. PMID:18781241
Soh, Zu; Nishikawa, Shinya; Kurita, Yuichi; Takiguchi, Noboru; Tsuji, Toshio
2016-01-01
To predict the odor quality of an odorant mixture, the interaction between odorants must be taken into account. Previously, an experiment in which mice discriminated between odorant mixtures identified a selective adaptation mechanism in the olfactory system. This paper proposes an olfactory model for odorant mixtures that can account for selective adaptation in terms of neural activity. The proposed model uses the spatial activity pattern of the mitral layer obtained from model simulations to predict the perceptual similarity between odors. Measured glomerular activity patterns are used as input to the model. The neural interaction between mitral cells and granular cells is then simulated, and a dissimilarity index between odors is defined using the activity patterns of the mitral layer. An odor set composed of three odorants is used to test the ability of the model. Simulations are performed based on the odor discrimination experiment on mice. As a result, we observe that part of the neural activity in the glomerular layer is enhanced in the mitral layer, whereas another part is suppressed. We find that the dissimilarity index strongly correlates with the odor discrimination rate of mice: r = 0.88 (p = 0.019). We conclude that our model has the ability to predict the perceptual similarity of odorant mixtures. In addition, the model also accounts for selective adaptation via the odor discrimination rate, and the enhancement and inhibition in the mitral layer may be related to this selective adaptation.
Fossils and living taxa agree on patterns of body mass evolution: a case study with Afrotheria.
Puttick, Mark N; Thomas, Gavin H
2015-12-22
Most of life is extinct, so incorporating some fossil evidence into analyses of macroevolution is typically seen as necessary to understand the diversification of life and patterns of morphological evolution. Here we test the effects of inclusion of fossils in a study of the body size evolution of afrotherian mammals, a clade that includes the elephants, sea cows and elephant shrews. We find that the inclusion of fossil tips has little impact on analyses of body mass evolution; from a small ancestral size (approx. 100 g), there is a shift in rate and an increase in mass leading to the larger-bodied Paenungulata and Tubulidentata, regardless of whether fossils are included or excluded from analyses. For Afrotheria, the inclusion of fossils and morphological character data affect phylogenetic topology, but these differences have little impact upon patterns of body mass evolution and these body mass evolutionary patterns are consistent with the fossil record. The largest differences between our analyses result from the evolutionary model, not the addition of fossils. For some clades, extant-only analyses may be reliable to reconstruct body mass evolution, but the addition of fossils and careful model selection is likely to increase confidence and accuracy of reconstructed macroevolutionary patterns. © 2015 The Authors.
Fossils and living taxa agree on patterns of body mass evolution: a case study with Afrotheria
Puttick, Mark N.; Thomas, Gavin H.
2015-01-01
Most of life is extinct, so incorporating some fossil evidence into analyses of macroevolution is typically seen as necessary to understand the diversification of life and patterns of morphological evolution. Here we test the effects of inclusion of fossils in a study of the body size evolution of afrotherian mammals, a clade that includes the elephants, sea cows and elephant shrews. We find that the inclusion of fossil tips has little impact on analyses of body mass evolution; from a small ancestral size (approx. 100 g), there is a shift in rate and an increase in mass leading to the larger-bodied Paenungulata and Tubulidentata, regardless of whether fossils are included or excluded from analyses. For Afrotheria, the inclusion of fossils and morphological character data affect phylogenetic topology, but these differences have little impact upon patterns of body mass evolution and these body mass evolutionary patterns are consistent with the fossil record. The largest differences between our analyses result from the evolutionary model, not the addition of fossils. For some clades, extant-only analyses may be reliable to reconstruct body mass evolution, but the addition of fossils and careful model selection is likely to increase confidence and accuracy of reconstructed macroevolutionary patterns. PMID:26674947
Umedachi, Takuya; Idei, Ryo; Ito, Kentaro; Ishiguro, Akio
2013-01-01
Behavioral diversity is an essential feature of living systems, enabling them to exhibit adaptive behavior in hostile and dynamically changing environments. However, traditional engineering approaches strive to avoid, or suppress, the behavioral diversity in artificial systems to achieve high performance in specific environments for given tasks. The goals of this research include understanding how living systems exhibit behavioral diversity and using these findings to build lifelike robots that exhibit truly adaptive behaviors. To this end, we have focused on one of the most primitive forms of intelligence concerning behavioral diversity, namely, a plasmodium of true slime mold. The plasmodium is a large amoeba-like unicellular organism that does not possess any nervous system or specialized organs. However, it exhibits versatile spatiotemporal oscillatory patterns and switches spontaneously between these. Inspired by the plasmodium, we built a mathematical model that exhibits versatile oscillatory patterns and spontaneously transitions between these patterns. This model demonstrates that, in contrast to coupled nonlinear oscillators with a well-designed complex diffusion network, physically interacting mechanosensory oscillators are capable of generating versatile oscillatory patterns without changing any parameters. Thus, the results are expected to shed new light on the design scheme for lifelike robots that exhibit amazingly versatile and adaptive behaviors.
Birth order in small multihospital systems.
Luke, R D; Ozcan, Y A; Begun, J W
1990-06-01
The strategic behaviors of small multihospital systems have received little attention in the literature despite the fact that small systems are the predominant scale among multihospital systems. This study examines one important aspect of small-system strategic behaviors: the birth-order or evolutionary patterns of hospital acquisition. The evolutionary patterns of acquisition are compared across three strategic model types studied elsewhere: local market, investment, and historical. Using data obtained from a variety of sources, local market model systems are found, in the sequence of acquisition, to be significantly different from the other two model types in terms of relative distances of acquisitions from the initiating or parent hospital, the sizes of acquisition hospitals, the complexity of those hospitals, and the likelihood that the acquisitions are located in rural areas. Differences between parents and acquisitions are also significant, as hypothesized, for the market model system types, although they are not generally significant for the other two model types. The findings suggest that the market model represents an important strategic form that may have important implications for the restructuring of hospital markets.
'Self body-management and thinness in youth: survey study on Italian girls'.
Di Giacomo, Dina; De Liso, Giulia; Ranieri, Jessica
2018-06-08
Adherence to the thinness model, self-acceptance such as self-esteem is psychological dynamics influencing the young age and emerging adulthood of women life. The purpose of this study was to investigate the girls and young women' ability to deal with the adherence to thinness model according to their self-body management thought daily self-perception of ownhabits and aptitude. We analysed their emotional patterns and body management to elucidate the Italian phenomenon. A cross-sectional study was conducted on 2287 Italian female distribute in range age 15-25 years old and distributed in girl and young women groups. We conducted a Survey study by snowball sampling technique. Our results showed that girls had higher emotional pattern scores when their weight and shape fit the thinness model: skinny girls felt positively about their body even if when they did not take adequate care of it. Italian girls consider the underweight body mass index an adherence model. Findings suggest the urgent need to plan prevention programme to model healthy behaviours about their daily good practice overcoming social and cultural models based on appearance.
NASA Astrophysics Data System (ADS)
King, Martin P.; Herceg-Bulić, Ivana; Kucharski, Fred; Keenlyside, Noel
2018-03-01
We investigate the Northern Hemisphere atmospheric circulation anomalies associated to the sea surface temperature (SST) anomalies that are related to the eastern-Pacific and central-Pacific El Nino-Southern Oscillations in the late autumn (November). This research is motivated by the need for improving understanding of the autumn climate conditions which can impact on winter climate, as well as the relative lack of study on the boreal autumn climate processes compared to winter. Using reanalysis and SST datasets available from the late nineteenth century through the recent years, we found that there are two major atmospheric responses; one is a hemispheric-wide wave number-4 pattern, another has a more annular pattern. Both of these project on the East Atlantic pattern (southward-shifted North Atlantic Oscillation) in the Atlantic sector. Which of the patterns is active is suggested to depend on the background mean flow, with the annular anomaly active in the most recent decades, while the wave-4 pattern in the decades before. This switch is associated with a change of correlation sign in the North Pacific. We discuss the robustness of this finding. The ability of two atmospheric general circulation models (ICTP-AGCM and ECHAM-AGCM) to reproduce the teleconnections is also examined. Evidence provided shows that the wave-4 pattern and the East Atlantic pattern signals can be reproduced by the models, while the shift from this to an annular response for the recent years is not found conclusively.
Jadiya, Pooja; Mir, Snober S; Nazir, Aamir
2012-12-01
Neurodegenerative diseases are known to be associated with genetic and environmental factors. The multifactorial Parkinson's disease (PD) is triggered and/or further worsened by exposure to certain pesticides. Existing literature suggests a link between pesticide exposure and increased incidence of PD. We carried out the present study to look into the stress gene expression pattern of transgenic Caenorhabditis elegans (C. elegans) model of PD after exposure to pesticides from different classes. Expression level of sod-1, sod-2, sod-3, hsp-70, hsp-60, and hsp-16.2 stress responsive genes was determined using qPCR. Our findings demonstrate that the expression of stress related genes does not follow a generalized pattern to different toxicants; rather each pesticide class has a specific expression signature.
Bunching at the kink: implications for spending responses to health insurance contracts
Einav, Liran; Finkelstein, Amy
2017-01-01
A large literature in empirical public finance relies on “bunching” to identify a behavioral response to non-linear incentives and to translate this response into an economic object to be used counterfactually. We conduct this type of analysis in the context of prescription drug insurance for the elderly in Medicare Part D, where a kink in the individual’s budget set generates substantial bunching in annual drug expenditure around the famous “donut hole”. We show that different alternative economic models can match the basic bunching pattern, but have very different quantitative implications for the counterfactual spending response to alternative insurance contracts. These findings illustrate the importance of modeling choices in mapping a compelling reduced form pattern into an economic object of interest. PMID:28785121
Decoding Spontaneous Emotional States in the Human Brain
Kragel, Philip A.; Knodt, Annchen R.; Hariri, Ahmad R.; LaBar, Kevin S.
2016-01-01
Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mills, Catrin M.; Cassano, John J.; Cassano, Elizabeth N.
Possible linkages between Arctic sea ice loss and midlatitude weather are strongly debated in the literature. We analyze a coupled model simulation to assess the possibility of Arctic ice variability forcing a midlatitude response, ensuring consistency between atmosphere, ocean, and ice components. We work with weekly running mean daily sensible heat fluxes with the self-organizing map technique to identify Arctic sensible heat flux anomaly patterns and the associated atmospheric response, without the need of metrics to define the Arctic forcing or measure the midlatitude response. We find that low-level warm anomalies during autumn can build planetary wave patterns that propagatemore » downstream into the midlatitudes, creating robust surface cold anomalies in the eastern United States.« less
Low order physical models of vertical axis wind turbines
NASA Astrophysics Data System (ADS)
Craig, Anna; Dabiri, John; Koseff, Jeffrey
2016-11-01
In order to examine the ability of low-order physical models of vertical axis wind turbines to accurately reproduce key flow characteristics, experiments were conducted on rotating turbine models, rotating solid cylinders, and stationary porous flat plates (of both uniform and non-uniform porosities). From examination of the patterns of mean flow, the wake turbulence spectra, and several quantitative metrics, it was concluded that the rotating cylinders represent a reasonably accurate analog for the rotating turbines. In contrast, from examination of the patterns of mean flow, it was found that the porous flat plates represent only a limited analog for rotating turbines (for the parameters examined). These findings have implications for both laboratory experiments and numerical simulations, which have previously used analogous low order models in order to reduce experimental/computational costs. NSF GRF and SGF to A.C; ONR N000141211047 and the Gordon and Betty Moore Foundation Grant GBMF2645 to J.D.; and the Bob and Norma Street Environmental Fluid Mechanics Laboratory at Stanford University.
Gauged multisoliton baby Skyrme model
NASA Astrophysics Data System (ADS)
Samoilenka, A.; Shnir, Ya.
2016-03-01
We present a study of U (1 ) gauged modification of the 2 +1 -dimensional planar Skyrme model with a particular choice of the symmetry breaking potential term which combines a short-range repulsion and a long-range attraction. In the absence of the gauge interaction, the multisolitons of the model are aloof, as they consist of the individual constituents which are well separated. A peculiar feature of the model is that there are usually several different stable static multisoliton solutions of rather similar energy in a topological sector of given degree. We investigate the pattern of the solutions and find new previously unknown local minima. It is shown that coupling of the aloof planar multi-Skyrmions to the magnetic field strongly affects the pattern of interaction between the constituents. We analyze the dependency of the structure of the solutions, their energies, and magnetic fluxes on the strength of the gauge coupling. It is found that, generically, in the strong coupling limit, the coupling to the gauge field results in effective recovery of the rotational invariance of the configuration.
Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M; Whelan, Robert; Dymond, Simon
2005-01-01
The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar–similar (e.g., “apple is to orange as dog is to cat”) versus different–different (e.g., “he is to his brother as chalk is to cheese”) derived relational responding, in both speed-contingent and speed-noncontingent conditions. Experiment 2 examined the event-related potentials (ERPs) associated with these two response patterns. Both experiments showed similar–similar responding to be significantly faster than different–different responding. Experiment 2 revealed significant differences between the waveforms of the two response patterns in the left-hemispheric prefrontal regions; different–different waveforms were significantly more negative than similar–similar waveforms. The behavioral and neurophysiological data support the RFT prediction that, all things being equal, similar–similar responding is relationally “simpler” than, and functionally distinct from, different–different analogical responding. The ERP data were fully consistent with findings in the neurocognitive literature on analogy. These findings strengthen the validity of the RFT model of analogical reasoning and supplement the behavior-analytic approach to analogy based on the relating of derived relations. PMID:16596974
NASA Astrophysics Data System (ADS)
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 dynamics. These results suggest that analysis of global inundation is feasible using a sub-grid model, but that spatial patterns at sub-kilometer resolutions still need to be adequately predicted.
THE NON-UNIVERSALITY OF THE LOW-MASS END OF THE IMF IS ROBUST AGAINST THE CHOICE OF SSP MODEL
DOE Office of Scientific and Technical Information (OSTI.GOV)
Spiniello, C.; Trager, S. C.; Koopmans, L. V. E.
2015-04-20
We perform a direct comparison of two state-of-the art single stellar population (SSP) models that have been used to demonstrate the non-universality of the low-mass end of the initial mass function (IMF) slope. The two public versions of the SSP models are restricted to either solar abundance patterns or solar metallicity, too restrictive if one aims to disentangle elemental enhancements, metallicity changes, and IMF variations in massive early-type galaxies (ETGs) with star formation histories different from those in the solar neighborhood. We define response functions (to metallicity and α-abundance) to extend the parameter space for each set of models. Wemore » compare these extended models with a sample of Sloan Digital Sky Survey (SDSS) ETG spectra with varying velocity dispersions. We measure equivalent widths of optical IMF-sensitive stellar features to examine the effect of the underlying model assumptions and ingredients, such as stellar libraries or isochrones, on the inference of the IMF slope down to ∼0.1 M{sub ⊙}. We demonstrate that the steepening of the low-mass end of the IMF based on a non-degenerate set of spectroscopic optical indicators is robust against the choice of the stellar population model. Although the models agree in a relative sense (i.e., both imply more bottom-heavy IMFs for more massive systems), we find non-negligible differences in the absolute values of the IMF slope inferred at each velocity dispersion by using the two different models. In particular, we find large inconsistencies in the quantitative predictions of the IMF slope variations and abundance patterns when sodium lines are used. We investigate the possible reasons for these inconsistencies.« less
A study of correlations in the stock market
NASA Astrophysics Data System (ADS)
Sharma, Chandradew; Banerjee, Kinjal
2015-08-01
We study the various sectors of the Bombay Stock Exchange (BSE) for a period of 8 years from April 2006 to March 2014. Using the data of daily returns of a period of eight years we make a direct model free analysis of the pattern of the sectorial indices movement and the correlations among them. Our analysis shows significant auto correlation among the individual sectors and also strong cross-correlation among sectors. We also find that auto correlations in some of the sectors persist in time. This is a very significant result and has not been reported so far in Indian context. These findings will be very useful in model building for prediction of price movement of equities, derivatives and portfolio management. We show that the Random Walk Hypothesis is not applicable in modeling the Indian market and mean-variance-skewness-kurtosis based portfolio optimization might be required. We also find that almost all sectors are highly correlated during large fluctuation periods and have only moderate correlation during normal periods.
