A comparative study of fuzzy target selection methods in direct marketing

NARCIS (Netherlands)

Costa Sousa, da J.M.; Kaymak, U.; Madeira, S.

2002-01-01

Target selection in direct marketing is an important data mining problem for which fuzzy modeling can be used. The paper compares several fuzzy modeling techniques applied to target selection based on recency, frequency and monetary value measures. The comparison uses cross validation applied to

The spatial patterns of directional phenotypic selection.

Science.gov (United States)

Siepielski, Adam M; Gotanda, Kiyoko M; Morrissey, Michael B; Diamond, Sarah E; DiBattista, Joseph D; Carlson, Stephanie M

2013-11-01

Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.

The spatial patterns of directional phenotypic selection

KAUST Repository

Siepielski, Adam M.

2013-09-12

Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.

Genetic trends of selection for pelt traits in Karakul sheep I. Direct ...

African Journals Online (AJOL)

Genetic trends of selection for pelt traits in Karakul sheep. I. Direct ... development in the Karakul Wereestimated with the Animal Model in four selection lines and in a control flock over ..... Selection experiments in laboratory and domestic.

The spatial patterns of directional phenotypic selection

KAUST Repository

Siepielski, Adam M.; Gotanda, Kiyoko M.; Morrissey, Michael B.; Diamond, Sarah E.; DiBattista, Joseph; Carlson, Stephanie Marie

2013-01-01

the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data

Directional selection can drive the evolution of modularity in complex traits.

Science.gov (United States)

Melo, Diogo; Marroig, Gabriel

2015-01-13

Modularity is a central concept in modern biology, providing a powerful framework for the study of living organisms on many organizational levels. Two central and related questions can be posed in regard to modularity: How does modularity appear in the first place, and what forces are responsible for keeping and/or changing modular patterns? We approached these questions using a quantitative genetics simulation framework, building on previous results obtained with bivariate systems and extending them to multivariate systems. We developed an individual-based model capable of simulating many traits controlled by many loci with variable pleiotropic relations between them, expressed in populations subject to mutation, recombination, drift, and selection. We used this model to study the problem of the emergence of modularity, and hereby show that drift and stabilizing selection are inefficient at creating modular variational structures. We also demonstrate that directional selection can have marked effects on the modular structure between traits, actively promoting a restructuring of genetic variation in the selected population and potentially facilitating the response to selection. Furthermore, we give examples of complex covariation created by simple regimes of combined directional and stabilizing selection and show that stabilizing selection is important in the maintenance of established covariation patterns. Our results are in full agreement with previous results for two-trait systems and further extend them to include scenarios of greater complexity. Finally, we discuss the evolutionary consequences of modular patterns being molded by directional selection.

Directional selection effects on patterns of phenotypic (co)variation in wild populations.

Science.gov (United States)

Assis, A P A; Patton, J L; Hubbe, A; Marroig, G

2016-11-30

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient. © 2016 The Author(s).

Directional Darwinian Selection in proteins.

Science.gov (United States)

McClellan, David A

2013-01-01

Molecular evolution is a very active field of research, with several complementary approaches, including dN/dS, HON90, MM01, and others. Each has documented strengths and weaknesses, and no one approach provides a clear picture of how natural selection works at the molecular level. The purpose of this work is to present a simple new method that uses quantitative amino acid properties to identify and characterize directional selection in proteins. Inferred amino acid replacements are viewed through the prism of a single physicochemical property to determine the amount and direction of change caused by each replacement. This allows the calculation of the probability that the mean change in the single property associated with the amino acid replacements is equal to zero (H0: μ = 0; i.e., no net change) using a simple two-tailed t-test. Example data from calanoid and cyclopoid copepod cytochrome oxidase subunit I sequence pairs are presented to demonstrate how directional selection may be linked to major shifts in adaptive zones, and that convergent evolution at the whole organism level may be the result of convergent protein adaptations. Rather than replace previous methods, this new method further complements existing methods to provide a holistic glimpse of how natural selection shapes protein structure and function over evolutionary time.

Finding Direction in the Search for Selection

OpenAIRE

Thiltgen, G.; Dos Reis, M.; Goldstein, R. A.

2016-01-01

Tests for positive selection have mostly been developed to look for diversifying selection where change away from the current amino acid is often favorable. However, in many cases we are interested in directional selection where there is a shift toward specific amino acids, resulting in increased fitness in the species. Recently, a few methods have been developed to detect and characterize directional selection on a molecular level. Using the results of evolutionary simulations as well as HIV...

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

Science.gov (United States)

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Strength and tempo of directional selection in the wild

OpenAIRE

Hoekstra, H. E.; Hoekstra, J. M.; Berrigan, D.; Vignieri, S. N.; Hoang, A.; Hill, C. E.; Beerli, P.; Kingsolver, J. G.

2001-01-01

Directional selection is a major force driving adaptation and evolutionary change. However, the distribution, strength, and tempo of phenotypic selection acting on quantitative traits in natural populations remain unclear across different study systems. We reviewed the literature (1984–1997) that reported the strength of directional selection as indexed by standardized linear selection gradients (β). We asked how strong are viability and sexual selection, and whether strength of selection is ...

Directed evolution: selecting today's biocatalysts : selecting today's biocatalysts

NARCIS (Netherlands)

Otten, Linda; Quax, Wim

2005-01-01

Directed evolution has become a full-grown tool in molecular biology nowadays. The methods that are involved in creating a mutant library are extensive and can be divided into several categories according to their basic ideas. Furthermore, both screening and selection can be used to target the

The evolution of trade-offs under directional and correlational selection.

Science.gov (United States)

Roff, Derek A; Fairbairn, Daphne J

2012-08-01

Using quantitative genetic theory, we develop predictions for the evolution of trade-offs in response to directional and correlational selection. We predict that directional selection favoring an increase in one trait in a trade-off will result in change in the intercept but not the slope of the trade-off function, with the mean value of the selected trait increasing and that of the correlated trait decreasing. Natural selection will generally favor an increase in some combination of trait values, which can be represented as directional selection on an index value. Such selection induces both directional and correlational selection on the component traits. Theory predicts that selection on an index value will also change the intercept but not the slope of the trade-off function but because of correlational selection, the direction of change in component traits may be in the same or opposite directions. We test these predictions using artificial selection on the well-established trade-off between fecundity and flight capability in the cricket, Gryllus firmus and compare the empirical results with a priori predictions made using genetic parameters from a separate half-sibling experiment. Our results support the predictions and illustrate the complexity of trade-off evolution when component traits are subject to both directional and correlational selection. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Direction selective structural-acoustic coupled radiator

Science.gov (United States)

Seo, Hee-Seon; Kim, Yang-Hann

2005-04-01

This paper presents a method of designing a structural-acoustic coupled radiator that can emit sound in the desired direction. The structural-acoustic coupled system is consisted of acoustic spaces and wall. The wall composes two plates and an opening, and the wall separates one space that is highly reverberant and the other that is unbounded without any reflection. An equation is developed that predicts energy distribution and energy flow in the two spaces separated by the wall, and its computational examples are presented including near field acoustic characteristics. To design the directional coupled radiator, Pareto optimization method is adapted. An objective is selected to maximize radiation power on a main axis and minimize a side lobe level and a subjective is selected direction of the main axis and dimensions of the walls geometry. Pressure and intensity distribution of the designed radiator is also presented.

Directional selection causes decanalization in a group I ribozyme.

Science.gov (United States)

Hayden, Eric J; Weikert, Christian; Wagner, Andreas

2012-01-01

A canalized genotype is robust to environmental or genetic perturbations. Canalization is expected to result from stabilizing selection on a well-adapted phenotype. Decanalization, the loss of robustness, might follow periods of directional selection toward a new optimum. The evolutionary forces causing decanalization are still unknown, in part because it is difficult to determine the fitness effects of mutations in populations of organisms with complex genotypes and phenotypes. Here, we report direct experimental measurements of robustness in a system with a simple genotype and phenotype, the catalytic activity of an RNA enzyme. We find that the robustness of a population of RNA enzymes decreases during a period of directional selection in the laboratory. The decrease in robustness is primarily caused by the selective sweep of a genotype that is decanalized relative to the wild-type, both in terms of mutational robustness and environmental robustness (thermodynamic stability). Our results experimentally demonstrate that directional selection can cause decanalization on short time scales, and demonstrate co-evolution of mutational and environmental robustness.

Directional selection in temporally replicated studies is remarkably consistent.

Science.gov (United States)

Morrissey, Michael B; Hadfield, Jarrod D

2012-02-01

Temporal variation in selection is a fundamental determinant of evolutionary outcomes. A recent paper presented a synthetic analysis of temporal variation in selection in natural populations. The authors concluded that there is substantial variation in the strength and direction of selection over time, but acknowledged that sampling error would result in estimates of selection that were more variable than the true values. We reanalyze their dataset using techniques that account for the necessary effect of sampling error to inflate apparent levels of variation and show that directional selection is remarkably constant over time, both in magnitude and direction. Thus we cannot claim that the available data support the existence of substantial temporal heterogeneity in selection. Nonetheless, we conject that temporal variation in selection could be important, but that there are good reasons why it may not appear in the available data. These new analyses highlight the importance of applying techniques that estimate parameters of the distribution of selection, rather than parameters of the distribution of estimated selection (which will reflect both sampling error and "real" variation in selection); indeed, despite availability of methods for the former, focus on the latter has been common in synthetic reviews of the aspects of selection in nature, and can lead to serious misinterpretations. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

Science.gov (United States)

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

Dynamic selection of ship responses for estimation of on-site directional wave spectra

DEFF Research Database (Denmark)

Andersen, Ingrid Marie Vincent; Storhaug, Gaute

2012-01-01

-estimate of the wave spectrum is suggested. The selection method needs to be robust for what reason a parameterised uni-directional, two-parameter wave spectrum is treated. The parameters included are the zero up-crossing period, the significant wave height and the main wave direction relative to the ship’s heading...... with the best overall agreement are selected for the actual estimation of the directional wave spectrum. The transfer functions for the ship responses can be determined using different computational methods such as striptheory, 3D panel codes, closed form expressions or model tests. The uncertainty associated......Knowledge of the wave environment in which a ship is operating is crucial for most on-board decision support systems. Previous research has shown that the directional wave spectrum can be estimated by the use of measured global ship responses and a set of transfer functions determined...

Effects of changing canopy directional reflectance on feature selection

Science.gov (United States)

Smith, J. A.; Oliver, R. E.; Kilpela, O. E.

1973-01-01

The use of a Monte Carlo model for generating sample directional reflectance data for two simplified target canopies at two different solar positions is reported. Successive iterations through the model permit the calculation of a mean vector and covariance matrix for canopy reflectance for varied sensor view angles. These data may then be used to calculate the divergence between the target distributions for various wavelength combinations and for these view angles. Results of a feature selection analysis indicate that different sets of wavelengths are optimum for target discrimination depending on sensor view angle and that the targets may be more easily discriminated for some scan angles than others. The time-varying behavior of these results is also pointed out.

The allele-frequency spectrum in a decoupled Moran model with mutation, drift, and directional selection, assuming small mutation rates.

Science.gov (United States)

Vogl, Claus; Clemente, Florian

2012-05-01

We analyze a decoupled Moran model with haploid population size N, a biallelic locus under mutation and drift with scaled forward and backward mutation rates θ(1)=μ(1)N and θ(0)=μ(0)N, and directional selection with scaled strength γ=sN. With small scaled mutation rates θ(0) and θ(1), which is appropriate for single nucleotide polymorphism data in highly recombining regions, we derive a simple approximate equilibrium distribution for polymorphic alleles with a constant of proportionality. We also put forth an even simpler model, where all mutations originate from monomorphic states. Using this model we derive the sojourn times, conditional on the ancestral and fixed allele, and under equilibrium the distributions of fixed and polymorphic alleles and fixation rates. Furthermore, we also derive the distribution of small samples in the diffusion limit and provide convenient recurrence relations for calculating this distribution. This enables us to give formulas analogous to the Ewens-Watterson estimator of θ for biased mutation rates and selection. We apply this theory to a polymorphism dataset of fourfold degenerate sites in Drosophila melanogaster. Copyright © 2012 Elsevier Inc. All rights reserved.

Bayesian Model Selection under Time Constraints

Science.gov (United States)

Hoege, M.; Nowak, W.; Illman, W. A.

2017-12-01

Bayesian model selection (BMS) provides a consistent framework for rating and comparing models in multi-model inference. In cases where models of vastly different complexity compete with each other, we also face vastly different computational runtimes of such models. For instance, time series of a quantity of interest can be simulated by an autoregressive process model that takes even less than a second for one run, or by a partial differential equations-based model with runtimes up to several hours or even days. The classical BMS is based on a quantity called Bayesian model evidence (BME). It determines the model weights in the selection process and resembles a trade-off between bias of a model and its complexity. However, in practice, the runtime of models is another weight relevant factor for model selection. Hence, we believe that it should be included, leading to an overall trade-off problem between bias, variance and computing effort. We approach this triple trade-off from the viewpoint of our ability to generate realizations of the models under a given computational budget. One way to obtain BME values is through sampling-based integration techniques. We argue with the fact that more expensive models can be sampled much less under time constraints than faster models (in straight proportion to their runtime). The computed evidence in favor of a more expensive model is statistically less significant than the evidence computed in favor of a faster model, since sampling-based strategies are always subject to statistical sampling error. We present a straightforward way to include this misbalance into the model weights that are the basis for model selection. Our approach follows directly from the idea of insufficient significance. It is based on a computationally cheap bootstrapping error estimate of model evidence and is easy to implement. The approach is illustrated in a small synthetic modeling study.

Evidence of directional and stabilizing selection in contemporary humans.

Science.gov (United States)

Sanjak, Jaleal S; Sidorenko, Julia; Robinson, Matthew R; Thornton, Kevin R; Visscher, Peter M

2018-01-02

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

Direction selectivity in the larval zebrafish tectum is mediated by asymmetric inhibition

Directory of Open Access Journals (Sweden)

Abhinav eGrama

2012-09-01

Full Text Available The extraction of the direction of motion is an important computation performed by many sensory systems and in particular, the mechanism by which direction selective ganglion cells (DS-RGCs in the retina acquire their selective properties, has been studied extensively. However, whether DS-RGCs simply relay this information to downstream areas or whether additional and potentially de-novo processing occurs in these recipient structures is a matter of great interest. Neurons in the larval zebrafish tectum, the largest retino-recipent area in this animal, show direction selective responses to moving visual stimuli but how these properties are acquired is still unknown. In order to study this, we first used two-photon calcium imaging to classify the population responses of tectal cells to bars moving at different speeds and in different directions. Subsequently, we performed in-vivo whole cell electrophysiology on these direction selective tectal neurons and we found that their inhibitory inputs were strongly biased towards the null direction of motion, whereas the excitatory inputs showed little selectivity. In addition, we found that excitatory currents evoked by a stimulus moving in the preferred direction occurred before the inhibitory currents whereas a stimulus moving in the null direction evoked currents in the reverse temporal order. The membrane potential modulations resulting from these currents were enhanced by the spike generation mechanism to generate amplified direction selectivity in the spike output. Thus our results implicate a local inhibitory circuit in generating direction selectivity in tectal neurons.

Directional selection has shaped the oral jaws of Lake Malawi cichlid fishes.

Science.gov (United States)

Albertson, R Craig; Streelman, J Todd; Kocher, Thomas D

2003-04-29

East African cichlid fishes represent one of the most striking examples of rapid and convergent evolutionary radiation among vertebrates. Models of ecological speciation would suggest that functional divergence in feeding morphology has contributed to the origin and maintenance of cichlid species diversity. However, definitive evidence for the action of natural selection has been missing. Here we use quantitative genetics to identify regions of the cichlid genome responsible for functionally important shape differences in the oral jaw apparatus. The consistent direction of effects for individual quantitative trait loci suggest that cichlid jaws and teeth evolved in response to strong, divergent selection. Moreover, several chromosomal regions contain a disproportionate number of quantitative trait loci, indicating a prominent role for pleiotropy or genetic linkage in the divergence of this character complex. Of particular interest are genomic intervals with concerted effects on both the length and height of the lower jaw. Coordinated changes in this area of the oral jaw apparatus are predicted to have direct consequences for the speed and strength of jaw movement. Taken together, our results imply that the rapid and replicative nature of cichlid trophic evolution is the result of directional selection on chromosomal packages that encode functionally linked aspects of the craniofacial skeleton.

Development of an Environment for Software Reliability Model Selection

Science.gov (United States)

1992-09-01

now is directed to other related problems such as tools for model selection, multiversion programming, and software fault tolerance modeling... multiversion programming, 7. Hlardware can be repaired by spare modules, which is not. the case for software, 2-6 N. Preventive maintenance is very important

Response to selection in finite locus models with nonadditive effects

NARCIS (Netherlands)

Esfandyari, Hadi; Henryon, Mark; Berg, Peer; Thomasen, Jørn Rind; Bijma, Piter; Sørensen, Anders Christian

2017-01-01

Under the finite-locus model in the absence of mutation, the additive genetic variation is expected to decrease when directional selection is acting on a population, according to quantitative-genetic theory. However, some theoretical studies of selection suggest that the level of additive

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

Science.gov (United States)

Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L

2016-04-01

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population. © 2015 Stichting International Foundation for Animal Genetics.

Visual Orientation and Directional Selectivity through Thalamic Synchrony

Science.gov (United States)

Stanley, Garrett B.; Jin, Jianzhong; Wang, Yushi; Desbordes, Gaëlle; Wang, Qi; Black, Michael J.; Alonso, Jose-Manuel

2012-01-01

Thalamic neurons respond to visual scenes by generating synchronous spike trains on the timescale of 10 – 20 ms that are very effective at driving cortical targets. Here we demonstrate that this synchronous activity contains unexpectedly rich information about fundamental properties of visual stimuli. We report that the occurrence of synchronous firing of cat thalamic cells with highly overlapping receptive fields is strongly sensitive to the orientation and the direction of motion of the visual stimulus. We show that this stimulus selectivity is robust, remaining relatively unchanged under different contrasts and temporal frequencies (stimulus velocities). A computational analysis based on an integrate-and-fire model of the direct thalamic input to a layer 4 cortical cell reveals a strong correlation between the degree of thalamic synchrony and the nonlinear relationship between cortical membrane potential and the resultant firing rate. Together, these findings suggest a novel population code in the synchronous firing of neurons in the early visual pathway that could serve as the substrate for establishing cortical representations of the visual scene. PMID:22745507

Bayesian estimation of direct and correlated responses to selection on linear or ratio expressions of feed efficiency in pigs

DEFF Research Database (Denmark)

Shirali, Mahmoud; Varley, Patrick Francis; Jensen, Just

2018-01-01

meat percentage (LMP) along with the derived traits of RFI and FCR; and (3) deriving Bayesian estimates of direct and correlated responses to selection on RFI, FCR, ADG, ADFI, and LMP. Response to selection was defined as the difference in additive genetic mean of the selected top individuals, expected......, respectively. Selection against RFIG showed a direct response of − 0.16 kg/d and correlated responses of − 0.16 kg/kg for FCR and − 0.15 kg/d for ADFI, with no effect on other production traits. Selection against FCR resulted in a direct response of − 0.17 kg/kg and correlated responses of − 0.14 kg/d for RFIG......, − 0.18 kg/d for ADFI, and 0.98% for LMP. Conclusions: The Bayesian methodology developed here enables prediction of breeding values for FCR and RFI from a single multi-variate model. In addition, we derived posterior distributions of direct and correlated responses to selection. Genetic parameter...

Site selection and directional models of deserts used for ERBE validation targets

Science.gov (United States)

Staylor, W. F.

1986-01-01

Broadband shortwave and longwave radiance measurements obtained from the Nimbus 7 Earth Radiation Budget scanner were used to develop reflectance and emittance models for the Sahara, Gibson, and Saudi Deserts. These deserts will serve as in-flight validation targets for the Earth Radiation Budget Experiment being flown on the Earth Radiation Budget Satellite and two National Oceanic and Atmospheric Administration polar satellites. The directional reflectance model derived for the deserts was a function of the sum and product of the cosines of the solar and viewing zenith angles, and thus reciprocity existed between these zenith angles. The emittance model was related by a power law of the cosine of the viewing zenith angle.

Directed forgetting of visual symbols: evidence for nonverbal selective rehearsal.

Science.gov (United States)

Hourihan, Kathleen L; Ozubko, Jason D; MacLeod, Colin M

2009-12-01

Is selective rehearsal possible for nonverbal information? Two experiments addressed this question using the item method directed forgetting paradigm, where the advantage of remember items over forget items is ascribed to selective rehearsal favoring the remember items. In both experiments, difficult-to-name abstract symbols were presented for study, followed by a recognition test. Directed forgetting effects were evident for these symbols, regardless of whether they were or were not spontaneously named. Critically, a directed forgetting effect was observed for unnamed symbols even when the symbols were studied under verbal suppression to prevent verbal rehearsal. This pattern indicates that a form of nonverbal rehearsal can be used strategically (i.e., selectively) to enhance memory, even when verbal rehearsal is not possible.

A computational neural model of goal-directed utterance selection.

Science.gov (United States)

Klein, Michael; Kamp, Hans; Palm, Guenther; Doya, Kenji

2010-06-01

It is generally agreed that much of human communication is motivated by extra-linguistic goals: we often make utterances in order to get others to do something, or to make them support our cause, or adopt our point of view, etc. However, thus far a computational foundation for this view on language use has been lacking. In this paper we propose such a foundation using Markov Decision Processes. We borrow computational components from the field of action selection and motor control, where a neurobiological basis of these components has been established. In particular, we make use of internal models (i.e., next-state transition functions defined on current state action pairs). The internal model is coupled with reinforcement learning of a value function that is used to assess the desirability of any state that utterances (as well as certain non-verbal actions) can bring about. This cognitive architecture is tested in a number of multi-agent game simulations. In these computational experiments an agent learns to predict the context-dependent effects of utterances by interacting with other agents that are already competent speakers. We show that the cognitive architecture can account for acquiring the capability of deciding when to speak in order to achieve a certain goal (instead of performing a non-verbal action or simply doing nothing), whom to address and what to say. Copyright 2010 Elsevier Ltd. All rights reserved.

Substrate-Directed Catalytic Selective Chemical Reactions.

Science.gov (United States)

Sawano, Takahiro; Yamamoto, Hisashi

2018-05-04

The development of highly efficient reactions at only the desired position is one of the most important subjects in organic chemistry. Most of the reactions in current organic chemistry are reagent- or catalyst-controlled reactions, and the regio- and stereoselectivity of the reactions are determined by the inherent nature of the reagent or catalyst. In sharp contrast, substrate-directed reaction determines the selectivity of the reactions by the functional group on the substrate and can strictly distinguish sterically and electronically similar multiple reaction sites in the substrate. In this Perspective, three topics of substrate-directed reaction are mainly reviewed: (1) directing group-assisted epoxidation of alkenes, (2) ring-opening reactions of epoxides by various nucleophiles, and (3) catalytic peptide synthesis. Our newly developed synthetic methods with new ligands including hydroxamic acid derived ligands realized not only highly efficient reactions but also pinpointed reactions at the expected position, demonstrating the substrate-directed reaction as a powerful method to achieve the desired regio- and stereoselective functionalization of molecules from different viewpoints of reagent- or catalyst-controlled reactions.

The Properties of Model Selection when Retaining Theory Variables

DEFF Research Database (Denmark)

Hendry, David F.; Johansen, Søren

Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....

Evolution of branched regulatory genetic pathways: directional selection on pleiotropic loci accelerates developmental system drift.

Science.gov (United States)

Johnson, Norman A; Porter, Adam H

2007-01-01

Developmental systems are regulated by a web of interacting loci. One common and useful approach in studying the evolution of development is to focus on classes of interacting elements within these systems. Here, we use individual-based simulations to study the evolution of traits controlled by branched developmental pathways involving three loci, where one locus regulates two different traits. We examined the system under a variety of selective regimes. In the case where one branch was under stabilizing selection and the other under directional selection, we observed "developmental system drift": the trait under stabilizing selection showed little phenotypic change even though the loci underlying that trait showed considerable evolutionary divergence. This occurs because the pleiotropic locus responds to directional selection and compensatory mutants are then favored in the pathway under stabilizing selection. Though developmental system drift may be caused by other mechanisms, it seems likely that it is accelerated by the same underlying genetic mechanism as that producing the Dobzhansky-Muller incompatibilities that lead to speciation in both linear and branched pathways. We also discuss predictions of our model for developmental system drift and how different selective regimes affect probabilities of speciation in the branched pathway system.

Visual Search for Motion-Form Conjunctions: Selective Attention to Movement Direction.

Science.gov (United States)

Von Mühlenen, Adrian; Müller, Hermann J

1999-07-01

In 2 experiments requiring visual search for conjunctions of motion and form, the authors reinvestigated whether motion-based filtering (e.g., P. McLeod, J. Driver, Z. Dienes, & J. Crisp, 1991) is direction selective and whether cuing of the target direction promotes efficient search performance. In both experiments, the authors varied the number of movement directions in the display and the predictability of the target direction. Search was less efficient when items moved in multiple (2, 3, and 4) directions as compared with just 1 direction. Furthermore, precuing of the target direction facilitated the search, even with "wrap-around" displays, relatively more when items moved in multiple directions. The authors proposed 2 principles to explain that pattern of effects: (a) interference on direction computation between items moving in different directions (e.g., N. Qian & R. A. Andersen, 1994) and (b) selective direction tuning of motion detectors involving a receptive-field contraction (cf. J. Moran & R. Desimone, 1985; S. Treue & J. H. R. Maunsell, 1996).

Effectiveness of ancestral irradiation on the direct and correlated responses to selection for body weight in rats

International Nuclear Information System (INIS)

Gianola, D.

1975-01-01

The effects of ancestral irradiation of rat spermatogonia (a cumulative total of 4050 r of x-rays) were studied in a highly inbred line of rats to explore the feasibility of using irradiation to enhance the effectiveness of selection. Six generations after irradiation was terminated, a selection experiment for body weight at six weeks of age was started in both ancestrally irradiated and non-irradiated populations. There were two non-contemporaneous replicates in each of the populations. Within each of the ancestral treatment-replicate combinations one line was selected for high, one for low body weight at six weeks of age, and a third line was maintained by random selection. In each line, avoidance of mating of animals with grandparents in common was attempted. Data on the first ten progeny generations of selection were included in this study. Five types of covariances among relatives were used to estimate causal components of variance for five different genetic models within the ''non-irradiated'' and ''irradiated'' randomly selected models. The parameters in the genetic models were estimated by generalized least-squares. This analysis suggested that a genetic model including direct genetic and maternal genetic effects was adequate to describe the body weights at 3, 6 and 10 weeks of age and the weight gains between these ages. Ancestral irradiation seemed to have enhanced the maternal genetic variance and the covariance between the direct genetic and the maternal genetic effects. On the basis of the above analysis, it was deduced that mass selection should have been more effective in the descendants of irradiated males than in those of the non-irradiated males as a consequence of greater phenotypic variability in their progeny and an enhancement in the regression of the genetic value on the selection criterion

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

Science.gov (United States)

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

2014-07-01

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

Cliff-edge model of obstetric selection in humans.

Science.gov (United States)

Mitteroecker, Philipp; Huttegger, Simon M; Fischer, Barbara; Pavlicev, Mihaela

2016-12-20

The strikingly high incidence of obstructed labor due to the disproportion of fetal size and the mother's pelvic dimensions has puzzled evolutionary scientists for decades. Here we propose that these high rates are a direct consequence of the distinct characteristics of human obstetric selection. Neonatal size relative to the birth-relevant maternal dimensions is highly variable and positively associated with reproductive success until it reaches a critical value, beyond which natural delivery becomes impossible. As a consequence, the symmetric phenotype distribution cannot match the highly asymmetric, cliff-edged fitness distribution well: The optimal phenotype distribution that maximizes population mean fitness entails a fraction of individuals falling beyond the "fitness edge" (i.e., those with fetopelvic disproportion). Using a simple mathematical model, we show that weak directional selection for a large neonate, a narrow pelvic canal, or both is sufficient to account for the considerable incidence of fetopelvic disproportion. Based on this model, we predict that the regular use of Caesarean sections throughout the last decades has led to an evolutionary increase of fetopelvic disproportion rates by 10 to 20%.

A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS.

Science.gov (United States)

Zhao, Yize; Kang, Jian; Yu, Tianwei

2014-06-01

It is very challenging to select informative features from tens of thousands of measured features in high-throughput data analysis. Recently, several parametric/regression models have been developed utilizing the gene network information to select genes or pathways strongly associated with a clinical/biological outcome. Alternatively, in this paper, we propose a nonparametric Bayesian model for gene selection incorporating network information. In addition to identifying genes that have a strong association with a clinical outcome, our model can select genes with particular expressional behavior, in which case the regression models are not directly applicable. We show that our proposed model is equivalent to an infinity mixture model for which we develop a posterior computation algorithm based on Markov chain Monte Carlo (MCMC) methods. We also propose two fast computing algorithms that approximate the posterior simulation with good accuracy but relatively low computational cost. We illustrate our methods on simulation studies and the analysis of Spellman yeast cell cycle microarray data.

A genome-wide scan for signatures of directional selection in domesticated pigs.

Science.gov (United States)

Moon, Sunjin; Kim, Tae-Hun; Lee, Kyung-Tai; Kwak, Woori; Lee, Taeheon; Lee, Si-Woo; Kim, Myung-Jick; Cho, Kyuho; Kim, Namshin; Chung, Won-Hyong; Sung, Samsun; Park, Taesung; Cho, Seoae; Groenen, Martien Am; Nielsen, Rasmus; Kim, Yuseob; Kim, Heebal

2015-02-25

Animal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication. Whole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an F ST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness. We show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.

Neural Networks for Target Selection in Direct Marketing

NARCIS (Netherlands)

R. Potharst (Rob); U. Kaymak (Uzay); W.H.L.M. Pijls (Wim)

2001-01-01

textabstractPartly due to a growing interest in direct marketing, it has become an important application field for data mining. Many techniques have been applied to select the targets in commercial applications, such as statistical regression, regression trees, neural computing, fuzzy clustering

Variable selection in Logistic regression model with genetic algorithm.

Science.gov (United States)

Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

2018-02-01

Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

A comparative study of approaches to direct methanol fuel cells modelling

Energy Technology Data Exchange (ETDEWEB)

Oliveira, V.B.; Falcao, D.S.; Pinto, A.M.F.R. [Centro de Estudos de Fenomenos de Transporte, Departamento de Eng. Quimica, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto (Portugal); Rangel, C.M. [Instituto Nacional de Engenharia, Tecnologia e Inovacao, Paco do Lumiar, 22,1649-038 (Portugal)

2007-03-15

Fuel cell modelling has received much attention over the past decade in an attempt to better understand the phenomena occurring within the cell. Mathematical models and simulation are needed as tools for design optimization of fuel cells, stacks and fuel cell power systems. Analytical, semi-empirical and mechanistic models for direct methanol fuel cells (DMFC) are reviewed. Effective models were until now developed describing the fundamental electrochemical and transport phenomena taking place in the cell. More research is required to develop models that can account for the two-phase flows occurring in the anode and cathode of the DMFC. The merits and demerits of the models are presented. Selected models of different categories are implemented and discussed. Finally, one of the selected simplified models is proposed as a computer-aided tool for real-time system level DMFC calculations. (author)

Directed Evolution of Membrane Transport Using Synthetic Selections

DEFF Research Database (Denmark)

Bali, Anne Pihl; Genee, Hans J.; Sommer, Morten O. A.

2018-01-01

systems that enable selective growth of E. coli cells only if they functionally express an importer that is specific to the biosensor ligand. Using this system in a directed evolution framework, we successfully engineer the specificity of nicotinamide riboside transporters, PnuC, to accept thiamine...

Evidence accumulation as a model for lexical selection.

Science.gov (United States)

Anders, R; Riès, S; van Maanen, L; Alario, F X

2015-11-01

We propose and demonstrate evidence accumulation as a plausible theoretical and/or empirical model for the lexical selection process of lexical retrieval. A number of current psycholinguistic theories consider lexical selection as a process related to selecting a lexical target from a number of alternatives, which each have varying activations (or signal supports), that are largely resultant of an initial stimulus recognition. We thoroughly present a case for how such a process may be theoretically explained by the evidence accumulation paradigm, and we demonstrate how this paradigm can be directly related or combined with conventional psycholinguistic theory and their simulatory instantiations (generally, neural network models). Then with a demonstrative application on a large new real data set, we establish how the empirical evidence accumulation approach is able to provide parameter results that are informative to leading psycholinguistic theory, and that motivate future theoretical development. Copyright © 2015 Elsevier Inc. All rights reserved.

