The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

PubMed Central

Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

2015-01-01

The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

A CLIPS-based expert system for the evaluation and selection of robots

NASA Technical Reports Server (NTRS)

Nour, Mohamed A.; Offodile, Felix O.; Madey, Gregory R.

1994-01-01

This paper describes the development of a prototype expert system for intelligent selection of robots for manufacturing operations. The paper first develops a comprehensive, three-stage process to model the robot selection problem. The decisions involved in this model easily lend themselves to an expert system application. A rule-based system, based on the selection model, is developed using the CLIPS expert system shell. Data about actual robots is used to test the performance of the prototype system. Further extensions to the rule-based system for data handling and interfacing capabilities are suggested.

A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

PubMed Central

Beissinger, Timothy M.; Hirsch, Candice N.; Vaillancourt, Brieanne; Deshpande, Shweta; Barry, Kerrie; Buell, C. Robin; Kaeppler, Shawn M.; Gianola, Daniel; de Leon, Natalia

2014-01-01

A genome-wide scan to detect evidence of selection was conducted in the Golden Glow maize long-term selection population. The population had been subjected to selection for increased number of ears per plant for 30 generations, with an empirically estimated effective population size ranging from 384 to 667 individuals and an increase of more than threefold in the number of ears per plant. Allele frequencies at >1.2 million single-nucleotide polymorphism loci were estimated from pooled whole-genome resequencing data, and FST values across sliding windows were employed to assess divergence between the population preselection and the population postselection. Twenty-eight highly divergent regions were identified, with half of these regions providing gene-level resolution on potentially selected variants. Approximately 93% of the divergent regions do not demonstrate a significant decrease in heterozygosity, which suggests that they are not approaching fixation. Also, most regions display a pattern consistent with a soft-sweep model as opposed to a hard-sweep model, suggesting that selection mostly operated on standing genetic variation. For at least 25% of the regions, results suggest that selection operated on variants located outside of currently annotated coding regions. These results provide insights into the underlying genetic effects of long-term artificial selection and identification of putative genetic elements underlying number of ears per plant in maize. PMID:24381334

Modeling HIV-1 Drug Resistance as Episodic Directional Selection

PubMed Central

Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L.; Scheffler, Konrad

2012-01-01

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance. PMID:22589711

Modeling HIV-1 drug resistance as episodic directional selection.

PubMed

Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad

2012-01-01

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

Magnetically multiplexed heating of single domain nanoparticles

NASA Astrophysics Data System (ADS)

Christiansen, M. G.; Senko, A. W.; Chen, R.; Romero, G.; Anikeeva, P.

2014-05-01

Selective hysteretic heating of multiple collocated types of single domain magnetic nanoparticles (SDMNPs) by alternating magnetic fields (AMFs) may offer a useful tool for biomedical applications. The possibility of "magnetothermal multiplexing" has not yet been realized, in part due to prevalent use of linear response theory to model SDMNP heating in AMFs. Dynamic hysteresis modeling suggests that specific driving conditions play an underappreciated role in determining optimal material selection strategies for high heat dissipation. Motivated by this observation, magnetothermal multiplexing is theoretically predicted and empirically demonstrated by selecting SDMNPs with properties that suggest optimal hysteretic heat dissipation at dissimilar AMF driving conditions. This form of multiplexing could effectively offer multiple channels for minimally invasive biological signaling applications.

Stimulus-response compatibility and psychological refractory period effects: implications for response selection

NASA Technical Reports Server (NTRS)

Lien, Mei-Ching; Proctor, Robert W.