NASA Technical Reports Server (NTRS)
Schubert, Siegfried; Wang, Hailan; Koster, Randal; Weaver, Scott; Gutzler, David; Dai, Aiguo; Delworth, Tom; Deser, Clara; Findell, Kristen; Fu, Rong;
2009-01-01
The USCLI VAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCM5), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models.
ERIC Educational Resources Information Center
Dishion, Thomas J.; Capaldi, Deborah M.; Yoerger, Karen
1999-01-01
This study examined antecedents to early patterned alcohol and tobacco use and marijuana experimentation between ages 11 and 16 for an at-risk male sample. Findings suggested that family, peer, and child characteristics were inextricably connected within an ecology of development. A structural equation prediction model suggested a higher order…
ERIC Educational Resources Information Center
Lewis, John D.; Elman, Jeffrey L.
2008-01-01
Theoretical considerations, and findings from computational modeling, comparative neuroanatomy and developmental neuroscience, motivate the hypothesis that a deviant brain growth trajectory will lead to deviant patterns of change in cortico-cortical connectivity. Differences in brain size during development will alter the relative cost and…
Teacher Professional Development as Knowledge Building: A Popperian Analysis
ERIC Educational Resources Information Center
Chitpin, Stephanie; Evers, Colin W.
2005-01-01
This paper offers an analysis of how six experienced teachers, and two in particular, used portfolios to aid and chart steps in their own professional development. The key finding of the study was that the pattern of growth of professional knowledge conformed strikingly to the central features of the model proposed by the philosopher of science,…
Wu, Mon-Ju; Wu, Hanjing Emily; Mwangi, Benson; Sanches, Marsal; Selvaraj, Sudhakar; Zunta-Soares, Giovana B; Soares, Jair C
2015-03-01
Diagnosis of pediatric neuropsychiatric disorders such as unipolar depression is largely based on clinical judgment - without objective biomarkers to guide diagnostic process and subsequent therapeutic interventions. Neuroimaging studies have previously reported average group-level neuroanatomical differences between patients with pediatric unipolar depression and healthy controls. In the present study, we investigated the utility of multiple neuromorphometric indices in distinguishing pediatric unipolar depression patients from healthy controls at an individual subject level. We acquired structural T1-weighted scans from 25 pediatric unipolar depression patients and 26 demographically matched healthy controls. Multiple neuromorphometric indices such as cortical thickness, volume, and cortical folding patterns were obtained. A support vector machine pattern classification model was 'trained' to distinguish individual subjects with pediatric unipolar depression from healthy controls based on multiple neuromorphometric indices and model predictive validity (sensitivity and specificity) calculated. The model correctly identified 40 out of 51 subjects translating to 78.4% accuracy, 76.0% sensitivity and 80.8% specificity, chi-square p-value = 0.000049. Volumetric and cortical folding abnormalities in the right thalamus and right temporal pole respectively were most central in distinguishing individual patients with pediatric unipolar depression from healthy controls. These findings provide evidence that a support vector machine pattern classification model using multiple neuromorphometric indices may qualify as diagnostic marker for pediatric unipolar depression. In addition, our results identified the most relevant neuromorphometric features in distinguishing PUD patients from healthy controls. Copyright © 2015 Elsevier Ltd. All rights reserved.
Magnetic intermittency of solar wind turbulence in the dissipation range
NASA Astrophysics Data System (ADS)
Pei, Zhongtian; He, Jiansen; Tu, Chuanyi; Marsch, Eckart; Wang, Linghua
2016-04-01
The feature, nature, and fate of intermittency in the dissipation range are an interesting topic in the solar wind turbulence. We calculate the distribution of flatness for the magnetic field fluctuations as a functionof angle and scale. The flatness distribution shows a "butterfly" pattern, with two wings located at angles parallel/anti-parallel to local mean magnetic field direction and main body located at angles perpendicular to local B0. This "butterfly" pattern illustrates that the flatness profile in (anti-) parallel direction approaches to the maximum value at larger scale and drops faster than that in perpendicular direction. The contours for probability distribution functions at different scales illustrate a "vase" pattern, more clear in parallel direction, which confirms the scale-variation of flatness and indicates the intermittency generation and dissipation. The angular distribution of structure function in the dissipation range shows an anisotropic pattern. The quasi-mono-fractal scaling of structure function in the dissipation range is also illustrated and investigated with the mathematical model for inhomogeneous cascading (extended p-model). Different from the inertial range, the extended p-model for the dissipation range results in approximate uniform fragmentation measure. However, more complete mathematicaland physical model involving both non-uniform cascading and dissipation is needed. The nature of intermittency may be strong structures or large amplitude fluctuations, which may be tested with magnetic helicity. In one case study, we find the heating effect in terms of entropy for large amplitude fluctuations seems to be more obvious than strong structures.
Kramer, Karen L; Schacht, Ryan; Bell, Adrian
2017-09-19
Small populations are susceptible to high genetic loads and random fluctuations in birth and death rates. While these selective forces can adversely affect their viability, small populations persist across taxa. Here, we investigate the resilience of small groups to demographic uncertainty, and specifically to fluctuations in adult sex ratio (ASR), partner availability and dispersal patterns. Using 25 years of demographic data for two Savannah Pumé groups of South American hunter-gatherers, we show that in small human populations: (i) ASRs fluctuate substantially from year to year, but do not consistently trend in a sex-biased direction; (ii) the primary driver of local variation in partner availability is stochasticity in the sex ratio at maturity; and (iii) dispersal outside of the group is an important behavioural means to mediate locally constrained mating options. To then simulate conditions under which dispersal outside of the local group may have evolved, we develop two mathematical models. Model results predict that if the ASR is biased, the globally rarer sex should disperse. The model's utility is then evaluated by applying our empirical data to this central prediction. The results are consistent with the observed hunter-gatherer pattern of variation in the sex that disperses. Together, these findings offer an alternative explanation to resource provisioning for the evolution of traits central to human sociality (e.g. flexible dispersal, bilocal post-marital residence and cooperation across local groups). We argue that in small populations, looking outside of one's local group is necessary to find a mate and that, motivated by ASR imbalance, the alliances formed to facilitate the movement of partners are an important foundation for the human-typical pattern of network formation across local groups.This article is part of the themed issue 'Adult sex ratios and reproductive decisions: a critical re-examination of sex differences in human and animal societies'. © 2017 The Author(s).
Beauty and the beholder: the role of visual sensitivity in visual preference
Spehar, Branka; Wong, Solomon; van de Klundert, Sarah; Lui, Jessie; Clifford, Colin W. G.; Taylor, Richard P.
2015-01-01
For centuries, the essence of aesthetic experience has remained one of the most intriguing mysteries for philosophers, artists, art historians and scientists alike. Recently, views emphasizing the link between aesthetics, perception and brain function have become increasingly prevalent (Ramachandran and Hirstein, 1999; Zeki, 1999; Livingstone, 2002; Ishizu and Zeki, 2013). The link between art and the fractal-like structure of natural images has also been highlighted (Spehar et al., 2003; Graham and Field, 2007; Graham and Redies, 2010). Motivated by these claims and our previous findings that humans display a consistent preference across various images with fractal-like statistics, here we explore the possibility that observers’ preference for visual patterns might be related to their sensitivity for such patterns. We measure sensitivity to simple visual patterns (sine-wave gratings varying in spatial frequency and random textures with varying scaling exponent) and find that they are highly correlated with visual preferences exhibited by the same observers. Although we do not attempt to offer a comprehensive neural model of aesthetic experience, we demonstrate a strong relationship between visual sensitivity and preference for simple visual patterns. Broadly speaking, our results support assertions that there is a close relationship between aesthetic experience and the sensory coding of natural stimuli. PMID:26441611
Miller, J
1997-01-01
The domain of inquiry for this study was the influence of the American political environmental context on professional and generic care patterns, expressions, and meanings of Czech American immigrants. The purpose of the research was to document, describe, interpret, and analyze the diversities and universalities of professional and generic care for this cultural group, to provide culturally congruent care to Czech Americans, and to explicate the role of politics as an influence on care patterns, health, and well being. The researcher's former transcultural ethnonursing study in Prague, Czechoslovakia in 1991 served as a stimulus for this in-depth study on politics and care. Twelve key and twenty general informants were interviewed. Five major themes were identified. The researcher discovered that the capitalist economic market structure of the United States influenced informant lifeways in all dimensions of Leininger's Theory of Culture Care Diversity and Universality, as depicted in the Sunrise Model. Specific care patterns discovered included care as choice, care as responsibility, and care as helping each other. Findings related to professional and generic care supported researcher predictions that generic culture care patterns would be important to immigrants. Provisions for culturally congruent nursing care were articulated based on research findings.
Yaroslavsky, Ilya; Bylsma, Lauren M.; Rottenberg, Jonathan; Kovacs, Maria
2013-01-01
We examined whether the combined indices of respiratory sinus arrhythmia at rest (resting RSA) and in response to a sad film (RSA reactivity) predict effective and ineffective responses to reduce sadness (adaptive vs. maladaptive mood repair) in women with histories of juvenile-onset depression (n = 74) and no history of major mental disorders (n = 75). Structural equation models were used to estimate latent resting RSA, depression, and adaptive and maladaptive mood repair and to test the study hypotheses. Results indicated that combinations of resting RSA+RSA reactivity (RSA patterns) predicted maladaptive mood repair, which in turn, mediated the effects of RSA pattern on depression. Further, RSA patterns moderated the depressogenic effects of maladaptive mood repair. RSA patterns were unrelated to adaptive mood repair. Our findings suggest that mood repair is one mechanism through which physiological vulnerabilities adversely affect mental health. PMID:23827087
Yaroslavsky, Ilya; Bylsma, Lauren M; Rottenberg, Jonathan; Kovacs, Maria
2013-10-01
We examined whether the combined indices of respiratory sinus arrhythmia at rest (resting RSA) and in response to a sad film (RSA reactivity) predict effective and ineffective responses to reduce sadness (adaptive vs. maladaptive mood repair) in women with histories of juvenile-onset depression (n=74) and no history of major mental disorders (n=75). Structural equation models were used to estimate latent resting RSA, depression, and adaptive and maladaptive mood repair and to test the study hypotheses. Results indicated that combinations of resting RSA+RSA reactivity (RSA patterns) predicted maladaptive mood repair, which in turn, mediated the effects of RSA pattern on depression. Further, RSA patterns moderated the depressogenic effects of maladaptive mood repair. RSA patterns were unrelated to adaptive mood repair. Our findings suggest that mood repair is one mechanism through which physiological vulnerabilities adversely affect mental health. Copyright © 2013 Elsevier B.V. All rights reserved.
Statistical Patterns in Movie Rating Behavior
2015-01-01
Currently, users and consumers can review and rate products through online services, which provide huge databases that can be used to explore people’s preferences and unveil behavioral patterns. In this work, we investigate patterns in movie ratings, considering IMDb (the Internet Movie Database), a highly visited site worldwide, as a source. We find that the distribution of votes presents scale-free behavior over several orders of magnitude, with an exponent very close to 3/2, with exponential cutoff. It is remarkable that this pattern emerges independently of movie attributes such as average rating, age and genre, with the exception of a few genres and of high-budget films. These results point to a very general underlying mechanism for the propagation of adoption across potential audiences that is independent of the intrinsic features of a movie and that can be understood through a simple spreading model with mean-field avalanche dynamics. PMID:26322899
Novel layered clustering-based approach for generating ensemble of classifiers.
Rahman, Ashfaqur; Verma, Brijesh
2011-05-01
This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.
Quantum Mechanics, Pattern Recognition, and the Mammalian Brain
NASA Astrophysics Data System (ADS)
Chapline, George
2008-10-01
Although the usual way of representing Markov processes is time asymmetric, there is a way of describing Markov processes, due to Schrodinger, which is time symmetric. This observation provides a link between quantum mechanics and the layered Bayesian networks that are often used in automated pattern recognition systems. In particular, there is a striking formal similarity between quantum mechanics and a particular type of Bayesian network, the Helmholtz machine, which provides a plausible model for how the mammalian brain recognizes important environmental situations. One interesting aspect of this relationship is that the "wake-sleep" algorithm for training a Helmholtz machine is very similar to the problem of finding the potential for the multi-channel Schrodinger equation. As a practical application of this insight it may be possible to use inverse scattering techniques to study the relationship between human brain wave patterns, pattern recognition, and learning. We also comment on whether there is a relationship between quantum measurements and consciousness.
Statistical Patterns in Movie Rating Behavior.
Ramos, Marlon; Calvão, Angelo M; Anteneodo, Celia
2015-01-01
Currently, users and consumers can review and rate products through online services, which provide huge databases that can be used to explore people's preferences and unveil behavioral patterns. In this work, we investigate patterns in movie ratings, considering IMDb (the Internet Movie Database), a highly visited site worldwide, as a source. We find that the distribution of votes presents scale-free behavior over several orders of magnitude, with an exponent very close to 3/2, with exponential cutoff. It is remarkable that this pattern emerges independently of movie attributes such as average rating, age and genre, with the exception of a few genres and of high-budget films. These results point to a very general underlying mechanism for the propagation of adoption across potential audiences that is independent of the intrinsic features of a movie and that can be understood through a simple spreading model with mean-field avalanche dynamics.
The Fine-Scale Functional Correlation of Striate Cortex in Sighted and Blind People
Butt, Omar H.; Benson, Noah C.; Datta, Ritobrato
2013-01-01
To what extent are spontaneous neural signals within striate cortex organized by vision? We examined the fine-scale pattern of striate cortex correlations within and between hemispheres in rest-state BOLD fMRI data from sighted and blind people. In the sighted, we find that corticocortico correlation is well modeled as a Gaussian point-spread function across millimeters of striate cortical surface, rather than degrees of visual angle. Blindness produces a subtle change in the pattern of fine-scale striate correlations between hemispheres. Across participants blind before the age of 18, the degree of pattern alteration covaries with the strength of long-range correlation between left striate cortex and Broca's area. This suggests that early blindness exchanges local, vision-driven pattern synchrony of the striate cortices for long-range functional correlations potentially related to cross-modal representation. PMID:24107953
Impact of mitochondrial Ca2+ cycling on pattern formation and stability.