Direct and correlated responses to selection for total weight of lamb ...

African Journals Online (AJOL)

The estimated selection responses indicate that direct selection for TWW would be the most suitable selection criterion for improving reproductive performance in flocks with a high reproduction rate where an increase in the number of lambs would be undesirable. (South African Journal of Animal Science, 2001, 31(2): ...

Post-model selection inference and model averaging

Directory of Open Access Journals (Sweden)

Georges Nguefack-Tsague

2011-07-01

Full Text Available Although model selection is routinely used in practice nowadays, little is known about its precise effects on any subsequent inference that is carried out. The same goes for the effects induced by the closely related technique of model averaging. This paper is concerned with the use of the same data first to select a model and then to carry out inference, in particular point estimation and point prediction. The properties of the resulting estimator, called a post-model-selection estimator (PMSE, are hard to derive. Using selection criteria such as hypothesis testing, AIC, BIC, HQ and Cp, we illustrate that, in terms of risk function, no single PMSE dominates the others. The same conclusion holds more generally for any penalised likelihood information criterion. We also compare various model averaging schemes and show that no single one dominates the others in terms of risk function. Since PMSEs can be regarded as a special case of model averaging, with 0-1 random-weights, we propose a connection between the two theories, in the frequentist approach, by taking account of the selection procedure when performing model averaging. We illustrate the point by simulating a simple linear regression model.

The temporal distribution of directional gradients under selection for an optimum.

Science.gov (United States)

Chevin, Luis-Miguel; Haller, Benjamin C

2014-12-01

Temporal variation in phenotypic selection is often attributed to environmental change causing movements of the adaptive surface relating traits to fitness, but this connection is rarely established empirically. Fluctuating phenotypic selection can be measured by the variance and autocorrelation of directional selection gradients through time. However, the dynamics of these gradients depend not only on environmental changes altering the fitness surface, but also on evolution of the phenotypic distribution. Therefore, it is unclear to what extent variability in selection gradients can inform us about the underlying drivers of their fluctuations. To investigate this question, we derive the temporal distribution of directional gradients under selection for a phenotypic optimum that is either constant or fluctuates randomly in various ways in a finite population. Our analytical results, combined with population- and individual-based simulations, show that although some characteristic patterns can be distinguished, very different types of change in the optimum (including a constant optimum) can generate similar temporal distributions of selection gradients, making it difficult to infer the processes underlying apparent fluctuating selection. Analyzing changes in phenotype distributions together with changes in selection gradients should prove more useful for inferring the mechanisms underlying estimated fluctuating selection. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Dominance genetic variance for traits under directional selection in Drosophila serrata.

Science.gov (United States)

Sztepanacz, Jacqueline L; Blows, Mark W

2015-05-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

Science.gov (United States)

Wickman, Jonas; Diehl, Sebastian; Blasius, Bernd; Klausmeier, Christopher A; Ryabov, Alexey B; Brännström, Åke

2017-04-01

Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

Directed selective-tunneling of bosons with periodically modulated interaction

International Nuclear Information System (INIS)

Lu, Gengbiao; Fu, Li-Bin; Hai, Wenhua; Zou, Mingliang; Guo, Yu

2015-01-01

We study the tunneling dynamics of bosons with periodically modulated interaction held in a triple-well potential. In high-frequency approximation, we derive a set of reduced coupled equations and the corresponding Floquet solutions are obtained. Based on the analytical results and their numerical correspondence, the directed selective-tunneling effect of a single atom is demonstrated when all bosons are prepared in middle well initially. A scheme for separating a single atom from N bosons is presented, in which the atom can be trapped in right or left well by adjusting the modulation strength. - Highlights: • The Floquet solutions in a modulating triple-well are obtained analytically. • The directed selective-tunneling effect of a single atom is demonstrated. • We present a manipulation scheme for separating a single atom from N bosons

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

Wentworth, Mami Tonoe

techniques for model calibration. For Bayesian model calibration, we employ adaptive Metropolis algorithms to construct densities for input parameters in the heat model and the HIV model. To quantify the uncertainty in the parameters, we employ two MCMC algorithms: Delayed Rejection Adaptive Metropolis (DRAM) [33] and Differential Evolution Adaptive Metropolis (DREAM) [66, 68]. The densities obtained using these methods are compared to those obtained through the direct numerical evaluation of the Bayes' formula. We also combine uncertainties in input parameters and measurement errors to construct predictive estimates for a model response. A significant emphasis is on the development and illustration of techniques to verify the accuracy of sampling-based Metropolis algorithms. We verify the accuracy of DRAM and DREAM by comparing chains, densities and correlations obtained using DRAM, DREAM and the direct evaluation of Bayes formula. We also perform similar analysis for credible and prediction intervals for responses. Once the parameters are estimated, we employ energy statistics test [63, 64] to compare the densities obtained by different methods for the HIV model. The energy statistics are used to test the equality of distributions. We also consider parameter selection and verification techniques for models having one or more parameters that are noninfluential in the sense that they minimally impact model outputs. We illustrate these techniques for a dynamic HIV model but note that the parameter selection and verification framework is applicable to a wide range of biological and physical models. To accommodate the nonlinear input to output relations, which are typical for such models, we focus on global sensitivity analysis techniques, including those based on partial correlations, Sobol indices based on second-order model representations, and Morris indices, as well as a parameter selection technique based on standard errors. A significant objective is to provide

Directional and balancing selection in human beta-defensins.

Science.gov (United States)

Hollox, Edward J; Armour, John A L

2008-04-16

In primates, infection is an important force driving gene evolution, and this is reflected in the importance of infectious disease in human morbidity today. The beta-defensins are key components of the innate immune system, with antimicrobial and cell signalling roles, but also reproductive functions. Here we examine evolution of beta-defensins in catarrhine primates and variation within different human populations. We show that five beta-defensin genes that do not show copy number variation in humans show evidence of positive selection in catarrhine primates, and identify specific codons that have been under selective pressure. Direct haplotyping of DEFB127 in humans suggests long-term balancing selection: there are two highly diverged haplotype clades carrying different variants of a codon that, in primates, is positively selected. For DEFB132, we show that extensive diversity, including a four-state amino acid polymorphism (valine, isoleucine, alanine and threonine at position 93), is present in hunter-gatherer populations, both African and non-African, but not found in samples from agricultural populations. Some, but not all, beta-defensin genes show positive selection in catarrhine primates. There is suggestive evidence of different selective pressures on these genes in humans, but the nature of the selective pressure remains unclear and is likely to differ between populations.

Visual coding with a population of direction-selective neurons.

Science.gov (United States)

Fiscella, Michele; Franke, Felix; Farrow, Karl; Müller, Jan; Roska, Botond; da Silveira, Rava Azeredo; Hierlemann, Andreas

2015-10-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. Copyright © 2015 the American Physiological Society.

A Simple K-Map Based Variable Selection Scheme in the Direct ...

African Journals Online (AJOL)

A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...

Propagative selection of tilted array patterns in directional solidification

Science.gov (United States)

Song, Younggil; Akamatsu, Silvère; Bottin-Rousseau, Sabine; Karma, Alain

2018-05-01

We investigate the dynamics of tilted cellular/dendritic array patterns that form during directional solidification of a binary alloy when a preferred-growth crystal axis is misoriented with respect to the temperature gradient. In situ experimental observations and phase-field simulations in thin samples reveal the existence of a propagative source-sink mechanism of array spacing selection that operates on larger space and time scales than the competitive growth at play during the initial solidification transient. For tilted arrays, tertiary branching at the diverging edge of the sample acts as a source of new cells with a spacing that can be significantly larger than the initial average spacing. A spatial domain of large spacing then invades the sample propagatively. It thus yields a uniform spacing everywhere, selected independently of the initial conditions, except in a small region near the converging edge of the sample, which acts as a sink of cells. We propose a discrete geometrical model that describes the large-scale evolution of the spatial spacing profile based on the local dependence of the cell drift velocity on the spacing. We also derive a nonlinear advection equation that predicts the invasion velocity of the large-spacing domain, and sheds light on the fundamental nature of this process. The models also account for more complex spacing modulations produced by an irregular dynamics at the source, in good quantitative agreement with both phase-field simulations and experiments. This basic knowledge provides a theoretical basis to improve the processing of single crystals or textured polycrystals for advanced materials.

A Heckman Selection- t Model

KAUST Repository

Marchenko, Yulia V.

2012-03-01

Sample selection arises often in practice as a result of the partial observability of the outcome of interest in a study. In the presence of sample selection, the observed data do not represent a random sample from the population, even after controlling for explanatory variables. That is, data are missing not at random. Thus, standard analysis using only complete cases will lead to biased results. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. The method was criticized in the literature because of its sensitivity to the normality assumption. In practice, data, such as income or expenditure data, often violate the normality assumption because of heavier tails. We first establish a new link between sample selection models and recently studied families of extended skew-elliptical distributions. Then, this allows us to introduce a selection-t (SLt) model, which models the error distribution using a Student\\'s t distribution. We study its properties and investigate the finite-sample performance of the maximum likelihood estimators for this model. We compare the performance of the SLt model to the conventional Heckman selection-normal (SLN) model and apply it to analyze ambulatory expenditures. Unlike the SLNmodel, our analysis using the SLt model provides statistical evidence for the existence of sample selection bias in these data. We also investigate the performance of the test for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical Association.

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

Science.gov (United States)

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Directed Innovation of Business Models

Directory of Open Access Journals (Sweden)

Stelian Brad

2016-06-01

Full Text Available Business model innovation is an important issue to keep business competitive and increase company’s profits. Due to many market attractors, identification of appropriate paths of business model evolution is a painful and risky process. To improve decision’s effectiveness in this process, an architectural construct of analysis and conceptualization for business model innovation that combines directed evolution and blue ocean concepts is proposed in this paper under the name of directed innovation. It displays the key points where innovations would happen to direct adaptation of the business model towards sustainable competitiveness. Formulation of mature solutions is supported by inventive problem solving tools. The significance of the directed innovation approach is demonstrated in a case study dealing with business model innovation of a software company.

Guidelines for selecting codes for ground-water transport modeling of low-level waste burial sites. Executive summary

International Nuclear Information System (INIS)

Simmons, C.S.; Cole, C.R.

1985-05-01

This document was written to provide guidance to managers and site operators on how ground-water transport codes should be selected for assessing burial site performance. There is a need for a formal approach to selecting appropriate codes from the multitude of potentially useful ground-water transport codes that are currently available. Code selection is a problem that requires more than merely considering mathematical equation-solving methods. These guidelines are very general and flexible and are also meant for developing systems simulation models to be used to assess the environmental safety of low-level waste burial facilities. Code selection is only a single aspect of the overall objective of developing a systems simulation model for a burial site. The guidance given here is mainly directed toward applications-oriented users, but managers and site operators need to be familiar with this information to direct the development of scientifically credible and defensible transport assessment models. Some specific advice for managers and site operators on how to direct a modeling exercise is based on the following five steps: identify specific questions and study objectives; establish costs and schedules for achieving answers; enlist the aid of professional model applications group; decide on approach with applications group and guide code selection; and facilitate the availability of site-specific data. These five steps for managers/site operators are discussed in detail following an explanation of the nine systems model development steps, which are presented first to clarify what code selection entails

On dynamic selection of households for direct marketing based on Markov chain models with memory

NARCIS (Netherlands)

Otter, Pieter W.

A simple, dynamic selection procedure is proposed, based on conditional, expected profits using Markov chain models with memory. The method is easy to apply, only frequencies and mean values have to be calculated or estimated. The method is empirically illustrated using a data set from a charitable

Directional and balancing selection in human beta-defensins

Directory of Open Access Journals (Sweden)

Armour John AL

2008-04-01

Full Text Available Abstract Background In primates, infection is an important force driving gene evolution, and this is reflected in the importance of infectious disease in human morbidity today. The beta-defensins are key components of the innate immune system, with antimicrobial and cell signalling roles, but also reproductive functions. Here we examine evolution of beta-defensins in catarrhine primates and variation within different human populations. Results We show that five beta-defensin genes that do not show copy number variation in humans show evidence of positive selection in catarrhine primates, and identify specific codons that have been under selective pressure. Direct haplotyping of DEFB127 in humans suggests long-term balancing selection: there are two highly diverged haplotype clades carrying different variants of a codon that, in primates, is positively selected. For DEFB132, we show that extensive diversity, including a four-state amino acid polymorphism (valine, isoleucine, alanine and threonine at position 93, is present in hunter-gatherer populations, both African and non-African, but not found in samples from agricultural populations. Conclusion Some, but not all, beta-defensin genes show positive selection in catarrhine primates. There is suggestive evidence of different selective pressures on these genes in humans, but the nature of the selective pressure remains unclear and is likely to differ between populations.

Radial Domany-Kinzel models with mutation and selection

Science.gov (United States)

Lavrentovich, Maxim O.; Korolev, Kirill S.; Nelson, David R.

2013-01-01

We study the effect of spatial structure, genetic drift, mutation, and selective pressure on the evolutionary dynamics in a simplified model of asexual organisms colonizing a new territory. Under an appropriate coarse-graining, the evolutionary dynamics is related to the directed percolation processes that arise in voter models, the Domany-Kinzel (DK) model, contact process, and so on. We explore the differences between linear (flat front) expansions and the much less familiar radial (curved front) range expansions. For the radial expansion, we develop a generalized, off-lattice DK model that minimizes otherwise persistent lattice artifacts. With both simulations and analytical techniques, we study the survival probability of advantageous mutants, the spatial correlations between domains of neutral strains, and the dynamics of populations with deleterious mutations. “Inflation” at the frontier leads to striking differences between radial and linear expansions. For a colony with initial radius R0 expanding at velocity v, significant genetic demixing, caused by local genetic drift, occurs only up to a finite time t*=R0/v, after which portions of the colony become causally disconnected due to the inflating perimeter of the expanding front. As a result, the effect of a selective advantage is amplified relative to genetic drift, increasing the survival probability of advantageous mutants. Inflation also modifies the underlying directed percolation transition, introducing novel scaling functions and modifications similar to a finite-size effect. Finally, we consider radial range expansions with deflating perimeters, as might arise from colonization initiated along the shores of an island.

Models of microbiome evolution incorporating host and microbial selection.

Science.gov (United States)

Zeng, Qinglong; Wu, Steven; Sukumaran, Jeet; Rodrigo, Allen

2017-09-25

Numerous empirical studies suggest that hosts and microbes exert reciprocal selective effects on their ecological partners. Nonetheless, we still lack an explicit framework to model the dynamics of both hosts and microbes under selection. In a previous study, we developed an agent-based forward-time computational framework to simulate the neutral evolution of host-associated microbial communities in a constant-sized, unstructured population of hosts. These neutral models allowed offspring to sample microbes randomly from parents and/or from the environment. Additionally, the environmental pool of available microbes was constituted by fixed and persistent microbial OTUs and by contributions from host individuals in the preceding generation. In this paper, we extend our neutral models to allow selection to operate on both hosts and microbes. We do this by constructing a phenome for each microbial OTU consisting of a sample of traits that influence host and microbial fitnesses independently. Microbial traits can influence the fitness of hosts ("host selection") and the fitness of microbes ("trait-mediated microbial selection"). Additionally, the fitness effects of traits on microbes can be modified by their hosts ("host-mediated microbial selection"). We simulate the effects of these three types of selection, individually or in combination, on microbiome diversities and the fitnesses of hosts and microbes over several thousand generations of hosts. We show that microbiome diversity is strongly influenced by selection acting on microbes. Selection acting on hosts only influences microbiome diversity when there is near-complete direct or indirect parental contribution to the microbiomes of offspring. Unsurprisingly, microbial fitness increases under microbial selection. Interestingly, when host selection operates, host fitness only increases under two conditions: (1) when there is a strong parental contribution to microbial communities or (2) in the absence of a strong

Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection.

Directory of Open Access Journals (Sweden)

Mark N Read

2016-09-01

Full Text Available The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto

Interspike Interval Based Filtering of Directional Selective Retinal Ganglion Cells Spike Trains

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Aurel Vasile Martiniuc

2012-01-01

Full Text Available The information regarding visual stimulus is encoded in spike trains at the output of retina by retinal ganglion cells (RGCs. Among these, the directional selective cells (DSRGC are signaling the direction of stimulus motion. DSRGCs' spike trains show accentuated periods of short interspike intervals (ISIs framed by periods of isolated spikes. Here we use two types of visual stimulus, white noise and drifting bars, and show that short ISI spikes of DSRGCs spike trains are more often correlated to their preferred stimulus feature (that is, the direction of stimulus motion and carry more information than longer ISI spikes. Firstly, our results show that correlation between stimulus and recorded neuronal response is best at short ISI spiking activity and decrease as ISI becomes larger. We then used grating bars stimulus and found that as ISI becomes shorter the directional selectivity is better and information rates are higher. Interestingly, for the less encountered type of DSRGC, known as ON-DSRGC, short ISI distribution and information rates revealed consistent differences when compared with the other directional selective cell type, the ON-OFF DSRGC. However, these findings suggest that ISI-based temporal filtering integrates a mechanism for visual information processing at the output of retina toward higher stages within early visual system.

Persistent directional selection on body size and a resolution to the paradox of stasis.

Science.gov (United States)

Rollinson, Njal; Rowe, Locke

2015-09-01

Directional selection on size is common but often fails to result in microevolution in the wild. Similarly, macroevolutionary rates in size are low relative to the observed strength of selection in nature. We show that many estimates of selection on size have been measured on juveniles, not adults. Further, parents influence juvenile size by adjusting investment per offspring. In light of these observations, we help resolve this paradox by suggesting that the observed upward selection on size is balanced by selection against investment per offspring, resulting in little or no net selection gradient on size. We find that trade-offs between fecundity and juvenile size are common, consistent with the notion of selection against investment per offspring. We also find that median directional selection on size is positive for juveniles but no net directional selection exists for adult size. This is expected because parent-offspring conflict exists over size, and juvenile size is more strongly affected by investment per offspring than adult size. These findings provide qualitative support for the hypothesis that upward selection on size is balanced by selection against investment per offspring, where parent-offspring conflict over size is embodied in the opposing signs of the two selection gradients. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

ModelMage: a tool for automatic model generation, selection and management.

Science.gov (United States)

Flöttmann, Max; Schaber, Jörg; Hoops, Stephan; Klipp, Edda; Mendes, Pedro

2008-01-01

Mathematical modeling of biological systems usually involves implementing, simulating, and discriminating several candidate models that represent alternative hypotheses. Generating and managing these candidate models is a tedious and difficult task and can easily lead to errors. ModelMage is a tool that facilitates management of candidate models. It is designed for the easy and rapid development, generation, simulation, and discrimination of candidate models. The main idea of the program is to automatically create a defined set of model alternatives from a single master model. The user provides only one SBML-model and a set of directives from which the candidate models are created by leaving out species, modifiers or reactions. After generating models the software can automatically fit all these models to the data and provides a ranking for model selection, in case data is available. In contrast to other model generation programs, ModelMage aims at generating only a limited set of models that the user can precisely define. ModelMage uses COPASI as a simulation and optimization engine. Thus, all simulation and optimization features of COPASI are readily incorporated. ModelMage can be downloaded from http://sysbio.molgen.mpg.de/modelmage and is distributed as free software.

Evolvability Search: Directly Selecting for Evolvability in order to Study and Produce It

DEFF Research Database (Denmark)

Mengistu, Henok; Lehman, Joel Anthony; Clune, Jeff

2016-01-01

of evolvable digital phenotypes. Although some types of selection in evolutionary computation indirectly encourage evolvability, one unexplored possibility is to directly select for evolvability. To do so, we estimate an individual's future potential for diversity by calculating the behavioral diversity of its...... immediate offspring, and select organisms with increased offspring variation. While the technique is computationally expensive, we hypothesized that direct selection would better encourage evolvability than indirect methods. Experiments in two evolutionary robotics domains confirm this hypothesis: in both...... domains, such Evolvability Search produces solutions with higher evolvability than those produced with Novelty Search or traditional objective-based search algorithms. Further experiments demonstrate that the higher evolvability produced by Evolvability Search in a training environment also generalizes...

Model selection in periodic autoregressions

NARCIS (Netherlands)

Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

1994-01-01

textabstractThis paper focuses on the issue of period autoagressive time series models (PAR) selection in practice. One aspect of model selection is the choice for the appropriate PAR order. This can be of interest for the valuation of economic models. Further, the appropriate PAR order is important

Direct and correlated responses to selection for total weight of lamb ...

African Journals Online (AJOL)

Unknown

productivity and that each of these components can be used as a selection criterion, as each has a direct impact on total ewe ... of lamb weaned per ewe joined is more efficient than selection for number of lambs born, number of lambs weaned or weaning ... The estimated grazing capacity is 5.5 ha per small stock unit.

Interface Pattern Selection Criterion for Cellular Structures in Directional Solidification

Science.gov (United States)

Trivedi, R.; Tewari, S. N.; Kurtze, D.

1999-01-01

The aim of this investigation is to establish key scientific concepts that govern the selection of cellular and dendritic patterns during the directional solidification of alloys. We shall first address scientific concepts that are crucial in the selection of interface patterns. Next, the results of ground-based experimental studies in the Al-4.0 wt % Cu system will be described. Both experimental studies and theoretical calculations will be presented to establish the need for microgravity experiments.

A Primer for Model Selection: The Decisive Role of Model Complexity

Science.gov (United States)

Höge, Marvin; Wöhling, Thomas; Nowak, Wolfgang

2018-03-01

Selecting a "best" model among several competing candidate models poses an often encountered problem in water resources modeling (and other disciplines which employ models). For a modeler, the best model fulfills a certain purpose best (e.g., flood prediction), which is typically assessed by comparing model simulations to data (e.g., stream flow). Model selection methods find the "best" trade-off between good fit with data and model complexity. In this context, the interpretations of model complexity implied by different model selection methods are crucial, because they represent different underlying goals of modeling. Over the last decades, numerous model selection criteria have been proposed, but modelers who primarily want to apply a model selection criterion often face a lack of guidance for choosing the right criterion that matches their goal. We propose a classification scheme for model selection criteria that helps to find the right criterion for a specific goal, i.e., which employs the correct complexity interpretation. We identify four model selection classes which seek to achieve high predictive density, low predictive error, high model probability, or shortest compression of data. These goals can be achieved by following either nonconsistent or consistent model selection and by either incorporating a Bayesian parameter prior or not. We allocate commonly used criteria to these four classes, analyze how they represent model complexity and what this means for the model selection task. Finally, we provide guidance on choosing the right type of criteria for specific model selection tasks. (A quick guide through all key points is given at the end of the introduction.)

Selection Finder (SelFi: A computational metabolic engineering tool to enable directed evolution of enzymes

Directory of Open Access Journals (Sweden)

Neda Hassanpour

2017-06-01

Full Text Available Directed evolution of enzymes consists of an iterative process of creating mutant libraries and choosing desired phenotypes through screening or selection until the enzymatic activity reaches a desired goal. The biggest challenge in directed enzyme evolution is identifying high-throughput screens or selections to isolate the variant(s with the desired property. We present in this paper a computational metabolic engineering framework, Selection Finder (SelFi, to construct a selection pathway from a desired enzymatic product to a cellular host and to couple the pathway with cell survival. We applied SelFi to construct selection pathways for four enzymes and their desired enzymatic products xylitol, D-ribulose-1,5-bisphosphate, methanol, and aniline. Two of the selection pathways identified by SelFi were previously experimentally validated for engineering Xylose Reductase and RuBisCO. Importantly, SelFi advances directed evolution of enzymes as there is currently no known generalized strategies or computational techniques for identifying high-throughput selections for engineering enzymes.

Directional enhancement of selected high-order-harmonics from intense laser irradiated blazed grating targets.

Science.gov (United States)

Zhang, Guobo; Chen, Min; Liu, Feng; Yuan, Xiaohui; Weng, Suming; Zheng, Jun; Ma, Yanyun; Shao, Fuqiu; Sheng, Zhengming; Zhang, Jie

2017-10-02

Relativistically intense laser solid target interaction has been proved to be a promising way to generate high-order harmonics, which can be used to diagnose ultrafast phenomena. However, their emission direction and spectra still lack tunability. Based upon two-dimensional particle-in-cell simulations, we show that directional enhancement of selected high-order-harmonics can be realized using blazed grating targets. Such targets can select harmonics with frequencies being integer times of the grating frequency. Meanwhile, the radiation intensity and emission area of the harmonics are increased. The emission direction is controlled by tailoring the local blazed structure. Theoretical and electron dynamics analysis for harmonics generation, selection and directional enhancement from the interaction between multi-cycle laser and grating target are carried out. These studies will benefit the generation and application of laser plasma-based high order harmonics.

Charles Darwin's Origin of Species, directional selection, and the evolutionary sciences today.

Science.gov (United States)

Kutschera, Ulrich

2009-11-01

The book On the Origin of Species, published in November 1859, is an "abstract" without references, compiled by Charles Darwin from a much longer manuscript entitled "Natural Selection." Here, I summarize the five theories that can be extracted from Darwin's monograph, explain the true meaning of the phrase "struggle for life" (i.e., competition and cooperation), and outline Darwin's original concept of natural selection in populations of animals and plants. Since neither Darwin nor Alfred R. Wallace distinguished between stabilizing and directional natural selection, the popular argument that "selection only eliminates but is not creative" is still alive today. However, I document that August Weismann (Die Bedeutung der sexuellen Fortpflanzung für die Selektions-Theorie. Gustav Fischer-Verlag, Jena, 1886) and Ivan Schmalhausen (Factors of evolution. The theory of stabilizing selection. The Blackiston Company, Philadelphia, 1949) provided precise definitions for directional (dynamic) selection in nature and illustrate this "Weismann-Schmalhausen principle" with respect to the evolutionary development of novel phenotypes. Then, the modern (synthetic) theory of biological evolution that is based on the work of Theodosius Dobzhansky (Genetics and the origin of species. Columbia University Press, New York, 1937) and others, and the expanded version of this system of theories, are outlined. Finally, I document that symbiogenesis (i.e., primary endosymbiosis, a process that gave rise to the first eukaryotic cells), ongoing directional natural selection, and the dynamic Earth (plate tectonics, i.e., geological events that both created and destroyed terrestrial and aquatic habitats) were the key processes responsible for the documented macroevolutionary patterns in all five kingdoms of life. Since the evolutionary development of the earliest archaic bacteria more than 3,500 mya, the biosphere of our dynamic planet has been dominated by prokaryotic microbes. Eubacteria

A dendrite-autonomous mechanism for direction selectivity in retinal starburst amacrine cells.

Science.gov (United States)

Hausselt, Susanne E; Euler, Thomas; Detwiler, Peter B; Denk, Winfried

2007-07-01

Detection of image motion direction begins in the retina, with starburst amacrine cells (SACs) playing a major role. SACs generate larger dendritic Ca(2+) signals when motion is from their somata towards their dendritic tips than for motion in the opposite direction. To study the mechanisms underlying the computation of direction selectivity (DS) in SAC dendrites, electrical responses to expanding and contracting circular wave visual stimuli were measured via somatic whole-cell recordings and quantified using Fourier analysis. Fundamental and, especially, harmonic frequency components were larger for expanding stimuli. This DS persists in the presence of GABA and glycine receptor antagonists, suggesting that inhibitory network interactions are not essential. The presence of harmonics indicates nonlinearity, which, as the relationship between harmonic amplitudes and holding potential indicates, is likely due to the activation of voltage-gated channels. [Ca(2+)] changes in SAC dendrites evoked by voltage steps and monitored by two-photon microscopy suggest that the distal dendrite is tonically depolarized relative to the soma, due in part to resting currents mediated by tonic glutamatergic synaptic input, and that high-voltage-activated Ca(2+) channels are active at rest. Supported by compartmental modeling, we conclude that dendritic DS in SACs can be computed by the dendrites themselves, relying on voltage-gated channels and a dendritic voltage gradient, which provides the spatial asymmetry necessary for direction discrimination.

A dendrite-autonomous mechanism for direction selectivity in retinal starburst amacrine cells.

Directory of Open Access Journals (Sweden)

Susanne E Hausselt

2007-07-01

Full Text Available Detection of image motion direction begins in the retina, with starburst amacrine cells (SACs playing a major role. SACs generate larger dendritic Ca(2+ signals when motion is from their somata towards their dendritic tips than for motion in the opposite direction. To study the mechanisms underlying the computation of direction selectivity (DS in SAC dendrites, electrical responses to expanding and contracting circular wave visual stimuli were measured via somatic whole-cell recordings and quantified using Fourier analysis. Fundamental and, especially, harmonic frequency components were larger for expanding stimuli. This DS persists in the presence of GABA and glycine receptor antagonists, suggesting that inhibitory network interactions are not essential. The presence of harmonics indicates nonlinearity, which, as the relationship between harmonic amplitudes and holding potential indicates, is likely due to the activation of voltage-gated channels. [Ca(2+] changes in SAC dendrites evoked by voltage steps and monitored by two-photon microscopy suggest that the distal dendrite is tonically depolarized relative to the soma, due in part to resting currents mediated by tonic glutamatergic synaptic input, and that high-voltage-activated Ca(2+ channels are active at rest. Supported by compartmental modeling, we conclude that dendritic DS in SACs can be computed by the dendrites themselves, relying on voltage-gated channels and a dendritic voltage gradient, which provides the spatial asymmetry necessary for direction discrimination.

Model-independent plot of dynamic PET data facilitates data interpretation and model selection.

Science.gov (United States)

Munk, Ole Lajord

2012-02-21

When testing new PET radiotracers or new applications of existing tracers, the blood-tissue exchange and the metabolism need to be examined. However, conventional plots of measured time-activity curves from dynamic PET do not reveal the inherent kinetic information. A novel model-independent volume-influx plot (vi-plot) was developed and validated. The new vi-plot shows the time course of the instantaneous distribution volume and the instantaneous influx rate. The vi-plot visualises physiological information that facilitates model selection and it reveals when a quasi-steady state is reached, which is a prerequisite for the use of the graphical analyses by Logan and Gjedde-Patlak. Both axes of the vi-plot have direct physiological interpretation, and the plot shows kinetic parameter in close agreement with estimates obtained by non-linear kinetic modelling. The vi-plot is equally useful for analyses of PET data based on a plasma input function or a reference region input function. The vi-plot is a model-independent and informative plot for data exploration that facilitates the selection of an appropriate method for data analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identifying footprints of directional and balancing selection in marine and freshwater three-spined stickleback (Gasterosteus aculeatus) populations.

Science.gov (United States)

Mäkinen, H S; Cano, J M; Merilä, J

2008-08-01

Natural selection is expected to leave an imprint on the neutral polymorphisms at the adjacent genomic regions of a selected gene. While directional selection tends to reduce within-population genetic diversity and increase among-population differentiation, the reverse is expected under balancing selection. To identify targets of natural selection in the three-spined stickleback (Gasterosteus aculeatus) genome, 103 microsatellite and two indel markers including expressed sequence tags (EST) and quantitative trait loci (QTL)-associated loci, were genotyped in four freshwater and three marine populations. The results indicated that a high proportion of loci (14.7%) might be affected by balancing selection and a lower proportion (2.8%) by directional selection. The strongest signatures of directional selection were detected in a microsatellite locus and two indel markers located in the intronic regions of the Eda-gene coding for the number of lateral plates. Yet, other microsatellite loci previously found to be informative in QTL-mapping studies revealed no signatures of selection. Two novel microsatellite loci (Stn12 and Stn90) located in chromosomes I and VIII, respectively, showed signals of directional selection and might be linked to genomic regions containing gene(s) important for adaptive divergence. Although the coverage of the total genomic content was relatively low, the predominance of balancing selection signals is in agreement with the contention that balancing, rather than directional selection is the predominant mode of selection in the wild.