2002-01-01

The purpose of this paper was to provide insight into the nature of response selection by reviewing the literature on stimulus-response compatibility (SRC) effects and the psychological refractory period (PRP) effect individually and jointly. The empirical findings and theoretical explanations of SRC effects that have been studied within a single-task context suggest that there are two response-selection routes-automatic activation and intentional translation. In contrast, all major PRP models reviewed in this paper have treated response selection as a single processing stage. In particular, the response-selection bottleneck (RSB) model assumes that the processing of Task 1 and Task 2 comprises two separate streams and that the PRP effect is due to a bottleneck located at response selection. Yet, considerable evidence from studies of SRC in the PRP paradigm shows that the processing of the two tasks is more interactive than is suggested by the RSB model and by most other models of the PRP effect. The major implication drawn from the studies of SRC effects in the PRP context is that response activation is a distinct process from final response selection. Response activation is based on both long-term and short-term task-defined S-R associations and occurs automatically and in parallel for the two tasks. The final response selection is an intentional act required even for highly compatible and practiced tasks and is restricted to processing one task at a time. Investigations of SRC effects and response-selection variables in dual-task contexts should be conducted more systematically because they provide significant insight into the nature of response-selection mechanisms.

High Selection Pressure Promotes Increase in Cumulative Adaptive Culture

PubMed Central

Vegvari, Carolin; Foley, Robert A.

2014-01-01

The evolution of cumulative adaptive culture has received widespread interest in recent years, especially the factors promoting its occurrence. Current evolutionary models suggest that an increase in population size may lead to an increase in cultural complexity via a higher rate of cultural transmission and innovation. However, relatively little attention has been paid to the role of natural selection in the evolution of cultural complexity. Here we use an agent-based simulation model to demonstrate that high selection pressure in the form of resource pressure promotes the accumulation of adaptive culture in spite of small population sizes and high innovation costs. We argue that the interaction of demography and selection is important, and that neither can be considered in isolation. We predict that an increase in cultural complexity is most likely to occur under conditions of population pressure relative to resource availability. Our model may help to explain why culture change can occur without major environmental change. We suggest that understanding the interaction between shifting selective pressures and demography is essential for explaining the evolution of cultural complexity. PMID:24489724

How Reliable is Bayesian Model Averaging Under Noisy Data? Statistical Assessment and Implications for Robust Model Selection

NASA Astrophysics Data System (ADS)

Schöniger, Anneli; Wöhling, Thomas; Nowak, Wolfgang

2014-05-01

Bayesian model averaging ranks the predictive capabilities of alternative conceptual models based on Bayes' theorem. The individual models are weighted with their posterior probability to be the best one in the considered set of models. Finally, their predictions are combined into a robust weighted average and the predictive uncertainty can be quantified. This rigorous procedure does, however, not yet account for possible instabilities due to measurement noise in the calibration data set. This is a major drawback, since posterior model weights may suffer a lack of robustness related to the uncertainty in noisy data, which may compromise the reliability of model ranking. We present a new statistical concept to account for measurement noise as source of uncertainty for the weights in Bayesian model averaging. Our suggested upgrade reflects the limited information content of data for the purpose of model selection. It allows us to assess the significance of the determined posterior model weights, the confidence in model selection, and the accuracy of the quantified predictive uncertainty. Our approach rests on a brute-force Monte Carlo framework. We determine the robustness of model weights against measurement noise by repeatedly perturbing the observed data with random realizations of measurement error. Then, we analyze the induced variability in posterior model weights and introduce this "weighting variance" as an additional term into the overall prediction uncertainty analysis scheme. We further determine the theoretical upper limit in performance of the model set which is imposed by measurement noise. As an extension to the merely relative model ranking, this analysis provides a measure of absolute model performance. To finally decide, whether better data or longer time series are needed to ensure a robust basis for model selection, we resample the measurement time series and assess the convergence of model weights for increasing time series length. We illustrate our suggested approach with an application to model selection between different soil-plant models following up on a study by Wöhling et al. (2013). Results show that measurement noise compromises the reliability of model ranking and causes a significant amount of weighting uncertainty, if the calibration data time series is not long enough to compensate for its noisiness. This additional contribution to the overall predictive uncertainty is neglected without our approach. Thus, we strongly advertise to include our suggested upgrade in the Bayesian model averaging routine.

Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland

USGS Publications Warehouse

Hill, Mary C.; L. Foglia,; S. W. Mehl,; P. Burlando,

2013-01-01

Model adequacy is evaluated with alternative models rated using model selection criteria (AICc, BIC, and KIC) and three other statistics. Model selection criteria are tested with cross-validation experiments and insights for using alternative models to evaluate model structural adequacy are provided. The study is conducted using the computer codes UCODE_2005 and MMA (MultiModel Analysis). One recharge alternative is simulated using the TOPKAPI hydrological model. The predictions evaluated include eight heads and three flows located where ecological consequences and model precision are of concern. Cross-validation is used to obtain measures of prediction accuracy. Sixty-four models were designed deterministically and differ in representation of river, recharge, bedrock topography, and hydraulic conductivity. Results include: (1) What may seem like inconsequential choices in model construction may be important to predictions. Analysis of predictions from alternative models is advised. (2) None of the model selection criteria consistently identified models with more accurate predictions. This is a disturbing result that suggests to reconsider the utility of model selection criteria, and/or the cross-validation measures used in this work to measure model accuracy. (3) KIC displayed poor performance for the present regression problems; theoretical considerations suggest that difficulties are associated with wide variations in the sensitivity term of KIC resulting from the models being nonlinear and the problems being ill-posed due to parameter correlations and insensitivity. The other criteria performed somewhat better, and similarly to each other. (4) Quantities with high leverage are more difficult to predict. The results are expected to be generally applicable to models of environmental systems.

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

PubMed

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement.

Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

NASA Astrophysics Data System (ADS)

Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

2017-03-01

Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction.

Characterization and applications of reversed-phase column selectivity based on the hydrophobic-subtraction model.

PubMed

Marchand, D H; Snyder, L R; Dolan, J W

2008-05-16

A total of 371 reversed-phase columns have now been characterized in terms of selectivity, based on five solute-column interactions (the hydrophobic-subtraction model). The present study illustrates the use of these data for interpreting peak-tailing and column stability. New insights are also provided concerning column selectivity as a function of ligand and silica type, and the selection of columns for orthogonal separations is re-examined. Some suggestions for the quality control of reversed-phase columns during manufacture are offered.

An Associative Index Model for the Results List Based on Vannevar Bush's Selection Concept

ERIC Educational Resources Information Center

Cole, Charles; Julien, Charles-Antoine; Leide, John E.

2010-01-01

Introduction: We define the results list problem in information search and suggest the "associative index model", an ad-hoc, user-derived indexing solution based on Vannevar Bush's description of an associative indexing approach for his memex machine. We further define what selection means in indexing terms with reference to Charles…

A Common Capacity Limitation for Response and Item Selection in Working Memory

ERIC Educational Resources Information Center

Janczyk, Markus

2017-01-01

Successful completion of any cognitive task requires selecting a particular action and the object the action is applied to. Oberauer (2009) suggested a working memory (WM) model comprising a declarative and a procedural part with analogous structures. One important assumption of this model is that both parts work independently of each other, and…

Similarity selection and the evolution of sex: revisiting the red queen.

PubMed

Agrawal, Aneil F

2006-08-01

For over 25 years, many evolutionary ecologists have believed that sexual reproduction occurs because it allows hosts to change genotypes each generation and thereby evade their coevolving parasites. However, recent influential theoretical analyses suggest that, though parasites can select for sex under some conditions, they often select against it. These models assume that encounters between hosts and parasites are completely random. Because of this assumption, the fitness of a host depends only on its own genotype ("genotypic selection"). If a host is even slightly more likely to encounter a parasite transmitted by its mother than expected by random chance, then the fitness of a host also depends on its genetic similarity to its mother ("similarity selection"). A population genetic model is presented here that includes both genotypic and similarity selection, allowing them to be directly compared in the same framework. It is shown that similarity selection is a much more potent force with respect to the evolution of sex than is genotypic selection. Consequently, similarity selection can drive the evolution of sex even if it is much weaker than genotypic selection with respect to fitness. Examination of explicit coevolutionary models reveals that even a small degree of mother-offspring parasite transmission can cause parasites to favor sex rather than oppose it. In contrast to previous predictions, the model shows that weakly virulent parasites are more likely to favor sex than are highly virulent ones. Parasites have figured prominently in discussions of the evolution of sex, but recent models suggest that parasites often select against sex rather than for it. With the inclusion of small and realistic exposure biases, parasites are much more likely to favor sex. Though parasites alone may not provide a complete explanation for sex, the results presented here expand the potential for parasites to contribute to the maintenance of sex rather than act against it.