Falcke, M; Hudson, J L; Camacho, P; Lechleiter, J D
1999-07-01
Energization of mitochondria significantly alters the pattern of Ca2+ wave activity mediated by activation of the inositol (1,4,5) trisphosphate (IP3) receptor (IP3R) in Xenopus oocytes. The number of pulsatile foci is reduced and spiral Ca2+ waves are no longer observed. Rather, target patterns of Ca2+ release predominate, and when fragmented, fail to form spirals. Ca2+ wave velocity, amplitude, decay time, and periodicity are also increased. We have simulated these experimental findings by supplementing an existing mathematical model with a differential equation for mitochondrial Ca2+ uptake and release. Our calculations show that mitochondrial Ca2+ efflux plays a critical role in pattern formation by prolonging the recovery time of IP3Rs from a refractory state. We also show that under conditions of high energization of mitochondria, the Ca2+ dynamics can become bistable with a second stable stationary state of high resting Ca2+ concentration.
Competition for popularity in bipartite networks.
Díaz, Mariano Beguerisse; Porter, Mason A; Onnela, Jukka-Pekka
2010-12-01
We present a dynamical model for rewiring and attachment in bipartite networks. Edges are placed between nodes that belong to catalogs that can either be fixed in size or growing in size. The model is motivated by an empirical study of data from the video rental service Netflix, which invites its users to give ratings to the videos available in its catalog. We find that the distribution of the number of ratings given by users and that of the number of ratings received by videos both follow a power law with an exponential cutoff. We also examine the activity patterns of Netflix users and find bursts of intense video-rating activity followed by long periods of inactivity. We derive ordinary differential equations to model the acquisition of edges by the nodes over time and obtain the corresponding time-dependent degree distributions. We then compare our results with the Netflix data and find good agreement. We conclude with a discussion of how catalog models can be used to study systems in which agents are forced to choose, rate, or prioritize their interactions from a large set of options. © 2010 American Institute of Physics.
Competition for popularity in bipartite networks
NASA Astrophysics Data System (ADS)
Beguerisse Díaz, Mariano; Porter, Mason A.; Onnela, Jukka-Pekka
2010-12-01
We present a dynamical model for rewiring and attachment in bipartite networks. Edges are placed between nodes that belong to catalogs that can either be fixed in size or growing in size. The model is motivated by an empirical study of data from the video rental service Netflix, which invites its users to give ratings to the videos available in its catalog. We find that the distribution of the number of ratings given by users and that of the number of ratings received by videos both follow a power law with an exponential cutoff. We also examine the activity patterns of Netflix users and find bursts of intense video-rating activity followed by long periods of inactivity. We derive ordinary differential equations to model the acquisition of edges by the nodes over time and obtain the corresponding time-dependent degree distributions. We then compare our results with the Netflix data and find good agreement. We conclude with a discussion of how catalog models can be used to study systems in which agents are forced to choose, rate, or prioritize their interactions from a large set of options.
Posterior Wnts Have Distinct Roles in Specification and Patterning of the Planarian Posterior Region
Sureda-Gómez, Miquel; Pascual-Carreras, Eudald; Adell, Teresa
2015-01-01
The wnt signaling pathway is an intercellular communication mechanism essential in cell-fate specification, tissue patterning and regional-identity specification. A βcatenin-dependent signal specifies the AP (Anteroposterior) axis of planarians, both during regeneration of new tissues and during normal homeostasis. Accordingly, four wnts (posterior wnts) are expressed in a nested manner in central and posterior regions of planarians. We have analyzed the specific role of each posterior wnt and the possible cooperation between them in specifying and patterning planarian central and posterior regions. We show that each posterior wnt exerts a distinct role during re-specification and maintenance of the central and posterior planarian regions, and that the integration of the different wnt signals (βcatenin dependent and independent) underlies the patterning of the AP axis from the central region to the tip of the tail. Based on these findings and data from the literature, we propose a model for patterning the planarian AP axis. PMID:26556349
Sureda-Gómez, Miquel; Pascual-Carreras, Eudald; Adell, Teresa
2015-11-05
The wnt signaling pathway is an intercellular communication mechanism essential in cell-fate specification, tissue patterning and regional-identity specification. A βcatenin-dependent signal specifies the AP (Anteroposterior) axis of planarians, both during regeneration of new tissues and during normal homeostasis. Accordingly, four wnts (posterior wnts) are expressed in a nested manner in central and posterior regions of planarians. We have analyzed the specific role of each posterior wnt and the possible cooperation between them in specifying and patterning planarian central and posterior regions. We show that each posterior wnt exerts a distinct role during re-specification and maintenance of the central and posterior planarian regions, and that the integration of the different wnt signals (βcatenin dependent and independent) underlies the patterning of the AP axis from the central region to the tip of the tail. Based on these findings and data from the literature, we propose a model for patterning the planarian AP axis.
Meyer, Heather M; Teles, José; Formosa-Jordan, Pau; Refahi, Yassin; San-Bento, Rita; Ingram, Gwyneth; Jönsson, Henrik; Locke, James C W; Roeder, Adrienne H K
2017-01-01
Multicellular development produces patterns of specialized cell types. Yet, it is often unclear how individual cells within a field of identical cells initiate the patterning process. Using live imaging, quantitative image analyses and modeling, we show that during Arabidopsis thaliana sepal development, fluctuations in the concentration of the transcription factor ATML1 pattern a field of identical epidermal cells to differentiate into giant cells interspersed between smaller cells. We find that ATML1 is expressed in all epidermal cells. However, its level fluctuates in each of these cells. If ATML1 levels surpass a threshold during the G2 phase of the cell cycle, the cell will likely enter a state of endoreduplication and become giant. Otherwise, the cell divides. Our results demonstrate a fluctuation-driven patterning mechanism for how cell fate decisions can be initiated through a random yet tightly regulated process. DOI: http://dx.doi.org/10.7554/eLife.19131.001 PMID:28145865
Rethinking pattern formation in reaction-diffusion systems
NASA Astrophysics Data System (ADS)
Halatek, J.; Frey, E.
2018-05-01
The present theoretical framework for the analysis of pattern formation in complex systems is mostly limited to the vicinity of fixed (global) equilibria. Here we present a new theoretical approach to characterize dynamical states arbitrarily far from (global) equilibrium. We show that reaction-diffusion systems that are driven by locally mass-conserving interactions can be understood in terms of local equilibria of diffusively coupled compartments. Diffusive coupling generically induces lateral redistribution of the globally conserved quantities, and the variable local amounts of these quantities determine the local equilibria in each compartment. We find that, even far from global equilibrium, the system is well characterized by its moving local equilibria. We apply this framework to in vitro Min protein pattern formation, a paradigmatic model for biological pattern formation. Within our framework we can predict and explain transitions between chemical turbulence and order arbitrarily far from global equilibrium. Our results reveal conceptually new principles of self-organized pattern formation that may well govern diverse dynamical systems.
Mulas, Marcello; Waniek, Nicolai; Conradt, Jörg
2016-01-01
After the discovery of grid cells, which are an essential component to understand how the mammalian brain encodes spatial information, three main classes of computational models were proposed in order to explain their working principles. Amongst them, the one based on continuous attractor networks (CAN), is promising in terms of biological plausibility and suitable for robotic applications. However, in its current formulation, it is unable to reproduce important electrophysiological findings and cannot be used to perform path integration for long periods of time. In fact, in absence of an appropriate resetting mechanism, the accumulation of errors over time due to the noise intrinsic in velocity estimation and neural computation prevents CAN models to reproduce stable spatial grid patterns. In this paper, we propose an extension of the CAN model using Hebbian plasticity to anchor grid cell activity to environmental landmarks. To validate our approach we used as input to the neural simulations both artificial data and real data recorded from a robotic setup. The additional neural mechanism can not only anchor grid patterns to external sensory cues but also recall grid patterns generated in previously explored environments. These results might be instrumental for next generation bio-inspired robotic navigation algorithms that take advantage of neural computation in order to cope with complex and dynamic environments. PMID:26924979
When Can Species Abundance Data Reveal Non-neutrality?
Al Hammal, Omar; Alonso, David; Etienne, Rampal S.; Cornell, Stephen J.
2015-01-01
Species abundance distributions (SAD) are probably ecology’s most well-known empirical pattern, and over the last decades many models have been proposed to explain their shape. There is no consensus over which model is correct, because the degree to which different processes can be discerned from SAD patterns has not yet been rigorously quantified. We present a power calculation to quantify our ability to detect deviations from neutrality using species abundance data. We study non-neutral stochastic community models, and show that the presence of non-neutral processes is detectable if sample size is large enough and/or the amplitude of the effect is strong enough. Our framework can be used for any candidate community model that can be simulated on a computer, and determines both the sampling effort required to distinguish between alternative processes, and a range for the strength of non-neutral processes in communities whose patterns are statistically consistent with neutral theory. We find that even data sets of the scale of the 50 Ha forest plot on Barro Colorado Island, Panama, are unlikely to be large enough to detect deviations from neutrality caused by competitive interactions alone, though the presence of multiple non-neutral processes with contrasting effects on abundance distributions may be detectable. PMID:25793889
18O Spatial Patterns of Vein Xylem Water, Leaf Water, and Dry Matter in Cotton Leaves
Gan, Kim Suan; Wong, Suan Chin; Yong, Jean Wan Hong; Farquhar, Graham Douglas
2002-01-01
Three leaf water models (two-pool model, Péclet effect, and string-of-lakes) were assessed for their robustness in predicting leaf water enrichment and its spatial heterogeneity. This was achieved by studying the 18O spatial patterns of vein xylem water, leaf water, and dry matter in cotton (Gossypium hirsutum) leaves grown at different humidities using new experimental approaches. Vein xylem water was collected from intact transpiring cotton leaves by pressurizing the roots in a pressure chamber, whereas the isotopic content of leaf water was determined without extracting it from fresh leaves with the aid of a purpose-designed leaf punch. Our results indicate that veins have a significant degree of lateral exchange with highly enriched leaf water. Vein xylem water is thus slightly, but progressively enriched in the direction of water flow. Leaf water enrichment is dependent on the relative distances from major veins, with water from the marginal and intercostal regions more enriched and that next to veins and near the leaf base more depleted than the Craig-Gordon modeled enrichment of water at the sites of evaporation. The spatial pattern of leaf water enrichment varies with humidity, as expected from the string-of-lakes model. This pattern is also reflected in leaf dry matter. All three models are realistic, but none could fully account for all of the facets of leaf water enrichment. Our findings acknowledge the presence of capacitance in the ground tissues of vein ribs and highlight the essential need to incorporate Péclet effects into the string-of-lakes model when applying it to leaves. PMID:12376664
Influence of gender constancy and social power on sex-linked modeling.
Bussey, K; Bandura, A
1984-12-01
Competing predictions derived from cognitive-developmental theory and social learning theory concerning sex-linked modeling were tested. In cognitive-developmental theory, gender constancy is considered a necessary prerequisite for the emulation of same-sex models, whereas according to social learning theory, sex-role development is promoted through a vast system of social influences with modeling serving as a major conveyor of sex role information. In accord with social learning theory, even children at a lower level of gender conception emulated same-sex models in preference to opposite-sex ones. Level of gender constancy was associated with higher emulation of both male and female models rather than operating as a selective determinant of modeling. This finding corroborates modeling as a basic mechanism in the sex-typing process. In a second experiment we explored the limits of same-sex modeling by pitting social power against the force of collective modeling of different patterns of behavior by male and female models. Social power over activities and rewarding resources produced cross-sex modeling in boys, but not in girls. This unexpected pattern of cross-sex modeling is explained by the differential sex-typing pressures that exist for boys and girls and socialization experiences that heighten the attractiveness of social power for boys.
NASA Astrophysics Data System (ADS)
Thomas, E. G.; Shepherd, S. G.
2018-04-01
Over the last decade, the Super Dual Auroral Radar Network (SuperDARN) has undergone a dramatic expansion in the Northern Hemisphere with the addition of more than a dozen radars offering improved coverage at mid-latitudes (50°-60° magnetic latitude) and in the polar cap (80°-90° magnetic latitude). In this study, we derive a statistical model of ionospheric convection (TS18) using line-of-sight velocity measurements from the complete network of mid-latitude, high-latitude, and polar radars for the years 2010-2016. These climatological patterns are organized by solar wind, interplanetary magnetic field (IMF), and dipole tilt angle conditions. We find that for weak solar wind driving conditions the TS18 model patterns are largely similar to the average patterns obtained using high-latitude radar data only. For stronger solar wind driving the inclusion of mid-latitude radar data at the equatorward extent of the ionospheric convection can increase the measured cross-polar cap potential (ΦPC) by as much as 40%. We also derive an alternative model organized by the Kp index to better characterize the statistical convection under a range of magnetic activity conditions. These Kp patterns exhibit similar IMF By dependencies as the TS18 model results and demonstrate a linear increase in ΦPC with increasing Kp for a given IMF orientation. Overall, the mid-latitude radars provide a better specification of the flows within the nightside Harang reversal region for moderate to strong solar wind driving or geomagnetic activity, while the polar radars improve the quality of velocity measurements in the deep polar cap under all conditions.
Patterns of attachment and parents' adjustment to the death of their child.
Wijngaards-de Meij, Leoniek; Stroebe, Margaret; Schut, Henk; Stroebe, Wolfgang; van den Bout, Jan; van der Heijden, Peter G M; Dijkstra, Iris
2007-04-01
The impact of adult attachment on psychological adjustment among bereaved parents and the mediating effect of relationship satisfaction were examined among a sample of 219 couples of parents. Data collection took place 6, 13, and 20 months after loss. Use of the actor partner interdependence model in multilevel regression analysis enabled exploration of both individual as well as partner attachment as predictors of grief and depression. Results indicated that the more insecurely attached parents were (on both avoidance and anxiety attachment), the higher the symptoms of grief and depression. Neither the attachment pattern of the partner nor similarity of attachment within the couple had any influence on psychological adjustment of the parent. Marital satisfaction partially mediated the association of anxious attachment with symptomatology. Contrary to previous research findings, avoidant attachment was associated with high grief intensity. These findings challenge the notion that the avoidantly attached are resilient.
Enhanced anger superiority effect in generalized anxiety disorder and panic disorder
Ashwin, Chris; Holas, Pawel; Broadhurst, Shanna; Kokoszka, Andrzej; Georgiou, George A.; Fox, Elaine
2012-01-01
People are typically faster and more accurate to detect angry compared to happy faces, which is known as the anger superiority effect. Many cognitive models of anxiety suggest anxiety disorders involve attentional biases towards threat, although the nature of these biases remains unclear. The present study used a Face-in-the-Crowd task to investigate the anger superiority effect in a control group and patients diagnosed with either generalized anxiety disorder (GAD) or panic disorder (PD). The main finding was that both anxiety groups showed an enhanced anger superiority effect compared to controls, which is consistent with key theories of anxiety. Furthermore, both anxiety groups showed a differential pattern of enhanced bias towards threat depending on the crowd in the displays. The different attentional bias patterns between the GAD and PD groups may be related to the diverse symptoms in these disorders. These findings have implications for the diagnosis and treatment of anxiety. PMID:22196167
Dodge, Kenneth A.; Lansford, Jennifer E.; Burks, Virginia Salzer; Bates, John E.; Pettit, Gregory S.; Fontaine, Reid; Price, Joseph M.