Importance of selecting archaeomagnetic data for geomagnetic modelling: example of the new Western Europe directional and intensity secular variation curves from 1500 BC to 200 AD

Science.gov (United States)

Herve, Gwenael; Chauvin, Annick; Lanos, Philippe

2014-05-01

At the regional scale, the dispersion between archaeomagnetic data and especially archaeointensities suggests that some of them may be biased. As a consequence, it appears necessary to perform a selection of available data before to compute mean regional secular variation curves or geomagnetic models. However the definition of suitable selection criteria is not obvious and we need to know how to manage "old" data acquired during the 60-70s. The Western Europe directional and intensity data set from 1500 BC to 200 AD allows to discuss these issues. It has recently been enhanced by 39 new archaeodirections and 23 new archaeointensities (Hervé et al., 2013a and 2013b data sets and 5 unpublished data). First, the whole Western Europe data set was selected but the strong dispersion restricted the accuracy and the reliability of the new Western Europe secular variation curves at Paris. The causes of the dispersion appear different between archaeodirections and archaeointensities. In the directional data set, the main problem comes from some age errors in the oldest published data. Since their publication their archaeological dating may have changed of 50 years or more. For intensity data that were acquired much more recently, the dispersion mainly results from the use of unreliable archaeointensity protocols. We propose a weighting approach based on the number of specimens and the use of pTRM-checks, anisotropy and cooling rate corrections. Only 63% of available archaeodirections and 32% of archaeointensities were used to build the new Western Europe secular variation curves from 1500 BC to 200 AD. These curves reveal that selecting the reference data avoids wrong estimations of the shape of the secular variation curves, the secular variation rate, the dating of archaeomagnetic jerks... Finally, it is worth pointing out that current geomagnetic global models take into account almost all the data that we decided to reject. It could partly explain why their predictions at

The evolution of phenotypic integration: How directional selection reshapes covariation in mice.

Science.gov (United States)

Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel

2017-10-01

Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Direction-selective circuitry in rat retina develops independently of GABAergic, cholinergic and action potential activity.

Directory of Open Access Journals (Sweden)

Le Sun

Full Text Available The ON-OFF direction selective ganglion cells (DSGCs in the mammalian retina code image motion by responding much more strongly to movement in one direction. They do so by receiving inhibitory inputs selectively from a particular sector of processes of the overlapping starburst amacrine cells, a type of retinal interneuron. The mechanisms of establishment and regulation of this selective connection are unknown. Here, we report that in the rat retina, the morphology, physiology of the ON-OFF DSGCs and the circuitry for coding motion directions develop normally with pharmacological blockade of GABAergic, cholinergic activity and/or action potentials for over two weeks from birth. With recent results demonstrating light independent formation of the retinal DS circuitry, our results strongly suggest the formation of the circuitry, i.e., the connections between the second and third order neurons in the visual system, can be genetically programmed, although emergence of direction selectivity in the visual cortex appears to require visual experience.

A Model for Selection of Eyespots on Butterfly Wings.

Science.gov (United States)

Sekimura, Toshio; Venkataraman, Chandrasekhar; Madzvamuse, Anotida

2015-01-01

The development of eyespots on the wing surface of butterflies of the family Nympalidae is one of the most studied examples of biological pattern formation.However, little is known about the mechanism that determines the number and precise locations of eyespots on the wing. Eyespots develop around signaling centers, called foci, that are located equidistant from wing veins along the midline of a wing cell (an area bounded by veins). A fundamental question that remains unsolved is, why a certain wing cell develops an eyespot, while other wing cells do not. We illustrate that the key to understanding focus point selection may be in the venation system of the wing disc. Our main hypothesis is that changes in morphogen concentration along the proximal boundary veins of wing cells govern focus point selection. Based on previous studies, we focus on a spatially two-dimensional reaction-diffusion system model posed in the interior of each wing cell that describes the formation of focus points. Using finite element based numerical simulations, we demonstrate that variation in the proximal boundary condition is sufficient to robustly select whether an eyespot focus point forms in otherwise identical wing cells. We also illustrate that this behavior is robust to small perturbations in the parameters and geometry and moderate levels of noise. Hence, we suggest that an anterior-posterior pattern of morphogen concentration along the proximal vein may be the main determinant of the distribution of focus points on the wing surface. In order to complete our model, we propose a two stage reaction-diffusion system model, in which an one-dimensional surface reaction-diffusion system, posed on the proximal vein, generates the morphogen concentrations that act as non-homogeneous Dirichlet (i.e., fixed) boundary conditions for the two-dimensional reaction-diffusion model posed in the wing cells. The two-stage model appears capable of generating focus point distributions observed in

A Model for Selection of Eyespots on Butterfly Wings.

Directory of Open Access Journals (Sweden)

Toshio Sekimura

Full Text Available The development of eyespots on the wing surface of butterflies of the family Nympalidae is one of the most studied examples of biological pattern formation.However, little is known about the mechanism that determines the number and precise locations of eyespots on the wing. Eyespots develop around signaling centers, called foci, that are located equidistant from wing veins along the midline of a wing cell (an area bounded by veins. A fundamental question that remains unsolved is, why a certain wing cell develops an eyespot, while other wing cells do not.We illustrate that the key to understanding focus point selection may be in the venation system of the wing disc. Our main hypothesis is that changes in morphogen concentration along the proximal boundary veins of wing cells govern focus point selection. Based on previous studies, we focus on a spatially two-dimensional reaction-diffusion system model posed in the interior of each wing cell that describes the formation of focus points. Using finite element based numerical simulations, we demonstrate that variation in the proximal boundary condition is sufficient to robustly select whether an eyespot focus point forms in otherwise identical wing cells. We also illustrate that this behavior is robust to small perturbations in the parameters and geometry and moderate levels of noise. Hence, we suggest that an anterior-posterior pattern of morphogen concentration along the proximal vein may be the main determinant of the distribution of focus points on the wing surface. In order to complete our model, we propose a two stage reaction-diffusion system model, in which an one-dimensional surface reaction-diffusion system, posed on the proximal vein, generates the morphogen concentrations that act as non-homogeneous Dirichlet (i.e., fixed boundary conditions for the two-dimensional reaction-diffusion model posed in the wing cells. The two-stage model appears capable of generating focus point distributions

Numerical Model based Reliability Estimation of Selective Laser Melting Process

DEFF Research Database (Denmark)

Mohanty, Sankhya; Hattel, Jesper Henri

2014-01-01

Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....

Charles Darwin's Origin of Species, directional selection, and the evolutionary sciences today

Science.gov (United States)

Kutschera, Ulrich

2009-11-01

The book On the Origin of Species, published in November 1859, is an “abstract” without references, compiled by Charles Darwin from a much longer manuscript entitled “Natural Selection.” Here, I summarize the five theories that can be extracted from Darwin’s monograph, explain the true meaning of the phrase “struggle for life” (i.e., competition and cooperation), and outline Darwin’s original concept of natural selection in populations of animals and plants. Since neither Darwin nor Alfred R. Wallace distinguished between stabilizing and directional natural selection, the popular argument that “selection only eliminates but is not creative” is still alive today. However, I document that August Weismann ( Die Bedeutung der sexuellen Fortpflanzung für die Selektions-Theorie. Gustav Fischer-Verlag, Jena, 1886) and Ivan Schmalhausen ( Factors of evolution. The theory of stabilizing selection. The Blackiston Company, Philadelphia, 1949) provided precise definitions for directional (dynamic) selection in nature and illustrate this “Weismann-Schmalhausen principle” with respect to the evolutionary development of novel phenotypes. Then, the modern (synthetic) theory of biological evolution that is based on the work of Theodosius Dobzhansky ( Genetics and the origin of species. Columbia University Press, New York, 1937) and others, and the expanded version of this system of theories, are outlined. Finally, I document that symbiogenesis (i.e., primary endosymbiosis, a process that gave rise to the first eukaryotic cells), ongoing directional natural selection, and the dynamic Earth (plate tectonics, i.e., geological events that both created and destroyed terrestrial and aquatic habitats) were the key processes responsible for the documented macroevolutionary patterns in all five kingdoms of life. Since the evolutionary development of the earliest archaic bacteria more than 3,500 mya, the biosphere of our dynamic planet has been dominated by

Variable selection and model choice in geoadditive regression models.

Science.gov (United States)

Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

2009-06-01

Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection.

Science.gov (United States)

Baston, Chiara; Ursino, Mauro

2015-01-01

The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments.

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

Directory of Open Access Journals (Sweden)

Chiara Baston

2015-01-01

Full Text Available The basal ganglia (BG are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go, indirect (NoGo, and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges, synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication. Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments.

Mutation directional selection sheds light on prion pathogenesis

International Nuclear Information System (INIS)

Shen, Liang; Ji, Hong-Fang

2011-01-01

Highlights: → Most pathogenic mutations possess strong directional selection, i.e., enhancing hydrophobicity or decreasing negative and increasing positive charge. → Mutation-induced changes may strengthen the interactions between PrP and facilitating factors. → The findings also have significant implications for exploring potential regions involved in the conformational transition from PrP C to PrP Sc . -- Abstract: As mutations in the PRNP gene account for human hereditary prion diseases (PrDs), it is crucial to elucidating how these mutations affect the central pathogenic conformational transition of normal cellular prion protein (PrP C ) to abnormal scrapie isoform (PrP Sc ). Many studies proposed that these pathogenic mutations may make PrP more susceptible to conformational change through altering its structure stability. By evaluating the most recent observations regarding pathogenic mutations, it was found that the pathogenic mutations do not exert a uniform effect on the thermodynamic stability of the human PrP's structure. Through analyzing the reported PrDs-related mutations, we found that 25 out of 27 mutations possess strong directional selection, i.e., enhancing hydrophobicity or decreasing negative and increasing positive charge. Based on the triggering role reported by previous studies of facilitating factors in PrP C conversion, e.g., lipid and polyanion, we proposed that the mutation-induced changes may strengthen the interaction between PrP and facilitating factors, which will accelerate PrP conversion and cause PrDs.

Mutation directional selection sheds light on prion pathogenesis

Energy Technology Data Exchange (ETDEWEB)

Shen, Liang [Shandong Provincial Research Center for Bioinformatic Engineering and Technique, Shandong University of Technology, Zibo 255049 (China); Ji, Hong-Fang, E-mail: jhf@sdut.edu.cn [Shandong Provincial Research Center for Bioinformatic Engineering and Technique, Shandong University of Technology, Zibo 255049 (China)

2011-07-01

Highlights: {yields} Most pathogenic mutations possess strong directional selection, i.e., enhancing hydrophobicity or decreasing negative and increasing positive charge. {yields} Mutation-induced changes may strengthen the interactions between PrP and facilitating factors. {yields} The findings also have significant implications for exploring potential regions involved in the conformational transition from PrP{sup C} to PrP{sup Sc}. -- Abstract: As mutations in the PRNP gene account for human hereditary prion diseases (PrDs), it is crucial to elucidating how these mutations affect the central pathogenic conformational transition of normal cellular prion protein (PrP{sup C}) to abnormal scrapie isoform (PrP{sup Sc}). Many studies proposed that these pathogenic mutations may make PrP more susceptible to conformational change through altering its structure stability. By evaluating the most recent observations regarding pathogenic mutations, it was found that the pathogenic mutations do not exert a uniform effect on the thermodynamic stability of the human PrP's structure. Through analyzing the reported PrDs-related mutations, we found that 25 out of 27 mutations possess strong directional selection, i.e., enhancing hydrophobicity or decreasing negative and increasing positive charge. Based on the triggering role reported by previous studies of facilitating factors in PrP{sup C} conversion, e.g., lipid and polyanion, we proposed that the mutation-induced changes may strengthen the interaction between PrP and facilitating factors, which will accelerate PrP conversion and cause PrDs.

Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents

Directory of Open Access Journals (Sweden)

Eric Aaron

2016-11-01

Full Text Available Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and

Comparison of NGA-West2 directivity models

Science.gov (United States)

Spudich, Paul A.; Rowshandel, Badie; Shahi, Shrey; Baker, Jack W.; Chiou, Brian S-J

2014-01-01

Five directivity models have been developed based on data from the NGA-West2 database and based on numerical simulations of large strike-slip and reverse-slip earthquakes. All models avoid the use of normalized rupture dimension, enabling them to scale up to the largest earthquakes in a physically reasonable way. Four of the five models are explicitly “narrow-band” (in which the effect of directivity is maximum at a specific period that is a function of earthquake magnitude). Several strategies for determining the zero-level for directivity have been developed. We show comparisons of maps of the directivity amplification. This comparison suggests that the predicted geographic distributions of directivity amplification are dominated by effects of the models' assumptions, and more than one model should be used for ruptures dipping less than about 65 degrees.

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

Science.gov (United States)

Belete, Zelalem; Baer, Eberhard; Erdmann, Andreas

2018-03-01

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

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

Science.gov (United States)

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

Footprints of directional selection in wild Atlantic salmon populations: evidence for parasite-driven evolution?

Science.gov (United States)

Zueva, Ksenia J; Lumme, Jaakko; Veselov, Alexey E; Kent, Matthew P; Lien, Sigbjørn; Primmer, Craig R

2014-01-01

Mechanisms of host-parasite co-adaptation have long been of interest in evolutionary biology; however, determining the genetic basis of parasite resistance has been challenging. Current advances in genome technologies provide new opportunities for obtaining a genome-scale view of the action of parasite-driven natural selection in wild populations and thus facilitate the search for specific genomic regions underlying inter-population differences in pathogen response. European populations of Atlantic salmon (Salmo salar L.) exhibit natural variance in susceptibility levels to the ectoparasite Gyrodactylus salaris Malmberg 1957, ranging from resistance to extreme susceptibility, and are therefore a good model for studying the evolution of virulence and resistance. However, distinguishing the molecular signatures of genetic drift and environment-associated selection in small populations such as land-locked Atlantic salmon populations presents a challenge, specifically in the search for pathogen-driven selection. We used a novel genome-scan analysis approach that enabled us to i) identify signals of selection in salmon populations affected by varying levels of genetic drift and ii) separate potentially selected loci into the categories of pathogen (G. salaris)-driven selection and selection acting upon other environmental characteristics. A total of 4631 single nucleotide polymorphisms (SNPs) were screened in Atlantic salmon from 12 different northern European populations. We identified three genomic regions potentially affected by parasite-driven selection, as well as three regions presumably affected by salinity-driven directional selection. Functional annotation of candidate SNPs is consistent with the role of the detected genomic regions in immune defence and, implicitly, in osmoregulation. These results provide new insights into the genetic basis of pathogen susceptibility in Atlantic salmon and will enable future searches for the specific genes involved.

Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

International Nuclear Information System (INIS)

Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim

2014-01-01

A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems

Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

Energy Technology Data Exchange (ETDEWEB)

Elsheikh, Ahmed H., E-mail: aelsheikh@ices.utexas.edu [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom); Wheeler, Mary F. [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Hoteit, Ibrahim [Department of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)

2014-02-01

A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems.

Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

KAUST Repository

Elsheikh, Ahmed H.

2014-02-01

A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems. © 2013 Elsevier Inc.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Science.gov (United States)

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

Distributions of Mutational Effects and the Estimation of Directional Selection in Divergent Lineages of Arabidopsis thaliana.

Science.gov (United States)

Park, Briton; Rutter, Matthew T; Fenster, Charles B; Symonds, V Vaughan; Ungerer, Mark C; Townsend, Jeffrey P

2017-08-01

Mutations are crucial to evolution, providing the ultimate source of variation on which natural selection acts. Due to their key role, the distribution of mutational effects on quantitative traits is a key component to any inference regarding historical selection on phenotypic traits. In this paper, we expand on a previously developed test for selection that could be conducted assuming a Gaussian mutation effect distribution by developing approaches to also incorporate any of a family of heavy-tailed Laplace distributions of mutational effects. We apply the test to detect directional natural selection on five traits along the divergence of Columbia and Landsberg lineages of Arabidopsis thaliana , constituting the first test for natural selection in any organism using quantitative trait locus and mutation accumulation data to quantify the intensity of directional selection on a phenotypic trait. We demonstrate that the results of the test for selection can depend on the mutation effect distribution specified. Using the distributions exhibiting the best fit to mutation accumulation data, we infer that natural directional selection caused divergence in the rosette diameter and trichome density traits of the Columbia and Landsberg lineages. Copyright © 2017 by the Genetics Society of America.

Directional selection on cold tolerance does not constrain plastic capacity in a butterfly.

Science.gov (United States)

Franke, Kristin; Dierks, Anneke; Fischer, Klaus

2012-12-05

Organisms may respond to environmental change by means of genetic adaptation, phenotypic plasticity or both, which may result in genotype-environment interactions (G x E) if genotypes differ in their phenotypic response. We here specifically target the latter source of variation (i.e. G x E) by comparing plastic responses among lines of the tropical butterfly Bicyclus anynana that had been selected for increased cold tolerance and according controls. Our main aim here was to test the hypothesis that directional selection on cold tolerance will interfere with plastic capacities. Plastic responses to temperature and feeding treatments were strong, with e.g. higher compared to lower temperatures reducing cold tolerance, longevity, pupal mass, and development time. We report a number of statistically significant genotype-environment interactions (i.e. interactions between selection regime and environmental variables), but most of these were not consistent across treatment groups. We found some evidence though for larger plastic responses to different rearing temperatures in the selection compared to the control lines, while plastic responses to different adult temperatures and feeding treatments were overall very similar across selection regimes. Our results indicate that plastic capacities are not always constrained by directional selection (on cold tolerance) and therefore genetic changes in trait means, but may operate independently.

Physics Implications of Flat Directions in Free Fermionic Superstring Models; 1, Mass Spectrum and Couplings

CERN Document Server

Cleaver, G; Espinosa, J R; Everett, L; Langacker, P G; Wang, J

1999-01-01

From the "top-down" approach we investigate physics implications of the class of D- and F- flat directions formed from non-Abelian singlets which are proven flat to all orders in the nonrenormalizable superpotential, for a prototype quasi-realistic free fermionic string model with the standard model gauge group and three families (CHL5). These flat directions have at least an additional U(1)' unbroken at the string scale. For each flat direction, the complete set of effective mass terms and effective trilinear superpotential terms in the observable sector are computed to all orders in the VEV's of the fields in the flat direction. The "string selection-rules" disallow a large number of couplings allowed by gauge invariance, resulting in a massless spectrum with a large number of exotics, in most cases excluded by experiment, thus signifying a generic flaw of these models. Nevertheless, the resulting trilinear couplings of the massless spectrum possess a number of interesting features which we analyse for two ...

Selection of doublet cellular patterns in directional solidification through spatially periodic perturbations

International Nuclear Information System (INIS)

Losert, W.; Stillman, D.A.; Cummins, H.Z.; Kopczynski, P.; Rappel, W.; Karma, A.

1998-01-01

Pattern formation at the solid-liquid interface of a growing crystal was studied in directional solidification using a perturbation technique. We analyzed both experimentally and numerically the stability range and dynamical selection of cellular arrays of 'doublets' with asymmetric tip shapes, separated by alternate deep and shallow grooves. Applying an initial periodic perturbation of arbitrary wavelength to the unstable planar interface allowed us to force the interface to evolve into doublet states that would not otherwise be dynamically accessible from a planar interface. We determined systematically the ranges of wavelength corresponding to stable singlets, stable doublets, and transient unstable patterns. Experimentally, this was accomplished by applying a brief UV light pulse of a desired spatial periodicity to the planar interface during the planar-cellular transient using the model alloy Succinonitrile-Coumarin 152. Numerical simulations of the nonlinear evolution of the interface were performed starting from a small sinusoidal perturbation of the steady-state planar interface. These simulations were carried out using a computationally efficient phase-field symmetric model of directional solidification with recently reformulated asymptotics and vanishing kinetics [A. Karma and W.-J. Rappel, Phys. Rev. E 53 R3017 (1996); Phys. Rev. Lett. 77, 4050 (1996); Phys. Rev. E 57, 4323 (1998)], which allowed us to simulate spatially extended arrays that can be meaningfully compared to experiments. Simulations and experiments show remarkable qualitative agreement in the dynamic evolution, steady-state structure, and instability mechanisms of doublet cellular arrays. copyright 1998 The American Physical Society

Omni-directional selective shielding material based on amorphous glass coated microwires.

Science.gov (United States)

Ababei, G; Chiriac, H; David, V; Dafinescu, V; Nica, I

2012-01-01

The shielding effectiveness of the omni-directional selective shielding material based on CoFe-glass coated amorphous wires in 0.8 GHz-3 GHz microwave frequency range is investigated. The measurements were done in a controlled medium using a TEM cell and in the free space using horn antennas, respectively. Experimental results indicate that the composite shielding material can be developed with desired shielding effectiveness and selective absorption of the microwave frequency range by controlling the number of the layers and the length of microwires.

An evolutionary algorithm for model selection

Energy Technology Data Exchange (ETDEWEB)

Bicker, Karl [CERN, Geneva (Switzerland); Chung, Suh-Urk; Friedrich, Jan; Grube, Boris; Haas, Florian; Ketzer, Bernhard; Neubert, Sebastian; Paul, Stephan; Ryabchikov, Dimitry [Technische Univ. Muenchen (Germany)

2013-07-01

When performing partial-wave analyses of multi-body final states, the choice of the fit model, i.e. the set of waves to be used in the fit, can significantly alter the results of the partial wave fit. Traditionally, the models were chosen based on physical arguments and by observing the changes in log-likelihood of the fits. To reduce possible bias in the model selection process, an evolutionary algorithm was developed based on a Bayesian goodness-of-fit criterion which takes into account the model complexity. Starting from systematically constructed pools of waves which contain significantly more waves than the typical fit model, the algorithm yields a model with an optimal log-likelihood and with a number of partial waves which is appropriate for the number of events in the data. Partial waves with small contributions to the total intensity are penalized and likely to be dropped during the selection process, as are models were excessive correlations between single waves occur. Due to the automated nature of the model selection, a much larger part of the model space can be explored than would be possible in a manual selection. In addition the method allows to assess the dependence of the fit result on the fit model which is an important contribution to the systematic uncertainty.

Examining speed versus selection in connectivity models using elk migration as an example

Science.gov (United States)

Brennan, Angela; Hanks, Ephraim M.; Merkle, Jerod A.; Cole, Eric K.; Dewey, Sarah R.; Courtemanch, Alyson B.; Cross, Paul C.

2018-01-01

ContextLandscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.ObjectiveTo compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.MethodsUsing movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.ResultsAll connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.ConclusionsCTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.

Sequence selection by dynamical symmetry breaking in an autocatalytic binary polymer model

DEFF Research Database (Denmark)

Fellermann, Harold; Tanaka, Shinpei; Rasmussen, Steen

2017-01-01

Template-directed replication of nucleic acids is at the essence of all living beings and a major milestone for any origin of life scenario. We present an idealized model of prebiotic sequence replication, where binary polymers act as templates for their autocatalytic replication, thereby serving...... as each others reactants and products in an intertwined molecular ecology. Our model demonstrates how autocatalysis alters the qualitative and quantitative system dynamics in counterintuitive ways. Most notably, numerical simulations reveal a very strong intrinsic selection mechanism that favors...... the appearance of a few population structures with highly ordered and repetitive sequence patterns when starting from a pool of monomers. We demonstrate both analytically and through simulation how this "selection of the dullest" is caused by continued symmetry breaking through random fluctuations...

The genealogy of samples in models with selection.

Science.gov (United States)

Neuhauser, C; Krone, S M

1997-02-01

We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models. DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case.

78 FR 63464 - William D. Ford Federal Direct Loan Program Repayment Plan Selection Form; Extension of Public...

Science.gov (United States)

2013-10-24

... DEPARTMENT OF EDUCATION William D. Ford Federal Direct Loan Program Repayment Plan Selection Form; Extension of Public Comment Period; Correction AGENCY: Department of Education. ACTION: Correction notice... entitled, ``William D. Ford Federal Direct Loan Program Repayment Plan Selection Form''. ED is extending...

Model Selection with the Linear Mixed Model for Longitudinal Data

Science.gov (United States)

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

Directory of Open Access Journals (Sweden)

Jun-He Yang

2017-01-01

Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

IT vendor selection model by using structural equation model & analytical hierarchy process

Science.gov (United States)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Dealing with selection bias in educational transition models

DEFF Research Database (Denmark)

Holm, Anders; Jæger, Mads Meier

2011-01-01

This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.......This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational...... transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which...

Multiplicative Genotype-Environment Interaction as a Cause of Reversed Response to Directional Selection

OpenAIRE

Gimelfarb, A.

1986-01-01

In experiments with directional selection on a quantitative character a "reversed response" to selection is occasionally observed, when selection of individuals for a higher (lower) value of the character results in a lower (higher) value of the character among their offspring. A sudden change in environments or random drift is often assumed to be responsible for this. It is demonstrated in this paper that these two causes cannot account for the reversed response at least in some of the exper...

Estimation of a multivariate mean under model selection uncertainty

Directory of Open Access Journals (Sweden)

Georges Nguefack-Tsague

2014-05-01

Full Text Available Model selection uncertainty would occur if we selected a model based on one data set and subsequently applied it for statistical inferences, because the "correct" model would not be selected with certainty.  When the selection and inference are based on the same dataset, some additional problems arise due to the correlation of the two stages (selection and inference. In this paper model selection uncertainty is considered and model averaging is proposed. The proposal is related to the theory of James and Stein of estimating more than three parameters from independent normal observations. We suggest that a model averaging scheme taking into account the selection procedure could be more appropriate than model selection alone. Some properties of this model averaging estimator are investigated; in particular we show using Stein's results that it is a minimax estimator and can outperform Stein-type estimators.

Strategies for Selecting Routes through Real-World Environments: Relative Topography, Initial Route Straightness, and Cardinal Direction.

Directory of Open Access Journals (Sweden)

Tad T Brunyé

Full Text Available Previous research has demonstrated that route planners use several reliable strategies for selecting between alternate routes. Strategies include selecting straight rather than winding routes leaving an origin, selecting generally south- rather than north-going routes, and selecting routes that avoid traversal of complex topography. The contribution of this paper is characterizing the relative influence and potential interactions of these strategies. We also examine whether individual differences would predict any strategy reliance. Results showed evidence for independent and additive influences of all three strategies, with a strong influence of topography and initial segment straightness, and relatively weak influence of cardinal direction. Additively, routes were also disproportionately selected when they traversed relatively flat regions, had relatively straight initial segments, and went generally south rather than north. Two individual differences, extraversion and sense of direction, predicted the extent of some effects. Under real-world conditions navigators indeed consider a route's initial straightness, cardinal direction, and topography, but these cues differ in relative influence and vary in their application across individuals.

Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings

Science.gov (United States)

Foard, M. B.; Nelson, A. S.; Harley, G. L.

2017-12-01

Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some

Goal-directed behaviour and instrumental devaluation: a neural system-level computational model

Directory of Open Access Journals (Sweden)

Francesco Mannella

2016-10-01

Full Text Available Devaluation is the key experimental paradigm used to demonstrate the presence of instrumental behaviours guided by goals in mammals. We propose a neural system-level computational model to address the question of which brain mechanisms allow the current value of rewards to control instrumental actions. The model pivots on and shows the computational soundness of the hypothesis for which the internal representation of instrumental manipulanda (e.g., levers activate the representation of rewards (or `action-outcomes', e.g. foods while attributing to them a value which depends on the current internal state of the animal (e.g., satiation for some but not all foods. The model also proposes an initial hypothesis of the integrated system of key brain components supporting this process and allowing the recalled outcomes to bias action selection: (a the sub-system formed by the basolateral amygdala and insular cortex acquiring the manipulanda-outcomes associations and attributing the current value to the outcomes; (b the three basal ganglia-cortical loops selecting respectively goals, associative sensory representations, and actions; (c the cortico-cortical and striato-nigro-striatal neural pathways supporting the selection, and selection learning, of actions based on habits and goals. The model reproduces and integrates the results of different devaluation experiments carried out with control rats and rats with pre- and post-training lesions of the basolateral amygdala, the nucleus accumbens core, the prelimbic cortex, and the dorso-medial striatum. The results support the soundness of the hypotheses of the model and show its capacity to integrate, at the system-level, the operations of the key brain structures underlying devaluation. Based on its hypotheses and predictions, the model also represents an operational framework to support the design and analysis of new experiments on the motivational aspects of goal-directed behaviour.

Review and selection of unsaturated flow models

Energy Technology Data Exchange (ETDEWEB)

Reeves, M.; Baker, N.A.; Duguid, J.O. [INTERA, Inc., Las Vegas, NV (United States)

1994-04-04

Since the 1960`s, ground-water flow models have been used for analysis of water resources problems. In the 1970`s, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970`s and well into the 1980`s focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M&O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing.

Review and selection of unsaturated flow models

International Nuclear Information System (INIS)

Reeves, M.; Baker, N.A.; Duguid, J.O.

1994-01-01

Since the 1960's, ground-water flow models have been used for analysis of water resources problems. In the 1970's, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970's and well into the 1980's focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M ampersand O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M ampersand O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing

How directional mobility affects coexistence in rock-paper-scissors models

Science.gov (United States)

Avelino, P. P.; Bazeia, D.; Losano, L.; Menezes, J.; de Oliveira, B. F.; Santos, M. A.

2018-03-01

This work deals with a system of three distinct species that changes in time under the presence of mobility, selection, and reproduction, as in the popular rock-paper-scissors game. The novelty of the current study is the modification of the mobility rule to the case of directional mobility, in which the species move following the direction associated to a larger (averaged) number density of selection targets in the surrounding neighborhood. Directional mobility can be used to simulate eyes that see or a nose that smells, and we show how it may contribute to reduce the probability of coexistence.

Continuum model for chiral induced spin selectivity in helical molecules

Energy Technology Data Exchange (ETDEWEB)

Medina, Ernesto [Centro de Física, Instituto Venezolano de Investigaciones Científicas, 21827, Caracas 1020 A (Venezuela, Bolivarian Republic of); Groupe de Physique Statistique, Institut Jean Lamour, Université de Lorraine, 54506 Vandoeuvre-les-Nancy Cedex (France); Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287 (United States); González-Arraga, Luis A. [IMDEA Nanoscience, Cantoblanco, 28049 Madrid (Spain); Finkelstein-Shapiro, Daniel; Mujica, Vladimiro [Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287 (United States); Berche, Bertrand [Centro de Física, Instituto Venezolano de Investigaciones Científicas, 21827, Caracas 1020 A (Venezuela, Bolivarian Republic of); Groupe de Physique Statistique, Institut Jean Lamour, Université de Lorraine, 54506 Vandoeuvre-les-Nancy Cedex (France)

2015-05-21

A minimal model is exactly solved for electron spin transport on a helix. Electron transport is assumed to be supported by well oriented p{sub z} type orbitals on base molecules forming a staircase of definite chirality. In a tight binding interpretation, the spin-orbit coupling (SOC) opens up an effective π{sub z} − π{sub z} coupling via interbase p{sub x,y} − p{sub z} hopping, introducing spin coupled transport. The resulting continuum model spectrum shows two Kramers doublet transport channels with a gap proportional to the SOC. Each doubly degenerate channel satisfies time reversal symmetry; nevertheless, a bias chooses a transport direction and thus selects for spin orientation. The model predicts (i) which spin orientation is selected depending on chirality and bias, (ii) changes in spin preference as a function of input Fermi level and (iii) back-scattering suppression protected by the SO gap. We compute the spin current with a definite helicity and find it to be proportional to the torsion of the chiral structure and the non-adiabatic Aharonov-Anandan phase. To describe room temperature transport, we assume that the total transmission is the result of a product of coherent steps.

Model Selection in Continuous Test Norming With GAMLSS.

Science.gov (United States)

Voncken, Lieke; Albers, Casper J; Timmerman, Marieke E

2017-06-01

To compute norms from reference group test scores, continuous norming is preferred over traditional norming. A suitable continuous norming approach for continuous data is the use of the Box-Cox Power Exponential model, which is found in the generalized additive models for location, scale, and shape. Applying the Box-Cox Power Exponential model for test norming requires model selection, but it is unknown how well this can be done with an automatic selection procedure. In a simulation study, we compared the performance of two stepwise model selection procedures combined with four model-fit criteria (Akaike information criterion, Bayesian information criterion, generalized Akaike information criterion (3), cross-validation), varying data complexity, sampling design, and sample size in a fully crossed design. The new procedure combined with one of the generalized Akaike information criterion was the most efficient model selection procedure (i.e., required the smallest sample size). The advocated model selection procedure is illustrated with norming data of an intelligence test.

A four-step sandwich radioimmunoassay for direct selection of monoclonal antibodies to allergen molecules

International Nuclear Information System (INIS)

Ley, V.; Corbi, A.L.; Sanchez-Madrid, F.; Carreira, J.C.