Adaptive Modeling Procedure Selection by Data Perturbation.

PubMed

Zhang, Yongli; Shen, Xiaotong

2015-10-01

Many procedures have been developed to deal with the high-dimensional problem that is emerging in various business and economics areas. To evaluate and compare these procedures, modeling uncertainty caused by model selection and parameter estimation has to be assessed and integrated into a modeling process. To do this, a data perturbation method estimates the modeling uncertainty inherited in a selection process by perturbing the data. Critical to data perturbation is the size of perturbation, as the perturbed data should resemble the original dataset. To account for the modeling uncertainty, we derive the optimal size of perturbation, which adapts to the data, the model space, and other relevant factors in the context of linear regression. On this basis, we develop an adaptive data-perturbation method that, unlike its nonadaptive counterpart, performs well in different situations. This leads to a data-adaptive model selection method. Both theoretical and numerical analysis suggest that the data-adaptive model selection method adapts to distinct situations in that it yields consistent model selection and optimal prediction, without knowing which situation exists a priori. The proposed method is applied to real data from the commodity market and outperforms its competitors in terms of price forecasting accuracy.

Paying for Primary Care: The Factors Associated with Physician Self-selection into Payment Models.

PubMed

Rudoler, David; Deber, Raisa; Barnsley, Janet; Glazier, Richard H; Dass, Adrian Rohit; Laporte, Audrey

2015-09-01

To determine the factors associated with primary care physician self-selection into different payment models, we used a panel of eight waves of administrative data for all primary care physicians who practiced in Ontario between 2003/2004 and 2010/2011. We used a mixed effects logistic regression model to estimate physicians' choice of three alternative payment models: fee for service, enhanced fee for service, and blended capitation. We found that primary care physicians self-selected into payment models based on existing practice characteristics. Physicians with more complex patient populations were less likely to switch into capitation-based payment models where higher levels of effort were not financially rewarded. These findings suggested that investigations aimed at assessing the impact of different primary care reimbursement models on outcomes, including costs and access, should first account for potential selection effects. Copyright © 2015 John Wiley & Sons, Ltd.

Contributions of natural and sexual selection to the evolution of premating reproductive isolation: a research agenda.

PubMed

Safran, Rebecca J; Scordato, Elizabeth S C; Symes, Laurel B; Rodríguez, Rafael L; Mendelson, Tamra C

2013-11-01

Speciation by divergent natural selection is well supported. However, the role of sexual selection in speciation is less well understood due to disagreement about whether sexual selection is a mechanism of evolution separate from natural selection, as well as confusion about various models and tests of sexual selection. Here, we outline how sexual selection and natural selection are different mechanisms of evolutionary change, and suggest that this distinction is critical when analyzing the role of sexual selection in speciation. Furthermore, we clarify models of sexual selection with respect to their interaction with ecology and natural selection. In doing so, we outline a research agenda for testing hypotheses about the relative significance of divergent sexual and natural selection in the evolution of reproductive isolation. Copyright © 2013 Elsevier Ltd. All rights reserved.

The dark side of incremental learning: a model of cumulative semantic interference during lexical access in speech production.

PubMed

Oppenheim, Gary M; Dell, Gary S; Schwartz, Myrna F

2010-02-01

Naming a picture of a dog primes the subsequent naming of a picture of a dog (repetition priming) and interferes with the subsequent naming of a picture of a cat (semantic interference). Behavioral studies suggest that these effects derive from persistent changes in the way that words are activated and selected for production, and some have claimed that the findings are only understandable by positing a competitive mechanism for lexical selection. We present a simple model of lexical retrieval in speech production that applies error-driven learning to its lexical activation network. This model naturally produces repetition priming and semantic interference effects. It predicts the major findings from several published experiments, demonstrating that these effects may arise from incremental learning. Furthermore, analysis of the model suggests that competition during lexical selection is not necessary for semantic interference if the learning process is itself competitive. Copyright 2009 Elsevier B.V. All rights reserved.