2009-01-01
The relation between social rejection and growth in antisocial behavior was investigated. In Study 1, 259 boys and girls (34% African American) were followed from Grades 1 to 3 (ages 6–8 years) to Grades 5 to 7 (ages 10–12 years). Early peer rejection predicted growth in aggression. In Study 2, 585 boys and girls (16% African American) were followed from kindergarten to Grade 3 (ages 5–8 years), and findings were replicated. Furthermore, early aggression moderated the effect of rejection, such that rejection exacerbated antisocial development only among children initially disposed toward aggression. In Study 3, social information-processing patterns measured in Study 1 were found to mediate partially the effect of early rejection on later aggression. In Study 4, processing patterns measured in Study 2 replicated the mediation effect. Findings are integrated into a recursive model of antisocial development. PMID:12705561
Nuijens, Louise; Medeiros, Brian; Sandu, Irina; ...
2015-11-06
We present patterns of covariability between low-level cloudiness and the trade-wind boundary layer structure using long-term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF’s Integrated Forecast System and 10 CMIP5 models. By using single-time step output at a single location, we find that models can produce a fairly realistic trade-wind layer structure in long-term means, but with unrealistic variability at shorter-time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed-layer relative humidity (RH) and temperature stratificationmore » at the mixed-layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the tradewind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade-wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large-scale vertical motion. No model stands out by reproducing the observed behavior in all respects. As a result, these findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade-wind clouds and their environments in present-day climate, which is relevant for how we interpret modeled cloud feedbacks.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nuijens, Louise; Medeiros, Brian; Sandu, Irina
We present patterns of covariability between low-level cloudiness and the trade-wind boundary layer structure using long-term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF’s Integrated Forecast System and 10 CMIP5 models. By using single-time step output at a single location, we find that models can produce a fairly realistic trade-wind layer structure in long-term means, but with unrealistic variability at shorter-time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed-layer relative humidity (RH) and temperature stratificationmore » at the mixed-layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the tradewind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade-wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large-scale vertical motion. No model stands out by reproducing the observed behavior in all respects. As a result, these findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade-wind clouds and their environments in present-day climate, which is relevant for how we interpret modeled cloud feedbacks.« less
Doostvandi, Tayebeh; Bahadoran, Zahra; Mozaffari-Khosravi, Hassan; Tahmasebinejad, Zhaleh; Mirmiran, Parvin; Azizi, Fereidoun
2017-05-01
The aim of this study was to investigate the relationship between major dietary patterns and the risk of insulin resistance (IR) among an urban Iranian population. In this longitudinal study, 802 adult men and women were studied within the framework of Tehran Lipid and Glucose Study. Fasting serum insulin and glucose were measured at baseline and again after a 3-year of followup. The usual dietary intakes were assessed using a validated 168 item semi-quantitative food frequency questionnaire and major dietary patterns were obtained using principal component analysis. Logistic regression models were used to estimate the occurrence of IR across tertiles of dietary patterns with adjustment for potential confounding variables. Mean age of participants was 39.0±11.2 years and 45.5% were men. Three major dietary patterns including the Western, traditional and healthy were extracted, which explained 25.3% of total variance in food intake. The healthy dietary pattern, loaded heavily on intake of vegetable oils, fresh and dried fruits, low-fat dairy, nuts and seeds, was accompanied with a reduced risk of insulin resistance by 51% (OR=0.49, 95% CI=0.30-0.81), and 81% (OR=0.19, 95% CI=0.10-0.36), in the second and third tertile, respectively (p trend=0.001). In the presence of all dietary pattern scores in the logistic regression model, a 45% reduced risk of IR was observed per 1 unit increase in healthy dietary pattern score. These findings confirmed the protective effect of a plant-based, low-fat dietary pattern against the development of insulin resistance as a main risk factor of type 2 diabetes and metabolic disorders.
Spinelli, Robert J
2006-01-01
The purpose of this study is to evaluate empirically in the hospital administrative environment the relationship of leadership behaviors to subordinate manager's perceived outcomes, through examination of B. M. Bass's (1985) model of transformational, transactional, and laissez-faire leadership. The author measured leadership orientation and outcome factors through subordinate managers' ratings of hospital CEOs using a questionnaire, which asked: Is there a relationship between the leadership styles of hospital CEOs and subordinate managers' self-reported willingness to exert extra effort, perception of leader effectiveness and satisfaction with their leader? Findings revealed that the relationship between transformational leadership and the outcome factors were stronger and more positive than were the transactional and laissez-faire styles. These findings are consistent with the hierarchal patterns reported and support the universality of the model.
Emergent Archetype Hydrological-Biogeochemical Response Patterns in Heterogeneous Catchments
NASA Astrophysics Data System (ADS)
Jawitz, J. W.; Gall, H. E.; Rao, P.
2013-12-01
What can spatiotemporally integrated patterns observed in stream hydrologic and biogeochemical signals generated in response to transient hydro-climatic and anthropogenic forcing tell us about the interactions between spatially heterogeneous soil-mediated hydrological and biogeochemical processes? We seek to understand how the spatial structure of solute sources coupled with hydrologic responses affect observed concentration-discharge (C-Q) patterns. These patterns are expressions of the spatiotemporal structure of solute loads exported from managed catchments, and their likely ecological consequences manifested in receiving water bodies (e.g., wetlands, rivers, lakes, and coastal waters). We investigated the following broad questions: (1) How does the correlation between flow-generating areas and biogeochemical source areas across a catchment evolve under stochastic hydro-climatic forcing? (2) What are the feasible hydrologic and biogeochemical responses that lead to the emergence of the observed archetype C-Q patterns? and; (3) What implications do these coupled dynamics have for catchment monitoring and implementation of management practices? We categorize the observed temporal signals into three archetypical C-Q patterns: dilution; accretion, and constant concentration. We introduce a parsimonious stochastic model of heterogeneous catchments, which act as hydrologic and biogeochemical filters, to examine the relationship between spatial heterogeneity and temporal history of solute export signals. The core concept of the modeling framework is considering the types and degree of spatial correlation between solute source zones and flow generating zones, and activation of different portions of the catchments during rainfall events. Our overarching hypothesis is that each of the archetype C-Q patterns can be generated by explicitly linking landscape-scale hydrologic responses and spatial distributions of solute source properties within a catchment. The model simulations reproduce the three major C-Q patterns observed in published data, offering valuable insight into coupled catchment processes. The findings have important implications for effective catchment management for water quality improvement, and stream monitoring strategies.
Early Menarche and Gestational Diabetes Mellitus at First Live Birth.
Shen, Yun; Hu, Hui; D Taylor, Brandie; Kan, Haidong; Xu, Xiaohui
2017-03-01
To examine the association between early menarche and gestational diabetes mellitus (GDM). Data from the National Health and Nutrition Examination Survey 2007-2012 were used to investigate the association between age at menarche and the risk of GDM at first birth among 5914 women. A growth mixture model was used to detect distinctive menarche onset patterns based on self-reported age at menarche. Logistic regression models were then used to examine the associations between menarche initiation patterns and GDM after adjusting for sociodemographic factors, family history of diabetes mellitus, lifetime greatest Body Mass Index, smoking status, and physical activity level. Among the 5914 first-time mothers, 3.4 % had self-reported GDM. We detected three groups with heterogeneous menarche onset patterns, the Early, Normal, and Late Menarche Groups. The regression model shows that compared to the Normal Menarche Group, the Early Menarche Group had 1.75 (95 % CI 1.10, 2.79) times the odds of having GDM. No statistically significant difference was observed between the Normal and the Late Menarche Group. This study suggests that early menarche may be a risk factor of GDM. Future studies are warranted to examine and confirm this finding.
Oliveira, João M.; Segurado, Pedro; Santos, José M.; Teixeira, Amílcar; Ferreira, Maria T.; Cortes, Rui V.
2012-01-01
Identifying the environmental gradients that control the functional structure of biological assemblages in reference conditions is fundamental to help river management and predict the consequences of anthropogenic stressors. Fish metrics (density of ecological guilds, and species richness) from 117 least disturbed stream reaches in several western Iberia river basins were modelled with generalized linear models in order to investigate the importance of regional- and local-scale abiotic gradients to variation in functional structure of fish assemblages. Functional patterns were primarily associated with regional features, such as catchment elevation and slope, rainfall, and drainage area. Spatial variations of fish guilds were thus associated with broad geographic gradients, showing (1) pronounced latitudinal patterns, affected mainly by climatic factors and topography, or (2) at the basin level, strong upstream-downstream patterns related to stream position in the longitudinal gradient. Maximum native species richness was observed in midsize streams in accordance with the river continuum concept. The findings of our study emphasized the need to use a multi-scale approach in order to fully assess the factors that govern the functional organization of biotic assemblages in ‘natural’ streams, as well as to improve biomonitoring and restoration of fluvial ecosystems. PMID:23029242
Linking Surface Topography Variations To Subsurface Mixing And Reaction Patterns
NASA Astrophysics Data System (ADS)
Le Borgne, T.; Bandopadhyay, A.; Davy, P.
2017-12-01
Fluctuations in surface topography generate nested streamline patterns in the subsurface over scales ranging from millimeters to kilometers. Because solute residence times can be very different for each streamlines, these patterns exert a strong control on biogeochemical reactions. While this effect has been quantified in reactive transport models, solute transfer across streamlines has been generally neglected. Yet, this process can lead to significant solute dilution and may trigger reactions by mixing water with different chemical compositions. Considering topography-driven subsurface flow cells of different sizes, we show that the resulting streamline structures act as shear flows, with shear rates that can vary over orders of magnitude depending on scale, permeability and hydraulic head gradient. This leads to the formation of localized layers of enhanced dilution and reaction, where mixing rates can be orders of magnitude larger than diffusion limited rates (Bandopadhyay et al. under review). We develop a theoretical model that predicts the depth and magnitude of these mixing hotspots and quantifies the resulting exports of conservative and reactive chemical species at discharge locations. We discuss consequences of these findings by applying this model at hyporheic zone, hillslope, and catchment scales.
Immune networks: multi-tasking capabilities at medium load
NASA Astrophysics Data System (ADS)
Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.
2013-08-01
Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ˜ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ˜ Nδ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ < 1 the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high-load regime δ = 1 we find that the system behaves as a spin-glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval.
A Model-Based Approach to Engineering Behavior of Complex Aerospace Systems
NASA Technical Reports Server (NTRS)
Ingham, Michel; Day, John; Donahue, Kenneth; Kadesch, Alex; Kennedy, Andrew; Khan, Mohammed Omair; Post, Ethan; Standley, Shaun
2012-01-01
One of the most challenging yet poorly defined aspects of engineering a complex aerospace system is behavior engineering, including definition, specification, design, implementation, and verification and validation of the system's behaviors. This is especially true for behaviors of highly autonomous and intelligent systems. Behavior engineering is more of an art than a science. As a process it is generally ad-hoc, poorly specified, and inconsistently applied from one project to the next. It uses largely informal representations, and results in system behavior being documented in a wide variety of disparate documents. To address this problem, JPL has undertaken a pilot project to apply its institutional capabilities in Model-Based Systems Engineering to the challenge of specifying complex spacecraft system behavior. This paper describes the results of the work in progress on this project. In particular, we discuss our approach to modeling spacecraft behavior including 1) requirements and design flowdown from system-level to subsystem-level, 2) patterns for behavior decomposition, 3) allocation of behaviors to physical elements in the system, and 4) patterns for capturing V&V activities associated with behavioral requirements. We provide examples of interesting behavior specification patterns, and discuss findings from the pilot project.
Assessment and prediction of road accident injuries trend using time-series models in Kurdistan.
Parvareh, Maryam; Karimi, Asrin; Rezaei, Satar; Woldemichael, Abraha; Nili, Sairan; Nouri, Bijan; Nasab, Nader Esmail
2018-01-01
Road traffic accidents are commonly encountered incidents that can cause high-intensity injuries to the victims and have direct impacts on the members of the society. Iran has one of the highest incident rates of road traffic accidents. The objective of this study was to model the patterns of road traffic accidents leading to injury in Kurdistan province, Iran. A time-series analysis was conducted to characterize and predict the frequency of road traffic accidents that lead to injury in Kurdistan province. The injuries were categorized into three separate groups which were related to the car occupants, motorcyclists and pedestrian road traffic accident injuries. The Box-Jenkins time-series analysis was used to model the injury observations applying autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) from March 2009 to February 2015 and to predict the accidents up to 24 months later (February 2017). The analysis was carried out using R-3.4.2 statistical software package. A total of 5199 pedestrians, 9015 motorcyclists, and 28,906 car occupants' accidents were observed. The mean (SD) number of car occupant, motorcyclist and pedestrian accident injuries observed were 401.01 (SD 32.78), 123.70 (SD 30.18) and 71.19 (SD 17.92) per year, respectively. The best models for the pattern of car occupant, motorcyclist, and pedestrian injuries were the ARIMA (1, 0, 0), SARIMA (1, 0, 2) (1, 0, 0) 12 , and SARIMA (1, 1, 1) (0, 0, 1) 12 , respectively. The motorcyclist and pedestrian injuries showed a seasonal pattern and the peak was during summer (August). The minimum frequency for the motorcyclist and pedestrian injuries were observed during the late autumn and early winter (December and January). Our findings revealed that the observed motorcyclist and pedestrian injuries had a seasonal pattern that was explained by air temperature changes overtime. These findings call the need for close monitoring of the accidents during the high-risk periods in order to control and decrease the rate of the injuries.
Multidimensional biochemical information processing of dynamical patterns
NASA Astrophysics Data System (ADS)
Hasegawa, Yoshihiko
2018-02-01
Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.
Correlations between human mobility and social interaction reveal general activity patterns.
Mollgaard, Anders; Lehmann, Sune; Mathiesen, Joachim
2017-01-01
A day in the life of a person involves a broad range of activities which are common across many people. Going beyond diurnal cycles, a central question is: to what extent do individuals act according to patterns shared across an entire population? Here we investigate the interplay between different activity types, namely communication, motion, and physical proximity by analyzing data collected from smartphones distributed among 638 individuals. We explore two central questions: Which underlying principles govern the formation of the activity patterns? Are the patterns specific to each individual or shared across the entire population? We find that statistics of the entire population allows us to successfully predict 71% of the activity and 85% of the inactivity involved in communication, mobility, and physical proximity. Surprisingly, individual level statistics only result in marginally better predictions, indicating that a majority of activity patterns are shared across our sample population. Finally, we predict short-term activity patterns using a generalized linear model, which suggests that a simple linear description might be sufficient to explain a wide range of actions, whether they be of social or of physical character.
Multidimensional biochemical information processing of dynamical patterns.
Hasegawa, Yoshihiko
2018-02-01
Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.
Seasonal Diversity Patterns of a Coastal Synechococcus Population
NASA Astrophysics Data System (ADS)
Hunter-Cevera, K. R.; Sosik, H. M.; Neubert, M.; Hammar, K.; Post, A.