1985-01-01

A 4-step radioimmunoassay has been devised for direct identification of monoclonal antibodies (MAb) directed to IgE-binding molecules. Polyvinyl chloride wells coated with purified anti-mouse kappa chain MAb (187-1) were successively incubated with: (1) MAb-containing hybridoma supernatants, (2) allergen extract, (3) allergic patients' serum pool, and (4) 125 I-labeled anti-human IgE antiserum, to detect MAb-allergen-IgE complexes. MAb to allergens from Parietaria judaica pollen and Dermatophagoides mites have been selected with this screening procedure. The affinity-purified allergen molecules competed the binding of IgE to allergen extracts coated to paper discs in a RAST inhibition assay, confirming the anti-allergen specificity of the selected MAb. This screening method is sensitive enough to allow detection of MAb directed to poorly represented allergens. (Auth.)

Selective attention modulates the direction of audio-visual temporal recalibration.

Science.gov (United States)

Ikumi, Nara; Soto-Faraco, Salvador

2014-01-01

Temporal recalibration of cross-modal synchrony has been proposed as a mechanism to compensate for timing differences between sensory modalities. However, far from the rich complexity of everyday life sensory environments, most studies to date have examined recalibration on isolated cross-modal pairings. Here, we hypothesize that selective attention might provide an effective filter to help resolve which stimuli are selected when multiple events compete for recalibration. We addressed this question by testing audio-visual recalibration following an adaptation phase where two opposing audio-visual asynchronies were present. The direction of voluntary visual attention, and therefore to one of the two possible asynchronies (flash leading or flash lagging), was manipulated using colour as a selection criterion. We found a shift in the point of subjective audio-visual simultaneity as a function of whether the observer had focused attention to audio-then-flash or to flash-then-audio groupings during the adaptation phase. A baseline adaptation condition revealed that this effect of endogenous attention was only effective toward the lagging flash. This hints at the role of exogenous capture and/or additional endogenous effects producing an asymmetry toward the leading flash. We conclude that selective attention helps promote selected audio-visual pairings to be combined and subsequently adjusted in time but, stimulus organization exerts a strong impact on recalibration. We tentatively hypothesize that the resolution of recalibration in complex scenarios involves the orchestration of top-down selection mechanisms and stimulus-driven processes.

Selective attention modulates the direction of audio-visual temporal recalibration.

Directory of Open Access Journals (Sweden)

Nara Ikumi

Full Text Available Temporal recalibration of cross-modal synchrony has been proposed as a mechanism to compensate for timing differences between sensory modalities. However, far from the rich complexity of everyday life sensory environments, most studies to date have examined recalibration on isolated cross-modal pairings. Here, we hypothesize that selective attention might provide an effective filter to help resolve which stimuli are selected when multiple events compete for recalibration. We addressed this question by testing audio-visual recalibration following an adaptation phase where two opposing audio-visual asynchronies were present. The direction of voluntary visual attention, and therefore to one of the two possible asynchronies (flash leading or flash lagging, was manipulated using colour as a selection criterion. We found a shift in the point of subjective audio-visual simultaneity as a function of whether the observer had focused attention to audio-then-flash or to flash-then-audio groupings during the adaptation phase. A baseline adaptation condition revealed that this effect of endogenous attention was only effective toward the lagging flash. This hints at the role of exogenous capture and/or additional endogenous effects producing an asymmetry toward the leading flash. We conclude that selective attention helps promote selected audio-visual pairings to be combined and subsequently adjusted in time but, stimulus organization exerts a strong impact on recalibration. We tentatively hypothesize that the resolution of recalibration in complex scenarios involves the orchestration of top-down selection mechanisms and stimulus-driven processes.

A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data

International Nuclear Information System (INIS)

Louit, D.M.; Pascual, R.; Jardine, A.K.S.

2009-01-01

Many times, reliability studies rely on false premises such as independent and identically distributed time between failures assumption (renewal process). This can lead to erroneous model selection for the time to failure of a particular component or system, which can in turn lead to wrong conclusions and decisions. A strong statistical focus, a lack of a systematic approach and sometimes inadequate theoretical background seem to have made it difficult for maintenance analysts to adopt the necessary stage of data testing before the selection of a suitable model. In this paper, a framework for model selection to represent the failure process for a component or system is presented, based on a review of available trend tests. The paper focuses only on single-time-variable models and is primarily directed to analysts responsible for reliability analyses in an industrial maintenance environment. The model selection framework is directed towards the discrimination between the use of statistical distributions to represent the time to failure ('renewal approach'); and the use of stochastic point processes ('repairable systems approach'), when there may be the presence of system ageing or reliability growth. An illustrative example based on failure data from a fleet of backhoes is included.

A novel Direct Small World network model

Directory of Open Access Journals (Sweden)

LIN Tao

2016-10-01

Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.

Spin and Wind Directions II: A Bell State Quantum Model.

Science.gov (United States)

Aerts, Diederik; Arguëlles, Jonito Aerts; Beltran, Lester; Geriente, Suzette; Sassoli de Bianchi, Massimiliano; Sozzo, Sandro; Veloz, Tomas

2018-01-01

In the first half of this two-part article (Aerts et al. in Found Sci. doi:10.1007/s10699-017-9528-9, 2017b), we analyzed a cognitive psychology experiment where participants were asked to select pairs of directions that they considered to be the best example of Two Different Wind Directions , and showed that the data violate the CHSH version of Bell's inequality, with same magnitude as in typical Bell-test experiments in physics. In this second part, we complete our analysis by presenting a symmetrized version of the experiment, still violating the CHSH inequality but now also obeying the marginal law, for which we provide a full quantum modeling in Hilbert space, using a singlet state and suitably chosen product measurements. We also address some of the criticisms that have been recently directed at experiments of this kind, according to which they would not highlight the presence of genuine forms of entanglement. We explain that these criticisms are based on a view of entanglement that is too restrictive, thus unable to capture all possible ways physical and conceptual entities can connect and form systems behaving as a whole. We also provide an example of a mechanical model showing that the violations of the marginal law and Bell inequalities are generally to be associated with different mechanisms.

Quality Quandaries- Time Series Model Selection and Parsimony

DEFF Research Database (Denmark)

Bisgaard, Søren; Kulahci, Murat

2009-01-01

Some of the issues involved in selecting adequate models for time series data are discussed using an example concerning the number of users of an Internet server. The process of selecting an appropriate model is subjective and requires experience and judgment. The authors believe an important...... consideration in model selection should be parameter parsimony. They favor the use of parsimonious mixed ARMA models, noting that research has shown that a model building strategy that considers only autoregressive representations will lead to non-parsimonious models and to loss of forecasting accuracy....

Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota.

Energy Technology Data Exchange (ETDEWEB)

Portone, Teresa; Niederhaus, John Henry; Sanchez, Jason James; Swiler, Laura Painton

2018-02-01

This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

Incorporating direct marketing activity into latent attrition models

NARCIS (Netherlands)

Schweidel, David A.; Knox, George

2013-01-01

When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,

The ancestral selection graph under strong directional selection.

Science.gov (United States)

Pokalyuk, Cornelia; Pfaffelhuber, Peter

2013-08-01

The ancestral selection graph (ASG) was introduced by  Neuhauser and Krone (1997) in order to study populations of constant size which evolve under selection. Coalescence events, which occur at rate 1 for every pair of lines, lead to joint ancestry. In addition, splitting events in the ASG at rate α, the scaled selection coefficient, produce possible ancestors, such that the real ancestor depends on the ancestral alleles. Here, we use the ASG in the case without mutation in order to study fixation of a beneficial mutant. Using our main tool, a reversibility property of the ASG, we provide a new proof of the fact that a beneficial allele fixes roughly in time (2logα)/α if α is large. Copyright © 2012 Elsevier Inc. All rights reserved.

Methods for model selection in applied science and engineering.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2004-10-01

Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

Direct phase selection of initial phases from single-wavelength anomalous dispersion (SAD) for the improvement of electron density and ab initio structure determination

International Nuclear Information System (INIS)

Chen, Chung-De; Huang, Yen-Chieh; Chiang, Hsin-Lin; Hsieh, Yin-Cheng; Guan, Hong-Hsiang; Chuankhayan, Phimonphan; Chen, Chun-Jung

2014-01-01

A novel direct phase-selection method to select optimized phases from the ambiguous phases of a subset of reflections to replace the corresponding initial SAD phases has been developed. With the improved phases, the completeness of built residues of protein molecules is enhanced for efficient structure determination. Optimization of the initial phasing has been a decisive factor in the success of the subsequent electron-density modification, model building and structure determination of biological macromolecules using the single-wavelength anomalous dispersion (SAD) method. Two possible phase solutions (ϕ 1 and ϕ 2 ) generated from two symmetric phase triangles in the Harker construction for the SAD method cause the well known phase ambiguity. A novel direct phase-selection method utilizing the θ DS list as a criterion to select optimized phases ϕ am from ϕ 1 or ϕ 2 of a subset of reflections with a high percentage of correct phases to replace the corresponding initial SAD phases ϕ SAD has been developed. Based on this work, reflections with an angle θ DS in the range 35–145° are selected for an optimized improvement, where θ DS is the angle between the initial phase ϕ SAD and a preliminary density-modification (DM) phase ϕ DM NHL . The results show that utilizing the additional direct phase-selection step prior to simple solvent flattening without phase combination using existing DM programs, such as RESOLVE or DM from CCP4, significantly improves the final phases in terms of increased correlation coefficients of electron-density maps and diminished mean phase errors. With the improved phases and density maps from the direct phase-selection method, the completeness of residues of protein molecules built with main chains and side chains is enhanced for efficient structure determination

Directed Innovation of Business Models

OpenAIRE

Stelian Brad; Emilia Brad

2016-01-01

Business model innovation is an important issue to keep business competitive and increase company’s profits. Due to many market attractors, identification of appropriate paths of business model evolution is a painful and risky process. To improve decision’s effectiveness in this process, an architectural construct of analysis and conceptualization for business model innovation that combines directed evolution and blue ocean concepts is proposed in this paper under the name o...

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

Directory of Open Access Journals (Sweden)

Mingyue Qiu

Full Text Available In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA. We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

Science.gov (United States)

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Selectivity of Direct Methanol Fuel Cell Membranes

Directory of Open Access Journals (Sweden)

Antonino S. Aricò

2015-11-01

Full Text Available Sulfonic acid-functionalized polymer electrolyte membranes alternative to Nafion® were developed. These were hydrocarbon systems, such as blend sulfonated polyetheretherketone (s-PEEK, new generation perfluorosulfonic acid (PFSA systems, and composite zirconium phosphate–PFSA polymers. The membranes varied in terms of composition, equivalent weight, thickness, and filler and were investigated with regard to their methanol permeation characteristics and proton conductivity for application in direct methanol fuel cells. The behavior of the membrane electrode assemblies (MEA was investigated in fuel cell with the aim to individuate a correlation between membrane characteristics and their performance in a direct methanol fuel cell (DMFC. The power density of the DMFC at 60 °C increased according to a square root-like function of the membrane selectivity. This was defined as the reciprocal of the product between area specific resistance and crossover. The power density achieved at 60 °C for the most promising s-PEEK-based membrane-electrode assembly (MEA was higher than the benchmark Nafion® 115-based MEA (77 mW·cm−2 vs. 64 mW·cm−2. This result was due to a lower methanol crossover (47 mA·cm−2 equivalent current density for s-PEEK vs. 120 mA·cm−2 for Nafion® 115 at 60 °C as recorded at OCV with 2 M methanol and a suitable area specific resistance (0.15 Ohm cm2 for s-PEEK vs. 0.22 Ohm cm2 for Nafion® 115.

Selectivity of Direct Methanol Fuel Cell Membranes.

Science.gov (United States)

Aricò, Antonino S; Sebastian, David; Schuster, Michael; Bauer, Bernd; D'Urso, Claudia; Lufrano, Francesco; Baglio, Vincenzo

2015-11-24

Sulfonic acid-functionalized polymer electrolyte membranes alternative to Nafion(®) were developed. These were hydrocarbon systems, such as blend sulfonated polyetheretherketone (s-PEEK), new generation perfluorosulfonic acid (PFSA) systems, and composite zirconium phosphate-PFSA polymers. The membranes varied in terms of composition, equivalent weight, thickness, and filler and were investigated with regard to their methanol permeation characteristics and proton conductivity for application in direct methanol fuel cells. The behavior of the membrane electrode assemblies (MEA) was investigated in fuel cell with the aim to individuate a correlation between membrane characteristics and their performance in a direct methanol fuel cell (DMFC). The power density of the DMFC at 60 °C increased according to a square root-like function of the membrane selectivity. This was defined as the reciprocal of the product between area specific resistance and crossover. The power density achieved at 60 °C for the most promising s-PEEK-based membrane-electrode assembly (MEA) was higher than the benchmark Nafion(®) 115-based MEA (77 mW·cm(-2) vs. 64 mW·cm(-2)). This result was due to a lower methanol crossover (47 mA·cm(-2) equivalent current density for s-PEEK vs. 120 mA·cm(-2) for Nafion(®) 115 at 60 °C as recorded at OCV with 2 M methanol) and a suitable area specific resistance (0.15 Ohm cm² for s-PEEK vs. 0.22 Ohm cm² for Nafion(®) 115).

An analytical–numerical model of laser direct metal deposition track and microstructure formation

International Nuclear Information System (INIS)

Ahsan, M Naveed; Pinkerton, Andrew J

2011-01-01

Multiple analytical and numerical models of the laser metal deposition process have been presented, but most rely on sequential solution of the energy and mass balance equations or discretization of the problem domain. Laser direct metal deposition is a complex process involving multiple interdependent processes which can be best simulated using a fully coupled mass-energy balance solution. In this work a coupled analytical–numerical solution is presented. Sub-models of the powder stream, quasi-stationary conduction in the substrate and powder assimilation into the area of the substrate above the liquidus temperature are combined. An iterative feedback loop is used to ensure mass and energy balances are maintained at the melt pool. The model is verified using Ti–6Al–4V single track deposition, produced with a coaxial nozzle and a diode laser. The model predictions of local temperature history, the track profile and microstructure scale show good agreement with the experimental results. The model is a useful industrial aid and alternative to finite element methods for selecting the parameters to use for laser direct metal deposition when separate geometric and microstructural outcomes are required

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

Science.gov (United States)

Pan, Yuchen; Ding, Shuai; Fan, Wenjuan; Li, Jing; Yang, Shanlin

2015-01-01

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard's Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.

A Heckman Selection- t Model

KAUST Repository

Marchenko, Yulia V.; Genton, Marc G.

2012-01-01

for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical

A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data

Energy Technology Data Exchange (ETDEWEB)

Louit, D.M. [Komatsu Chile, Av. Americo Vespucio 0631, Quilicura, Santiago (Chile)], E-mail: rpascual@ing.puc.cl; Pascual, R. [Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Jardine, A.K.S. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King' s College Road, Toronto, Ont., M5S 3G8 (Canada)

2009-10-15

Many times, reliability studies rely on false premises such as independent and identically distributed time between failures assumption (renewal process). This can lead to erroneous model selection for the time to failure of a particular component or system, which can in turn lead to wrong conclusions and decisions. A strong statistical focus, a lack of a systematic approach and sometimes inadequate theoretical background seem to have made it difficult for maintenance analysts to adopt the necessary stage of data testing before the selection of a suitable model. In this paper, a framework for model selection to represent the failure process for a component or system is presented, based on a review of available trend tests. The paper focuses only on single-time-variable models and is primarily directed to analysts responsible for reliability analyses in an industrial maintenance environment. The model selection framework is directed towards the discrimination between the use of statistical distributions to represent the time to failure ('renewal approach'); and the use of stochastic point processes ('repairable systems approach'), when there may be the presence of system ageing or reliability growth. An illustrative example based on failure data from a fleet of backhoes is included.

The Effects of Methylphenidate on Goal-Directed Behavior in a Rat Model of ADHD

Directory of Open Access Journals (Sweden)

Joman Y. Natsheh

2015-11-01

Full Text Available Although attentional and motor alterations in Attention Deficit Hyperactivity Disorder (ADHD have been well characterized, less is known about how this disorder impacts goal-directed behavior. To investigate whether there is a misbalance between goal-directed and habitual behaviors in an animal model of ADHD, we tested adult [P75-P105] Spontaneously Hypertensive Rats (SHR (ADHD rat model and Wistar-Kyoto rats (WKY, the normotensive control strain, on an instrumental conditioning paradigm with two phases: a free-operant training phase in which rats separately acquired two distinct action-outcome contingencies, and a choice test conducted in extinction prior to which one of the food outcomes was devalued through specific satiety. To assess the effects of Methylphenidate, a commonly used ADHD medication, on goal-directed behavior, we injected rats with either Methylphenidate or saline prior to the choice test. Both rat strains acquired an instrumental response, with SHR responding at greater rates over the course of training. During the choice test WKY demonstrated goal-directed behavior, responding more frequently on the lever that delivered, during training, the still-valued outcome. In contrast, SHR showed no goal-directed behavior, responding equally on both levers. However, methylphenidate administration prior to the choice test restored goal-directed behavior in SHR, and disrupted this behavior in WKY rats. This study provides the first experimental evidence for selective impairment in goal-directed behavior in rat models of ADHD, and how methylphenidate acts differently on SHR and WKY animals to restore or impair this behavior, respectively.

Mutation-selection models of codon substitution and their use to estimate selective strengths on codon usage

DEFF Research Database (Denmark)

Yang, Ziheng; Nielsen, Rasmus

2008-01-01

Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we impl...... codon usage in mammals. Estimates of selection coefficients nevertheless suggest that selection on codon usage is weak and most mutations are nearly neutral. The sensitivity of the analysis on the assumed mutation model is discussed.......Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we...... implement a few population genetics models of codon substitution that explicitly consider mutation bias and natural selection at the DNA level. Selection on codon usage is modeled by introducing codon-fitness parameters, which together with mutation-bias parameters, predict optimal codon frequencies...

Traditional Amerindian cultivators combine directional and ideotypic selection for sustainable management of cassava genetic diversity.

Science.gov (United States)

Duputié, A; Massol, F; David, P; Haxaire, C; McKey, D

2009-06-01

Plant domestication provides striking examples of rapid evolution. Yet, it involves more complex processes than plain directional selection. Understanding the dynamics of diversity in traditional agroecosystems is both a fundamental goal in evolutionary biology and a practical goal in conservation. We studied how Amerindian cultivators maintain dynamically evolving gene pools in cassava. Farmers purposely maintain diversity in the form of phenotypically distinct, clonally propagated landraces. Landrace gene pools are continuously renewed by incorporating seedlings issued from spontaneous sexual reproduction. This poses two problems: agronomic quality may decrease because some seedlings are inbred, and landrace identity may be progressively lost through the incorporation of unrelated seedlings. Using a large microsatellite dataset, we show that farmers solve these problems by applying two kinds of selection: directional selection against inbred genotypes, and counter-selection of off-type phenotypes, which maintains high intra-landrace relatedness. Thus, cultural elements such as ideotypes (a representation of the ideal phenotype of a landrace) can shape genetic diversity.

Novel Harmonic Regularization Approach for Variable Selection in Cox’s Proportional Hazards Model

Directory of Open Access Journals (Sweden)

Ge-Jin Chu

2014-01-01

Full Text Available Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2select key risk factors in the Cox’s proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL, the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods.

A Computational Model of Selection by Consequences

Science.gov (United States)

McDowell, J. J.

2004-01-01

Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of…

Directional Dipole Model for Subsurface Scattering

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall; Hachisuka, Toshiya; Kjeldsen, Thomas Kim

2014-01-01

Rendering translucent materials using Monte Carlo ray tracing is computationally expensive due to a large number of subsurface scattering events. Faster approaches are based on analytical models derived from diffusion theory. While such analytical models are efficient, they miss out on some...... point source diffusion. A ray source corresponds better to the light that refracts through the surface of a translucent material. Using this ray source, we are able to take the direction of the incident light ray and the direction toward the point of emergence into account. We use a dipole construction...

A computational model of selection by consequences.

OpenAIRE

McDowell, J J

2004-01-01

Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of computational experiments that arranged reinforcement according to random-interval (RI) schedules. The quantitative features of the model were varied o...

Search Directions for Direct H2O2 Synthesis Catalysts Starting from Au-12 Nanoclusters

DEFF Research Database (Denmark)

Grabow, Lars; Larsen, Britt Hvolbæk; Falsig, Hanne

2012-01-01

that the rate of H2O2 and H2O formation can be determined from a single descriptor, namely, the binding energy of oxygen (E-O). Our model predicts the search direction starting from an Au-12 nanocluster for an optimal catalyst in terms of activity and selectivity for direct H2O2 synthesis. Taking also stability......We present density functional theory calculations on the direct synthesis of H2O2 from H-2 and O-2 over an Au-12 corner model of a gold nanoparticle. We first show a simple route for the direct formation of H2O2 over a gold nanocatalyst, by studying the energetics of 20 possible elementary...... reactions involved in the oxidation of H-2 by O-2. The unwanted side reaction to H2O is also considered. Next we evaluate the degree of catalyst control and address the factors controlling the activity and the selectivity. By combining well-known energy scaling relations with microkinetic modeling, we show...

Selection platforms for directed evolution in synthetic biology.

Science.gov (United States)

Tizei, Pedro A G; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B

2016-08-15

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. © 2016 The Author(s).

Statistical model selection with “Big Data”

Directory of Open Access Journals (Sweden)

Jurgen A. Doornik

2015-12-01

Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

Computer Modeling of Direct Metal Laser Sintering

Science.gov (United States)

Cross, Matthew

2014-01-01

A computational approach to modeling direct metal laser sintering (DMLS) additive manufacturing process is presented. The primary application of the model is for determining the temperature history of parts fabricated using DMLS to evaluate residual stresses found in finished pieces and to assess manufacturing process strategies to reduce part slumping. The model utilizes MSC SINDA as a heat transfer solver with imbedded FORTRAN computer code to direct laser motion, apply laser heating as a boundary condition, and simulate the addition of metal powder layers during part fabrication. Model results are compared to available data collected during in situ DMLS part manufacture.

Direct Synthesis of Telechelic Polyethylene by Selective Insertion Polymerization

KAUST Repository

Jian, Zhongbao

2016-10-14

A single-step route to telechelic polyethylene (PE) is enabled by selective insertion polymerization. PdII-catalyzed copolymerization of ethylene and 2-vinylfuran (VF) generates α,ω-di-furan telechelic polyethylene. Orthogonally reactive exclusively in-chain anhydride groups are formed by terpolymerization with carbic anhydride. Combined experimental and theoretical DFT studies reveal the key for this direct approach to telechelics to be a match of the comonomers’ different electronics and bulk. Identified essential features of the comonomer are that it is an electron-rich olefin that forms an insertion product stabilized by an additional interaction, namely a π–η3 interaction for the case of VF.

Nanoscale layer-selective readout of magnetization direction from a magnetic multilayer using a spin-torque oscillator

International Nuclear Information System (INIS)

Suto, Hirofumi; Nagasawa, Tazumi; Kudo, Kiwamu; Mizushima, Koichi; Sato, Rie

2014-01-01

Technology for detecting the magnetization direction of nanoscale magnetic material is crucial for realizing high-density magnetic recording devices. Conventionally, a magnetoresistive device is used that changes its resistivity in accordance with the direction of the stray field from an objective magnet. However, when several magnets are near such a device, the superposition of stray fields from all the magnets acts on the sensor, preventing selective recognition of their individual magnetization directions. Here we introduce a novel readout method for detecting the magnetization direction of a nanoscale magnet by use of a spin-torque oscillator (STO). The principles behind this method are dynamic dipolar coupling between an STO and a nanoscale magnet, and detection of ferromagnetic resonance (FMR) of this coupled system from the STO signal. Because the STO couples with a specific magnet by tuning the STO oscillation frequency to match its FMR frequency, this readout method can selectively determine the magnetization direction of the magnet. (papers)

A Dual-Stage Two-Phase Model of Selective Attention

Science.gov (United States)

Hubner, Ronald; Steinhauser, Marco; Lehle, Carola

2010-01-01

The dual-stage two-phase (DSTP) model is introduced as a formal and general model of selective attention that includes both an early and a late stage of stimulus selection. Whereas at the early stage information is selected by perceptual filters whose selectivity is relatively limited, at the late stage stimuli are selected more efficiently on a…

The effects of stabilizing and directional selection on phenotypic and genotypic variation in a population of RNA enzymes.

Science.gov (United States)

Hayden, Eric J; Bratulic, Sinisa; Koenig, Iwo; Ferrada, Evandro; Wagner, Andreas

2014-02-01

The distribution of variation in a quantitative trait and its underlying distribution of genotypic diversity can both be shaped by stabilizing and directional selection. Understanding either distribution is important, because it determines a population's response to natural selection. Unfortunately, existing theory makes conflicting predictions about how selection shapes these distributions, and very little pertinent experimental evidence exists. Here we study a simple genetic system, an evolving RNA enzyme (ribozyme) in which a combination of high throughput genotyping and measurement of a biochemical phenotype allow us to address this question. We show that directional selection, compared to stabilizing selection, increases the genotypic diversity of an evolving ribozyme population. In contrast, it leaves the variance in the phenotypic trait unchanged.

Bayesian model selection of template forward models for EEG source reconstruction.

Science.gov (United States)

Strobbe, Gregor; van Mierlo, Pieter; De Vos, Maarten; Mijović, Bogdan; Hallez, Hans; Van Huffel, Sabine; López, José David; Vandenberghe, Stefaan

2014-06-01

Several EEG source reconstruction techniques have been proposed to identify the generating neuronal sources of electrical activity measured on the scalp. The solution of these techniques depends directly on the accuracy of the forward model that is inverted. Recently, a parametric empirical Bayesian (PEB) framework for distributed source reconstruction in EEG/MEG was introduced and implemented in the Statistical Parametric Mapping (SPM) software. The framework allows us to compare different forward modeling approaches, using real data, instead of using more traditional simulated data from an assumed true forward model. In the absence of a subject specific MR image, a 3-layered boundary element method (BEM) template head model is currently used including a scalp, skull and brain compartment. In this study, we introduced volumetric template head models based on the finite difference method (FDM). We constructed a FDM head model equivalent to the BEM model and an extended FDM model including CSF. These models were compared within the context of three different types of source priors related to the type of inversion used in the PEB framework: independent and identically distributed (IID) sources, equivalent to classical minimum norm approaches, coherence (COH) priors similar to methods such as LORETA, and multiple sparse priors (MSP). The resulting models were compared based on ERP data of 20 subjects using Bayesian model selection for group studies. The reconstructed activity was also compared with the findings of previous studies using functional magnetic resonance imaging. We found very strong evidence in favor of the extended FDM head model with CSF and assuming MSP. These results suggest that the use of realistic volumetric forward models can improve PEB EEG source reconstruction. Copyright © 2014 Elsevier Inc. All rights reserved.

Elementary Teachers' Selection and Use of Visual Models

Science.gov (United States)

Lee, Tammy D.; Gail Jones, M.

2018-02-01

As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service and preservice teachers in the development of a science lesson about a complex system (e.g., water cycle). Sixty-seven elementary in-service and 69 elementary preservice teachers completed a card sort task designed to document the types of visual models (e.g., images) that teachers choose when planning science instruction. Quantitative and qualitative analyses were conducted to analyze the card sort task. Semistructured interviews were conducted with a subsample of teachers to elicit the rationale for image selection. Results from this study showed that both experienced in-service teachers and novice preservice teachers tended to select similar models and use similar rationales for images to be used in lessons. Teachers tended to select models that were aesthetically pleasing and simple in design and illustrated specific elements of the water cycle. The results also showed that teachers were not likely to select images that represented the less obvious dimensions of the water cycle. Furthermore, teachers selected visual models more as a pedagogical tool to illustrate specific elements of the water cycle and less often as a tool to promote student learning related to complex systems.

Genetic search feature selection for affective modeling

DEFF Research Database (Denmark)

Martínez, Héctor P.; Yannakakis, Georgios N.

2010-01-01

Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

Direct phase selection of initial phases from single-wavelength anomalous dispersion (SAD) for the improvement of electron density and ab initio structure determination.

Science.gov (United States)

Chen, Chung-De; Huang, Yen-Chieh; Chiang, Hsin-Lin; Hsieh, Yin-Cheng; Guan, Hong-Hsiang; Chuankhayan, Phimonphan; Chen, Chun-Jung

2014-09-01

Optimization of the initial phasing has been a decisive factor in the success of the subsequent electron-density modification, model building and structure determination of biological macromolecules using the single-wavelength anomalous dispersion (SAD) method. Two possible phase solutions (φ1 and φ2) generated from two symmetric phase triangles in the Harker construction for the SAD method cause the well known phase ambiguity. A novel direct phase-selection method utilizing the θ(DS) list as a criterion to select optimized phases φ(am) from φ1 or φ2 of a subset of reflections with a high percentage of correct phases to replace the corresponding initial SAD phases φ(SAD) has been developed. Based on this work, reflections with an angle θ(DS) in the range 35-145° are selected for an optimized improvement, where θ(DS) is the angle between the initial phase φ(SAD) and a preliminary density-modification (DM) phase φ(DM)(NHL). The results show that utilizing the additional direct phase-selection step prior to simple solvent flattening without phase combination using existing DM programs, such as RESOLVE or DM from CCP4, significantly improves the final phases in terms of increased correlation coefficients of electron-density maps and diminished mean phase errors. With the improved phases and density maps from the direct phase-selection method, the completeness of residues of protein molecules built with main chains and side chains is enhanced for efficient structure determination.

Modeling switching behaviour of direct selling customers

Directory of Open Access Journals (Sweden)

P Msweli-Mbanga

2004-04-01

Full Text Available The direct selling industry suffers a high turnover rate of salespeople, resulting in high costs of training new salespeople. Further costs are incurred when broken relationships with customers cause them to switch from one product supplier to another. This study identifies twelve factors that drive the switching behaviour of direct sales customers and examines the extent to which these factors influence switching. Exploratory factor analysis was used to assess the validity of these factors. The factors were represented in a model that posits that an interpersonal relationship between a direct sales person and a customer moderates the relationship between switching behaviour and loyalty. Structural equation modeling was used to test the proposed model. The author then discusses the empirical findings and their managerial implications, providing further avenues for research.

Training directionally selective motion pathways can significantly improve reading efficiency

Science.gov (United States)

Lawton, Teri

2004-06-01

This study examined whether perceptual learning at early levels of visual processing would facilitate learning at higher levels of processing. This was examined by determining whether training the motion pathways by practicing leftright movement discrimination, as found previously, would improve the reading skills of inefficient readers significantly more than another computer game, a word discrimination game, or the reading program offered by the school. This controlled validation study found that practicing left-right movement discrimination 5-10 minutes twice a week (rapidly) for 15 weeks doubled reading fluency, and significantly improved all reading skills by more than one grade level, whereas inefficient readers in the control groups barely improved on these reading skills. In contrast to previous studies of perceptual learning, these experiments show that perceptual learning of direction discrimination significantly improved reading skills determined at higher levels of cognitive processing, thereby being generalized to a new task. The deficits in reading performance and attentional focus experienced by the person who struggles when reading are suggested to result from an information overload, resulting from timing deficits in the direction-selectivity network proposed by Russell De Valois et al. (2000), that following practice on direction discrimination goes away. This study found that practicing direction discrimination rapidly transitions the inefficient 7-year-old reader to an efficient reader.

Effects of Adaptation on Discrimination of Whisker Deflection Velocity and Angular Direction in a Model of the Barrel Cortex

Directory of Open Access Journals (Sweden)

Mainak J. Patel

2018-06-01

Full Text Available Two important stimulus features represented within the rodent barrel cortex are velocity and angular direction of whisker deflection. Each cortical barrel receives information from thalamocortical (TC cells that relay information from a single whisker, and TC input is decoded by barrel regular-spiking (RS cells through a feedforward inhibitory architecture (with inhibition delivered by cortical fast-spiking or FS cells. TC cells encode deflection velocity through population synchrony, while deflection direction is encoded through the distribution of spike counts across the TC population. Barrel RS cells encode both deflection direction and velocity with spike rate, and are divided into functional domains by direction preference. Following repetitive whisker stimulation, system adaptation causes a weakening of synaptic inputs to RS cells and diminishes RS cell spike responses, though evidence suggests that stimulus discrimination may improve following adaptation. In this work, I construct a model of the TC, FS, and RS cells comprising a single barrel system—the model incorporates realistic synaptic connectivity and dynamics and simulates both angular direction (through the spatial pattern of TC activation and velocity (through synchrony of the TC population spikes of a deflection of the primary whisker, and I use the model to examine direction and velocity selectivity of barrel RS cells before and after adaptation. I find that velocity and direction selectivity of individual RS cells (measured over multiple trials sharpens following adaptation, but stimulus discrimination using a simple linear classifier by the RS population response during a single trial (a more biologically meaningful measure than single cell discrimination over multiple trials exhibits strikingly different behavior—velocity discrimination is similar both before and after adaptation, while direction classification improves substantially following adaptation. This is the

An evidence-based approach to case management model selection for an acute care facility: is there really a preferred model?