How Darwinian is cultural evolution?

PubMed Central

Claidière, Nicolas; Scott-Phillips, Thomas C.; Sperber, Dan

2014-01-01

Darwin-inspired population thinking suggests approaching culture as a population of items of different types, whose relative frequencies may change over time. Three nested subtypes of populational models can be distinguished: evolutionary, selectional and replicative. Substantial progress has been made in the study of cultural evolution by modelling it within the selectional frame. This progress has involved idealizing away from phenomena that may be critical to an adequate understanding of culture and cultural evolution, particularly the constructive aspect of the mechanisms of cultural transmission. Taking these aspects into account, we describe cultural evolution in terms of cultural attraction, which is populational and evolutionary, but only selectional under certain circumstances. As such, in order to model cultural evolution, we must not simply adjust existing replicative or selectional models but we should rather generalize them, so that, just as replicator-based selection is one form that Darwinian selection can take, selection itself is one of several different forms that attraction can take. We present an elementary formalization of the idea of cultural attraction. PMID:24686939

How Darwinian is cultural evolution?

PubMed

Claidière, Nicolas; Scott-Phillips, Thomas C; Sperber, Dan

2014-05-19

Darwin-inspired population thinking suggests approaching culture as a population of items of different types, whose relative frequencies may change over time. Three nested subtypes of populational models can be distinguished: evolutionary, selectional and replicative. Substantial progress has been made in the study of cultural evolution by modelling it within the selectional frame. This progress has involved idealizing away from phenomena that may be critical to an adequate understanding of culture and cultural evolution, particularly the constructive aspect of the mechanisms of cultural transmission. Taking these aspects into account, we describe cultural evolution in terms of cultural attraction, which is populational and evolutionary, but only selectional under certain circumstances. As such, in order to model cultural evolution, we must not simply adjust existing replicative or selectional models but we should rather generalize them, so that, just as replicator-based selection is one form that Darwinian selection can take, selection itself is one of several different forms that attraction can take. We present an elementary formalization of the idea of cultural attraction.

Shape Selectivity of Middle Superior Temporal Sulcus Body Patch Neurons

PubMed Central

2017-01-01

Abstract Functional MRI studies in primates have demonstrated cortical regions that are strongly activated by visual images of bodies. The presence of such body patches in macaques allows characterization of the stimulus selectivity of their single neurons. Middle superior temporal sulcus body (MSB) patch neurons showed similar stimulus selectivity for natural, shaded, and textured images compared with their silhouettes, suggesting that shape is an important determinant of MSB responses. Here, we examined and modeled the shape selectivity of single MSB neurons. We measured the responses of single MSB neurons to a variety of shapes producing a wide range of responses. We used an adaptive stimulus sampling procedure, selecting and modifying shapes based on the responses of the neuron. Forty percent of shapes that produced the maximal response were rated by humans as animal-like, but the top shape of many MSB neurons was not judged as resembling a body. We fitted the shape selectivity of MSB neurons with a model that parameterizes shapes in terms of curvature and orientation of contour segments, with a pixel-based model, and with layers of units of convolutional neural networks (CNNs). The deep convolutional layers of CNNs provided the best goodness-of-fit, with a median explained explainable variance of the neurons’ responses of 77%. The goodness-of-fit increased along the convolutional layers’ hierarchy but was lower for the fully connected layers. Together with demonstrating the successful modeling of single unit shape selectivity with deep CNNs, the data suggest that semantic or category knowledge determines only slightly the single MSB neuron’s shape selectivity. PMID:28660250

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops

PubMed Central

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an “island model” inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement. PMID:27115872

The Role of Nice and Nasty Theory of Mind in Teacher-Selected Peer Models for Adolescents with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Laghi, Fiorenzo; Lonigro, Antonia; Levanto, Simona; Ferraro, Maurizio; Baumgartner, Emma; Baiocco, Roberto

2016-01-01

The study aimed at verifying if nice and nasty theory of mind behaviors, in association with teachers' peer buddy nomination, could be used to correctly select peer models for adolescents with autism spectrum disorder. Mentalizing abilities and emotional and behavioral characteristics of 601 adolescents were assessed. Results suggest that teachers…

Gene flow from domesticated species to wild relatives: migration load in a model of multivariate selection.