2016-02-01
Understanding how environmental and ecological factors determine phytoplankton species abundances requires knowledge of the diversity present within a population. For the important primary producer Synechococcus, clades demonstrate differences in temperature tolerance, light acclimation, grazer palatability, and more. Marine Synechococcus populations are often composed of more than one clade, and overall population dynamics will be governed by the types of cells present and by their individual physiological capabilities. We investigate the diversity of the Synechococcus assemblage at the Martha's Vineyard Coastal Observatory with high-throughput sequencing of the V6 hypervariable region of the 16S rRNA gene. Small nucleotide differences within this region allow for resolution of distinct phylotypes that can have a direct correspondence to the well-defined Synechococcus clades. From a three-year time series, we find that the Synechococcus population is dominated by 5 distinct phylotypes, and that each type exhibits a repeatable, seasonal pattern in relative abundance. We use compositional data analysis techniques to investigate the relationships between these patterns and environmental factors. We further interpret these patterns in the context of Synechococcus population dynamics assessed by automated, submersible flow cytometry (FlowCytobot). Observed diel changes in cell size distributions, coupled with a validated matrix population model, provide estimates of in situ population division rates. We find strong evidence that the main seasonal diversity patterns are governed by temperature, but that biological loss agents likely shape the diversity structure for certain times of year. For some phylotypes, relative abundance patterns are also related to light and nutrients. The composition of Synechococcus over the annual cycle appears to directly affect seasonal features of cell abundance patterns, such as the spring bloom.
Investigating species co-occurrence patterns when species are detected imperfectly
MacKenzie, D.I.; Bailey, L.L.; Nichols, J.D.
2004-01-01
1. Over the last 30 years there has been a great deal of interest in investigating patterns of species co-occurrence across a number of locations, which has led to the development of numerous methods to determine whether there is evidence that a particular pattern may not have occurred by random chance. 2. A key aspect that seems to have been largely overlooked is the possibility that species may not always be detected at a location when present, which leads to 'false absences' in a species presence/absence matrix that may cause incorrect inferences to be made about co-occurrence patterns. Furthermore, many of the published methods for investigating patterns of species co-occurrence do not account for potential differences in the site characteristics that may partially (at least) explain non-random patterns (e.g. due to species having similar/different habitat preferences). 3. Here we present a statistical method for modelling co-occurrence patterns between species while accounting for imperfect detection and site characteristics. This method requires that multiple presence/absence surveys for the species be conducted over a reasonably short period of time at most sites. The method yields unbiased estimates of probabilities of occurrence, and is practical when the number of species is small (< 4). 4. To illustrate the method we consider data collected on two terrestrial salamander species, Plethodonjordani and members of the Plethodon glutinosus complex, collected in the Great Smoky Mountains National Park, USA. We find no evidence that the species do not occur independently at sites once site elevation has been allowed for, although we find some evidence of a statistical interaction between species in terms of detectability that we suggest may be due to changes in relative abundances.
Hunley, Keith L; Cabana, Graciela S
2016-07-01
Geneticists have argued that the linear decay in within-population genetic diversity with increasing geographic distance from East Africa is best explained by a phylogenetic process of repeated founder effects, growth, and isolation. However, this serial founder effect (SFE) process has not yet been adequately vetted against other evolutionary processes that may also affect geospatial patterns of diversity. Additionally, studies of the SFE process have been largely based on a limited 52-population sample. Here, we assess the effects of founder effect, admixture, and localized gene flow processes on patterns of global and regional diversity using a published data set of 645 autosomal microsatellite genotypes from 5,415 individuals in 248 widespread populations. We used a formal tree-fitting approach to explore the role of founder effects. The approach involved fitting global and regional population trees to extant patterns of gene diversity and then systematically examining the deviations in fit. We also informally tested the SFE process using linear models of gene diversity versus waypoint geographic distances from Africa. We tested the role of localized gene flow using partial Mantel correlograms of gene diversity versus geographic distance controlling for the confounding effects of treelike genetic structure. We corroborate previous findings that global patterns of diversity, both within and between populations, are the product of an out-of-Africa SFE process. Within regions, however, diversity within populations is uncorrelated with geographic distance from Africa. Here, patterns of diversity have been largely shaped by recent interregional admixture and secondary range expansions. Our detailed analyses of the pattern of diversity within and between populations reveal that the signatures of different evolutionary processes dominate at different geographic scales. These findings have important implications for recent publications on the biology of race.
A Western dietary pattern is associated with higher blood pressure in Iranian adolescents.
Hojhabrimanesh, Abdollah; Akhlaghi, Masoumeh; Rahmani, Elham; Amanat, Sasan; Atefi, Masoumeh; Najafi, Maryam; Hashemzadeh, Maral; Salehi, Saedeh; Faghih, Shiva
2017-02-01
The dietary determinants of adolescent blood pressure (BP) are not well understood. We determined the association between major dietary patterns and BP in a sample of Iranian adolescents. This cross-sectional study was conducted among a representative sample (n = 557) of Shirazi adolescents aged 12-19 years. Participants' systolic and diastolic BP was measured using a validated oscillometric BP monitor. Usual dietary intakes during the past 12 months were assessed using a valid and reproducible 168-item semiquantitative food frequency questionnaire through face-to-face interviews. Principal component factor analysis was used to identify major dietary patterns based on a set of 25 predefined food groups. Overall, three major dietary patterns were identified, among which only the Western pattern (abundant in soft drinks, sweets and desserts, salt, mayonnaise, tea and coffee, salty snacks, high-fat dairy products, French fries, and red or processed meats) had a significant association with BP. After adjusting for potential confounders in the analysis of covariance models, multivariable adjusted means of the systolic and mean BP of subjects in the highest tertile of the Western pattern score were significantly higher than those in the lowest tertile (for systolic BP: mean difference 6.9 mmHg, P = 0.001; and for mean BP: mean difference 4.2 mmHg, P = 0.003). A similar but statistically insignificant difference was observed in terms of diastolic BP. The findings suggest that a Western dietary pattern is associated with higher BP in Iranian adolescents. However, additional large-scale prospective studies with adequate methodological quality are required to confirm these findings.
Kinematic signature of a rotating bar near a resonance
NASA Technical Reports Server (NTRS)
Weinberg, Martin D.
1994-01-01
Recent work based on H I, star count and emission data suggests that the Milky Way has rotating bar-like features. In this paper, I show that such features cause distinctive stellar kinematic signatures near Outer Lindblad Resonance (OLR) and Inner Lindblad Resonance (ILR). The effect of these resonances may be observable far from the peak density of the pattern and relatively nearby the solar position. The details of the kinematic signatures depend on the evolutionary history of the 'bar' and therefore velocity data, both systematic and velocity dispersion, may be used to probe the evolutionary history as well as the present state of Galaxy. Kinematic models for a variety of sample scenarios are presented. Models with evolving pattern speeds show significantly stronger dispersion signatures than those with static pattern speeds, suggesting that useful observational constraints are possible. The models are applied to the proposed rotating spheroid and bar models; we find (1) none of these models chosen to represent the proposed large-scale rotating spheroid are consistent with the stellar kinematics and (2) a Galactic bar with semimajor axis of 3 kpc will cause a large increase in velocity dispersion in the vicinity of OLR (approximately 5 kpc) with little change in the net radial motion and such a signature is suggested by K-giant velocity data. Potential future observations and analyses are discussed.
High-LET Patterns of DSBs in DNA Loops, the HPRT Gene and Phosphorylation Foci
NASA Technical Reports Server (NTRS)
Ponomarev, Artem L.; Huff, Janice L.; Cucinotta, Francis A.
2007-01-01
We present new results obtained with our model based on the track structure and chromatin geometry that predicts the DSB spatial and genomic distributions in a cell nucleus with the full genome represented. The model generates stochastic patterns of DSBs in the physical space of the nucleus filled with the realistic configuration of human chromosomes. The model was re-used to find the distribution of DSBs in a physical volume corresponding to a visible phosphorylation focus believed to be associated with a DSB. The data shows whether there must more than one DSB per foci due to finite size of the visible focus, even if a single DSB is radiochemically responsible for the phosphorylation of DNA in its vicinity. The same model can predict patterns of closely located DSBs in a given gene, or in a DNA loop, one of the large-scale chromatin structures. We demonstrated for the example of the HPRT gene, how different sorts of radiation lead to proximity effect in DSB locations, which is important for modeling gene deletions. The spectrum of intron deletions and total gene deletions was simulated for the HPRT gene. The same proximity effect of DSBs in a loop can hinder DSB restitutions, as parts of the loop between DSBs is deleted with a higher likelihood. The distributions of DSBs and deletions of DNA in a loop are presented.
Distinct developmental genetic mechanisms underlie convergently evolved tooth gain in sticklebacks
Ellis, Nicholas A.; Glazer, Andrew M.; Donde, Nikunj N.; Cleves, Phillip A.; Agoglia, Rachel M.; Miller, Craig T.
2015-01-01
Teeth are a classic model system of organogenesis, as repeated and reciprocal epithelial and mesenchymal interactions pattern placode formation and outgrowth. Less is known about the developmental and genetic bases of tooth formation and replacement in polyphyodonts, which are vertebrates with continual tooth replacement. Here, we leverage natural variation in the threespine stickleback fish Gasterosteus aculeatus to investigate the genetic basis of tooth development and replacement. We find that two derived freshwater stickleback populations have both convergently evolved more ventral pharyngeal teeth through heritable genetic changes. In both populations, evolved tooth gain manifests late in development. Using pulse-chase vital dye labeling to mark newly forming teeth in adult fish, we find that both high-toothed freshwater populations have accelerated tooth replacement rates relative to low-toothed ancestral marine fish. Despite the similar evolved phenotype of more teeth and an accelerated adult replacement rate, the timing of tooth number divergence and the spatial patterns of newly formed adult teeth are different in the two populations, suggesting distinct developmental mechanisms. Using genome-wide linkage mapping in marine-freshwater F2 genetic crosses, we find that the genetic basis of evolved tooth gain in the two freshwater populations is largely distinct. Together, our results support a model whereby increased tooth number and an accelerated tooth replacement rate have evolved convergently in two independently derived freshwater stickleback populations using largely distinct developmental and genetic mechanisms. PMID:26062935
De Felice, Alessia; Scattoni, Maria Luisa; Ricceri, Laura; Calamandrei, Gemma
2015-01-01
Autism spectrum disorders are characterized by impaired social and communicative skills and repetitive behaviors. Emerging evidence supported the hypothesis that these neurodevelopmental disorders may result from a combination of genetic susceptibility and exposure to environmental toxins in early developmental phases. This study assessed the effects of prenatal exposure to chlorpyrifos (CPF), a widely diffused organophosphate insecticide endowed with developmental neurotoxicity at sub-toxic doses, in the BTBR T+tf/J mouse strain, a validated model of idiopathic autism that displays several behavioral traits relevant to the autism spectrum. To this aim, pregnant BTBR mice were administered from gestational day 14 to 17 with either vehicle or CPF at a dose of 6 mg/kg/bw by oral gavages. Offspring of both sexes underwent assessment of early developmental milestones, including somatic growth, motor behavior and ultrasound vocalization. To evaluate the potential long-term effects of CPF, two different social behavior patterns typically altered in the BTBR strain (free social interaction with a same-sex companion in females, or interaction with a sexually receptive female in males) were also examined in the two sexes at adulthood. Our findings indicate significant effects of CPF on somatic growth and neonatal motor patterns. CPF treated pups showed reduced weight gain, delayed motor maturation (i.e., persistency of immature patterns such as pivoting at the expenses of coordinated locomotion) and a trend to enhanced ultrasound vocalization. At adulthood, CPF associated alterations were found in males only: the altered pattern of investigation of a sexual partner, previously described in BTBR mice, was enhanced in CPF males, and associated to increased ultrasonic vocalization rate. These findings strengthen the need of future studies to evaluate the role of environmental chemicals in the etiology of neurodevelopment disorders.
NASA Astrophysics Data System (ADS)
Benza, Magdalena
The characteristics of places where people live and work play an important role in explaining complex social, political, economic and demographic processes. In sub-Saharan Africa rapid urban growth combined with rising poverty is creating diverse urban environments inhabited by people with a wide variety of lifestyles. This research examines how spatial patterns of land cover in a southern portion of the West African country of Ghana are associated with particular characteristics of family organization and reproduction decisions. Satellite imagery and landscape metrics are used to create an urban context definition based on landscape patterns using a gradient approach. Census data are used to estimate fertility levels and household structure, and the association between urban context, household composition and fertility levels is modeled through OLS regression, spatial autoregressive models and geographically weighted regression. Results indicate that there are significant differences in fertility levels between different urban contexts, with below average fertility levels found in the most urbanized end of the urban context definition and above average fertility levels found on the opposite end. The spatial patterns identified in the association between urban context and fertility levels indicate that, within the city areas with lower fertility have significant impacts on the reproductive levels of adjacent neighborhoods. Findings also indicate that there are clear patterns that link urban context to living arrangements and fertility levels. Female- and single-headed households are associated with below average fertility levels, a result that connects dropping fertility levels with the spread of smaller nuclear households in developing countries. At the same time, larger extended family households are linked to below average fertility levels for highly clustered areas, a finding that points to the prevalence of extended family housing in the West African city.
More than one way to see it: Individual heuristics in avian visual computation
Ravignani, Andrea; Westphal-Fitch, Gesche; Aust, Ulrike; Schlumpp, Martin M.; Fitch, W. Tecumseh
2015-01-01
Comparative pattern learning experiments investigate how different species find regularities in sensory input, providing insights into cognitive processing in humans and other animals. Past research has focused either on one species’ ability to process pattern classes or different species’ performance in recognizing the same pattern, with little attention to individual and species-specific heuristics and decision strategies. We trained and tested two bird species, pigeons (Columba livia) and kea (Nestor notabilis, a parrot species), on visual patterns using touch-screen technology. Patterns were composed of several abstract elements and had varying degrees of structural complexity. We developed a model selection paradigm, based on regular expressions, that allowed us to reconstruct the specific decision strategies and cognitive heuristics adopted by a given individual in our task. Individual birds showed considerable differences in the number, type and heterogeneity of heuristic strategies adopted. Birds’ choices also exhibited consistent species-level differences. Kea adopted effective heuristic strategies, based on matching learned bigrams to stimulus edges. Individual pigeons, in contrast, adopted an idiosyncratic mix of strategies that included local transition probabilities and global string similarity. Although performance was above chance and quite high for kea, no individual of either species provided clear evidence of learning exactly the rule used to generate the training stimuli. Our results show that similar behavioral outcomes can be achieved using dramatically different strategies and highlight the dangers of combining multiple individuals in a group analysis. These findings, and our general approach, have implications for the design of future pattern learning experiments, and the interpretation of comparative cognition research more generally. PMID:26113444
Describing temporal variation in reticuloruminal pH using continuous monitoring data.
Denwood, M J; Kleen, J L; Jensen, D B; Jonsson, N N
2018-01-01
Reticuloruminal pH has been linked to subclinical disease in dairy cattle, leading to considerable interest in identifying pH observations below a given threshold. The relatively recent availability of continuously monitored data from pH boluses gives new opportunities for characterizing the normal patterns of pH over time and distinguishing these from abnormal patterns using more sensitive and specific methods than simple thresholds. We fitted a series of statistical models to continuously monitored data from 93 animals on 13 farms to characterize normal variation within and between animals. We used a subset of the data to relate deviations from the normal pattern to the productivity of 24 dairy cows from a single herd. Our findings show substantial variation in pH characteristics between animals, although animals within the same farm tended to show more consistent patterns. There was strong evidence for a predictable diurnal variation in all animals, and up to 70% of the observed variation in pH could be explained using a simple statistical model. For the 24 animals with available production information, there was also a strong association between productivity (as measured by both milk yield and dry matter intake) and deviations from the expected diurnal pattern of pH 2 d before the productivity observation. In contrast, there was no association between productivity and the occurrence of observations below a threshold pH. We conclude that statistical models can be used to account for a substantial proportion of the observed variability in pH and that future work with continuously monitored pH data should focus on deviations from a predictable pattern rather than the frequency of observations below an arbitrary pH threshold. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Dykeman, Eric C.; Sankey, Otto F.