Science.gov (United States)

Terra, Sandra M

2007-01-01

This research seeks to determine whether there is adequate evidence-based justification for selection of one acute care case management model over another. Acute Inpatient Hospital. This article presents a systematic review of published case management literature, resulting in classification specific to terms of level of evidence. This review examines the best available evidence in an effort to select an acute care case management model. Although no single case management model can be identified as preferred, it is clear that adequate evidence-based literature exists to acknowledge key factors driving the acute care model and to form a foundation for the efficacy of hospital case management practice. Although no single case management model can be identified as preferred, this systematic review demonstrates that adequate evidence-based literature exists to acknowledge key factors driving the acute care model and forming a foundation for the efficacy of hospital case management practice. Distinctive aspects of case management frameworks can be used to guide the development of an acute care case management model. The study illustrates: * The effectiveness of case management when there is direct patient contact by the case manager regardless of disease condition: not only does the quality of care increase but also length of stay (LOS) decreases, care is defragmented, and both patient and physician satisfaction can increase. * The preferred case management models result in measurable outcomes that can directly relate to, and demonstrate alignment with, organizational strategy. * Acute care management programs reduce cost and LOS, and improve outcomes. * An integrated case management program that includes social workers, as well as nursing, is the most effective acute care management model. * The successful case management model will recognize physicians, as well as patients, as valued customers with whom partnership can positively affect financial outcomes in terms of

Statistical mechanics of directed models of polymers in the square lattice

CERN Document Server

Rensburg, J V

2003-01-01

Directed square lattice models of polymers and vesicles have received considerable attention in the recent mathematical and physical sciences literature. These are idealized geometric directed lattice models introduced to study phase behaviour in polymers, and include Dyck paths, partially directed paths, directed trees and directed vesicles models. Directed models are closely related to models studied in the combinatorics literature (and are often exactly solvable). They are also simplified versions of a number of statistical mechanics models, including the self-avoiding walk, lattice animals and lattice vesicles. The exchange of approaches and ideas between statistical mechanics and combinatorics have considerably advanced the description and understanding of directed lattice models, and this will be explored in this review. The combinatorial nature of directed lattice path models makes a study using generating function approaches most natural. In contrast, the statistical mechanics approach would introduce...

Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation.

Science.gov (United States)

Weaver, Timothy D; Gunz, Philipp

2018-04-01

Researchers studying extant and extinct taxa are often interested in identifying the evolutionary processes that have lead to the morphological differences among the taxa. Ideally, one could distinguish the influences of neutral evolutionary processes (genetic drift, mutation) from natural selection, and in situations for which selection is implicated, identify the targets of selection. The directional selection gradient is an effective tool for investigating evolutionary process, because it can relate form (size and shape) differences between taxa to the variation and covariation found within taxa. However, although most modern morphometric analyses use the tools of geometric morphometrics (GM) to analyze landmark data, to date, selection gradients have mainly been calculated from linear measurements. To address this methodological gap, here we present a GM approach for visualizing and comparing between-taxon selection gradients with each other, associated difference vectors, and "selection" gradients from neutral simulations. To exemplify our approach, we use a dataset of 347 three-dimensional landmarks and semilandmarks recorded on the crania of 260 primate specimens (112 humans, 67 common chimpanzees, 36 bonobos, 45 gorillas). Results on this example dataset show how incorporating geometric information can provide important insights into the evolution of the human braincase, and serve to demonstrate the utility of our approach for understanding morphological evolution. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Target selection for direct marketing.

NARCIS (Netherlands)

Bult, Jan Roelf

1993-01-01

In this thesis we concentrated on the use ol direct mail for targeting potential buyers. The major characteristics that influences the success of a plomotional direct mail campaign are the of-fbr,the communication elements, the timing or sequence of these communication elements, and the list of

A Dynamic Model for Limb Selection

NARCIS (Netherlands)

Cox, R.F.A; Smitsman, A.W.

2008-01-01

Two experiments and a model on limb selection are reported. In Experiment 1 left-handed and right-handed participants (N = 36) repeatedly used one hand for grasping a small cube. After a clear switch in the cube’s location, perseverative limb selection was revealed in both handedness groups. In

Longitudinal analysis of direct and indirect effects on average daily gain in rabbits using a structured antedependence model.

Science.gov (United States)

David, Ingrid; Sánchez, Juan-Pablo; Piles, Miriam

2018-05-10

Indirect genetic effects (IGE) are important components of various traits in several species. Although the intensity of social interactions between partners likely vary over time, very few genetic studies have investigated how IGE vary over time for traits under selection in livestock species. To overcome this issue, our aim was: (1) to analyze longitudinal records of average daily gain (ADG) in rabbits subjected to a 5-week period of feed restriction using a structured antedependence (SAD) model that includes IGE and (2) to evaluate, by simulation, the response to selection when IGE are present and genetic evaluation is based on a SAD model that includes IGE or not. The direct genetic variance for ADG (g/d) increased from week 1 to 3 [from 8.03 to 13.47 (g/d) 2 ] and then decreased [6.20 (g/d) 2 at week 5], while the indirect genetic variance decreased from week 1 to 4 [from 0.43 to 0.22 (g/d) 2 ]. The correlation between the direct genetic effects of different weeks was moderate to high (ranging from 0.46 to 0.86) and tended to decrease with time interval between measurements. The same trend was observed for IGE for weeks 2 to 5 (correlations ranging from 0.62 to 0.91). Estimates of the correlation between IGE of week 1 and IGE of the other weeks did not follow the same pattern and correlations were lower. Estimates of correlations between direct and indirect effects were negative at all times. After seven generations of simulated selection, the increase in ADG from selection on EBV from a SAD model that included IGE was higher (~ 30%) than when those effects were omitted. Indirect genetic effects are larger just after mixing animals at weaning than later in the fattening period, probably because of the establishment of social hierarchy that is generally observed at that time. Accounting for IGE in the selection criterion maximizes genetic progress.

Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

Science.gov (United States)

Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

2017-12-04

Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

Chaotic inflation in models with flat directions

International Nuclear Information System (INIS)

Graziani, F.; Olive, K.

1989-01-01

We consider the chaotic inflationary scenario in models with flat directions. We find that unless the scalars along the flat directions have vacuum expectation values p or 10 14 M p 15 M p depending on the expectation values of the chaotic inflator, Ψ, one or two or more periods of inflation occur but with a resulting energy density perturbation δρ/ρ ≅ 10 -16 , far too small to be of any consequence for galaxy formation. Even with p only limited initial values of ≅ (3-200) M p result in inflation with reasonable density perturbations. Thus chaotic inflation in models with flat directions require rather special initial conditions. (orig.)

A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

Science.gov (United States)

Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

2015-01-01

Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

Markov chain Monte Carlo methods in directed graphical models

DEFF Research Database (Denmark)

Højbjerre, Malene

Directed graphical models present data possessing a complex dependence structure, and MCMC methods are computer-intensive simulation techniques to approximate high-dimensional intractable integrals, which emerge in such models with incomplete data. MCMC computations in directed graphical models h...

Selection bias in species distribution models: An econometric approach on forest trees based on structural modeling

Science.gov (United States)

Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.

2014-12-01

Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents

A model-based approach for identifying signatures of ancient balancing selection in genetic data.

Science.gov (United States)

DeGiorgio, Michael; Lohmueller, Kirk E; Nielsen, Rasmus

2014-08-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

A model-based approach for identifying signatures of ancient balancing selection in genetic data.

Directory of Open Access Journals (Sweden)

Michael DeGiorgio

2014-08-01

Full Text Available While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio

2015-01-01

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Robust inference in sample selection models

KAUST Repository

Zhelonkin, Mikhail

2015-11-20

The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

Model Selection in Data Analysis Competitions

DEFF Research Database (Denmark)

Wind, David Kofoed; Winther, Ole

2014-01-01

The use of data analysis competitions for selecting the most appropriate model for a problem is a recent innovation in the field of predictive machine learning. Two of the most well-known examples of this trend was the Netflix Competition and recently the competitions hosted on the online platform...... performers from Kaggle and use previous personal experiences from competing in Kaggle competitions. The stated hypotheses about feature engineering, ensembling, overfitting, model complexity and evaluation metrics give indications and guidelines on how to select a proper model for performing well...... Kaggle. In this paper, we will state and try to verify a set of qualitative hypotheses about predictive modelling, both in general and in the scope of data analysis competitions. To verify our hypotheses we will look at previous competitions and their outcomes, use qualitative interviews with top...

Adverse selection model regarding tobacco consumption

Directory of Open Access Journals (Sweden)

Dumitru MARIN

2006-01-01

Full Text Available The impact of introducing a tax on tobacco consumption can be studied trough an adverse selection model. The objective of the model presented in the following is to characterize the optimal contractual relationship between the governmental authorities and the two type employees: smokers and non-smokers, taking into account that the consumers’ decision to smoke or not represents an element of risk and uncertainty. Two scenarios are run using the General Algebraic Modeling Systems software: one without taxes set on tobacco consumption and another one with taxes set on tobacco consumption, based on an adverse selection model described previously. The results of the two scenarios are compared in the end of the paper: the wage earnings levels and the social welfare in case of a smoking agent and in case of a non-smoking agent.

Two-step variable selection in quantile regression models

Directory of Open Access Journals (Sweden)

FAN Yali

2015-06-01

Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.

Automated sample plan selection for OPC modeling

Science.gov (United States)

Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

2014-03-01

It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

Flat directions in left-right symmetric string derived models

International Nuclear Information System (INIS)

Cleaver, Gerald B.; Clements, David J.; Faraggi, Alon E.

2002-01-01

The only string models known to reproduce the minimal supersymmetric standard model in the low energy effective field theory are those constructed in the free fermionic formulation. We demonstrate the existence of quasirealistic free fermionic heterotic string models in which supersymmetric singlet flat directions do not exist. This raises the possibility that supersymmetry is broken perturbatively in such models by the one-loop Fayet-Iliopoulos term. We show, however, that supersymmetric flat directions that utilize vacuum expectation values of some non-Abelian fields in the massless string spectrum do exist in the model. We argue that hidden sector condensates lift the flat directions and break supersymmetry hierarchically

Directional Selection from Host Plants Is a Major Force Driving Host Specificity in Magnaporthe Species.

Science.gov (United States)

Zhong, Zhenhui; Norvienyeku, Justice; Chen, Meilian; Bao, Jiandong; Lin, Lianyu; Chen, Liqiong; Lin, Yahong; Wu, Xiaoxian; Cai, Zena; Zhang, Qi; Lin, Xiaoye; Hong, Yonghe; Huang, Jun; Xu, Linghong; Zhang, Honghong; Chen, Long; Tang, Wei; Zheng, Huakun; Chen, Xiaofeng; Wang, Yanli; Lian, Bi; Zhang, Liangsheng; Tang, Haibao; Lu, Guodong; Ebbole, Daniel J; Wang, Baohua; Wang, Zonghua

2016-05-06

One major threat to global food security that requires immediate attention, is the increasing incidence of host shift and host expansion in growing number of pathogenic fungi and emergence of new pathogens. The threat is more alarming because, yield quality and quantity improvement efforts are encouraging the cultivation of uniform plants with low genetic diversity that are increasingly susceptible to emerging pathogens. However, the influence of host genome differentiation on pathogen genome differentiation and its contribution to emergence and adaptability is still obscure. Here, we compared genome sequence of 6 isolates of Magnaporthe species obtained from three different host plants. We demonstrated the evolutionary relationship between Magnaporthe species and the influence of host differentiation on pathogens. Phylogenetic analysis showed that evolution of pathogen directly corresponds with host divergence, suggesting that host-pathogen interaction has led to co-evolution. Furthermore, we identified an asymmetric selection pressure on Magnaporthe species. Oryza sativa-infecting isolates showed higher directional selection from host and subsequently tends to lower the genetic diversity in its genome. We concluded that, frequent gene loss or gain, new transposon acquisition and sequence divergence are host adaptability mechanisms for Magnaporthe species, and this coevolution processes is greatly driven by directional selection from host plants.

Direct numerical simulation and modeling of turbulent natural convection in a vertical differentially heated slot

International Nuclear Information System (INIS)

Boudjemadi, R.

1996-03-01

The main objectives of this thesis are the direct numerical simulation of natural convection in a vertical differentially heated slot and the improvements of second-order turbulence modelling. A three-dimensional direct numerical simulation code has been developed in order to gain a better understanding of turbulence properties in natural convection flows. This code has been validated in several physical configurations: non-stratified natural convection flows (conduction solution), stratified natural convection flows (double boundary layer solution), transitional and turbulent Poiseuille flows. For the conduction solution, the turbulent regime was reached at a Rayleigh number of 1*10 5 and 5.4*10 5 . A detailed analysis of these results has revealed the principal qualities of the available models but has also pointed our their shortcomings. This data base has been used in order to improve the triple correlations transport models and to select the turbulent time scales suitable for such flows. (author). 122 refs., figs., tabs., 4 appends

Acoustic Noise Alters Selective Attention Processes as Indicated by Direct Current (DC) Brain Potential Changes

OpenAIRE

Trimmel, Karin; Schätzer, Julia; Trimmel, Michael

2014-01-01

Acoustic environmental noise, even of low to moderate intensity, is known to adversely affect information processing in animals and humans via attention mechanisms. In particular, facilitation and inhibition of information processing are basic functions of selective attention. Such mechanisms can be investigated by analyzing brain potentials under conditions of externally directed attention (intake of environmental information) versus internally directed attention (rejection of environmental ...

High-dimensional model estimation and model selection

CERN Multimedia

CERN. Geneva

2015-01-01

I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

Early processing variations in selective attention to the color and direction of moving stimuli during 30 days head-down bed rest

Science.gov (United States)

Wang, Lin-Jie; He, Si-Yang; Niu, Dong-Bin; Guo, Jian-Ping; Xu, Yun-Long; Wang, De-Sheng; Cao, Yi; Zhao, Qi; Tan, Cheng; Li, Zhi-Li; Tang, Guo-Hua; Li, Yin-Hui; Bai, Yan-Qiang

2013-11-01

Dynamic variations in early selective attention to the color and direction of moving stimuli were explored during a 30 days period of head-down bed rest. Event-related potentials (ERPs) were recorded at F5, F6, P5, P6 scalp locations in seven male subjects who attended to pairs of bicolored light emitting diodes that flashed sequentially to produce a perception of movement. Subjects were required to attend selectively to a critical feature of the moving target, e.g., color or direction. The tasks included: a no response task, a color selective response task, a moving direction selective response task, and a combined color-direction selective response task. Subjects were asked to perform these four tasks on: the 3rd day before bed rest; the 3rd, 15th and 30th day during the bed rest; and the 5th day after bed rest. Subjects responded quickly to the color than moving direction and combined color-direction response. And they had a longer reaction time during bed rest on the 15th and 30th day during bed rest after a relatively quicker response on the 3rd day. Using brain event-related potentials technique, we found that in the color selective response task, the mean amplitudes of P1 and N1 for target ERPs decreased in the 3rd day during bed rest and 5th day after bed rest in comparison with pre-bed rest, 15th day and 30th day during bed rest. In the combined color-direction selective response task, the P1 latencies for target ERPs on the 3rd and 30th day during bed rest were longer than on the 15th day during bed rest. As 3rd day during bed rest was in the acute adaptation period and 30th day during bed rest was in the relatively adaptation stage of head-down bed rest, the results help to clarify the effects of bed rest on different task loads and patterns of attention. It was suggested that subjects expended more time to give correct decision in the head-down tilt bed rest state. A difficulty in the recruitment of brain resources was found in feature selection task

Selective electrocatalysts toward a prototype of the membraneless direct methanol fuel cell.

Science.gov (United States)

Feng, Yan; Yang, Jinhua; Liu, Hui; Ye, Feng; Yang, Jun

2014-01-22

Mastery over the structure of nanomaterials enables control of their properties to enhance their performance for a given application. Herein we demonstrate the design and fabrication of Pt-based nanomaterials with enhanced catalytic activity and superior selectivity toward the reactions in direct methanol fuel cells (DMFCs) upon the deep understanding of the mechanisms of these electrochemical reactions. In particular, the ternary Au@Ag2S-Pt nanocomposites display superior methanol oxidation reaction (MOR) selectivity due to the electronic coupling effect among different domains of the nanocomposites, while the cage-bell structured Pt-Ru nanoparticles exhibit excellent methanol tolerance for oxygen reduction reaction (ORR) at the cathode because of the differential diffusion of methanol and oxygen in the porous Ru shell of the cage-bell nanoparticles. The good catalytic selectivity of these Pt-based nanomaterials via structural construction enables a DMFC to be built without a proton exchange membrane between the fuel electrode and the oxygen electrode.

Melody Track Selection Using Discriminative Language Model

Science.gov (United States)

Wu, Xiao; Li, Ming; Suo, Hongbin; Yan, Yonghong

In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.

Model selection for Gaussian kernel PCA denoising

DEFF Research Database (Denmark)

Jørgensen, Kasper Winther; Hansen, Lars Kai

2012-01-01

We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

Crowd of individuals walking in opposite directions. A toy model to study the segregation of the group into lanes of individuals moving in the same direction

Science.gov (United States)

Goldsztein, Guillermo H.

2017-08-01

Consider a corridor, street or bridge crowded with pedestrians walking in both directions. The individuals do not walk in a completely straight line. They adjust their path to avoid colliding with incoming pedestrians. As a result of these adjustments, the whole group sometimes end up split into lanes of individuals moving in the same direction. While this formation of lanes facilitates the flow and benefits the whole group, it is believed that results from the actions of the individuals acting only on their behalf, without considering others. This phenomenon is an example of self-organization. We analyze a simple model. We assume that individuals move around a two-lane circular track. All of them at the same speed. Half of them in one direction and the rest in the opposite direction. Each time two individuals collide, one of them moves to the other lane. The individual changing lanes is selected randomly. The system self-organizes. Eventually each lane is occupied with individuals moving in only one direction. We show that the time required for the system to self-organize is bounded by a linear function on the number of individuals. This toy model provides an example where global self-organization occurs even though each member of the group acts without considering the rest.

Statistical mechanics of directed models of polymers in the square lattice

International Nuclear Information System (INIS)

Rensburg, E J Janse van

2003-01-01

Directed square lattice models of polymers and vesicles have received considerable attention in the recent mathematical and physical sciences literature. These are idealized geometric directed lattice models introduced to study phase behaviour in polymers, and include Dyck paths, partially directed paths, directed trees and directed vesicles models. Directed models are closely related to models studied in the combinatorics literature (and are often exactly solvable). They are also simplified versions of a number of statistical mechanics models, including the self-avoiding walk, lattice animals and lattice vesicles. The exchange of approaches and ideas between statistical mechanics and combinatorics have considerably advanced the description and understanding of directed lattice models, and this will be explored in this review. The combinatorial nature of directed lattice path models makes a study using generating function approaches most natural. In contrast, the statistical mechanics approach would introduce partition functions and free energies, and then investigate these using the general framework of critical phenomena. Generating function and statistical mechanics approaches are closely related. For example, questions regarding the limiting free energy may be approached by considering the radius of convergence of a generating function, and the scaling properties of thermodynamic quantities are related to the asymptotic properties of the generating function. In this review the methods for obtaining generating functions and determining free energies in directed lattice path models of linear polymers is presented. These methods include decomposition methods leading to functional recursions, as well as the Temperley method (that is implemented by creating a combinatorial object, one slice at a time). A constant term formulation of the generating function will also be reviewed. The thermodynamic features and critical behaviour in models of directed paths may be

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS.

Science.gov (United States)

Wiedermann, Wolfgang; Li, Xintong

2018-04-16

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.

Direct and Indirect Factors Influencing Selection of Birthing Attendants in Gunungsari, West Lombok (NTB

Directory of Open Access Journals (Sweden)

Ni Nyoman Aryaniti

2015-04-01

Full Text Available Background and purpose: This study aims to determine the direct and indirect factors influencing the selection of birth attendants in Gunungsari subdistrict, West Lombok.Methods: This study was cross-sectional with a purposively selected sample of 27 mothers giving birth assisted by non-health professionals. Samples of those assisted by health professionals were taken by means of proportional systematic random sampling in Gunungsari and Penimbung health centers, respectively 29 of 916 and 14 of 437. Exogenous factors were maternal education levels, attendance to ANC classes, knowledge levels regarding to birthing attendants, maternal attitude, family support, and access to facilities. Birth attendant selection was the endogenousfactor. Data were collected by means of interviews. Data analysis includes descriptive and inferential analysis with path analysis by linear regression.Results: The majority of respondents were 21-25 years old (87.4% , housewives (47.14% had educat ion under high school (65.72% and were married (88.57%. Family support had a direct influence in decision making with a coefficient of 0.534 and 35.54% influence overall. Attendance to ANC classes in addition to family support had anindirect influence with a coefficient of 0.520 and 34.78% influence overall. Family support had a direct influence and the factor of attendance to ANC classes and family support has an indirect effect with the overall effect of 70.32%.Conclusion: The presence of the husband/family was needed in ANC class, through an implementation of schedule agreement.Keywords: family support, ANC class, birth attendants, path analysis, West Lombok

Geometry directed self-selection in the coordination-driven self-assembly of irregular supramolecular polygons.

Science.gov (United States)

Zheng, Yao-Rong; Northrop, Brian H; Yang, Hai-Bo; Zhao, Liang; Stang, Peter J

2009-05-01

The self-assembly of irregular metallo-supramolecular hexagons and parallelograms has been achieved in a self-selective manner upon mixing 120 degrees unsymmetrical dipyridyl ligands with 60 degrees or 120 degrees organoplatinum acceptors in a 1:1 ratio. The polygons have been characterized using (31)P and (1)H multinuclear NMR spectroscopy and electrospray ionization mass spectrometry (ESI-MS) as well as X-ray crystallography. Geometric features of the molecular subunits direct the self-selection process, which is supported by molecular force field computations.

Dendritic spikes amplify the synaptic signal to enhance detection of motion in a simulation of the direction-selective ganglion cell.

Directory of Open Access Journals (Sweden)

Michael J Schachter

2010-08-01

Full Text Available The On-Off direction-selective ganglion cell (DSGC in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within

Dendritic spikes amplify the synaptic signal to enhance detection of motion in a simulation of the direction-selective ganglion cell.

Science.gov (United States)

Schachter, Michael J; Oesch, Nicholas; Smith, Robert G; Taylor, W Rowland

2010-08-19

The On-Off direction-selective ganglion cell (DSGC) in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials) are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS) in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within cortical circuitry.

Relativistic direct interaction and hadron models

International Nuclear Information System (INIS)

Biswas, T.

1984-01-01

Direct interaction theories at a nonrelativistic level have been used successfully in several areas earlier (e.g. nuclear physics). But for hadron spectroscopy relativistic effects are important and hence the need for a relativistic direct interaction theory arises. It is the goal of this thesis to suggest such a theory which has the simplicity and the flexibility required for phenomenological model building. In general the introduction of relativity in a direct interaction theory is shown to be non-trivial. A first attempt leads to only an approximate form for allowed interactions. Even this is far too complex for phenomenological applicability. To simplify the model an extra spacelike particle called the vertex is introduced in any set of physical (timelike) particles. The vertex model is successfully used to fit and to predict experimental data on hadron spectra, γ and psi states fit very well with an interaction function inspired by QCD. Light mesons also fit reasonably well. Better forms of hyperfine interaction functions would be needed to improve the fitting of light mesons. The unexpectedly low pi meson mass is partially explained. Baryon ground states are fitted with unprecedented accuracy with very few adjustable parameters. For baryon excited states it is shown that better QCD motivated interaction functions are needed for a fit. Predictions for bb states in e + e - experiments are made to assist current experiments

Quantitative genetic models of sexual selection by male choice.

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Nakahashi, Wataru

2008-09-01

There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

ASYMMETRIC PRICE TRANSMISSION MODELING: THE IMPORTANCE OF MODEL COMPLEXITY AND THE PERFORMANCE OF THE SELECTION CRITERIA

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Henry de-Graft Acquah

2013-01-01

Full Text Available Information Criteria provides an attractive basis for selecting the best model from a set of competing asymmetric price transmission models or theories. However, little is understood about the sensitivity of the model selection methods to model complexity. This study therefore fits competing asymmetric price transmission models that differ in complexity to simulated data and evaluates the ability of the model selection methods to recover the true model. The results of Monte Carlo experimentation suggest that in general BIC, CAIC and DIC were superior to AIC when the true data generating process was the standard error correction model, whereas AIC was more successful when the true model was the complex error correction model. It is also shown that the model selection methods performed better in large samples for a complex asymmetric data generating process than with a standard asymmetric data generating process. Except for complex models, AIC's performance did not make substantial gains in recovery rates as sample size increased. The research findings demonstrate the influence of model complexity in asymmetric price transmission model comparison and selection.

Orientation selection of equiaxed dendritic growth by three-dimensional cellular automaton model

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Wei Lei [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an 710072 (China); Lin Xin, E-mail: xlin@nwpu.edu.cn [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an 710072 (China); Wang Meng; Huang Weidong [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an 710072 (China)

2012-07-01

A three-dimensional (3-D) adaptive mesh refinement (AMR) cellular automata (CA) model is developed to simulate the equiaxed dendritic growth of pure substance. In order to reduce the mesh induced anisotropy by CA capture rules, a limited neighbor solid fraction (LNSF) method is presented. It is shown that the LNSF method reduced the mesh induced anisotropy based on the simulated morphologies for isotropic interface free energy. An expansion description using two interface free energy anisotropy parameters ({epsilon}{sub 1}, {epsilon}{sub 2}) is used in the present 3-D CA model. It is illustrated by present 3-D CA model that the positive {epsilon}{sub 1} favors the dendritic growth with the Left-Pointing-Angle-Bracket 100 Right-Pointing-Angle-Bracket preferred directions, and negative {epsilon}{sub 2} favors dendritic growth with the Left-Pointing-Angle-Bracket 110 Right-Pointing-Angle-Bracket preferred directions, which has a good agreement with the prediction of the spherical plot of the inverse of the interfacial stiffness. The dendritic growths with the orientation selection between Left-Pointing-Angle-Bracket 100 Right-Pointing-Angle-Bracket and Left-Pointing-Angle-Bracket 110 Right-Pointing-Angle-Bracket are also discussed using the different {epsilon}{sub 1} with {epsilon}{sub 2}=-0.02. It is found that the simulated morphologies by present CA model are as expected from the minimum stiffness criterion.

A SUPPLIER SELECTION MODEL FOR SOFTWARE DEVELOPMENT OUTSOURCING

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Hancu Lucian-Viorel

2010-12-01

Full Text Available This paper presents a multi-criteria decision making model used for supplier selection for software development outsourcing on e-marketplaces. This model can be used in auctions. The supplier selection process becomes complex and difficult on last twenty years since the Internet plays an important role in business management. Companies have to concentrate their efforts on their core activities and the others activities should be realized by outsourcing. They can achieve significant cost reduction by using e-marketplaces in their purchase process and by using decision support systems on supplier selection. In the literature were proposed many approaches for supplier evaluation and selection process. The performance of potential suppliers is evaluated using multi criteria decision making methods rather than considering a single factor cost.

Theory of Alike Selectivity in Biological Channels

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Luchinsky, Dmitry G.; Gibby, Will A. T.; Kaufman, Igor Kh.; Eisenberg, Robert S.; McClintock, Peter V. E.

2016-01-01

We introduce a statistical mechanical model of the selectivity filter that accounts for the interaction between ions within the channel and derive Eisenman equation of the filter selectivity directly from the condition of barrier-less conduction.

Dual brush process for selective surface modification in graphoepitaxy directed self-assembly

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Doise, Jan; Chan, Boon Teik; Hori, Masafumi; Gronheid, Roel

2017-07-01

Graphoepitaxy directed self-assembly is a potential low-cost solution for patterning via layers with pitches beyond the reach of a single optical lithographic exposure. In this process, selective control of the interfacial energy at the bottom and sidewall of the template is an important but challenging exercise. A dual brush process is implemented, in which two brushes with distinct end-groups are consecutively grafted to the prepattern to achieve fully independent modification of the bottom and sidewall surface of the template. A comprehensive study of hole pattern quality shows that using a dual brush process leads to a substantial improvement in terms of positional and dimensional variability across the process window. These findings will be useful to others who wish to manipulate polymer-surface interactions in directed self-assembly flows.

Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

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Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

2016-01-01

Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

Tuberculosis diagnosis and multidrug resistance testing by direct sputum culture in selective broth without decontamination or centrifugation.

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Grandjean, Louis; Martin, Laura; Gilman, Robert H; Valencia, Teresa; Herrera, Beatriz; Quino, Willi; Ramos, Eric; Rivero, Maribel; Montoya, Rosario; Escombe, A Roderick; Coleman, David; Mitchison, Denis; Evans, Carlton A

2008-07-01

Tuberculosis culture usually requires sputum decontamination and centrifugation to prevent cultures from being overgrown by contaminating bacteria and fungi. However, decontamination destroys many tuberculous bacilli, and centrifugation often is not possible in resource-poor settings. We therefore assessed the performance of Mycobacterium tuberculosis culture with unprocessed samples plated directly by using tuberculosis-selective media and compared this procedure to conventional culture using centrifuge decontamination. Quadruplicate aliquots of strain H37RV were cultured in 7H9 broth with and without selective antimicrobials and after centrifuge decontamination. The subsequent comparison was made with 715 sputum samples. Split paired sputum samples were cultured conventionally with centrifuge decontamination and by direct culture in tuberculosis-selective media containing antibiotics. Centrifuge decontamination reduced tuberculosis H37RV colonies by 78% (P laboratories this deficit may be outweighed by the ease of use.

Pareto-Optimal Model Selection via SPRINT-Race.

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Zhang, Tiantian; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

2018-02-01

In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of Pareto-optimal models that optimize by compromising more than one predefined objectives simultaneously. This paper introduces SPRINT-Race, the first multi-objective racing algorithm in a fixed-confidence setting, which is based on the sequential probability ratio with indifference zone test. SPRINT-Race addresses the problem of MOMS with multiple stochastic optimization objectives in the proper Pareto-optimality sense. In SPRINT-Race, a pairwise dominance or non-dominance relationship is statistically inferred via a non-parametric, ternary-decision, dual-sequential probability ratio test. The overall probability of falsely eliminating any Pareto-optimal models or mistakenly returning any clearly dominated models is strictly controlled by a sequential Holm's step-down family-wise error rate control method. As a fixed-confidence model selection algorithm, the objective of SPRINT-Race is to minimize the computational effort required to achieve a prescribed confidence level about the quality of the returned models. The performance of SPRINT-Race is first examined via an artificially constructed MOMS problem with known ground truth. Subsequently, SPRINT-Race is applied on two real-world applications: 1) hybrid recommender system design and 2) multi-criteria stock selection. The experimental results verify that SPRINT-Race is an effective and efficient tool for such MOMS problems. code of SPRINT-Race is available at https://github.com/watera427/SPRINT-Race.

Selecting ground-motion models developed for induced seismicity in geothermal areas

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Edwards, Benjamin; Douglas, John

2013-11-01

We present a case study of the ranking and weighting of ground-motion prediction equations (GMPEs) for seismic hazard assessment of enhanced geothermal systems (EGSs). The study region is Cooper Basin (Australia), where a hot-fractured-rock project was established in 2002. We test the applicability of 36 GMPEs based on stochastic simulations previously proposed for use at EGSs. Each GMPE has a set of corresponding model parameters describing stress drop, regional and local (near-surface) attenuation. To select suitable GMPEs for Cooper Basin from the full set, we applied two methods. In the first, seismograms recorded on the local monitoring network were spectrally analysed to determine characteristic stress and attenuation parameters. In a second approach, residual analysis using the log-likelihood (LLH) method was used to directly compare recorded and predicted short-period response spectral accelerations. The resulting ranking was consistent with the models selected based on spectral analysis, with the advantage that a transparent weighting approach was available using the LLH method. Region-specific estimates of variability were computed, with significantly lower values observed compared to previous studies of small earthquakes. This was consistent with the limited range of stress drops and attenuation observed from the spectral analysis.