PubMed

Tufto, Jarle

2010-01-01

Domesticated species frequently spread their genes into populations of wild relatives through interbreeding. The domestication process often involves artificial selection for economically desirable traits. This can lead to an indirect response in unknown correlated traits and a reduction in fitness of domesticated individuals in the wild. Previous models for the effect of gene flow from domesticated species to wild relatives have assumed that evolution occurs in one dimension. Here, I develop a quantitative genetic model for the balance between migration and multivariate stabilizing selection. Different forms of correlational selection consistent with a given observed ratio between average fitness of domesticated and wild individuals offsets the phenotypic means at migration-selection balance away from predictions based on simpler one-dimensional models. For almost all parameter values, correlational selection leads to a reduction in the migration load. For ridge selection, this reduction arises because the distance the immigrants deviates from the local optimum in effect is reduced. For realistic parameter values, however, the effect of correlational selection on the load is small, suggesting that simpler one-dimensional models may still be adequate in terms of predicting mean population fitness and viability.

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

PubMed

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Fitness consequences of sex-specific selection.

PubMed

Connallon, Tim; Cox, Robert M; Calsbeek, Ryan

2010-06-01

Theory suggests that sex-specific selection can facilitate adaptation in sexually reproducing populations. However, sexual conflict theory and recent experiments indicate that sex-specific selection is potentially costly due to sexual antagonism: alleles harmful to one sex can accumulate within a population because they are favored in the other sex. Whether sex-specific selection provides a net fitness benefit or cost depends, in part, on the relative frequency and strength of sexually concordant versus sexually antagonistic selection throughout a species' genome. Here, we model the net fitness consequences of sex-specific selection while explicitly considering both sexually concordant and sexually antagonistic selection. The model shows that, even when sexual antagonism is rare, the fitness costs that it imposes will generally overwhelm fitness benefits of sexually concordant selection. Furthermore, the cost of sexual antagonism is, at best, only partially resolved by the evolution of sex-limited gene expression. To evaluate the key parameters of the model, we analyze an extensive dataset of sex-specific selection gradients from wild populations, along with data from the experimental evolution literature. The model and data imply that sex-specific selection may likely impose a net cost on sexually reproducing species, although additional research will be required to confirm this conclusion.

Continuous and discontinuous phase transitions in the evolution of a polygenic trait under stabilizing selective pressure

NASA Astrophysics Data System (ADS)

Fierro, Annalisa; Cocozza, Sergio; Monticelli, Antonella; Scala, Giovanni; Miele, Gennaro

2017-06-01

The presence of phenomena analogous to phase transition in Statistical Mechanics has been suggested in the evolution of a polygenic trait under stabilizing selection, mutation and genetic drift. By using numerical simulations of a model system, we analyze the evolution of a population of N diploid hermaphrodites in random mating regime. The population evolves under the effect of drift, selective pressure in form of viability on an additive polygenic trait, and mutation. The analysis allows to determine a phase diagram in the plane of mutation rate and strength of selection. The involved pattern of phase transitions is characterized by a line of critical points for weak selective pressure (smaller than a threshold), whereas discontinuous phase transitions, characterized by metastable hysteresis, are observed for strong selective pressure. A finite-size scaling analysis suggests the analogy between our system and the mean-field Ising model for selective pressure approaching the threshold from weaker values. In this framework, the mutation rate, which allows the system to explore the accessible microscopic states, is the parameter controlling the transition from large heterozygosity ( disordered phase) to small heterozygosity ( ordered one).

Genome-wide heterogeneity of nucleotide substitution model fit.

PubMed

Arbiza, Leonardo; Patricio, Mateus; Dopazo, Hernán; Posada, David

2011-01-01

At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.