2010-02-01
We describe a technique for calculating the low-frequency mechanical modes and frequencies of a large symmetric biological molecule where the eigenvectors of the Hessian matrix are determined with full atomic detail. The method, which follows order N methods used in electronic structure theory, determines the subset of lowest-frequency modes while using group theory to reduce the complexity of the problem. We apply the method to three icosahedral viruses of various T numbers and sizes; the human viruses polio and hepatitis B, and the cowpea chlorotic mottle virus, a plant virus. From the normal-mode eigenvectors, we use a bond polarizability model to predict a low-frequency Raman scattering profile for the viruses. The full atomic detail in the displacement patterns combined with an empirical potential-energy model allows a comparison of the fully atomic normal modes with elastic network models and normal-mode analysis with only dihedral degrees of freedom. We find that coarse-graining normal-mode analysis (particularly the elastic network model) can predict the displacement patterns for the first few (˜10) low-frequency modes that are global and cooperative.
Glassy dynamics in three-dimensional embryonic tissues
Schötz, Eva-Maria; Lanio, Marcos; Talbot, Jared A.; Manning, M. Lisa
2013-01-01
Many biological tissues are viscoelastic, behaving as elastic solids on short timescales and fluids on long timescales. This collective mechanical behaviour enables and helps to guide pattern formation and tissue layering. Here, we investigate the mechanical properties of three-dimensional tissue explants from zebrafish embryos by analysing individual cell tracks and macroscopic mechanical response. We find that the cell dynamics inside the tissue exhibit features of supercooled fluids, including subdiffusive trajectories and signatures of caging behaviour. We develop a minimal, three-parameter mechanical model for these dynamics, which we calibrate using only information about cell tracks. This model generates predictions about the macroscopic bulk response of the tissue (with no fit parameters) that are verified experimentally, providing a strong validation of the model. The best-fit model parameters indicate that although the tissue is fluid-like, it is close to a glass transition, suggesting that small changes to single-cell parameters could generate a significant change in the viscoelastic properties of the tissue. These results provide a robust framework for quantifying and modelling mechanically driven pattern formation in tissues. PMID:24068179
Explaining cross-national differences in marriage, cohabitation, and divorce in Europe, 1990-2000.
Kalmijn, Matthijs
2007-11-01
European countries differ considerably in their marriage patterns. The study presented in this paper describes these differences for the 1990s and attempts to explain them from a macro-level perspective. We find that different indicators of marriage (i.e., marriage rate, age at marriage, divorce rate, and prevalence of unmarried cohabitation) cannot be seen as indicators of an underlying concept such as the 'strength of marriage'. Multivariate ordinary least squares (OLS) regression analyses are estimated with countries as units and panel regression models are estimated in which annual time series for multiple countries are pooled. Using these models, we find that popular explanations of trends in the indicators - explanations that focus on gender roles, secularization, unemployment, and educational expansion - are also important for understanding differences among countries. We also find evidence for the role of historical continuity and societal disintegration in understanding cross-national differences.
Constraints on dynamic topography from asymmetric subsidence of the mid-ocean ridges
NASA Astrophysics Data System (ADS)
Watkins, C. Evan; Conrad, Clinton P.
2018-02-01
Stresses from mantle convection deflect Earth's surface vertically, producing dynamic topography that is important for continental dynamics and sea-level change but difficult to observe due to overprinting by isostatic topography. For long wavelengths (∼104 km), the amplitude of dynamic topography is particularly uncertain, with mantle flow models typically suggesting larger amplitudes (>1000 m) than direct observations. Here we develop a new constraint on the amplitude of long-wavelength dynamic topography by examining asymmetries in seafloor bathymetry across mid-ocean ridges. We compare bathymetric profiles across the Mid-Atlantic Ridge (MAR) and the East Pacific Rise (EPR) and we find that the South American flank of both ridges subsides faster than its opposing flank. This pattern is consistent with dynamic subsidence across South America, supported by downwelling in the lower mantle. To constrain the amplitude of dynamic topography, we compare bathymetric profiles across both ridges after correcting bathymetry for several different models of dynamic topography with varying amplitudes and spatial patterns. We find that long-wavelength dynamic topography with an amplitude of only ∼500 m explains the observed asymmetry of the MAR. A similar model can explain EPR asymmetry but is complicated by additional asymmetrical topography associated with tectonic, crustal thickness, and/or asthenospheric temperature asymmetries across the EPR. After removing 500 m of dynamic topography, both the MAR and EPR exhibit a slower seafloor subsidence rate (∼280-290 m/Myr1/2) than previously reported. Our finding of only ∼500 m of long-wavelength dynamic topography may indicate the importance of thermochemical convection and/or large viscosity variations for lower mantle dynamics.
Universal scaling in the branching of the tree of life.
Herrada, E Alejandro; Tessone, Claudio J; Klemm, Konstantin; Eguíluz, Víctor M; Hernández-García, Emilio; Duarte, Carlos M
2008-07-23
Understanding the patterns and processes of diversification of life in the planet is a key challenge of science. The Tree of Life represents such diversification processes through the evolutionary relationships among the different taxa, and can be extended down to intra-specific relationships. Here we examine the topological properties of a large set of interspecific and intraspecific phylogenies and show that the branching patterns follow allometric rules conserved across the different levels in the Tree of Life, all significantly departing from those expected from the standard null models. The finding of non-random universal patterns of phylogenetic differentiation suggests that similar evolutionary forces drive diversification across the broad range of scales, from macro-evolutionary to micro-evolutionary processes, shaping the diversity of life on the planet.
Navier-Stokes flow field analysis of compressible flow in a high pressure safety relief valve
NASA Technical Reports Server (NTRS)
Vu, Bruce; Wang, Ten-See; Shih, Ming-Hsin; Soni, Bharat
1993-01-01
The objective of this study is to investigate the complex three-dimensional flowfield of an oxygen safety pressure relieve valve during an incident, with a computational fluid dynamic (CFD) analysis. Specifically, the analysis will provide a flow pattern that would lead to the expansion of the eventual erosion pattern of the hardware, so as to combine it with other findings to piece together a most likely scenario for the investigation. The CFD model is a pressure based solver. An adaptive upwind difference scheme is employed for the spatial discretization, and a predictor, multiple corrector method is used for the velocity-pressure coupling. The computational result indicated vortices formation near the opening of the valve which matched the erosion pattern of the damaged hardware.
NASA Astrophysics Data System (ADS)
Hayes, A. G.; Ewing, R. C.; Cassini Radar Science Team, T.
2011-12-01
Fields of bedform patterns persist across many orders of magnitude, from cm-scale sub-aqueous current ripples to km-scale aeolian dunes, and form with surprisingly little difference in expression despite a range of formative environments. Because of the remarkable similarity between and among patterns, extracting information about climate and environment from these patterns is a challenge. For example, crest orientation is not diagnostic of a particular flow regime; similar patterns form under many different flow configurations. On Titan, these challenges have played out with many attempts to reconcile dune-field patterns with modeled and expected wind regimes. We propose that thinking about the change in dune orientation, rather than the orientation itself, can provide new insights on the long-term stability of the dune-field patterns and the formative wind regime. In this work, we apply the re-orientation model presented by Werner and Kocurek [Geology, 1997] to the equatorial dune fields of Titan. We measure variations in pattern parameters (crest spacing, crest length and defect density, which is the number of defect pairs per total crest length) both within and between Titan's dune fields to describe pattern maturity and identify areas where changes in dune orientation are likely to occur (or may already be occurring). Measured defect densities are similar to Earth's largest linear dune fields, such as the Namib Sand Sea and the Simpson Desert. We use measured defect densities in the Werner and Kocurek model to estimate crestline reorientation rates. We find reorientation timescales varying from ten to a hundred thousand times the average migration timescale (time to migrate a bedform one meter, ~1 Titan year according to Tokano (Aeolian Research, 2010)). Well organized patterns have the longest reorientation time scales (~10^5 migration timescales), while the topographically or spatially isolated patches of dunes show the shortest reorientation times (~10^3 migration timescales). In addition, comparisons between spacing and defect density of Titan's dunes and some of the largest fields observed on Earth and Mars reveal that dune patterns on all three planets are geometrically similar, suggesting that growth and organization share common pattern dynamics. Our results suggest that Titan's dunes may react to gross bedform transport averaged over orbital timescales, relaxing the requirement that a single modern wind regime is required to produce the observed pattern.
Modification of medullary respiratory-related discharge patterns by behaviors and states of arousal.
Chang, F C
1992-02-07
The modulatory influences of behaviors and states of arousal on bulbar respiratory-related unit (RRU) discharge patterns were studied in an unanesthetized, freely behaving guinea pig respiratory model system. When fully instrumented, this model system permits concurrent monitoring and recording of (i) single units from either Bötzinger complex or nucleus para-ambiguus; (ii) electrocorticogram; and, (iii) diaphragmatic EMG. In addition to being used in surveys of RRU discharge patterns in freely behaving states, the model system also offered a unique opportunity in investigating the effects of pentobarbital on RRU discharge patterns before, throughout the course of, and during recovery from anesthesia. In anesthetized preparations, a particular RRU discharge pattern (such as tonic, incrementing or decrementing) typically displayed little, if any notable variation. The most striking development following pentobarbital was a state of progressive bradypnea attributable to a significantly augmented RRU cycle duration, burst duration and an increase in the RRU spike frequencies during anesthesia. In freely behaving states, medullary RRU activities rarely adhered to a fixed, immutable discharge pattern. More specifically, the temporal organization (such as burst duration, cycle duration, and the extent of modulation of within-burst spike frequencies) of RRU discharge patterns regularly showed complex and striking variations, not only with states of arousal (sleep/wakefulness, anesthesia) but also with discrete alterations in electrocorticogram (ECoG) activities and a multitude of on-going behavioral repertoires such as volitional movement, postural modification, phonation, mastication, deglutition, sniffing/exploratory behavior, alerting/startle reflexes. Only during sleep, and on occasions when the animal assumed a motionless, resting posture, could burst patterns of relatively invariable periodicity and uniform temporal attributes be observed. RRU activities during sniffing reflex is worthy of further note in that, based on power spectrum analyses of concurrently recorded ECoG activities, this particular discharge pattern was clearly associated with the activation of a 6-10 Hz theta rhythm. These findings indicated that bulbar RRU activity patterns are subject to change by not only behaviors and sleep/wakefulness cycles, but also a variety of modulatory influences and feedback/feedforward biases from other central and peripheral physiological control mechanisms.
The punctum fixum-punctum mobile model: a neuromuscular principle for efficient movement generation?
von Laßberg, Christoph; Rapp, Walter
2015-01-01
According to the "punctum fixum-punctum mobile model" that was introduced in prior studies, for generation of the most effective intentional acceleration of a body part the intersegmental neuromuscular onset succession has to spread successively from the rotation axis (punctum fixum) toward the body part that shall be accelerated (punctum mobile). The aim of the present study was to investigate whether this principle is, indeed, fundamental for any kind of efficient rotational accelerations in general, independent of the kind of movements, type of rotational axis, the current body position, or movement direction. Neuromuscular onset succession was captured by surface electromyography of relevant muscles of the anterior and posterior muscle chain in 16 high-level gymnasts during intentional accelerating movement phases while performing 18 different gymnastics elements (in various body positions to forward and backward, performed on high bar, parallel bars, rings and trampoline), as well as during non-sport specific pivot movements around the longitudinal axis. The succession patterns to generate the acceleration phases during these movements were described and statistically evaluated based on the onset time difference between the muscles of the corresponding muscle chain. In all the analyzed movement phases, the results clearly support the hypothesized succession pattern from punctum fixum to punctum mobile. This principle was further underlined by the finding that the succession patterns do change their direction running through the body when the rotational axis (punctum fixum) has been changed (e.g., high bar or rings [hands] vs. floor or trampoline [feet]). The findings improve our understanding of intersegmental neuromuscular coordination patterns to generate intentional movements most efficiently. This could help to develop more specific methods to facilitate such patterns in particular contexts, thus allowing for shorter motor learning procedures of context-specific key movement sequences in different disciplines of sports, as well as during non-sport specific movements.
Guillot, Michel; Gerland, Patrick; Pelletier, François; Saabneh, Ameed
2012-01-01
Background The under-five mortality rate (the probability of dying between birth and age 5 y, also denoted in the literature as U5MR and 5 q 0) is a key indicator of child health, but it conceals important information about how this mortality is distributed by age. One important distinction is what amount of the under-five mortality occurs below age 1 y (1 q 0) versus at age 1 y and above (4 q 1). However, in many country settings, this distinction is often difficult to establish because of various types of data errors. As a result, it is common practice to resort to model age patterns to estimate 1 q 0 and 4 q 1 on the basis of an observed value of 5 q 0. The most commonly used model age patterns for this purpose are the Coale and Demeny and the United Nations systems. Since the development of these models, many additional sources of data for under-five mortality have become available, making possible a general evaluation of age patterns of infant and child mortality. In this paper, we do a systematic comparison of empirical values of 1 q 0 and 4 q 1 against model age patterns, and discuss whether observed deviations are due to data errors, or whether they reflect true epidemiological patterns not addressed in existing model life tables. Methods and Findings We used vital registration data from the Human Mortality Database, sample survey data from the World Fertility Survey and Demographic and Health Surveys programs, and data from Demographic Surveillance Systems. For each of these data sources, we compared empirical combinations of 1 q 0 and 4 q 1 against combinations provided by Coale and Demeny and United Nations model age patterns. We found that, on the whole, empirical values fall relatively well within the range provided by these models, but we also found important exceptions. Sub-Saharan African countries have a tendency to exhibit high values of 4 q 1 relative to 1 q 0, a pattern that appears to arise for the most part from true epidemiological causes. While this pattern is well known in the case of western Africa, we observed that it is more widespread than commonly thought. We also found that the emergence of HIV/AIDS, while perhaps contributing to high relative values of 4 q 1, does not appear to have substantially modified preexisting patterns. We also identified a small number of countries scattered in different parts of the world that exhibit unusually low values of 4 q 1 relative to 1 q 0, a pattern that is not likely to arise merely from data errors. Finally, we illustrate that it is relatively common for populations to experience changes in age patterns of infant and child mortality as they experience a decline in mortality. Conclusions Existing models do not appear to cover the entire range of epidemiological situations and trajectories. Therefore, model life tables should be used with caution for estimating 1 q 0 and 4 q 1 on the basis of 5 q 0. Moreover, this model-based estimation procedure assumes that the input value of 5 q 0 is correct, which may not always be warranted, especially in the case of survey data. A systematic evaluation of data errors in sample surveys and their impact on age patterns of 1 q 0 and 4 q 1 is urgently needed, along with the development of model age patterns of under-five mortality that would cover a wider range of epidemiological situations and trajectories. Please see later in the article for the Editors' Summary. PMID:22952438
Yan, Yuanwei; Bejoy, Julie; Xia, Junfei; Guan, Jingjiao; Zhou, Yi; Li, Yan
2016-09-15
Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells/tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capacity of signaling factors that regulate 3-D neural tissue patterning in vitro and differential responses of the resulting neural populations to various biomolecules have not yet been fully understood. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog (SHH) signaling, this study generated different 3-D neuronal cultures that were mainly comprised of either cortical glutamatergic neurons or motor neurons. Abundant glutamatergic neurons were observed following the treatment with an antagonist of SHH signaling, cyclopamine, while Islet-1 and HB9-expressing motor neurons were enriched by an SHH agonist, purmorphamine. In neurons derived with different neural patterning factors, whole-cell patch clamp recordings showed similar voltage-gated Na(+)/K(+) currents, depolarization-evoked action potentials and spontaneous excitatory post-synaptic currents. Moreover, these different neuronal populations exhibited differential responses to three classes of biomolecules, including (1) matrix metalloproteinase inhibitors that affect extracellular matrix remodeling; (2) N-methyl-d-aspartate that induces general neurotoxicity; and (3) amyloid β (1-42) oligomers that cause neuronal subtype-specific neurotoxicity. This study should advance our understanding of hiPSC self-organization and neural tissue development and provide a transformative approach to establish 3-D models for neurological disease modeling and drug discovery. Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells, tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capability of sonic hedgehog-related small molecules to tune different neuronal subtypes in 3-D differentiation from hiPSCs and the differential cellular responses of region-specific neuronal subtypes to various biomolecules have not been fully investigated. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog signaling, this study provides knowledge on the differential susceptibility of region-specific neuronal subtypes derived from hiPSCs to different biomolecules in extracellular matrix remodeling and neurotoxicity. The findings are significant for understanding 3-D neural patterning of hiPSCs for the applications in brain organoid formation, neurological disease modeling, and drug discovery. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Fiedler, S.; Stevens, B.; Mauritsen, T.