On Optimal Input Design and Model Selection for Communication Channels

Energy Technology Data Exchange (ETDEWEB)

Li, Yanyan [ORNL; Djouadi, Seddik M [ORNL; Olama, Mohammed M [ORNL

2013-01-01

In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.

Selection Criteria in Regime Switching Conditional Volatility Models

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Thomas Chuffart

2015-05-01

Full Text Available A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and loss functions can lead to misspecification ; BIC sometimes indicates the wrong regime switching framework. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion.

Working covariance model selection for generalized estimating equations.

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Carey, Vincent J; Wang, You-Gan

2011-11-20

We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.

Applying Four Different Risk Models in Local Ore Selection

International Nuclear Information System (INIS)

Richmond, Andrew

2002-01-01

Given the uncertainty in grade at a mine location, a financially risk-averse decision-maker may prefer to incorporate this uncertainty into the ore selection process. A FORTRAN program risksel is presented to calculate local risk-adjusted optimal ore selections using a negative exponential utility function and three dominance models: mean-variance, mean-downside risk, and stochastic dominance. All four methods are demonstrated in a grade control environment. In the case study, optimal selections range with the magnitude of financial risk that a decision-maker is prepared to accept. Except for the stochastic dominance method, the risk models reassign material from higher cost to lower cost processing options as the aversion to financial risk increases. The stochastic dominance model usually was unable to determine the optimal local selection

On the selection of ordinary differential equation models with application to predator-prey dynamical models.

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Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2015-03-01

We consider model selection and estimation in a context where there are competing ordinary differential equation (ODE) models, and all the models are special cases of a "full" model. We propose a computationally inexpensive approach that employs statistical estimation of the full model, followed by a combination of a least squares approximation (LSA) and the adaptive Lasso. We show the resulting method, here called the LSA method, to be an (asymptotically) oracle model selection method. The finite sample performance of the proposed LSA method is investigated with Monte Carlo simulations, in which we examine the percentage of selecting true ODE models, the efficiency of the parameter estimation compared to simply using the full and true models, and coverage probabilities of the estimated confidence intervals for ODE parameters, all of which have satisfactory performances. Our method is also demonstrated by selecting the best predator-prey ODE to model a lynx and hare population dynamical system among some well-known and biologically interpretable ODE models. © 2014, The International Biometric Society.

Detecting directional selection in the presence of recent admixture in African-Americans.

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Lohmueller, Kirk E; Bustamante, Carlos D; Clark, Andrew G

2011-03-01

We investigate the performance of tests of neutrality in admixed populations using plausible demographic models for African-American history as well as resequencing data from African and African-American populations. The analysis of both simulated and human resequencing data suggests that recent admixture does not result in an excess of false-positive results for neutrality tests based on the frequency spectrum after accounting for the population growth in the parental African population. Furthermore, when simulating positive selection, Tajima's D, Fu and Li's D, and haplotype homozygosity have lower power to detect population-specific selection using individuals sampled from the admixed population than from the nonadmixed population. Fay and Wu's H test, however, has more power to detect selection using individuals from the admixed population than from the nonadmixed population, especially when the selective sweep ended long ago. Our results have implications for interpreting recent genome-wide scans for positive selection in human populations. © 2011 by the Genetics Society of America

Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

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Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

2015-01-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

On a Robust MaxEnt Process Regression Model with Sample-Selection

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Hea-Jung Kim

2018-04-01

Full Text Available In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt process regression model that assumes a MaxEnt prior distribution for its nonparametric regression function and finds that the MaxEnt process regression model includes the well-known Gaussian process regression (GPR model as a special case. Then, this special MaxEnt process regression model, i.e., the GPR model, is generalized to obtain a robust sample-selection Gaussian process regression (RSGPR model that deals with non-normal data in the sample selection. Various properties of the RSGPR model are established, including the stochastic representation, distributional hierarchy, and magnitude of the sample-selection bias. These properties are used in the paper to develop a hierarchical Bayesian methodology to estimate the model. This involves a simple and computationally feasible Markov chain Monte Carlo algorithm that avoids analytical or numerical derivatives of the log-likelihood function of the model. The performance of the RSGPR model in terms of the sample-selection bias correction, robustness to non-normality, and prediction, is demonstrated through results in simulations that attest to its good finite-sample performance.

Accounting for selection bias in species distribution models: An econometric approach on forested trees based on structural modeling

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Ay, Jean-Sauveur; Guillemot, Joannès; Martin-StPaul, Nicolas K.; Doyen, Luc; Leadley, Paul

2015-04-01

Species distribution models (SDMs) are widely used to study and predict the outcome of global change on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of application on forested trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8 km). We also compared the output of the SSDM with outputs of a classical SDM in term of bioclimatic response curves and potential distribution under current climate. According to the species and the spatial resolution of the calibration dataset, shapes of bioclimatic response curves the modelled species distribution maps differed markedly between the SSDM and classical SDMs. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents a crucial step to account for economic constraints on tree

Selective production of arenes via direct lignin upgrading over a niobium-based catalyst

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Shao, Yi; Xia, Qineng; Dong, Lin; Liu, Xiaohui; Han, Xue; Parker, Stewart F.; Cheng, Yongqiang; Daemen, Luke L.; Ramirez-Cuesta, Anibal J.; Yang, Sihai; Wang, Yanqin

2017-07-01

Lignin is the only large-volume renewable source of aromatic chemicals. Efficient depolymerization and deoxygenation of lignin while retaining the aromatic functionality are attractive but extremely challenging. Here we report the selective production of arenes via direct hydrodeoxygenation of organosolv lignin over a porous Ru/Nb2O5 catalyst that enabled the complete removal of the oxygen content from lignin. The conversion of birch lignin to monomer C7-C9 hydrocarbons is nearly quantitative based on its monomer content, with a total mass yield of 35.5 wt% and an exceptional arene selectivity of 71 wt%. Inelastic neutron scattering and DFT calculations confirm that the Nb2O5 support is catalytically unique compared with other traditional oxide supports, and the disassociation energy of Caromatic-OH bonds in phenolics is significantly reduced upon adsorption on Nb2O5, resulting in its distinct selectivity to arenes. This one-pot process provides a promising approach for improved lignin valorization with general applicability.

Directionality Theory and the Entropic Principle of Natural Selection

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Lloyd A. Demetrius

2014-10-01

Full Text Available Darwinian fitness describes the capacity of an organism to appropriate resources from the environment and to convert these resources into net-offspring production. Studies of competition between related types indicate that fitness is analytically described by entropy, a statistical measure which is positively correlated with population stability, and describes the number of accessible pathways of energy flow between the individuals in the population. Directionality theory is a mathematical model of the evolutionary process based on the concept evolutionary entropy as the measure of fitness. The theory predicts that the changes which occur as a population evolves from one non-equilibrium steady state to another are described by the following directionality principle–fundamental theorem of evolution: (a an increase in evolutionary entropy when resource composition is diverse, and resource abundance constant; (b a decrease in evolutionary entropy when resource composition is singular, and resource abundance variable. Evolutionary entropy characterizes the dynamics of energy flow between the individual elements in various classes of biological networks: (a where the units are individuals parameterized by age, and their age-specific fecundity and mortality; where the units are metabolites, and the transitions are the biochemical reactions that convert substrates to products; (c where the units are social groups, and the forces are the cooperative and competitive interactions between the individual groups. % This article reviews the analytical basis of the evolutionary entropic principle, and describes applications of directionality theory to the study of evolutionary dynamics in two biological systems; (i social networks–the evolution of cooperation; (ii metabolic networks–the evolution of body size. Statistical thermodynamics is a mathematical model of macroscopic behavior in inanimate matter based on entropy, a statistical measure which

Equilibrium and nonequilibrium attractors for a discrete, selection-migration model

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James F. Selgrade; James H. Roberds

2003-01-01

This study presents a discrete-time model for the effects of selection and immigration on the demographic and genetic compositions of a population. Under biologically reasonable conditions, it is shown that the model always has an equilibrium. Although equilibria for similar models without migration must have real eigenvalues, for this selection-migration model we...

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

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Ren, Huazhong; Liu, Rongyuan; Yan, Guangjian; Li, Zhao-Liang; Qin, Qiming; Liu, Qiang; Nerry, Françoise

2015-04-06

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

A Gambler's Model of Natural Selection.

Science.gov (United States)

Nolan, Michael J.; Ostrovsky, David S.

1996-01-01

Presents an activity that highlights the mechanism and power of natural selection. Allows students to think in terms of modeling a biological process and instills an appreciation for a mathematical approach to biological problems. (JRH)

Subgenomic Diversity Patterns Caused by Directional Selection in Bread Wheat Gene Pools

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Kai Voss-Fels

2015-07-01

Full Text Available Genetic diversity represents the fundamental key to breeding success, providing the basis for breeders to select varieties with constantly improving yield performance. On the other hand, strong selection during domestication and breeding have eliminated considerable genetic diversity in the breeding pools of major crops, causing erosion of genetic potential for adaptation to emerging challenges like climate change. High-throughput genomic technologies can address this dilemma by providing detailed knowledge to characterize and replenish genetic diversity in breeding programs. In hexaploid bread wheat ( L., the staple food for 35% of the world’s population, bottlenecks during allopolyploidisation followed by strong artificial selection have considerably narrowed diversity to the extent that yields in many regions appear to be unexpectedly stagnating. In this study, we used a 90,000 single nucleotide polymorphism (SNP wheat genotyping array to assay high-frequency, polymorphic SNP markers in 460 accessions representing different phenological diversity groups from Asian, Australian, European, and North American bread wheat breeding materials. Detailed analysis of subgroup diversity at the chromosome and subgenome scale revealed highly distinct patterns of conserved linkage disequilibrium between different gene pools. The data enable identification of genome regions in most need of rejuvenation with novel diversity and provide a high-resolution molecular basis for genomic-assisted introgression of new variation into chromosome segments surrounding directionally selected metaloci conferring important adaptation and quality traits.

Evaluation and comparison of alternative fleet-level selective maintenance models

International Nuclear Information System (INIS)

Schneider, Kellie; Richard Cassady, C.

2015-01-01

Fleet-level selective maintenance refers to the process of identifying the subset of maintenance actions to perform on a fleet of repairable systems when the maintenance resources allocated to the fleet are insufficient for performing all desirable maintenance actions. The original fleet-level selective maintenance model is designed to maximize the probability that all missions in a future set are completed successfully. We extend this model in several ways. First, we consider a cost-based optimization model and show that a special case of this model maximizes the expected value of the number of successful missions in the future set. We also consider the situation in which one or more of the future missions may be canceled. These models and the original fleet-level selective maintenance optimization models are nonlinear. Therefore, we also consider an alternative model in which the objective function can be linearized. We show that the alternative model is a good approximation to the other models. - Highlights: • Investigate nonlinear fleet-level selective maintenance optimization models. • A cost based model is used to maximize the expected number of successful missions. • Another model is allowed to cancel missions if reliability is sufficiently low. • An alternative model has an objective function that can be linearized. • We show that the alternative model is a good approximation to the other models

Toward the development of the direct and selective detection of nitrates by a bioinspired Mo-Cu system.

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Marom, Hanit; Popowski, Yanay; Antonov, Svetlana; Gozin, Michael

2011-10-21

The development of a new platform for the direct and selective detection of nitrates is described. Two thioether-based chemosensors and the corresponding sulfoxides and sulfones were prepared, and their photophysical properties were evaluated. Upon selective sulfoxidation of these thioethers with nitrates via an oxygen-transfer reaction promoted by a bioinspired Mo-Cu system, significant fluorescence shifts were measured. A selective response of these systems, discriminating between nitrate salts and H(2)O(2), was also shown. © 2011 American Chemical Society

Market study for direct utilization of geothermal resources by selected sectors of economy

Energy Technology Data Exchange (ETDEWEB)

1980-08-01

A comprehensive analysis is presented of industrial markets potential for direct use of geothermal energy by a total of six industry sectors: food and kindred products; tobacco manufactures; textile mill products; lumber and wood products (except furniture); chemicals and allied products; and leather and leather products. A brief statement is presented regarding sectors of the economy and major manufacturing processes which can readily utilize direct geothermal energy. Previous studies on plant location determinants are summarized and appropriate empirical data provided on plant locations. Location determinants and potential for direct use of geothermal resources are presented. The data was gathered through interviews with 30 senior executives in the six sectors of economy selected for study. Probable locations of plants in geothermal resource areas and recommendations for geothermal resource marketing are presented. Appendix A presents factors which impact on industry location decisions. Appendix B presents industry executives interviewed during the course of this study. (MHR)

Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model

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Jiping Yang

2017-09-01

Full Text Available Yang and Qiu proposed and then recently improved an expected utility-entropy (EU-E measure of risk and decision model. When segregation holds, Luce et al. derived an expected utility term, plus a constant multiplies the Shannon entropy as the representation of risky choices, further demonstrating the reasonability of the EU-E decision model. In this paper, we apply the EU-E decision model to selecting the set of stocks to be included in the portfolios. We first select 7 and 10 stocks from the 30 component stocks of Dow Jones Industrial Average index, and then derive and compare the efficient portfolios in the mean-variance framework. The conclusions imply that efficient portfolios composed of 7(10 stocks selected using the EU-E model with intermediate intervals of the tradeoff coefficients are more efficient than that composed of the sets of stocks selected using the expected utility model. Furthermore, the efficient portfolio of 7(10 stocks selected by the EU-E decision model have almost the same efficient frontier as that of the sample of all stocks. This suggests the necessity of incorporating both the expected utility and Shannon entropy together when taking risky decisions, further demonstrating the importance of Shannon entropy as the measure of uncertainty, as well as the applicability of the EU-E model as a decision-making model.

Markov Chain model for the stochastic behaviors of wind-direction data

International Nuclear Information System (INIS)

Masseran, Nurulkamal

2015-01-01

Highlights: • I develop a Markov chain model to describe about the stochastic and probabilistic behaviors of wind direction data. • I describe some of the theoretical arguments regarding the Markov chain model in term of wind direction data. • I suggest a limiting probabilities approach to determine a dominant directions of wind blow. - Abstract: Analyzing the behaviors of wind direction can complement knowledge concerning wind speed and help researchers draw conclusions regarding wind energy potential. Knowledge of the wind’s direction enables the wind turbine to be positioned in such a way as to maximize the total amount of captured energy and optimize the wind farm’s performance. In this paper, first-order and higher-order Markov chain models are proposed to describe the probabilistic behaviors of wind-direction data. A case study is conducted using data from Mersing, Malaysia. The wind-direction data are classified according to an eight-state Markov chain based on natural geographical directions. The model’s parameters are estimated using the maximum likelihood method and the linear programming formulation. Several theoretical arguments regarding the model are also discussed. Finally, limiting probabilities are used to determine a long-run proportion of the wind directions generated. The results explain the dominant direction for Mersing’s wind in terms of probability metrics

Short-Run Asset Selection using a Logistic Model

Directory of Open Access Journals (Sweden)

Walter Gonçalves Junior

2011-06-01

Full Text Available Investors constantly look for significant predictors and accurate models to forecast future results, whose occasional efficacy end up being neutralized by market efficiency. Regardless, such predictors are widely used for seeking better (and more unique perceptions. This paper aims to investigate to what extent some of the most notorious indicators have discriminatory power to select stocks, and if it is feasible with such variables to build models that could anticipate those with good performance. In order to do that, logistical regressions were conducted with stocks traded at Bovespa using the selected indicators as explanatory variables. Investigated in this study were the outputs of Bovespa Index, liquidity, the Sharpe Ratio, ROE, MB, size and age evidenced to be significant predictors. Also examined were half-year, logistical models, which were adjusted in order to check the potential acceptable discriminatory power for the asset selection.

Integrated model for supplier selection and performance evaluation

Directory of Open Access Journals (Sweden)

Borges de Araújo, Maria Creuza

2015-08-01

Full Text Available This paper puts forward a model for selecting suppliers and evaluating the performance of those already working with a company. A simulation was conducted in a food industry. This sector has high significance in the economy of Brazil. The model enables the phases of selecting and evaluating suppliers to be integrated. This is important so that a company can have partnerships with suppliers who are able to meet their needs. Additionally, a group method is used to enable managers who will be affected by this decision to take part in the selection stage. Finally, the classes resulting from the performance evaluation are shown to support the contractor in choosing the most appropriate relationship with its suppliers.

Dual platinum and pyrrolidine catalysis in the direct alkylation of allylic alcohols: selective synthesis of monoallylation products.

Science.gov (United States)

Shibuya, Ryozo; Lin, Lu; Nakahara, Yasuhito; Mashima, Kazushi; Ohshima, Takashi

2014-04-22

A dual platinum- and pyrrolidine-catalyzed direct allylic alkylation of allylic alcohols with various active methylene compounds to produce products with high monoallylation selectivity was developed. The use of pyrrolidine and acetic acid was essential, not only for preventing undesirable side reactions, but also for obtaining high monoallylation selectivity. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Natural selection promotes antigenic evolvability.

Science.gov (United States)

Graves, Christopher J; Ros, Vera I D; Stevenson, Brian; Sniegowski, Paul D; Brisson, Dustin

2013-01-01

The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.

Natural selection promotes antigenic evolvability.

Directory of Open Access Journals (Sweden)

Christopher J Graves

Full Text Available The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish

Developmental memory capacity resources of typical children retrieving picture communication symbols using direct selection and visual linear scanning with fixed communication displays.

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Wagner, Barry T; Jackson, Heather M

2006-02-01

This study examined the cognitive demands of 2 selection techniques in augmentative and alternative communication (AAC), direct selection, and visual linear scanning, by determining the memory retrieval abilities of typically developing children when presented with fixed communication displays. One hundred twenty typical children from kindergarten, 1st, and 3rd grades were randomly assigned to either a direct selection or visual linear scanning group. Memory retrieval was assessed through word span using Picture Communication Symbols (PCSs). Participants were presented various numbers and arrays of PCSs and asked to retrieve them by placing identical graphic symbols on fixed communication displays with grid layouts. The results revealed that participants were able to retrieve more PCSs during direct selection than scanning. Additionally, 3rd-grade children retrieved more PCSs than kindergarten and 1st-grade children. An analysis on the type of errors during retrieval indicated that children were more successful at retrieving the correct PCSs than the designated location of those symbols on fixed communication displays. AAC practitioners should consider using direct selection over scanning whenever possible and account for anticipatory monitoring and pulses when scanning is used in the service delivery of children with little or no functional speech. Also, researchers should continue to investigate AAC selection techniques in relationship to working memory resources.

Genomic signatures of local directional selection in a high gene flow marine organism, the Atlantic cod (Gadus morhua)

DEFF Research Database (Denmark)

Eg Nielsen, Einar; Hansen, Jakob Hemmer; Poulsen, Nina Aagaard

2009-01-01

-associated single nucleotide polymorphisms (SNPs) for evidence of selection in local populations of Atlantic cod (Gadus morhua L.) across the species distribution. Results: Our global genome scan analysis identified eight outlier gene loci with very high statistical support, likely to be subject to directional...... selection in local demes, or closely linked to loci under selection. Likewise, on a regional south/north transect of central and eastern Atlantic populations, seven loci displayed strongly elevated levels of genetic differentiation. Selection patterns among populations appeared to be relatively widespread...

Model Selection in Historical Research Using Approximate Bayesian Computation

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Rubio-Campillo, Xavier

2016-01-01

Formal Models and History Computational models are increasingly being used to study historical dynamics. This new trend, which could be named Model-Based History, makes use of recently published datasets and innovative quantitative methods to improve our understanding of past societies based on their written sources. The extensive use of formal models allows historians to re-evaluate hypotheses formulated decades ago and still subject to debate due to the lack of an adequate quantitative framework. The initiative has the potential to transform the discipline if it solves the challenges posed by the study of historical dynamics. These difficulties are based on the complexities of modelling social interaction, and the methodological issues raised by the evaluation of formal models against data with low sample size, high variance and strong fragmentation. Case Study This work examines an alternate approach to this evaluation based on a Bayesian-inspired model selection method. The validity of the classical Lanchester’s laws of combat is examined against a dataset comprising over a thousand battles spanning 300 years. Four variations of the basic equations are discussed, including the three most common formulations (linear, squared, and logarithmic) and a new variant introducing fatigue. Approximate Bayesian Computation is then used to infer both parameter values and model selection via Bayes Factors. Impact Results indicate decisive evidence favouring the new fatigue model. The interpretation of both parameter estimations and model selection provides new insights into the factors guiding the evolution of warfare. At a methodological level, the case study shows how model selection methods can be used to guide historical research through the comparison between existing hypotheses and empirical evidence. PMID:26730953

A meta-selective C-H borylation directed by a secondary interaction between ligand and substrate

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Kuninobu, Yoichiro; Ida, Haruka; Nishi, Mitsumi; Kanai, Motomu

2015-09-01

Regioselective C-H bond transformations are potentially the most efficient method for the synthesis of organic molecules. However, the presence of many C-H bonds in organic molecules and the high activation barrier for these reactions make these transformations difficult. Directing groups in the reaction substrate are often used to control regioselectivity, which has been especially successful for the ortho-selective functionalization of aromatic substrates. Here, we describe an iridium-catalysed meta-selective C-H borylation of aromatic compounds using a newly designed catalytic system. The bipyridine-derived ligand that binds iridium contains a pendant urea moiety. A secondary interaction between this urea and a hydrogen-bond acceptor in the substrate places the iridium in close proximity to the meta-C-H bond and thus controls the regioselectivity. 1H NMR studies and control experiments support the participation of hydrogen bonds in inducing regioselectivity. Reversible direction of the catalyst through hydrogen bonds is a versatile concept for regioselective C-H transformations.

Estimating directional epistasis

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Le Rouzic, Arnaud

2014-01-01

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

Measures and limits of models of fixation selection.

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Niklas Wilming

Full Text Available Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly different properties, which makes a comparison difficult. We make three main contributions to this line of research: First we argue for a set of desirable properties, review commonly used measures, and conclude that no single measure unites all desirable properties. However the area under the ROC curve (a classification measure and the KL-divergence (a distance measure of probability distributions combine many desirable properties and allow a meaningful comparison of critical model performance. We give an analytical proof of the linearity of the ROC measure with respect to averaging over subjects and demonstrate an appropriate correction of entropy-based measures like KL-divergence for small sample sizes in the context of eye-tracking data. Second, we provide a lower bound and an upper bound of these measures, based on image-independent properties of fixation data and between subject consistency respectively. Based on these bounds it is possible to give a reference frame to judge the predictive power of a model of fixation selection. We provide open-source python code to compute the reference frame. Third, we show that the upper, between subject consistency bound holds only for models that predict averages of subject populations. Departing from this we show that incorporating subject-specific viewing behavior can generate predictions which surpass that upper bound. Taken together, these findings lay out the required information that allow a well-founded judgment of the quality of any model of fixation selection and should therefore be reported when a new model is introduced.

Direct modeling for computational fluid dynamics

Science.gov (United States)

Xu, Kun

2015-06-01

All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct

Beyond the standard model in many directions

Energy Technology Data Exchange (ETDEWEB)

Chris Quigg

2004-04-28

These four lectures constitute a gentle introduction to what may lie beyond the standard model of quarks and leptons interacting through SU(3){sub c} {direct_product} SU(2){sub L} {direct_product} U(1){sub Y} gauge bosons, prepared for an audience of graduate students in experimental particle physics. In the first lecture, I introduce a novel graphical representation of the particles and interactions, the double simplex, to elicit questions that motivate our interest in physics beyond the standard model, without recourse to equations and formalism. Lecture 2 is devoted to a short review of the current status of the standard model, especially the electroweak theory, which serves as the point of departure for our explorations. The third lecture is concerned with unified theories of the strong, weak, and electromagnetic interactions. In the fourth lecture, I survey some attempts to extend and complete the electroweak theory, emphasizing some of the promise and challenges of supersymmetry. A short concluding section looks forward.

Selected Tether Applications Cost Model

Science.gov (United States)

Keeley, Michael G.

1988-01-01

Diverse cost-estimating techniques and data combined into single program. Selected Tether Applications Cost Model (STACOM 1.0) is interactive accounting software tool providing means for combining several independent cost-estimating programs into fully-integrated mathematical model capable of assessing costs, analyzing benefits, providing file-handling utilities, and putting out information in text and graphical forms to screen, printer, or plotter. Program based on Lotus 1-2-3, version 2.0. Developed to provide clear, concise traceability and visibility into methodology and rationale for estimating costs and benefits of operations of Space Station tether deployer system.

Modeling the effect of selection history on pop-out visual search.

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Yuan-Chi Tseng

Full Text Available While attentional effects in visual selection tasks have traditionally been assigned "top-down" or "bottom-up" origins, more recently it has been proposed that there are three major factors affecting visual selection: (1 physical salience, (2 current goals and (3 selection history. Here, we look further into selection history by investigating Priming of Pop-out (POP and the Distractor Preview Effect (DPE, two inter-trial effects that demonstrate the influence of recent history on visual search performance. Using the Ratcliff diffusion model, we model observed saccadic selections from an oddball search experiment that included a mix of both POP and DPE conditions. We find that the Ratcliff diffusion model can effectively model the manner in which selection history affects current attentional control in visual inter-trial effects. The model evidence shows that bias regarding the current trial's most likely target color is the most critical parameter underlying the effect of selection history. Our results are consistent with the view that the 3-item color-oddball task used for POP and DPE experiments is best understood as an attentional decision making task.

Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

DEFF Research Database (Denmark)

Bork, Lasse; Møller, Stig Vinther

2015-01-01

We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

Ensembling Variable Selectors by Stability Selection for the Cox Model

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Qing-Yan Yin

2017-01-01

Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

Skewed factor models using selection mechanisms

KAUST Repository

Kim, Hyoung-Moon

2015-12-21

Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

Skewed factor models using selection mechanisms

KAUST Repository

Kim, Hyoung-Moon; Maadooliat, Mehdi; Arellano-Valle, Reinaldo B.; Genton, Marc G.

2015-01-01

Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

Selective loss of bi-directional synaptic plasticity in the direct and indirect striatal output pathways accompanies generation of parkinsonism and l-DOPA induced dyskinesia in mouse models.

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Thiele, Sherri L; Chen, Betty; Lo, Charlotte; Gertler, Tracey S; Warre, Ruth; Surmeier, James D; Brotchie, Jonathan M; Nash, Joanne E

2014-11-01

Parkinsonian symptoms arise due to over-activity of the indirect striatal output pathway, and under-activity of the direct striatal output pathway. l-DOPA-induced dyskinesia (LID) is caused when the opposite circuitry problems are established, with the indirect pathway becoming underactive, and the direct pathway becoming over-active. Here, we define synaptic plasticity abnormalities in these pathways associated with parkinsonism, symptomatic benefits of l-DOPA, and LID. We applied spike-timing dependent plasticity protocols to cortico-striatal synapses in slices from 6-OHDA-lesioned mouse models of parkinsonism and LID, generated in BAC transgenic mice with eGFP targeting the direct or indirect output pathways, with and without l-DOPA present. In naïve mice, bidirectional synaptic plasticity, i.e. LTP and LTD, was induced, resulting in an EPSP amplitude change of approximately 50% in each direction in both striatal output pathways, as shown previously. In parkinsonism and dyskinesia, both pathways exhibited unidirectional plasticity, irrespective of stimulation paradigm. In parkinsonian animals, the indirect pathway only exhibited LTP (LTP protocol: 143.5±14.6%; LTD protocol 177.7±22.3% of baseline), whereas the direct pathway only showed LTD (LTP protocol: 74.3±4.0% and LTD protocol: 63.3±8.7%). A symptomatic dose of l-DOPA restored bidirectional plasticity on both pathways to levels comparable to naïve animals (Indirect pathway: LTP protocol: 124.4±22.0% and LTD protocol: 52.1±18.5% of baseline. Direct pathway: LTP protocol: 140.7±7.3% and LTD protocol: 58.4±6.0% of baseline). In dyskinesia, in the presence of l-DOPA, the indirect pathway exhibited only LTD (LTP protocol: 68.9±21.3% and LTD protocol 52.0±14.2% of baseline), whereas in the direct pathway, only LTP could be induced (LTP protocol: 156.6±13.2% and LTD protocol 166.7±15.8% of baseline). We conclude that normal motor control requires bidirectional plasticity of both striatal outputs

New Directions in Modeling the Lighting Systems

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P. Fiala

2004-12-01

Full Text Available This paper presents information about new directions in the modelingof lighting systems, and an overview of methods for the modeling oflighting systems. The new R-FEM method is described, which is acombination of the Radiosity method and the Finite Elements Method. Thepaper contains modeling results and their verification by experimentalmeasurements and by the Matlab simulation for this R-FEM method.

A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents.

Science.gov (United States)

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control-enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates.

National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models

Science.gov (United States)

Hogan, Daniel R; Salomon, Joshua A; Canning, David; Hammitt, James K; Zaslavsky, Alan M; Bärnighausen, Till

2012-01-01

Objectives Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors. Methods For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals. Results Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5. Conclusions Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence. PMID:23172342

Selective Cooperation in Early Childhood - How to Choose Models and Partners.

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Jonas Hermes

Full Text Available Cooperation is essential for human society, and children engage in cooperation from early on. It is unclear, however, how children select their partners for cooperation. We know that children choose selectively whom to learn from (e.g. preferring reliable over unreliable models on a rational basis. The present study investigated whether children (and adults also choose their cooperative partners selectively and what model characteristics they regard as important for cooperative partners and for informants about novel words. Three- and four-year-old children (N = 64 and adults (N = 14 saw contrasting pairs of models differing either in physical strength or in accuracy (in labeling known objects. Participants then performed different tasks (cooperative problem solving and word learning requiring the choice of a partner or informant. Both children and adults chose their cooperative partners selectively. Moreover they showed the same pattern of selective model choice, regarding a wide range of model characteristics as important for cooperation (preferring both the strong and the accurate model for a strength-requiring cooperation tasks, but only prior knowledge as important for word learning (preferring the knowledgeable but not the strong model for word learning tasks. Young children's selective model choice thus reveals an early rational competence: They infer characteristics from past behavior and flexibly consider what characteristics are relevant for certain tasks.

The directed mutation controversy and neo-Darwinism.

Science.gov (United States)

Lenski, R E; Mittler, J E

1993-01-08

According to neo-Darwinian theory, random mutation produces genetic differences among organisms whereas natural selection tends to increase the frequency of advantageous alleles. However, several recent papers claim that certain mutations in bacteria and yeast occur at much higher rates specifically when the mutant phenotypes are advantageous. Various molecular models have been proposed that might explain these directed mutations, but the models have not been confirmed. Critics contend that studies purporting to demonstrate directed mutation lack certain controls and fail to account adequately for population dynamics. Further experiments that address these criticisms do not support the existence of directed mutations.

Penalized variable selection in competing risks regression.

Science.gov (United States)

Fu, Zhixuan; Parikh, Chirag R; Zhou, Bingqing

2017-07-01

Penalized variable selection methods have been extensively studied for standard time-to-event data. Such methods cannot be directly applied when subjects are at risk of multiple mutually exclusive events, known as competing risks. The proportional subdistribution hazard (PSH) model proposed by Fine and Gray (J Am Stat Assoc 94:496-509, 1999) has become a popular semi-parametric model for time-to-event data with competing risks. It allows for direct assessment of covariate effects on the cumulative incidence function. In this paper, we propose a general penalized variable selection strategy that simultaneously handles variable selection and parameter estimation in the PSH model. We rigorously establish the asymptotic properties of the proposed penalized estimators and modify the coordinate descent algorithm for implementation. Simulation studies are conducted to demonstrate the good performance of the proposed method. Data from deceased donor kidney transplants from the United Network of Organ Sharing illustrate the utility of the proposed method.

Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

Science.gov (United States)

Wang, Rongrong; Qi, Liang; Xie, Xiaofeng; Ding, Qingqing; Li, Chunwen; Ma, ChenChi M.