A Heckman selection model for the safety analysis of signalized intersections

PubMed Central

Wong, S. C.; Zhu, Feng; Pei, Xin; Huang, Helai; Liu, Youjun

2017-01-01

Purpose The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods 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. Results The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions 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. PMID:28732050

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Bayesian selection of misspecified models is overconfident and may cause spurious posterior probabilities for phylogenetic trees.

PubMed

Yang, Ziheng; Zhu, Tianqi

2018-02-20

The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this overconfidence are unknown. In general, the performance of Bayesian selection of misspecified models is poorly understood, even though this is of great scientific interest since models are never true in real data analysis. Here we characterize the asymptotic behavior of Bayesian model selection and show that when the competing models are equally wrong, Bayesian model selection exhibits surprising and polarized behaviors in large datasets, supporting one model with full force while rejecting the others. If one model is slightly less wrong than the other, the less wrong model will eventually win when the amount of data increases, but the method may become overconfident before it becomes reliable. We suggest that this extreme behavior may be a major factor for the spuriously high posterior probabilities for evolutionary trees. The philosophical implications of our results to the application of Bayesian model selection to evaluate opposing scientific hypotheses are yet to be explored, as are the behaviors of non-Bayesian methods in similar situations.

Foraging Behaviour in Magellanic Woodpeckers Is Consistent with a Multi-Scale Assessment of Tree Quality

PubMed Central

Vergara, Pablo M.; Soto, Gerardo E.; Rodewald, Amanda D.; Meneses, Luis O.; Pérez-Hernández, Christian G.

2016-01-01

Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox’s proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales. PMID:27416115

Foraging Behaviour in Magellanic Woodpeckers Is Consistent with a Multi-Scale Assessment of Tree Quality.

PubMed

Vergara, Pablo M; Soto, Gerardo E; Moreira-Arce, Darío; Rodewald, Amanda D; Meneses, Luis O; Pérez-Hernández, Christian G

2016-01-01

Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox's proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales.

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

SOME USES OF MODELS OF QUANTITATIVE GENETIC SELECTION IN SOCIAL SCIENCE.

PubMed

Weight, Michael D; Harpending, Henry

2017-01-01

The theory of selection of quantitative traits is widely used in evolutionary biology, agriculture and other related fields. The fundamental model known as the breeder's equation is simple, robust over short time scales, and it is often possible to estimate plausible parameters. In this paper it is suggested that the results of this model provide useful yardsticks for the description of social traits and the evaluation of transmission models. The differences on a standard personality test between samples of Old Order Amish and Indiana rural young men from the same county and the decline of homicide in Medieval Europe are used as illustrative examples of the overall approach. It is shown that the decline of homicide is unremarkable under a threshold model while the differences between rural Amish and non-Amish young men are too large to be a plausible outcome of simple genetic selection in which assortative mating by affiliation is equivalent to truncation selection.

The effects of modeling contingencies in the treatment of food selectivity in children with autism.

PubMed

Fu, Sherrene B; Penrod, Becky; Fernand, Jonathan K; Whelan, Colleen M; Griffith, Kristin; Medved, Shannon

2015-11-01

The current study investigated the effectiveness of stating and modeling contingencies in increasing food consumption for two children with food selectivity. Results suggested that stating and modeling a differential reinforcement (DR) contingency for food consumption was effective in increasing consumption of two target foods for one child, and stating and modeling a DR plus nonremoval of the spoon contingency was effective in increasing consumption of the remaining food for the first child and all target foods for the second child. © The Author(s) 2015.

Increasing Student Motivation and the Perception of Chemistry's Relevance in the Classroom by Learning about Tattooing from a Chemical and Societal View

ERIC Educational Resources Information Center

Stuckey, Marc; Eilks, Ingo

2014-01-01

This paper presents a study on tattooing as a topic for chemistry education. The selection of the topic was inspired by a newly suggested framework, which focuses on the question of relevance of science education. The aim of this case was to get evidence on how topics selected based on the suggested model of relevance of science education affect…

Effects of selection and training on unit-level performance over time: a latent growth modeling approach.