2017-12-01
State-of-the-art climate models have persistently shown a spread in estimates of the effective radiative forcing (ERF) associated with anthropogenic aerosol. Different reasons for the spread are known, but their relative importance is poorly understood. In this presentation we investigate the role of natural atmospheric variability, global patterns of aerosol radiative effects, and magnitudes of aerosol-cloud interaction in controlling the ERF of anthropogenic aerosol (Fiedler et al., 2017). We use the Earth system model MPI-ESM1.2 for conducting ensembles of atmosphere-only simulations and calculate the shortwave ERF of anthropogenic aerosol at the top of the atmosphere. The radiative effects are induced with the new parameterisation MACv2-SP (Stevens et al., 2017) that prescribes observationally constrained anthropogenic aerosol optical properties and an associated Twomey effect. Firstly, we compare the ERF of global patterns of anthropogenic aerosol from the mid-1970s and today. Our results suggest that such a substantial pattern difference has a negligible impact on the global mean ERF, when the natural variability of the atmosphere is considered. The clouds herein efficiently mask the clear-sky contributions to the forcing and reduce the detectability of significant anthropogenic aerosol radiative effects in all-sky conditions. Secondly, we strengthen the forcing magnitude through increasing the effect of aerosol-cloud interaction by prescribing an enhanced Twomey effect. In that case, the different spatial pattern of aerosol radiative effects from the mid-1970s and today causes a moderate change (15%) in the ERF of anthropogenic aerosol in our model. This finding lets us speculate that models with strong aerosol-cloud interactions would show a stronger ERF change with anthropogenic aerosol patterns. Testing whether the anthropogenic aerosol radiative forcing is model-dependent under prescribed aerosol conditions is currently ongoing work using MACv2-SP in comprehensive aerosol-climate models in the framework of the EU-funded project BACCHUS. In the future, MACv2-SP will be used in models participating in the Radiative Forcing Model Intercomparison Project (Pincus et al., 2016).
Leyk, Stefan; Binder, Claudia R; Nuckols, John R
2009-03-30
Pesticide poisoning is a global health issue with the largest impacts in the developing countries where residential and small-scale agricultural areas are often integrated and pesticides sprayed manually. To reduce health risks from pesticide exposure approaches for personalized exposure assessment (PEA) are needed. We present a conceptual framework to develop a spatial individual-based model (IBM) prototype for assessing potential exposure of farm-workers conducting small-scale agricultural production, which accounts for a considerable portion of global food crop production. Our approach accounts for dynamics in the contaminant distributions in the environment, as well as patterns of movement and activities performed on an individual level under different safety scenarios. We demonstrate a first prototype using data from a study area in a rural part of Colombia, South America. Different safety scenarios of PEA were run by including weighting schemes for activities performed under different safety conditions. We examined the sensitivity of individual exposure estimates to varying patterns of pesticide application and varying individual patterns of movement. This resulted in a considerable variation in estimates of magnitude, frequency and duration of exposure over the model runs for each individual as well as between individuals. These findings indicate the influence of patterns of pesticide application, individual spatial patterns of movement as well as safety conditions on personalized exposure in the agricultural production landscape that is the focus of our research. This approach represents a conceptual framework for developing individual based models to carry out PEA in small-scale agricultural settings in the developing world based on individual patterns of movement, safety conditions, and dynamic contaminant distributions. The results of our analysis indicate our prototype model is sufficiently sensitive to differentiate and quantify the influence of individual patterns of movement and decision-based pesticide management activities on potential exposure. This approach represents a framework for further understanding the contribution of agricultural pesticide use to exposure in the small-scale agricultural production landscape of many developing countries, and could be useful to evaluate public health intervention strategies to reduce risks to farm-workers and their families. Further research is needed to fully develop an operational version of the model.
Henry, Laurence; Craig, Adrian J. F. K.; Lemasson, Alban; Hausberger, Martine
2015-01-01
Turn-taking in conversation appears to be a common feature in various human cultures and this universality raises questions about its biological basis and evolutionary trajectory. Functional convergence is a widespread phenomenon in evolution, revealing sometimes striking functional similarities between very distant species even though the mechanisms involved may be different. Studies on mammals (including non-human primates) and bird species with different levels of social coordination reveal that temporal and structural regularities in vocal interactions may depend on the species' social structure. Here we test the hypothesis that turn-taking and associated rules of conversations may be an adaptive response to the requirements of social life, by testing the applicability of turn-taking rules to an animal model, the European starling. Birdsong has for many decades been considered as one of the best models of human language and starling songs have been well described in terms of vocal production and perception. Starlings do have vocal interactions where alternating patterns predominate. Observational and experimental data on vocal interactions reveal that (1) there are indeed clear temporal and structural regularities, (2) the temporal and structural patterning is influenced by the immediate social context, the general social situation, the individual history, and the internal state of the emitter. Comparison of phylogenetically close species of Sturnids reveals that the alternating pattern of vocal interactions varies greatly according to the species' social structure, suggesting that interactional regularities may have evolved together with social systems. These findings lead to solid bases of discussion on the evolution of communication rules in relation to social evolution. They will be discussed also in terms of processes, at the light of recent neurobiological findings. PMID:26441787
Roth, Zvi N
2016-01-01
Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream.
Roth, Zvi N.
2016-01-01
Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream. PMID:27242455
Musz, Elizabeth; Thompson-Schill, Sharon L.
2017-01-01
To successfully comprehend a sentence that contains a homonym, readers must select the ambiguous word’s context-appropriate meaning. The outcome of this process is influenced both by top-down contextual support and bottom-up, word-specific characteristics. We examined how these factors jointly affect the neural signatures of lexical ambiguity resolution. We measured the similarity between multi-voxel patterns evoked by the same homonym in two distinct linguistic contexts: once after subjects read sentences that biased interpretation toward each homonym’s most frequent, dominant meaning, and again after interpretation was biased toward a weaker, subordinate meaning. We predicted that, following a subordinate-biasing context, the dominant yet inappropriate meaning would nevertheless compete for activation, manifesting in increased similarity between the neural patterns evoked by the two word meanings. In left anterior temporal lobe (ATL), degree of within-word pattern similarity was positively predicted by the association strength of each homonym’s dominant meaning. Further, within-word pattern similarity in left ATL was negatively predicted by item-specific responses in a region of left ventrolateral prefrontal cortex (VLPFC) sensitive to semantic conflict. These findings have implications for psycholinguistic models of lexical ambiguity resolution, and for the role of left VLPFC function during this process. Moreover, these findings demonstrate the utility of item-level, similarity-based analyses of fMRI data for our understanding of competition between co-activated word meanings during language comprehension. PMID:27898341
Initiation and propagation of a PKN hydraulic fracture in permeable rock: Toughness dominated regime
NASA Astrophysics Data System (ADS)
Sarvaramini, E.; Garagash, D.
2011-12-01
The present work investigates the injection of a low-viscosity fluid into a pre-existing fracture with constrained height (PKN), as in waterflooding or supercritical CO2 injection. Contrary to conventional hydraulic fracturing, where 'cake build up' limits diffusion to a small zone, the low viscosity fluid allows for diffusion over a wider range of scales. Over large injection times the pattern becomes 2 or 3-D, necessitating a full-space diffusion modeling. In addition, the dissipation of energy associated with fracturing of rock dominates the energy needed for the low-viscosity fluid flow into the propagating crack. As a result, the fracture toughness is important in evaluating both the initiation and the ensuing propagation of these fractures. Classical PKN hydraulic fracturing model, amended to account for full-space leak-off and the toughness [Garagash, unpublished 2009], is used to evaluate the pressure history and fluid leak-off volume during the injection of low viscosity fluid into a pre-existing and initially stationary. In order to find the pressure history, the stationary crack is first subject to a step pressure increase. The response of the porous medium to the step pressure increase in terms of fluid leak-off volume provides the fundamental solution, which then can be used to find the transient pressurization using Duhamel theorem [Detournay & Cheng, IJSS 1991]. For the step pressure increase an integral equation technique is used to find the leak-off rate history. For small time the solution must converge to short time asymptote, which corresponds to 1-D diffusion pattern. However, as the diffusion length in the zone around the fracture increases the assumption of a 1-D pattern is no longer valid and the diffusion follows a 2-D pattern. The solution to the corresponding integral equation gives the leak-off rate history, which is used to find the cumulative leak-off volume. The transient pressurization solution is obtained using global conservation of fluid injected into the fracture. With increasing pressure in the fracture due to the fluid injection, the energy release rate eventually becomes equal to the toughness and fracture propagates. The evolution of the fracture length is established using the method similar to the one employed for the stationary crack.
Striving for Discussion: An Analysis of a Teacher Educator's Comments in Whole-Class Conversation
ERIC Educational Resources Information Center
Reynolds, Todd
2016-01-01
During my English Language Arts methods class, I noticed that my discussion patterns were teacher-focused and in an Initiation-Response-Evaluation format. Because I wanted to model dialogic methods of whole-class discussions for my preservice teachers, I recoiled from this finding and began a self-study using an action research method to examine…
ERIC Educational Resources Information Center
Simpkins, Sandra D.; Vest, Andrea E.; Becnel, Jennifer N.
2010-01-01
This investigation examined the precursors of adolescents' participation in sport and music activities in the United States by testing a developmental model across 7 years. Data were drawn from youth questionnaires in the Childhood and Beyond Study (92% European American; N = 594). Findings suggest that patterns of participation across a 3-year…
Artificial bee colony in neuro - Symbolic integration
NASA Astrophysics Data System (ADS)
Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf
2017-08-01
Swarm intelligence is a research area that models the population of the swarm based on natural computation. Artificial bee colony (ABC) algorithm is a swarm based metaheuristic algorithm introduced by Karaboga to optimize numerical problem. Pattern-SAT is a pattern reconstruction paradigm that utilized 2SAT logical rule in representing the behavior of the desired pattern. The information of the desired pattern in terms of 2SAT logic is embedded to Hopfield neural network (HNN-P2SAT) and the desired pattern is reconstructed during the retrieval phase. Since the performance of HNN-P2SAT in Pattern-SAT deteriorates when the number of 2SAT clause increased, newly improved ABC is used to reduce the computation burden during the learning phase of HNN-P2SAT (HNN-P2SATABC). The aim of this study is to investigate the performance of Pattern-SAT produced by ABC incorporated with HNN-P2SAT and compare it with conventional standalone HNN. The comparison is examined by using Microsoft Visual Basic C++ 2013 software. The detailed comparison in doing Pattern-SAT is discussed based on global Pattern-SAT, ratio of activated clauses and computation time. The result obtained from computer simulation indicates the beneficial features of HNN-P2SATABC in doing Pattern-SAT. This finding is expected to result in a significant implication on the choice of searching method used to do Pattern-SAT.
Colour and pattern change against visually heterogeneous backgrounds in the tree frog Hyla japonica.
Kang, Changku; Kim, Ye Eun; Jang, Yikweon
2016-03-02
Colour change in animals can be adaptive phenotypic plasticity in heterogeneous environments. Camouflage through background colour matching has been considered a primary force that drives the evolution of colour changing ability. However, the mechanism to which animals change their colour and patterns under visually heterogeneous backgrounds (i.e. consisting of more than one colour) has only been identified in limited taxa. Here, we investigated the colour change process of the Japanese tree frog (Hyla japonica) against patterned backgrounds and elucidated how the expression of dorsal patterns changes against various achromatic/chromatic backgrounds with/without patterns. Our main findings are i) frogs primarily responded to the achromatic differences in background, ii) their contrasting dorsal patterns were conditionally expressed dependent on the brightness of backgrounds, iii) against mixed coloured background, frogs adopted intermediate forms between two colours. Using predator (avian and snake) vision models, we determined that colour differences against different backgrounds yielded perceptible changes in dorsal colours. We also found substantial individual variation in colour changing ability and the levels of dorsal pattern expression between individuals. We discuss the possibility of correlational selection on colour changing ability and resting behaviour that maintains the high variation in colour changing ability within population.
Hermens, Frouke; Matthews, William J.