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system.

Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Rongrong; Li, Chunwen [Department of Automation, Tsinghua University, Beijing 100084 (China); Qi, Liang; Xie, Xiaofeng [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China); Ding, Qingqing [Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China); Ma, ChenChi M. [National Tsing Hua University, Hsinchu 300 (China)

2008-12-01

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system. (author)

Contrasting Patterns of Genomic Diversity Reveal Accelerated Genetic Drift but Reduced Directional Selection on X-Chromosome in Wild and Domestic Sheep Species.

Science.gov (United States)

Chen, Ze-Hui; Zhang, Min; Lv, Feng-Hua; Ren, Xue; Li, Wen-Rong; Liu, Ming-Jun; Nam, Kiwoong; Bruford, Michael W; Li, Meng-Hua

2018-04-01

Analyses of genomic diversity along the X chromosome and of its correlation with autosomal diversity can facilitate understanding of evolutionary forces in shaping sex-linked genomic architecture. Strong selective sweeps and accelerated genetic drift on the X-chromosome have been inferred in primates and other model species, but no such insight has yet been gained in domestic animals compared with their wild relatives. Here, we analyzed X-chromosome variability in a large ovine data set, including a BeadChip array for 943 ewes from the world's sheep populations and 110 whole genomes of wild and domestic sheep. Analyzing whole-genome sequences, we observed a substantially reduced X-to-autosome diversity ratio (∼0.6) compared with the value expected under a neutral model (0.75). In particular, one large X-linked segment (43.05-79.25 Mb) was found to show extremely low diversity, most likely due to a high density of coding genes, featuring highly conserved regions. In general, we observed higher nucleotide diversity on the autosomes, but a flat diversity gradient in X-linked segments, as a function of increasing distance from the nearest genes, leading to a decreased X: autosome (X/A) diversity ratio and contrasting to the positive correlation detected in primates and other model animals. Our evidence suggests that accelerated genetic drift but reduced directional selection on X chromosome, as well as sex-biased demographic events, explain low X-chromosome diversity in sheep species. The distinct patterns of X-linked and X/A diversity we observed between Middle Eastern and non-Middle Eastern sheep populations can be explained by multiple migrations, selection, and admixture during the domestic sheep's recent postdomestication demographic expansion, coupled with natural selection for adaptation to new environments. In addition, we identify important novel genes involved in abnormal behavioral phenotypes, metabolism, and immunity, under selection on the sheep X-chromosome.

Direct numerical simulation and modeling of turbulent natural convection in a vertical differentially heated slot; Simulation numerique directe et modelisation de la convection naturelle turbulente dans un canal differentiellement chauffe

Energy Technology Data Exchange (ETDEWEB)

Boudjemadi, R.

1996-03-01

The main objectives of this thesis are the direct numerical simulation of natural convection in a vertical differentially heated slot and the improvements of second-order turbulence modelling. A three-dimensional direct numerical simulation code has been developed in order to gain a better understanding of turbulence properties in natural convection flows. This code has been validated in several physical configurations: non-stratified natural convection flows (conduction solution), stratified natural convection flows (double boundary layer solution), transitional and turbulent Poiseuille flows. For the conduction solution, the turbulent regime was reached at a Rayleigh number of 1*10{sup 5} and 5.4*10{sup 5}. A detailed analysis of these results has revealed the principal qualities of the available models but has also pointed our their shortcomings. This data base has been used in order to improve the triple correlations transport models and to select the turbulent time scales suitable for such flows. (author). 122 refs., figs., tabs., 4 appends.

A genetically optimized kinetic model for ethanol electro-oxidation on Pt-based binary catalysts used in direct ethanol fuel cells

Science.gov (United States)

Sánchez-Monreal, Juan; García-Salaberri, Pablo A.; Vera, Marcos

2017-09-01

A one-dimensional model is proposed for the anode of a liquid-feed direct ethanol fuel cell. The complex kinetics of the ethanol electro-oxidation reaction is described using a multi-step reaction mechanism that considers free and adsorbed intermediate species on Pt-based binary catalysts. The adsorbed species are modeled using coverage factors to account for the blockage of the active reaction sites on the catalyst surface. The reaction rates are described by Butler-Volmer equations that are coupled to a one-dimensional mass transport model, which incorporates the effect of ethanol and acetaldehyde crossover. The proposed kinetic model circumvents the acetaldehyde bottleneck effect observed in previous studies by incorporating CH3CHOHads among the adsorbed intermediates. A multi-objetive genetic algorithm is used to determine the reaction constants using anode polarization and product selectivity data obtained from the literature. By adjusting the reaction constants using the methodology developed here, different catalyst layers could be modeled and their selectivities could be successfully reproduced.

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

Science.gov (United States)

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models.

Science.gov (United States)

Kranstauber, Bart; Safi, Kamran; Bartumeus, Frederic

2014-01-01

In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion. Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk. We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the "move" package for R.

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Gulnaz Ahmed

2017-02-01

Full Text Available The longer network lifetime of Wireless Sensor Networks (WSNs is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED clustering, Artificial Bee Colony (ABC, Zone Based Routing (ZBR, and Centralized Energy Efficient Clustering (CEEC using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput.

Variable selection for mixture and promotion time cure rate models.

Science.gov (United States)

Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

2016-11-16

Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

Model structure selection in convolutive mixtures

DEFF Research Database (Denmark)

Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

2006-01-01

The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....

A Direct Adaptive Control Approach in the Presence of Model Mismatch

Science.gov (United States)

Joshi, Suresh M.; Tao, Gang; Khong, Thuan

2009-01-01

This paper considers the problem of direct model reference adaptive control when the plant-model matching conditions are violated due to abnormal changes in the plant or incorrect knowledge of the plant's mathematical structure. The approach consists of direct adaptation of state feedback gains for state tracking, and simultaneous estimation of the plant-model mismatch. Because of the mismatch, the plant can no longer track the state of the original reference model, but may be able to track a new reference model that still provides satisfactory performance. The reference model is updated if the estimated plant-model mismatch exceeds a bound that is determined via robust stability and/or performance criteria. The resulting controller is a hybrid direct-indirect adaptive controller that offers asymptotic state tracking in the presence of plant-model mismatch as well as parameter deviations.

Expert System Model for Educational Personnel Selection

Directory of Open Access Journals (Sweden)

Héctor A. Tabares-Ospina

2013-06-01

Full Text Available The staff selection is a difficult task due to the subjectivity that the evaluation means. This process can be complemented using a system to support decision. This paper presents the implementation of an expert system to systematize the selection process of professors. The management of software development is divided into 4 parts: requirements, design, implementation and commissioning. The proposed system models a specific knowledge through relationships between variables evidence and objective.

Diversified models for portfolio selection based on uncertain semivariance

Science.gov (United States)

Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini

2017-02-01

Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.

Comparing consumer-directed and agency models for providing supportive services at home.

Science.gov (United States)

Benjamin, A E; Matthias, R; Franke, T M

2000-04-01

To examine the service experiences and outcomes of low-income Medicaid beneficiaries with disabilities under two different models for organizing home-based personal assistance services: agency-directed and consumer-directed. A survey of a random sample of 1,095 clients, age 18 and over, who receive services in California's In-Home Supportive Services (IHSS) program funded primarily by Medicaid. Other data were obtained from the California Management and Payrolling System (CMIPS). The sample was stratified by service model (agency-directed or consumer-directed), client age (over or under age 65), and severity. Data were collected on client demographics, condition/functional status, and supportive service experience. Outcome measures were developed in three areas: safety, unmet need, and service satisfaction. Factor analysis was used to reduce multiple outcome measures to nine dimensions. Multiple regression analysis was used to assess the effect of service model on each outcome dimension, taking into account the client-provider relationship, client demographics, and case mix. Recipients of IHSS services as of mid-1996 were interviewed by telephone. The survey was conducted in late 1996 and early 1997. On various outcomes, recipients in the consumer-directed model report more positive outcomes than those in the agency model, or they report no difference. Statistically significant differences emerge on recipient safety, unmet needs, and service satisfaction. A family member present as a paid provider is also associated with more positive reported outcomes within the consumer-directed model, but model differences persist even when this is taken into account. Although both models have strengths and weaknesses, from a recipient perspective the consumer-directed model is associated with more positive outcomes. Although health professionals have expressed concerns about the capacity of consumer direction to assure quality, particularly with respect to safety, meeting unmet

Selection on skewed characters and the paradox of stasis.

Science.gov (United States)

Bonamour, Suzanne; Teplitsky, Céline; Charmantier, Anne; Crochet, Pierre-André; Chevin, Luis-Miguel

2017-11-01

Observed phenotypic responses to selection in the wild often differ from predictions based on measurements of selection and genetic variance. An overlooked hypothesis to explain this paradox of stasis is that a skewed phenotypic distribution affects natural selection and evolution. We show through mathematical modeling that, when a trait selected for an optimum phenotype has a skewed distribution, directional selection is detected even at evolutionary equilibrium, where it causes no change in the mean phenotype. When environmental effects are skewed, Lande and Arnold's (1983) directional gradient is in the direction opposite to the skew. In contrast, skewed breeding values can displace the mean phenotype from the optimum, causing directional selection in the direction of the skew. These effects can be partitioned out using alternative selection estimates based on average derivatives of individual relative fitness, or additive genetic covariances between relative fitness and trait (Robertson-Price identity). We assess the validity of these predictions using simulations of selection estimation under moderate sample sizes. Ecologically relevant traits may commonly have skewed distributions, as we here exemplify with avian laying date - repeatedly described as more evolutionarily stable than expected - so this skewness should be accounted for when investigating evolutionary dynamics in the wild. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Behavioral optimization models for multicriteria portfolio selection

Directory of Open Access Journals (Sweden)

Mehlawat Mukesh Kumar

2013-01-01

Full Text Available In this paper, behavioral construct of suitability is used to develop a multicriteria decision making framework for portfolio selection. To achieve this purpose, we rely on multiple methodologies. Analytical hierarchy process technique is used to model the suitability considerations with a view to obtaining the suitability performance score in respect of each asset. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor's rating on the financial criteria. Two optimization models are developed for optimal asset allocation considering simultaneously financial and suitability criteria. An empirical study is conducted on randomly selected assets from National Stock Exchange, Mumbai, India to demonstrate the effectiveness of the proposed methodology.

Silent reading of direct versus indirect speech activates voice-selective areas in the auditory cortex.

Science.gov (United States)

Yao, Bo; Belin, Pascal; Scheepers, Christoph

2011-10-01

In human communication, direct speech (e.g., Mary said: "I'm hungry") is perceived to be more vivid than indirect speech (e.g., Mary said [that] she was hungry). However, for silent reading, the representational consequences of this distinction are still unclear. Although many of us share the intuition of an "inner voice," particularly during silent reading of direct speech statements in text, there has been little direct empirical confirmation of this experience so far. Combining fMRI with eye tracking in human volunteers, we show that silent reading of direct versus indirect speech engenders differential brain activation in voice-selective areas of the auditory cortex. This suggests that readers are indeed more likely to engage in perceptual simulations (or spontaneous imagery) of the reported speaker's voice when reading direct speech as opposed to meaning-equivalent indirect speech statements as part of a more vivid representation of the former. Our results may be interpreted in line with embodied cognition and form a starting point for more sophisticated interdisciplinary research on the nature of auditory mental simulation during reading.

Fisher-Wright model with deterministic seed bank and selection.

Science.gov (United States)

Koopmann, Bendix; Müller, Johannes; Tellier, Aurélien; Živković, Daniel

2017-04-01

Seed banks are common characteristics to many plant species, which allow storage of genetic diversity in the soil as dormant seeds for various periods of time. We investigate an above-ground population following a Fisher-Wright model with selection coupled with a deterministic seed bank assuming the length of the seed bank is kept constant and the number of seeds is large. To assess the combined impact of seed banks and selection on genetic diversity, we derive a general diffusion model. The applied techniques outline a path of approximating a stochastic delay differential equation by an appropriately rescaled stochastic differential equation. We compute the equilibrium solution of the site-frequency spectrum and derive the times to fixation of an allele with and without selection. Finally, it is demonstrated that seed banks enhance the effect of selection onto the site-frequency spectrum while slowing down the time until the mutation-selection equilibrium is reached. Copyright © 2016 Elsevier Inc. All rights reserved.

A Model of Direct Gauge Mediation of Supersymmetry Breaking

International Nuclear Information System (INIS)

Murayama, H.

1997-01-01

We present the first phenomenologically viable model of gauge meditation of supersymmetry breaking without a messenger sector or gauge singlet fields. The standard model gauge groups couple directly to the sector which breaks supersymmetry dynamically. Despite the direct coupling, it can preserve perturbative gauge unification thanks to the inverted hierarchy mechanism. There is no dangerous negative contribution to m 2 q , m 2 l due to two-loop renormalization group equation. The potentially nonuniversal supergravity contribution to m 2 q and m 2 l can be suppressed enough. The model is completely chiral, and one does not need to forbid mass terms for the messenger fields by hand. Cosmology of the model is briefly discussed. copyright 1997 The American Physical Society

Multi-Criteria Decision Making For Determining A Simple Model of Supplier Selection

Science.gov (United States)

Harwati

2017-06-01

Supplier selection is a decision with many criteria. Supplier selection model usually involves more than five main criteria and more than 10 sub-criteria. In fact many model includes more than 20 criteria. Too many criteria involved in supplier selection models sometimes make it difficult to apply in many companies. This research focuses on designing supplier selection that easy and simple to be applied in the company. Analytical Hierarchy Process (AHP) is used to weighting criteria. The analysis results there are four criteria that are easy and simple can be used to select suppliers: Price (weight 0.4) shipment (weight 0.3), quality (weight 0.2) and services (weight 0.1). A real case simulation shows that simple model provides the same decision with a more complex model.

Selection of climate change scenario data for impact modelling

DEFF Research Database (Denmark)

Sloth Madsen, M; Fox Maule, C; MacKellar, N

2012-01-01

Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...... illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...

Direct Model Reference Adaptive Control for a Magnetic Bearing

Energy Technology Data Exchange (ETDEWEB)

Durling, Mike [Rensselaer Polytechnic Inst., Troy, NY (United States)

1999-11-01

A Direct Model Reference Adaptive Controller (DMRAC) is applied to a magnetic bearing test stand. The bearing of interest is the MBC 500 Magnetic Bearing System manufactured by Magnetic Moments, LLC. The bearing model is presented in state space form and the system transfer function is measured directly using a closed-loop swept sine technique. Next, the bearing models are used to design a phase-lead controller, notch filter and then a DMRAC. The controllers are tuned in simulations and finally are implemented using a combination of MATLAB, SIMULINK and dSPACE. The results show a successful implementation of a DMRAC on the magnetic bearing hardware.

A model selection support system for numerical simulations of nuclear thermal-hydraulics

International Nuclear Information System (INIS)

Gofuku, Akio; Shimizu, Kenji; Sugano, Keiji; Yoshikawa, Hidekazu; Wakabayashi, Jiro

1990-01-01

In order to execute efficiently a dynamic simulation of a large-scaled engineering system such as a nuclear power plant, it is necessary to develop intelligent simulation support system for all phases of the simulation. This study is concerned with the intelligent support for the program development phase and is engaged in the adequate model selection support method by applying AI (Artificial Intelligence) techniques to execute a simulation consistent with its purpose and conditions. A proto-type expert system to support the model selection for numerical simulations of nuclear thermal-hydraulics in the case of cold leg small break loss-of-coolant accident of PWR plant is now under development on a personal computer. The steps to support the selection of both fluid model and constitutive equations for the drift flux model have been developed. Several cases of model selection were carried out and reasonable model selection results were obtained. (author)

Optogenetic stimulation in a computational model of the basal ganglia biases action selection and reward prediction error.

Science.gov (United States)

Berthet, Pierre; Lansner, Anders

2014-01-01

Optogenetic stimulation of specific types of medium spiny neurons (MSNs) in the striatum has been shown to bias the selection of mice in a two choices task. This shift is dependent on the localisation and on the intensity of the stimulation but also on the recent reward history. We have implemented a way to simulate this increased activity produced by the optical flash in our computational model of the basal ganglia (BG). This abstract model features the direct and indirect pathways commonly described in biology, and a reward prediction pathway (RP). The framework is similar to Actor-Critic methods and to the ventral/dorsal distinction in the striatum. We thus investigated the impact on the selection caused by an added stimulation in each of the three pathways. We were able to reproduce in our model the bias in action selection observed in mice. Our results also showed that biasing the reward prediction is sufficient to create a modification in the action selection. However, we had to increase the percentage of trials with stimulation relative to that in experiments in order to impact the selection. We found that increasing only the reward prediction had a different effect if the stimulation in RP was action dependent (only for a specific action) or not. We further looked at the evolution of the change in the weights depending on the stage of learning within a block. A bias in RP impacts the plasticity differently depending on that stage but also on the outcome. It remains to experimentally test how the dopaminergic neurons are affected by specific stimulations of neurons in the striatum and to relate data to predictions of our model.

Modeling selective pressures on phytoplankton in the global ocean.

Directory of Open Access Journals (Sweden)

Jason G Bragg

Full Text Available Our view of marine microbes is transforming, as culture-independent methods facilitate rapid characterization of microbial diversity. It is difficult to assimilate this information into our understanding of marine microbe ecology and evolution, because their distributions, traits, and genomes are shaped by forces that are complex and dynamic. Here we incorporate diverse forces--physical, biogeochemical, ecological, and mutational--into a global ocean model to study selective pressures on a simple trait in a widely distributed lineage of picophytoplankton: the nitrogen use abilities of Synechococcus and Prochlorococcus cyanobacteria. Some Prochlorococcus ecotypes have lost the ability to use nitrate, whereas their close relatives, marine Synechococcus, typically retain it. We impose mutations for the loss of nitrogen use abilities in modeled picophytoplankton, and ask: in which parts of the ocean are mutants most disadvantaged by losing the ability to use nitrate, and in which parts are they least disadvantaged? Our model predicts that this selective disadvantage is smallest for picophytoplankton that live in tropical regions where Prochlorococcus are abundant in the real ocean. Conversely, the selective disadvantage of losing the ability to use nitrate is larger for modeled picophytoplankton that live at higher latitudes, where Synechococcus are abundant. In regions where we expect Prochlorococcus and Synechococcus populations to cycle seasonally in the real ocean, we find that model ecotypes with seasonal population dynamics similar to Prochlorococcus are less disadvantaged by losing the ability to use nitrate than model ecotypes with seasonal population dynamics similar to Synechococcus. The model predictions for the selective advantage associated with nitrate use are broadly consistent with the distribution of this ability among marine picocyanobacteria, and at finer scales, can provide insights into interactions between temporally varying

Modeling selective pressures on phytoplankton in the global ocean.

Science.gov (United States)

Bragg, Jason G; Dutkiewicz, Stephanie; Jahn, Oliver; Follows, Michael J; Chisholm, Sallie W

2010-03-10

Our view of marine microbes is transforming, as culture-independent methods facilitate rapid characterization of microbial diversity. It is difficult to assimilate this information into our understanding of marine microbe ecology and evolution, because their distributions, traits, and genomes are shaped by forces that are complex and dynamic. Here we incorporate diverse forces--physical, biogeochemical, ecological, and mutational--into a global ocean model to study selective pressures on a simple trait in a widely distributed lineage of picophytoplankton: the nitrogen use abilities of Synechococcus and Prochlorococcus cyanobacteria. Some Prochlorococcus ecotypes have lost the ability to use nitrate, whereas their close relatives, marine Synechococcus, typically retain it. We impose mutations for the loss of nitrogen use abilities in modeled picophytoplankton, and ask: in which parts of the ocean are mutants most disadvantaged by losing the ability to use nitrate, and in which parts are they least disadvantaged? Our model predicts that this selective disadvantage is smallest for picophytoplankton that live in tropical regions where Prochlorococcus are abundant in the real ocean. Conversely, the selective disadvantage of losing the ability to use nitrate is larger for modeled picophytoplankton that live at higher latitudes, where Synechococcus are abundant. In regions where we expect Prochlorococcus and Synechococcus populations to cycle seasonally in the real ocean, we find that model ecotypes with seasonal population dynamics similar to Prochlorococcus are less disadvantaged by losing the ability to use nitrate than model ecotypes with seasonal population dynamics similar to Synechococcus. The model predictions for the selective advantage associated with nitrate use are broadly consistent with the distribution of this ability among marine picocyanobacteria, and at finer scales, can provide insights into interactions between temporally varying ocean processes and

Using Direct Sub-Level Entity Access to Improve Nuclear Stockpile Simulation Modeling

Energy Technology Data Exchange (ETDEWEB)

Parker, Robert Y. [Brigham Young Univ., Provo, UT (United States)

1999-08-01

Direct sub-level entity access is a seldom-used technique in discrete-event simulation modeling that addresses the accessibility of sub-level entity information. The technique has significant advantages over more common, alternative modeling methods--especially where hierarchical entity structures are modeled. As such, direct sub-level entity access is often preferable in modeling nuclear stockpile, life-extension issues, an area to which it has not been previously applied. Current nuclear stockpile, life-extension models were demonstrated to benefit greatly from the advantages of direct sub-level entity access. In specific cases, the application of the technique resulted in models that were up to 10 times faster than functionally equivalent models where alternative techniques were applied. Furthermore, specific implementations of direct sub-level entity access were observed to be more flexible, efficient, functional, and scalable than corresponding implementations using common modeling techniques. Common modeling techniques (''unbatch/batch'' and ''attribute-copying'') proved inefficient and cumbersome in handling many nuclear stockpile modeling complexities, including multiple weapon sites, true defect analysis, and large numbers of weapon and subsystem types. While significant effort was required to enable direct sub-level entity access in the nuclear stockpile simulation models, the enhancements were worth the effort--resulting in more efficient, more capable, and more informative models that effectively addressed the complexities of the nuclear stockpile.

Heteroscedasticity as a Basis of Direction Dependence in Reversible Linear Regression Models.

Science.gov (United States)

Wiedermann, Wolfgang; Artner, Richard; von Eye, Alexander

2017-01-01

Heteroscedasticity is a well-known issue in linear regression modeling. When heteroscedasticity is observed, researchers are advised to remedy possible model misspecification of the explanatory part of the model (e.g., considering alternative functional forms and/or omitted variables). The present contribution discusses another source of heteroscedasticity in observational data: Directional model misspecifications in the case of nonnormal variables. Directional misspecification refers to situations where alternative models are equally likely to explain the data-generating process (e.g., x → y versus y → x). It is shown that the homoscedasticity assumption is likely to be violated in models that erroneously treat true nonnormal predictors as response variables. Recently, Direction Dependence Analysis (DDA) has been proposed as a framework to empirically evaluate the direction of effects in linear models. The present study links the phenomenon of heteroscedasticity with DDA and describes visual diagnostics and nine homoscedasticity tests that can be used to make decisions concerning the direction of effects in linear models. Results of a Monte Carlo simulation that demonstrate the adequacy of the approach are presented. An empirical example is provided, and applicability of the methodology in cases of violated assumptions is discussed.

The CEDSS model of direct domestic energy demand

OpenAIRE

Gotts, Nicholas Mark

2014-01-01

This paper describes the design, implementation and testing of the CEDSS model of direct domestic energy demand, and the first results of its use to produce estimates of future demand under a range of scenarios. CEDSS simulates direct domestic energy demand at within communities of approximately 200 households. The scenarios explored differ in the economic conditions assumed, and policy measures adopted at national level.

Evolution of the additive genetic variance–covariance matrix under continuous directional selection on a complex behavioural phenotype

Science.gov (United States)

Careau, Vincent; Wolak, Matthew E.; Carter, Patrick A.; Garland, Theodore

2015-01-01

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance–covariance matrix (G). Yet knowledge of G in a population experiencing new or altered selection is not sufficient to predict selection response because G itself evolves in ways that are poorly understood. We experimentally evaluated changes in G when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. PMID:26582016

Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

Science.gov (United States)

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2015-11-22

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. © 2015 The Author(s).

Uniform design based SVM model selection for face recognition

Science.gov (United States)

Li, Weihong; Liu, Lijuan; Gong, Weiguo

2010-02-01

Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

Selecting an optimal mixed products using grey relationship model

Directory of Open Access Journals (Sweden)

Farshad Faezy Razi

2013-06-01

Full Text Available This paper presents an integrated supplier selection and inventory management using grey relationship model (GRM as well as multi-objective decision making process. The proposed model of this paper first ranks different suppliers based on GRM technique and then determines the optimum level of inventory by considering different objectives. To show the implementation of the proposed model, we use some benchmark data presented by Talluri and Baker [Talluri, S., & Baker, R. C. (2002. A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3, 544-558.]. The preliminary results indicate that the proposed model of this paper is capable of handling different criteria for supplier selection.

Selection, calibration, and validation of models of tumor growth.

Science.gov (United States)

Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C

2016-11-01

This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory

ERP Software Selection Model using Analytic Network Process

OpenAIRE

Lesmana , Andre Surya; Astanti, Ririn Diar; Ai, The Jin

2014-01-01

During the implementation of Enterprise Resource Planning (ERP) in any company, one of the most important issues is the selection of ERP software that can satisfy the needs and objectives of the company. This issue is crucial since it may affect the duration of ERP implementation and the costs incurred for the ERP implementation. This research tries to construct a model of the selection of ERP software that are beneficial to the company in order to carry out the selection of the right ERP sof...

Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects

Directory of Open Access Journals (Sweden)

Guangjie Li

2015-07-01

Full Text Available We examine the relationship between consistent parameter estimation and model selection for autoregressive panel data models with fixed effects. We find that the transformation of fixed effects proposed by Lancaster (2002 does not necessarily lead to consistent estimation of common parameters when some true exogenous regressors are excluded. We propose a data dependent way to specify the prior of the autoregressive coefficient and argue for comparing different model specifications before parameter estimation. Model selection properties of Bayes factors and Bayesian information criterion (BIC are investigated. When model uncertainty is substantial, we recommend the use of Bayesian Model Averaging to obtain point estimators with lower root mean squared errors (RMSE. We also study the implications of different levels of inclusion probabilities by simulations.

Methods for selecting fixed-effect models for heterogeneous codon evolution, with comments on their application to gene and genome data.

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Bao, Le; Gu, Hong; Dunn, Katherine A; Bielawski, Joseph P

2007-02-08

Models of codon evolution have proven useful for investigating the strength and direction of natural selection. In some cases, a priori biological knowledge has been used successfully to model heterogeneous evolutionary dynamics among codon sites. These are called fixed-effect models, and they require that all codon sites are assigned to one of several partitions which are permitted to have independent parameters for selection pressure, evolutionary rate, transition to transversion ratio or codon frequencies. For single gene analysis, partitions might be defined according to protein tertiary structure, and for multiple gene analysis partitions might be defined according to a gene's functional category. Given a set of related fixed-effect models, the task of selecting the model that best fits the data is not trivial. In this study, we implement a set of fixed-effect codon models which allow for different levels of heterogeneity among partitions in the substitution process. We describe strategies for selecting among these models by a backward elimination procedure, Akaike information criterion (AIC) or a corrected Akaike information criterion (AICc). We evaluate the performance of these model selection methods via a simulation study, and make several recommendations for real data analysis. Our simulation study indicates that the backward elimination procedure can provide a reliable method for model selection in this setting. We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria). Fixed-effect models have advantages and disadvantages. Fixed-effect models are desirable when data partitions are known to exhibit significant heterogeneity or when a statistical test of such heterogeneity is desired. They have the disadvantage of requiring a priori

Variable Selection for Regression Models of Percentile Flows

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Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

Hydraulic head interpolation using ANFIS—model selection and sensitivity analysis

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Kurtulus, Bedri; Flipo, Nicolas

2012-01-01

The aim of this study is to investigate the efficiency of ANFIS (adaptive neuro fuzzy inference system) for interpolating hydraulic head in a 40-km 2 agricultural watershed of the Seine basin (France). Inputs of ANFIS are Cartesian coordinates and the elevation of the ground. Hydraulic head was measured at 73 locations during a snapshot campaign on September 2009, which characterizes low-water-flow regime in the aquifer unit. The dataset was then split into three subsets using a square-based selection method: a calibration one (55%), a training one (27%), and a test one (18%). First, a method is proposed to select the best ANFIS model, which corresponds to a sensitivity analysis of ANFIS to the type and number of membership functions (MF). Triangular, Gaussian, general bell, and spline-based MF are used with 2, 3, 4, and 5 MF per input node. Performance criteria on the test subset are used to select the 5 best ANFIS models among 16. Then each is used to interpolate the hydraulic head distribution on a (50×50)-m grid, which is compared to the soil elevation. The cells where the hydraulic head is higher than the soil elevation are counted as "error cells." The ANFIS model that exhibits the less "error cells" is selected as the best ANFIS model. The best model selection reveals that ANFIS models are very sensitive to the type and number of MF. Finally, a sensibility analysis of the best ANFIS model with four triangular MF is performed on the interpolation grid, which shows that ANFIS remains stable to error propagation with a higher sensitivity to soil elevation.

A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

Directory of Open Access Journals (Sweden)

Chung-Min Wu

2013-01-01

Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

Modeling of Clostridium tyrobutyricum for Butyric Acid Selectivity in Continuous Fermentation

Directory of Open Access Journals (Sweden)

Jianjun Du

2014-04-01

Full Text Available A mathematical model was developed to describe batch and continuous fermentation of glucose to organic acids with Clostridium tyrobutyricum. A modified Monod equation was used to describe cell growth, and a Luedeking-Piret equation was used to describe the production of butyric and acetic acids. Using the batch fermentation equations, models predicting butyric acid selectivity for continuous fermentation were also developed. The model showed that butyric acid production was a strong function of cell mass, while acetic acid production was a function of cell growth rate. Further, it was found that at high acetic acid concentrations, acetic acid was metabolized to butyric acid and that this conversion could be modeled. In batch fermentation, high butyric acid selectivity occurred at high initial cell or glucose concentrations. In continuous fermentation, decreased dilution rate improved selectivity; at a dilution rate of 0.028 h−1, the selectivity reached 95.8%. The model and experimental data showed that at total cell recycle, the butyric acid selectivity could reach 97.3%. This model could be used to optimize butyric acid production using C. tyrobutyricum in a continuous fermentation scheme. This is the first study that mathematically describes batch, steady state, and dynamic behavior of C. tyrobutyricum for butyric acid production.

Cross-validation pitfalls when selecting and assessing regression and classification models.

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Krstajic, Damjan; Buturovic, Ljubomir J; Leahy, David E; Thomas, Simon

2014-03-29

We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. We describe in detail an algorithm for repeated grid-search V-fold cross-validation for parameter tuning in classification and regression, and we define a repeated nested cross-validation algorithm for model assessment. As regards variable selection and parameter tuning we define two algorithms (repeated grid-search cross-validation and double cross-validation), and provide arguments for using the repeated grid-search in the general case. We show results of our algorithms on seven QSAR datasets. The variation of the prediction performance, which is the result of choosing different splits of the dataset in V-fold cross-validation, needs to be taken into account when selecting and assessing classification and regression models. We demonstrate the importance of repeating cross-validation when selecting an optimal model, as well as the importance of repeating nested cross-validation when assessing a prediction error.

A Heckman selection model for the safety analysis of signalized intersections.

Directory of Open Access Journals (Sweden)

Xuecai Xu

Full Text Available The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously.This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI, respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years.The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels.A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections.

Automating an integrated spatial data-mining model for landfill site selection

Science.gov (United States)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

2017-10-01

An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

Multilevel selection in a resource-based model

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Ferreira, Fernando Fagundes; Campos, Paulo R. A.

2013-07-01

In the present work we investigate the emergence of cooperation in a multilevel selection model that assumes limiting resources. Following the work by R. J. Requejo and J. Camacho [Phys. Rev. Lett.0031-900710.1103/PhysRevLett.108.038701 108, 038701 (2012)], the interaction among individuals is initially ruled by a prisoner's dilemma (PD) game. The payoff matrix may change, influenced by the resource availability, and hence may also evolve to a non-PD game. Furthermore, one assumes that the population is divided into groups, whose local dynamics is driven by the payoff matrix, whereas an intergroup competition results from the nonuniformity of the growth rate of groups. We study the probability that a single cooperator can invade and establish in a population initially dominated by defectors. Cooperation is strongly favored when group sizes are small. We observe the existence of a critical group size beyond which cooperation becomes counterselected. Although the critical size depends on the parameters of the model, it is seen that a saturation value for the critical group size is achieved. The results conform to the thought that the evolutionary history of life repeatedly involved transitions from smaller selective units to larger selective units.