2015-01-01
Abstract We asked participants to make simple risky choices while we recorded their eye movements. We built a complete statistical model of the eye movements and found very little systematic variation in eye movements over the time course of a choice or across the different choices. The only exceptions were finding more (of the same) eye movements when choice options were similar, and an emerging gaze bias in which people looked more at the gamble they ultimately chose. These findings are inconsistent with prospect theory, the priority heuristic, or decision field theory. However, the eye movements made during a choice have a large relationship with the final choice, and this is mostly independent from the contribution of the actual attribute values in the choice options. That is, eye movements tell us not just about the processing of attribute values but also are independently associated with choice. The pattern is simple—people choose the gamble they look at more often, independently of the actual numbers they see—and this pattern is simpler than predicted by decision field theory, decision by sampling, and the parallel constraint satisfaction model. © 2015 The Authors. Journal of Behavioral Decision Making published by John Wiley & Sons Ltd. PMID:27522985
Palmer, Cameron; Pe’er, Itsik
2016-01-01
Missing data are an unavoidable component of modern statistical genetics. Different array or sequencing technologies cover different single nucleotide polymorphisms (SNPs), leading to a complicated mosaic pattern of missingness where both individual genotypes and entire SNPs are sporadically absent. Such missing data patterns cannot be ignored without introducing bias, yet cannot be inferred exclusively from nonmissing data. In genome-wide association studies, the accepted solution to missingness is to impute missing data using external reference haplotypes. The resulting probabilistic genotypes may be analyzed in the place of genotype calls. A general-purpose paradigm, called Multiple Imputation (MI), is known to model uncertainty in many contexts, yet it is not widely used in association studies. Here, we undertake a systematic evaluation of existing imputed data analysis methods and MI. We characterize biases related to uncertainty in association studies, and find that bias is introduced both at the imputation level, when imputation algorithms generate inconsistent genotype probabilities, and at the association level, when analysis methods inadequately model genotype uncertainty. We find that MI performs at least as well as existing methods or in some cases much better, and provides a straightforward paradigm for adapting existing genotype association methods to uncertain data. PMID:27310603
NASA Astrophysics Data System (ADS)
Hussain, Kamal; Pratap Singh, Satya; Kumar Datta, Prasanta
2013-11-01
A numerical investigation is presented to show the dependence of patterning effect (PE) of an amplified signal in a bulk semiconductor optical amplifier (SOA) and an optical bandpass filter based amplifier on various input signal and filter parameters considering both the cases of including and excluding intraband effects in the SOA model. The simulation shows that the variation of PE with input energy has a characteristic nature which is similar for both the cases. However the variation of PE with pulse width is quite different for the two cases, PE being independent of the pulse width when intraband effects are neglected in the model. We find a simple relationship between the PE and the signal pulse width. Using a simple treatment we study the effect of the amplified spontaneous emission (ASE) on PE and find that the ASE has almost no effect on the PE in the range of energy considered here. The optimum filter parameters are determined to obtain an acceptable extinction ratio greater than 10 dB and a PE less than 1 dB for the amplified signal over a wide range of input signal energy and bit-rate.
Probabilistic models for neural populations that naturally capture global coupling and criticality
2017-01-01
Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality. PMID:28926564
Distributed and Dynamic Storage of Working Memory Stimulus Information in Extrastriate Cortex
Sreenivasan, Kartik K.; Vytlacil, Jason; D'Esposito, Mark
2015-01-01
The predominant neurobiological model of working memory (WM) posits that stimulus information is stored via stable elevated activity within highly selective neurons. Based on this model, which we refer to as the canonical model, the storage of stimulus information is largely associated with lateral prefrontal cortex (lPFC). A growing number of studies describe results that cannot be fully explained by the canonical model, suggesting that it is in need of revision. In the present study, we directly test key elements of the canonical model. We analyzed functional MRI data collected as participants performed a task requiring WM for faces and scenes. Multivariate decoding procedures identified patterns of activity containing information about the items maintained in WM (faces, scenes, or both). While information about WM items was identified in extrastriate visual cortex (EC) and lPFC, only EC exhibited a pattern of results consistent with a sensory representation. Information in both regions persisted even in the absence of elevated activity, suggesting that elevated population activity may not represent the storage of information in WM. Additionally, we observed that WM information was distributed across EC neural populations that exhibited a broad range of selectivity for the WM items rather than restricted to highly selective EC populations. Finally, we determined that activity patterns coding for WM information were not stable, but instead varied over the course of a trial, indicating that the neural code for WM information is dynamic rather than static. Together, these findings challenge the canonical model of WM. PMID:24392897
Movement Patterns, Social Dynamics, and the Evolution of Cooperation
Smaldino, Paul E.; Schank, Jeffrey C.
2012-01-01
The structure of social interactions influences many aspects of social life, including the spread of information and behavior, and the evolution of social phenotypes. After dispersal, organisms move around throughout their lives, and the patterns of their movement influence their social encounters over the course of their lifespan. Though both space and mobility are known to influence social evolution, there is little analysis of the influence of specific movement patterns on evolutionary dynamics. We explored the effects of random movement strategies on the evolution of cooperation using an agent-based prisoner’s dilemma model with mobile agents. This is the first systematic analysis of a model in which cooperators and defectors can use different random movement strategies, which we chose to fall on a spectrum between highly exploratory and highly restricted in their search tendencies. Because limited dispersal and restrictions to local neighborhood size are known to influence the ability of cooperators to effectively assort, we also assessed the robustness of our findings with respect to dispersal and local capacity constraints. We show that differences in patterns of movement can dramatically influence the likelihood of cooperator success, and that the effects of different movement patterns are sensitive to environmental assumptions about offspring dispersal and local space constraints. Since local interactions implicitly generate dynamic social interaction networks, we also measured the average number of unique and total interactions over a lifetime and considered how these emergent network dynamics helped explain the results. This work extends what is known about mobility and the evolution of cooperation, and also has general implications for social models with randomly moving agents. PMID:22838026
Gaseous spiral structure and mass drift in spiral galaxies
NASA Astrophysics Data System (ADS)
Kim, Yonghwi; Kim, Woong-Tae
2014-05-01
We use hydrodynamic simulations to investigate non-linear gas responses to an imposed stellar spiral potential in disc galaxies. The gaseous medium is assumed to be infinitesimally thin, isothermal, and unmagnetized. We consider various spiral-arm models with differing strength and pattern speed. We find that the extent and shapes of gaseous arms as well as the related mass drift rate depend rather sensitively on the arm pattern speed. In models where the arm pattern is rotating slow, the gaseous arms extend across the corotation resonance (CR) all the way to the outer boundary, with a pitch angle slightly smaller than that of the stellar counterpart. In models with a fast rotating pattern, on the other hand, spiral shocks are much more tightly wound than the stellar arms, and cease to exist in the regions near and outside the CR where mathcal {M}_perp /sin p_* gtrsim 25-40, with mathcal {M}_perp denoting the perpendicular Mach number of a rotating gas relative to the arms with pitch angle p*. Inside the CR, the arms drive mass inflows at a rate of ˜0.05-3.0 M⊙ yr-1 to the central region, with larger values corresponding to stronger and slower arms. The contribution of the shock dissipation, external torque, and self-gravitational torque to the mass inflow is roughly 50, 40, and 10 per cent, respectively. We demonstrate that the distributions of line-of-sight velocities and spiral-arm densities can be a useful diagnostic tool to distinguish if the spiral pattern is rotating fast or slow.
NASA Astrophysics Data System (ADS)
Dinske, C.; Langenbruch, C.; Shapiro, S. A.
2017-12-01
We investigate seismicity related to hydrothermal systems in Germany and Italy, focussing on temporal changes of seismicity rates. Our analysis was motivated by numerical simulations The modeling of stress changes caused by the injection and production of fluid revealed that seismicity rates decrease on a long-term perspective which is not observed in the considered case studies. We analyze the waiting time distributions of the seismic events in both time domain (inter event times) and fluid volume domain (inter event volume). We find clear indications that the observed seismicity comprises two components: (1) seismicity that is directly triggered by production and re-injection of fluid, i.e. induced events, and (2) seismicity that is triggered by earthquake interactions, i.e. aftershock triggering. In order to better constrain our numerical simulations using the observed induced seismicity we apply catalog declustering to seperate the two components. We use the magnitude-dependent space-time windowing approach introduced by Gardner and Knopoff (1974) and test several published algorithms to calculate the space-time windows. After declustering, we conclude that the different hydrothermal reservoirs show a comparable seismic response to the circulation of fluid and additional triggering by earthquake interactions. The declustered catalogs contain approximately 50 per cent of the number of events in the original catalogs. We then perform ETAS (Epidemic Type Aftershock; Ogata, 1986, 1988) modeling for two reasons. First, we want to know whether the different reservoirs are also comparable regarding earthquake interaction patterns. Second, if we identify systematic patterns, ETAS modeling can contribute to forecast seismicity during production of geothermal energy. We find that stationary ETAS models cannot accurately capture real seismicity rate changes. One reason for this finding is given by the rate of observed induced events which is not constant over time. Hence we utilize non-stationary ETAS modeling (Kumazawa and Ogata, 2013, 2014) which results in a good agreement with the observation. But the required non-stationarity of the process of seismicity triggering complicates an implementation of ETAS modeling in induced seismicity forecast models.
A robust operational model for predicting where tropical cyclone waves damage coral reefs
NASA Astrophysics Data System (ADS)
Puotinen, Marji; Maynard, Jeffrey A.; Beeden, Roger; Radford, Ben; Williams, Gareth J.
2016-05-01
Tropical cyclone (TC) waves can severely damage coral reefs. Models that predict where to find such damage (the ‘damage zone’) enable reef managers to: 1) target management responses after major TCs in near-real time to promote recovery at severely damaged sites; and 2) identify spatial patterns in historic TC exposure to explain habitat condition trajectories. For damage models to meet these needs, they must be valid for TCs of varying intensity, circulation size and duration. Here, we map damage zones for 46 TCs that crossed Australia’s Great Barrier Reef from 1985-2015 using three models - including one we develop which extends the capability of the others. We ground truth model performance with field data of wave damage from seven TCs of varying characteristics. The model we develop (4MW) out-performed the other models at capturing all incidences of known damage. The next best performing model (AHF) both under-predicted and over-predicted damage for TCs of various types. 4MW and AHF produce strikingly different spatial and temporal patterns of damage potential when used to reconstruct past TCs from 1985-2015. The 4MW model greatly enhances both of the main capabilities TC damage models provide to managers, and is useful wherever TCs and coral reefs co-occur.
A robust operational model for predicting where tropical cyclone waves damage coral reefs.
Puotinen, Marji; Maynard, Jeffrey A; Beeden, Roger; Radford, Ben; Williams, Gareth J
2016-05-17
Tropical cyclone (TC) waves can severely damage coral reefs. Models that predict where to find such damage (the 'damage zone') enable reef managers to: 1) target management responses after major TCs in near-real time to promote recovery at severely damaged sites; and 2) identify spatial patterns in historic TC exposure to explain habitat condition trajectories. For damage models to meet these needs, they must be valid for TCs of varying intensity, circulation size and duration. Here, we map damage zones for 46 TCs that crossed Australia's Great Barrier Reef from 1985-2015 using three models - including one we develop which extends the capability of the others. We ground truth model performance with field data of wave damage from seven TCs of varying characteristics. The model we develop (4MW) out-performed the other models at capturing all incidences of known damage. The next best performing model (AHF) both under-predicted and over-predicted damage for TCs of various types. 4MW and AHF produce strikingly different spatial and temporal patterns of damage potential when used to reconstruct past TCs from 1985-2015. The 4MW model greatly enhances both of the main capabilities TC damage models provide to managers, and is useful wherever TCs and coral reefs co-occur.
Nonlinear dynamics and rheology of active fluids: simulations in two dimensions.
Fielding, S M; Marenduzzo, D; Cates, M E
2011-04-01
We report simulations of a continuum model for (apolar, flow aligning) active fluids in two dimensions. Both free and anchored boundary conditions are considered, at parallel confining walls that are either static or moving at fixed relative velocity. We focus on extensile materials and find that steady shear bands, previously shown to arise ubiquitously in one dimension for the active nematic phase at small (or indeed zero) shear rate, are generally replaced in two dimensions by more complex flow patterns that can be stationary, oscillatory, or apparently chaotic. The consequences of these flow patterns for time-averaged steady-state rheology are examined. ©2011 American Physical Society
Polarization mode control of long-wavelength VCSELs by intracavity patterning
Long, Christopher Michael; Mickovic, Zlatko; Dwir, Benjamin; ...
2016-04-26
Polarization mode control is enhanced in wafer-fused vertical-cavity surface-emitting lasers emitting at 1310 nm wavelength by etching two symmetrically arranged arcs above the gain structure within the laser cavity. The intracavity patterning introduces birefringence and dichroism, which discriminates between the two polarization states of the fundamental transverse modes. We find that the cavity modifications define the polarization angle at threshold with respect to the crystal axes, and increase the gain anisotropy and birefringence on average, leading to an increase in the polarization switching current. As a result, experimental measurements are explained using the spin-flip model of VCSEL polarization dynamics.
Fukunaga, Tsukasa; Iwasaki, Wataru
2017-01-19
With rapid advances in genome sequencing and editing technologies, systematic and quantitative analysis of animal behavior is expected to be another key to facilitating data-driven behavioral genetics. The nematode Caenorhabditis elegans is a model organism in this field. Several video-tracking systems are available for automatically recording behavioral data for the nematode, but computational methods for analyzing these data are still under development. In this study, we applied the Gaussian mixture model-based binning method to time-series postural data for 322 C. elegans strains. We revealed that the occurrence patterns of the postural states and the transition patterns among these states have a relationship as expected, and such a relationship must be taken into account to identify strains with atypical behaviors that are different from those of wild type. Based on this observation, we identified several strains that exhibit atypical transition patterns that cannot be fully explained by their occurrence patterns of postural states. Surprisingly, we found that two simple factors-overall acceleration of postural movement and elimination of inactivity periods-explained the behavioral characteristics of strains with very atypical transition patterns; therefore, computational analysis of animal behavior must be accompanied by evaluation of the effects of these simple factors. Finally, we found that the npr-1 and npr-3 mutants have similar behavioral patterns that were not predictable by sequence homology, proving that our data-driven approach can reveal the functions of genes that have not yet been characterized. We propose that elimination of inactivity periods and overall acceleration of postural change speed can explain behavioral phenotypes of strains with very atypical postural transition patterns. Our methods and results constitute guidelines for effectively finding strains that show "truly" interesting behaviors and systematically uncovering novel gene functions by bioimage-informatic approaches.
EFFECTS OF NON-CIRCULAR MOTIONS ON AZIMUTHAL COLOR GRADIENTS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martinez-Garcia, Eric E.; Gonzalez-Lopezlira, Rosa A.; Gomez, Gilberto C., E-mail: emartinez@cida.v, E-mail: r.gonzalez@crya.unam.m, E-mail: g.gomez@crya.unam.m
2009-12-20
Assuming that density waves trigger star formation, and that young stars preserve the velocity components of the molecular gas where they are born, we analyze the effects that non-circular gas orbits have on color gradients across spiral arms. We try two approaches, one involving semianalytical solutions for spiral shocks, and another with magnetohydrodynamic (MHD) numerical simulation data. We find that, if non-circular motions are ignored, the comparison between observed color gradients and stellar population synthesis models would in principle yield pattern speed values that are systematically too high for regions inside corotation, with the difference between the real and themore » measured pattern speeds increasing with decreasing radius. On the other hand, image processing and pixel averaging result in systematically lower measured spiral pattern speed values, regardless of the kinematics of stellar orbits. The net effect is that roughly the correct pattern speeds are recovered, although the trend of higher measured OMEGA{sub p} at lower radii (as expected when non-circular motions exist but are neglected) should still be observed. We examine the MartInez-GarcIa et al. photometric data and confirm that this is indeed the case. The comparison of the size of the systematic pattern speed offset in the data with the predictions of the semianalytical and MHD models corroborates that spirals are more likely to end at outer Lindblad resonance, as these authors had already found.« less
An Age-Structured Extension to the Vectorial Capacity Model
Novoseltsev, Vasiliy N.; Michalski, Anatoli I.; Novoseltseva, Janna A.; Yashin, Anatoliy I.; Carey, James R.; Ellis, Alicia M.
2012-01-01
Background Vectorial capacity and the basic reproductive number (R0) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention. Methodology/Principal Findings Based on survival analysis we derived new equations for vectorial capacity and R0 that are valid for any pattern of age-dependent (or age–independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies. Conclusions/Significance Accounting for age-dependent vector mortality in estimates of vectorial capacity and R0 was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R0 is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R0∼1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field. PMID:22724022