Region-specificity of GABAA receptor mediated effects on orientation and direction selectivity in cat visual cortical area 18.

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Jirmann, Kay-Uwe; Pernberg, Joachim; Eysel, Ulf T

2009-01-01

The role of GABAergic inhibition in orientation and direction selectivity has been investigated with the GABA(A)-Blocker bicuculline in the cat visual cortex, and results indicated a region specific difference of functional contributions of GABAergic inhibition in areas 17 and 18. In area 17 inhibition appeared mainly involved in sculpturing orientation and direction tuning, while in area 18 inhibition seemed more closely associated with temporal receptive field properties. However, different types of stimuli were used to test areas 17 and 18 and further studies performed in area 17 suggested an important influence of the stimulus type (single light bars vs. moving gratings) on the evoked responses (transient vs. sustained) and inhibitory mechanisms (GABA(A) vs. GABA(B)) which in turn might be more decisive for the specific results than the cortical region. To insert the missing link in this chain of arguments it was necessary to study GABAergic inhibition in area 18 with moving light bars, which has not been done so far. Therefore, in the present study we investigated area 18 cells responding to oriented moving light bars with extracellular recordings and reversible microiontophoretic blockade of GABAergig inhibition with bicuculline methiodide. The majority of neurons was characterized by a pronounced orientation specificity and variable degrees of direction selectivity. GABA(A)ergic inhibition significantly influenced preferred orientation and preferred direction in area 18. During the action of bicuculline orientation tuning width increased and orientation and direction selectivity indices decreased. Our results obtained in area 18 with moving bar stimuli, although in the proportion of affected cells similar to those described in area 17, quantitatively matched the findings for direction and orientation specificity obtained with moving gratings in area 18. Accordingly, stimulus type is not decisive in area 18 and the GABA(A) dependent, inhibitory intracortical

Directional Track Selection Technique in CR39 SSNTD for lowyield reaction experiments

Science.gov (United States)

Ingenito, Francesco; Andreoli, Pierluigi; Batani, Dimitri; Bonasera, Aldo; Boutoux, Guillaume; Burgy, Frederic; Cipriani, Mattia; Consoli, Fabrizio; Cristofari, Giuseppe; De Angelis, Riccardo; Di Giorgio, Giorgio; Ducret, Jean Eric; Giulietti, Danilo; Jakubowska, Katarzyna

2018-01-01

There is a great interest in the study of p-11B aneutronic nuclear fusion reactions, both for energy production and for determination of fusion cross-sections at low energies. In this context we performed experiments at CELIA in which energetic protons, accelerated by the laser ECLIPSE, were directed toward a solid Boron target. Because of the small cross-sections at these energies the number of expected reactions is low. CR39 Solid-State Nuclear Track Detectors (SSNTD) were used to detect the alpha particles produced. Because of the low expected yield, it is difficult to discriminate the tracks due to true fusion products from those due to natural background in the CR39. To this purpose we developed a methodology of particle recognition according to their direction with respect to the detector normal, able to determine the position of their source. We applied this to the specific experiment geometry, so to select from all the tracks those due to particles coming from the region of interaction between accelerated protons and solid boron target. This technique can be of great help on the analysis of SSNTD in experiments with low yield reactions, but can be also generally applied to any experiment where particles reach the track detector with known directions, and for example to improve the detection limit of particle spectrometers using CR39.

Effect of Model Selection on Computed Water Balance Components

NARCIS (Netherlands)

Jhorar, R.K.; Smit, A.A.M.F.R.; Roest, C.W.J.

2009-01-01

Soil water flow modelling approaches as used in four selected on-farm water management models, namely CROPWAT. FAIDS, CERES and SWAP, are compared through numerical experiments. The soil water simulation approaches used in the first three models are reformulated to incorporate ail evapotranspiration

Method and apparatus for producing and selectively directing x-rays to different points on an object

International Nuclear Information System (INIS)

Haimson, J.

1981-01-01

The invention relates to apparatus suitable for use in a computer tomography X-ray scanner. High intensity X-rays are produced and directed towards the object of interest from any of a plurality of preselected coplanar points spaced from the object and spaced radially about a line through the object. There are no moving parts. The electron beam, which produces X-rays as a consequence of impact with the target, is directed selectively to preselected points on the stationary target. Beam-direction compensates for the beam spreading effect of space charge forces acting on the beam, and beam-shaping shapes the beam to a predetermined cross-sectional configuration at its point of incidence with the target. Beam aberrations including sextupole aberrations are corrected. (U.K.)

The Impact of Varied Discrimination Parameters on Mixed-Format Item Response Theory Model Selection

Science.gov (United States)

Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G.

2013-01-01

Whittaker, Chang, and Dodd compared the performance of model selection criteria when selecting among mixed-format IRT models and found that the criteria did not perform adequately when selecting the more parameterized models. It was suggested by M. S. Johnson that the problems when selecting the more parameterized models may be because of the low…

Boltzmann, Darwin and Directionality theory

Energy Technology Data Exchange (ETDEWEB)

Demetrius, Lloyd A., E-mail: ldemetr@oeb.harvard.edu

2013-09-01

Boltzmann’s statistical thermodynamics is a mathematical theory which relates the macroscopic properties of aggregates of interacting molecules with the laws of their interaction. The theory is based on the concept thermodynamic entropy, a statistical measure of the extent to which energy is spread throughout macroscopic matter. Macroscopic evolution of material aggregates is quantitatively explained in terms of the principle: Thermodynamic entropy increases as the composition of the aggregate changes under molecular collision. Darwin’s theory of evolution is a qualitative theory of the origin of species and the adaptation of populations to their environment. A central concept in the theory is fitness, a qualitative measure of the capacity of an organism to contribute to the ancestry of future generations. Macroscopic evolution of populations of living organisms can be qualitatively explained in terms of a neo-Darwinian principle: Fitness increases as the composition of the population changes under variation and natural selection. Directionality theory is a quantitative model of the Darwinian argument of evolution by variation and selection. This mathematical theory is based on the concept evolutionary entropy, a statistical measure which describes the rate at which an organism appropriates energy from the environment and reinvests this energy into survivorship and reproduction. According to directionality theory, microevolutionary dynamics, that is evolution by mutation and natural selection, can be quantitatively explained in terms of a directionality principle: Evolutionary entropy increases when the resources are diverse and of constant abundance; but decreases when the resource is singular and of variable abundance. This report reviews the analytical and empirical support for directionality theory, and invokes the microevolutionary dynamics of variation and selection to delineate the principles which govern macroevolutionary dynamics of speciation and

Boltzmann, Darwin and Directionality theory

International Nuclear Information System (INIS)

Demetrius, Lloyd A.

2013-01-01

Boltzmann’s statistical thermodynamics is a mathematical theory which relates the macroscopic properties of aggregates of interacting molecules with the laws of their interaction. The theory is based on the concept thermodynamic entropy, a statistical measure of the extent to which energy is spread throughout macroscopic matter. Macroscopic evolution of material aggregates is quantitatively explained in terms of the principle: Thermodynamic entropy increases as the composition of the aggregate changes under molecular collision. Darwin’s theory of evolution is a qualitative theory of the origin of species and the adaptation of populations to their environment. A central concept in the theory is fitness, a qualitative measure of the capacity of an organism to contribute to the ancestry of future generations. Macroscopic evolution of populations of living organisms can be qualitatively explained in terms of a neo-Darwinian principle: Fitness increases as the composition of the population changes under variation and natural selection. Directionality theory is a quantitative model of the Darwinian argument of evolution by variation and selection. This mathematical theory is based on the concept evolutionary entropy, a statistical measure which describes the rate at which an organism appropriates energy from the environment and reinvests this energy into survivorship and reproduction. According to directionality theory, microevolutionary dynamics, that is evolution by mutation and natural selection, can be quantitatively explained in terms of a directionality principle: Evolutionary entropy increases when the resources are diverse and of constant abundance; but decreases when the resource is singular and of variable abundance. This report reviews the analytical and empirical support for directionality theory, and invokes the microevolutionary dynamics of variation and selection to delineate the principles which govern macroevolutionary dynamics of speciation and

An experimentally verified model for estimating the distance resolution capability of direct time of flight 3D optical imaging systems

International Nuclear Information System (INIS)

Nguyen, K Q K; Fisher, E M D; Walton, A J; Underwood, I

2013-01-01

This report introduces a new statistical model for time-resolved photon detection in a generic single-photon-sensitive sensor array. The model is validated by comparing modelled data with experimental data collected on a single-photon avalanche diode sensor array. Data produced by the model are used alongside corresponding experimental data to calculate, for the first time, the effective distance resolution of a pulsed direct time of flight 3D optical imaging system over a range of conditions using four peak-detection algorithms. The relative performance of the algorithms is compared. The model can be used to improve the system design process and inform selection of the optimal peak-detection algorithm. (paper)

Nonmathematical models for evolution of altruism, and for group selection (peck order-territoriality-ant colony-dual-determinant model-tri-determinant model).

Science.gov (United States)

Darlington, P J

1972-02-01

Mathematical biologists have failed to produce a satisfactory general model for evolution of altruism, i.e., of behaviors by which "altruists" benefit other individuals but not themselves; kin selection does not seem to be a sufficient explanation of nonreciprocal altruism. Nonmathematical (but mathematically acceptable) models are now proposed for evolution of negative altruism in dual-determinant and of positive altruism in tri-determinant systems. Peck orders, territorial systems, and an ant society are analyzed as examples. In all models, evolution is primarily by individual selection, probably supplemented by group selection. Group selection is differential extinction of populations. It can act only on populations preformed by selection at the individual level, but can either cancel individual selective trends (effecting evolutionary homeostasis) or supplement them; its supplementary effect is probably increasingly important in the evolution of increasingly organized populations.

Traditional and robust vector selection methods for use with similarity based models

International Nuclear Information System (INIS)

Hines, J. W.; Garvey, D. R.

2006-01-01

Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

Channel selection in e-commerce age: A strategic analysis of co-op advertising models

Directory of Open Access Journals (Sweden)

Yongmei Liu

2013-03-01

, such as service and price. We can do some researches from the point of these factors. Third, how demand uncertainty affects the channel selection and co-op advertising strategy is another interesting research item.Practical implications: The manufacturer and the retailer know that the impact of co-op adverting on the demands of traditional channel and direct channel, both would like to choose reasonable strategies to improve the channel coordination. Therefore, it would be best if business managers conduct market survey before they start their co-op advertising campaign.Originality/value: Two new co-op advertising models in E-commerce age are developed, and the impact of product web-fit on these optimal strategies are analyzed and illustrate by some numeral examples. In addition, optimal channel structure in E-commerce age are selected for manufacturer and the retailer.

tBuLi-Mediated One-Pot Direct Highly Selective Cross-Coupling of Two Distinct Aryl Bromides

NARCIS (Netherlands)

Vila, Carlos; Cembellin, Sara; Hornillos, Valentin; Giannerini, Massimo; Fananas-Mastral, Martin; Feringa, Ben L.

2015-01-01

A Pd-catalyzed direct cross-coupling of two distinct aryl bromides mediated by tBuLi is described. The use of [Pd-PEPPSI-IPr] or [Pd-PEPPSI-IPent] as catalyst allows for the efficient one-pot synthesis of unsymmetrical biaryls at room temperature. The key for this selective cross-coupling is the use

Assessment of materials selection and performance for direct-coal- liquefaction plants in the United States

Energy Technology Data Exchange (ETDEWEB)

Olsen, A.R.; Judkins, R.R.; Keiser, J.R.

1996-09-01

Several direct coal liquefaction processes have been demonstrated at the pilot plant level in the United States. Presently only one plant remains operational, namely, the Hydrocarbon Technologies, Inc., 4.0- ton-per-day process development unit in Lawrenceville, New Jersey. The period from 1974 to 1982 saw the greatest amount of development of direct coal liquefaction in the United States with four major pilot plants being devoted to variants of this technology. The plants included the SRC-I plant at Wilsonville, Alabama, which operated from 1974 to 1992; the SRC-I/II plant at Fort Lewis, Washington, which operated from 1974 to 1981; the H-Coal plant at Catlettsburg, Kentucky, which operated from 1980 to 1982; and the Exxon Coal Liquefaction Pilot Plant at Baytown, Texas, which operated from 1980 to 1982. Oak Ridge National Laboratory scientists and engineers were actively involved in many phases and technical disciplines at all four of these plants, especially in materials testing, evaluation, and failure analyses. In addition, ORNL materials scientists and engineers conducted reviews of the demonstration and commercial plant designs for materials selections. The ORNL staff members worked closely with materials engineers at the pilot plants in identifying causes of materials degradation and failures, and in identifying solutions to these problems. This report provides a comprehensive summary of those materials activities. Materials performance data from laboratory and coal liquefaction pilot plant tests, failure analyses, and analyses of components after use in pilot plants were reviewed and assessed to determine the extent and causes of materials degradation in direct coal liquefaction process environments. Reviews of demonstration and commercial plant design documents for materials selections were conducted. These reviews and assessments are presented to capture the knowledge base on the most likely materials of construction for direct coal liquefaction plants.

The selective generation of acetic acid directly from synthesis gas

International Nuclear Information System (INIS)

Knifton, J.F.

1986-01-01

The authors conclude that each of the ruthenium, cobalt and iodide-containing catalyst components have very specific roles to play in the ''melt'' catalyzed conversion of synthesis gas to acetic acid. C 1 -Oxygenate formation is only observed in the presence of ruthenium carbonyls - [Ru(CO) 3 I 3 ] - is here the dominant species - and there is a direct relationship between liquid yield, ΣOAc - productivity and [Ru(CO) 3 I 3 ] - content. Controlled quantities of iodide ensure that initially formed MeOH is rapidly converted to the more reactive methyl iodide. Subsequent cobalt-catalyzed carbonylation to acetic acid may be preparatively attractive (>80% selectivity, good yields) relative to competing syntheses, where the [Co(CO) 4 ] - concentration is maximized that is, where the Co/Ru ratio is >1, the syngas feedstock is rich in CO, and the initial iodide/cobalt ratios are ca. unity. Formation of cobalt-iodide species appears to be a competing, inhibitory step in this catalysis

Fixation probability in a two-locus intersexual selection model.

Science.gov (United States)

Durand, Guillermo; Lessard, Sabin

2016-06-01

We study a two-locus model of intersexual selection in a finite haploid population reproducing according to a discrete-time Moran model with a trait locus expressed in males and a preference locus expressed in females. We show that the probability of ultimate fixation of a single mutant allele for a male ornament introduced at random at the trait locus given any initial frequency state at the preference locus is increased by weak intersexual selection and recombination, weak or strong. Moreover, this probability exceeds the initial frequency of the mutant allele even in the case of a costly male ornament if intersexual selection is not too weak. On the other hand, the probability of ultimate fixation of a single mutant allele for a female preference towards a male ornament introduced at random at the preference locus is increased by weak intersexual selection and weak recombination if the female preference is not costly, and is strong enough in the case of a costly male ornament. The analysis relies on an extension of the ancestral recombination-selection graph for samples of haplotypes to take into account events of intersexual selection, while the symbolic calculation of the fixation probabilities is made possible in a reasonable time by an optimizing algorithm. Copyright © 2016 Elsevier Inc. All rights reserved.

A new methodology for modeling of direct landslide costs for transportation infrastructures

Science.gov (United States)

Klose, Martin; Terhorst, Birgit

2014-05-01

The world's transportation infrastructure is at risk of landslides in many areas across the globe. A safe and affordable operation of traffic routes are the two main criteria for transportation planning in landslide-prone areas. The right balancing of these often conflicting priorities requires, amongst others, profound knowledge of the direct costs of landslide damage. These costs include capital investments for landslide repair and mitigation as well as operational expenditures for first response and maintenance works. This contribution presents a new methodology for ex post assessment of direct landslide costs for transportation infrastructures. The methodology includes tools to compile, model, and extrapolate landslide losses on different spatial scales over time. A landslide susceptibility model enables regional cost extrapolation by means of a cost figure obtained from local cost compilation for representative case study areas. On local level, cost survey is closely linked with cost modeling, a toolset for cost estimation based on landslide databases. Cost modeling uses Landslide Disaster Management Process Models (LDMMs) and cost modules to simulate and monetize cost factors for certain types of landslide damage. The landslide susceptibility model provides a regional exposure index and updates the cost figure to a cost index which describes the costs per km of traffic route at risk of landslides. Both indexes enable the regionalization of local landslide losses. The methodology is applied and tested in a cost assessment for highways in the Lower Saxon Uplands, NW Germany, in the period 1980 to 2010. The basis of this research is a regional subset of a landslide database for the Federal Republic of Germany. In the 7,000 km² large Lower Saxon Uplands, 77 km of highway are located in potential landslide hazard area. Annual average costs of 52k per km of highway at risk of landslides are identified as cost index for a local case study area in this region. The

A concurrent optimization model for supplier selection with fuzzy quality loss

International Nuclear Information System (INIS)

Rosyidi, C.; Murtisari, R.; Jauhari, W.

2017-01-01

The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

A concurrent optimization model for supplier selection with fuzzy quality loss

Energy Technology Data Exchange (ETDEWEB)

Rosyidi, C.; Murtisari, R.; Jauhari, W.

2017-07-01

The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

Model selection approach suggests causal association between 25-hydroxyvitamin D and colorectal cancer.

Directory of Open Access Journals (Sweden)

Lina Zgaga

Full Text Available Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC, but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders.Plasma 25-hydroxyvitamin D (25-OHD, genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions.Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model, and also for deviance information criteria (DIC computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores.Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations.

Probabilistic wind power forecasting with online model selection and warped gaussian process

International Nuclear Information System (INIS)

Kou, Peng; Liang, Deliang; Gao, Feng; Gao, Lin

2014-01-01

Highlights: • A new online ensemble model for the probabilistic wind power forecasting. • Quantifying the non-Gaussian uncertainties in wind power. • Online model selection that tracks the time-varying characteristic of wind generation. • Dynamically altering the input features. • Recursive update of base models. - Abstract: Based on the online model selection and the warped Gaussian process (WGP), this paper presents an ensemble model for the probabilistic wind power forecasting. This model provides the non-Gaussian predictive distributions, which quantify the non-Gaussian uncertainties associated with wind power. In order to follow the time-varying characteristics of wind generation, multiple time dependent base forecasting models and an online model selection strategy are established, thus adaptively selecting the most probable base model for each prediction. WGP is employed as the base model, which handles the non-Gaussian uncertainties in wind power series. Furthermore, a regime switch strategy is designed to modify the input feature set dynamically, thereby enhancing the adaptiveness of the model. In an online learning framework, the base models should also be time adaptive. To achieve this, a recursive algorithm is introduced, thus permitting the online updating of WGP base models. The proposed model has been tested on the actual data collected from both single and aggregated wind farms

Adiabatic equilibrium models for direct containment heating

International Nuclear Information System (INIS)

Pilch, M.; Allen, M.D.

1991-01-01

Probabilistic risk assessment (PRA) studies are being extended to include a wider spectrum of reactor plants than was considered in NUREG-1150. There is a need for simple direct containment heating (DCH) models that can be used for screening studies aimed at identifying potentially significant contributors to overall risk in individual nuclear power plants. This paper presents two adiabatic equilibrium models suitable for the task. The first, a single-cell model, places a true upper bound on DCH loads. This upper bound, however, often far exceeds reasonable expectations of containment loads based on CONTAIN calculations and experiment observations. In this paper, a two cell model is developed that captures the major mitigating feature of containment compartmentalization, thus providing more reasonable estimates of the containment load

Augmented Self-Modeling as an Intervention for Selective Mutism

Science.gov (United States)

Kehle, Thomas J.; Bray, Melissa A.; Byer-Alcorace, Gabriel F.; Theodore, Lea A.; Kovac, Lisa M.

2012-01-01

Selective mutism is a rare disorder that is difficult to treat. It is often associated with oppositional defiant behavior, particularly in the home setting, social phobia, and, at times, autism spectrum disorder characteristics. The augmented self-modeling treatment has been relatively successful in promoting rapid diminishment of selective mutism…

Social determinants of health in selected slum areas in Jordan: challenges and policy directions.

Science.gov (United States)

Ajlouni, Musa T

2016-01-01

The unplanned urbanization in Jordan has over time created many informal settlements "slums" around big cities as Amman, Zerka and Aqaba. The purpose of this study was to highlight the most common challenges related to social determinants of health in two selected slum areas in Amman and Aqaba and suggest policy directions and interventions to meet these challenges. In addition to a prestructured interview with all household heads living in the two slum sites, focus group meetings with a purposefully selected sample of 12 slum dwellers in each site were used to assess the structural and intermediary determinants of health as perceived by slum residents in the two study locations. The study found that slum residents in the two locations suffer from many challenges as severe poverty; unemployment; illiteracy and low education attainments; gender discrimination; insufficient and poor diet; social and official exclusion; unhealthy environment; lack of water supply, electricity and basic sanitation facilities; high prevalence of diseases; and insufficient and inappropriate health services. Specific policy directions to meet these challenges were recommended and grouped into three main clusters: social protection, social inclusion and empowerment. New plans and tools should be developed by local authorities in Jordan to understand, protect, include and empower those vulnerable people who are forced to live in these unhealthy and inhuman environments. Copyright © 2014 John Wiley & Sons, Ltd.

Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.

Science.gov (United States)

Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf

2018-01-01

Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Selective silicate-directed motility in diatoms

DEFF Research Database (Denmark)

Bondoc, Karen Grace V.; Heuschele, Jan; Gillard, Jeroen

2016-01-01

the major sink in the global Si cycle. Dissolved silicic acid (dSi) availability frequently limits diatom productivity and influences species composition of communities. We show that benthic diatoms selectively perceive and behaviourally react to gradients of dSi. Cell speed increases under d...

Heat transfer modelling and stability analysis of selective laser melting

International Nuclear Information System (INIS)

Gusarov, A.V.; Yadroitsev, I.; Bertrand, Ph.; Smurov, I.

2007-01-01

The process of direct manufacturing by selective laser melting basically consists of laser beam scanning over a thin powder layer deposited on a dense substrate. Complete remelting of the powder in the scanned zone and its good adhesion to the substrate ensure obtaining functional parts with improved mechanical properties. Experiments with single-line scanning indicate, that an interval of scanning velocities exists where the remelted tracks are uniform. The tracks become broken if the scanning velocity is outside this interval. This is extremely undesirable and referred to as the 'balling' effect. A numerical model of coupled radiation and heat transfer is proposed to analyse the observed instability. The 'balling' effect at high scanning velocities (above ∼20 cm/s for the present conditions) can be explained by the Plateau-Rayleigh capillary instability of the melt pool. Two factors stabilize the process with decreasing the scanning velocity: reducing the length-to-width ratio of the melt pool and increasing the width of its contact with the substrate

Modelling fragmentations of amino-acids after resonant electron attachment: quantum evidence of possible direct -OH detachment

Energy Technology Data Exchange (ETDEWEB)

Panosetti, C.; Sebastianelli, F.; Gianturco, F.A. [Department of Chemistry and CNISM, University of Rome -La Sapienza-, Roma (Italy); Baccarelli, I. [CASPUR, Supercomputing Consortium for University and Research, Roma (Italy)

2010-10-15

We investigate some aspects of the radiation damage mechanisms in biomolecules, focusing on the modelling of resonant fragmentation caused by the attachment of low-energy electrons (LEEs) initially ejected by biological tissues when exposed to ionizing radiation. Scattering equations are formulated within a symmetry-adapted, single-center expansion of both continuum and bound electrons, and the interaction forces are obtained from a combination of ab initio calculations and a nonempirical model of exchange and correlation effects developed in our group. We present total elastic scattering cross-sections and resonance features obtained for the equilibrium geometries of glycine, alanine, proline and valine. Our results at those geometries of the target molecules are briefly shown to qualitatively explain some of the fragmentation patterns obtained in experiments. We further carry out a one-dimensional (1D) modeling for the dynamics of intramolecular energy transfers mediated by the vibrational activation of selected bonds: our calculations indicate that resonant electron attachment to glycine can trigger direct, dissociative evolution of the complex into (Gly-OH)- and -OH losses, while they also find that the same process does not occur via a direct, 1D dissociative path in the larger amino acids of the present study. (authors)

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

KAUST Repository

Xu, Zhiqiang

2017-02-16

Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

KAUST Repository

Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

2017-01-01

Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

Investigations of incorporating source directivity into room acoustics computer models to improve auralizations

Science.gov (United States)

Vigeant, Michelle C.

Room acoustics computer modeling and auralizations are useful tools when designing or modifying acoustically sensitive spaces. In this dissertation, the input parameter of source directivity has been studied in great detail to determine first its effect in room acoustics computer models and secondly how to better incorporate the directional source characteristics into these models to improve auralizations. To increase the accuracy of room acoustics computer models, the source directivity of real sources, such as musical instruments, must be included in the models. The traditional method for incorporating source directivity into room acoustics computer models involves inputting the measured static directivity data taken every 10° in a sphere-shaped pattern around the source. This data can be entered into the room acoustics software to create a directivity balloon, which is used in the ray tracing algorithm to simulate the room impulse response. The first study in this dissertation shows that using directional sources over an omni-directional source in room acoustics computer models produces significant differences both in terms of calculated room acoustics parameters and auralizations. The room acoustics computer model was also validated in terms of accurately incorporating the input source directivity. A recently proposed technique for creating auralizations using a multi-channel source representation has been investigated with numerous subjective studies, applied to both solo instruments and an orchestra. The method of multi-channel auralizations involves obtaining multi-channel anechoic recordings of short melodies from various instruments and creating individual channel auralizations. These auralizations are then combined to create a total multi-channel auralization. Through many subjective studies, this process was shown to be effective in terms of improving the realism and source width of the auralizations in a number of cases, and also modeling different

Adverse Selection Models with Three States of Nature

Directory of Open Access Journals (Sweden)

Daniela MARINESCU

2011-02-01

Full Text Available In the paper we analyze an adverse selection model with three states of nature, where both the Principal and the Agent are risk neutral. When solving the model, we use the informational rents and the efforts as variables. We derive the optimal contract in the situation of asymmetric information. The paper ends with the characteristics of the optimal contract and the main conclusions of the model.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

International Nuclear Information System (INIS)

Zhou, Z; Folkert, M; Wang, J

2016-01-01

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z; Folkert, M; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

Stimulus selection and tracking during urination: autoshaping directed behavior with toilet targets.

Science.gov (United States)

Siegel, R K

1977-01-01

A simple procedure is described for investigating stimuli selected as targets during urination in the commode. Ten normal males preferred a floating target that could be tracked to a series of stationary targets. This technique was used to bring misdirected urinations in a severely retarded male under rapid stimulus control of a floating target in the commode. The float stimulus was also evaluated with nine institionalized, moderately retarded males and results indicated rapid autoshaping of directed urination without the use of verbal instructions or conventional toilet training. The technique can be applied in training children to control misdirected urinations in institution for the retarded, in psychiatric wards with regressed populations, and in certain male school dormitories. PMID:885828

Tools for model-independent bounds in direct dark matter searches

DEFF Research Database (Denmark)

Cirelli, M.; Del Nobile, E.; Panci, P.

2013-01-01

We discuss a framework (based on non-relativistic operators) and a self-contained set of numerical tools to derive the bounds from some current direct detection experiments on virtually any arbitrary model of Dark Matter elastically scattering on nuclei.......We discuss a framework (based on non-relativistic operators) and a self-contained set of numerical tools to derive the bounds from some current direct detection experiments on virtually any arbitrary model of Dark Matter elastically scattering on nuclei....

Economic assessment model architecture for AGC/AVLIS selection

International Nuclear Information System (INIS)

Hoglund, R.L.

1984-01-01

The economic assessment model architecture described provides the flexibility and completeness in economic analysis that the selection between AGC and AVLIS demands. Process models which are technology-specific will provide the first-order responses of process performance and cost to variations in process parameters. The economics models can be used to test the impacts of alternative deployment scenarios for a technology. Enterprise models provide global figures of merit for evaluating the DOE perspective on the uranium enrichment enterprise, and business analysis models compute the financial parameters from the private investor's viewpoint

Acoustic noise alters selective attention processes as indicated by direct current (DC) brain potential changes.

Science.gov (United States)

Trimmel, Karin; Schätzer, Julia; Trimmel, Michael

2014-09-26

Acoustic environmental noise, even of low to moderate intensity, is known to adversely affect information processing in animals and humans via attention mechanisms. In particular, facilitation and inhibition of information processing are basic functions of selective attention. Such mechanisms can be investigated by analyzing brain potentials under conditions of externally directed attention (intake of environmental information) versus internally directed attention (rejection of environmental stimuli and focusing on memory/planning processes). This study investigated brain direct current (DC) potential shifts-which are discussed to represent different states of cortical activation-of tasks that require intake and rejection of environmental information under noise. It was hypothesized that without background noise rejection tasks would show more positive DC potential changes compared to intake tasks and that under noise both kinds of tasks would show positive DC shifts as an expression of cortical inhibition caused by noise. DC potential shifts during intake and rejection tasks were analyzed at 16 standard locations in 45 persons during irrelevant speech or white noise vs. control condition. Without noise, rejection tasks were associated with more positive DC potential changes compared to intake tasks. During background noise, however, this difference disappeared and both kinds of tasks led to positive DC shifts. Results suggest-besides some limitations-that noise modulates selective attention mechanisms by switching to an environmental information processing and noise rejection mode, which could represent a suggested "attention shift". Implications for fMRI studies as well as for public health in learning and performance environments including susceptible persons are discussed.

Acoustic Noise Alters Selective Attention Processes as Indicated by Direct Current (DC Brain Potential Changes

Directory of Open Access Journals (Sweden)

Karin Trimmel

2014-09-01

Full Text Available Acoustic environmental noise, even of low to moderate intensity, is known to adversely affect information processing in animals and humans via attention mechanisms. In particular, facilitation and inhibition of information processing are basic functions of selective attention. Such mechanisms can be investigated by analyzing brain potentials under conditions of externally directed attention (intake of environmental information versus internally directed attention (rejection of environmental stimuli and focusing on memory/planning processes. This study investigated brain direct current (DC potential shifts—which are discussed to represent different states of cortical activation—of tasks that require intake and rejection of environmental information under noise. It was hypothesized that without background noise rejection tasks would show more positive DC potential changes compared to intake tasks and that under noise both kinds of tasks would show positive DC shifts as an expression of cortical inhibition caused by noise. DC potential shifts during intake and rejection tasks were analyzed at 16 standard locations in 45 persons during irrelevant speech or white noise vs. control condition. Without noise, rejection tasks were associated with more positive DC potential changes compared to intake tasks. During background noise, however, this difference disappeared and both kinds of tasks led to positive DC shifts. Results suggest—besides some limitations—that noise modulates selective attention mechanisms by switching to an environmental information processing and noise rejection mode, which could represent a suggested “attention shift”. Implications for fMRI studies as well as for public health in learning and performance environments including susceptible persons are discussed.

A decision theoretic framework for profit maximization in direct marketing

NARCIS (Netherlands)

Muus, L.; van der Scheer, H.; Wansbeek, T.J.; Montgomery, A.; Franses, P.H.B.F.

2002-01-01

One of the most important issues facing a firm involved in direct marketing is the selection of addresses from a mailing list. When the parameters of the model describing consumers' reaction to a mailing are known, addresses for a future mailing can be selected in a profit-maximizing way. Usually,

The Use of Evolution in a Central Action Selection Model

Directory of Open Access Journals (Sweden)

F. Montes-Gonzalez

2007-01-01

Full Text Available The use of effective central selection provides flexibility in design by offering modularity and extensibility. In earlier papers we have focused on the development of a simple centralized selection mechanism. Our current goal is to integrate evolutionary methods in the design of non-sequential behaviours and the tuning of specific parameters of the selection model. The foraging behaviour of an animal robot (animat has been modelled in order to integrate the sensory information from the robot to perform selection that is nearly optimized by the use of genetic algorithms. In this paper we present how selection through optimization finally arranges the pattern of presented behaviours for the foraging task. Hence, the execution of specific parts in a behavioural pattern may be ruled out by the tuning of these parameters. Furthermore, the intensive use of colour segmentation from a colour camera for locating a cylinder sets a burden on the calculations carried out by the genetic algorithm.