PubMed

Van Iddekinge, Chad H; Ferris, Gerald R; Perrewé, Pamela L; Blass, Fred R; Heetderks, Thomas D; Perryman, Alexa A

2009-07-01

Surprisingly few data exist concerning whether and how utilization of job-related selection and training procedures affects different aspects of unit or organizational performance over time. The authors used longitudinal data from a large fast-food organization (N = 861 units) to examine how change in use of selection and training relates to change in unit performance. Latent growth modeling analyses revealed significant variation in both the use and the change in use of selection and training across units. Change in selection and training was related to change in 2 proximal unit outcomes: customer service performance and retention. Change in service performance, in turn, was related to change in the more distal outcome of unit financial performance (i.e., profits). Selection and training also affected financial performance, both directly and indirectly (e.g., through service performance). Finally, results of a cross-lagged panel analysis suggested the existence of a reciprocal causal relationship between the utilization of the human resources practices and unit performance. However, there was some evidence to suggest that selection and training may be associated with different causal sequences, such that use of the training procedure appeared to lead to unit performance, whereas unit performance appeared to lead to use of the selection procedure.

Modeling extreme PM10 concentration in Malaysia using generalized extreme value distribution

NASA Astrophysics Data System (ADS)

Hasan, Husna; Mansor, Nadiah; Salleh, Nur Hanim Mohd

2015-05-01

Extreme PM10 concentration from the Air Pollutant Index (API) at thirteen monitoring stations in Malaysia is modeled using the Generalized Extreme Value (GEV) distribution. The data is blocked into monthly selection period. The Mann-Kendall (MK) test suggests a non-stationary model so two models are considered for the stations with trend. The likelihood ratio test is used to determine the best fitted model and the result shows that only two stations favor the non-stationary model (Model 2) while the other eleven stations favor stationary model (Model 1). The return level of PM10 concentration that is expected to exceed the maximum once within a selected period is obtained.

The Assessment of Climatological Impacts on Agricultural Production and Residential Energy Demand

NASA Astrophysics Data System (ADS)

Cooter, Ellen Jean

The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter -disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication. Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand. The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model. The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology -free" modeled energy demand or input weather variables which would correspond to that contained in observed state -level residential energy use was detected. It is suggested that this trend is largely the result of non-weather factors such as population and home usage patterns rather than regional climate change. Year-to-year changes in modeled residential heating demand on the order of 10('6) Btu's per household were determined and later related to state -level components of the Oklahoma economy. Products developed include the definition of regional forecast areas, likelihood estimates of extreme seasonal conditions and an energy/climate index. This information is communicated in economic terms through an input/output model which is used to estimate changes in Gross State Product and Household income attributable to weather variability.

Indirect Genetic Effects and the Spread of Infectious Disease: Are We Capturing the Full Heritable Variation Underlying Disease Prevalence?

PubMed Central

Lipschutz-Powell, Debby; Woolliams, John A.; Bijma, Piter; Doeschl-Wilson, Andrea B.

2012-01-01

Reducing disease prevalence through selection for host resistance offers a desirable alternative to chemical treatment. Selection for host resistance has proven difficult, however, due to low heritability estimates. These low estimates may be caused by a failure to capture all the relevant genetic variance in disease resistance, as genetic analysis currently is not taylored to estimate genetic variation in infectivity. Host infectivity is the propensity of transmitting infection upon contact with a susceptible individual, and can be regarded as an indirect effect to disease status. It may be caused by a combination of physiological and behavioural traits. Though genetic variation in infectivity is difficult to measure directly, Indirect Genetic Effect (IGE) models, also referred to as associative effects or social interaction models, allow the estimation of this variance from more readily available binary disease data (infected/non-infected). We therefore generated binary disease data from simulated populations with known amounts of variation in susceptibility and infectivity to test the adequacy of traditional and IGE models. Our results show that a conventional model fails to capture the genetic variation in infectivity inherent in populations with simulated infectivity. An IGE model, on the other hand, does capture some of the variation in infectivity. Comparison with expected genetic variance suggests that there is scope for further methodological improvement, and that potential responses to selection may be greater than values presented here. Nonetheless, selection using an index of estimated direct and indirect breeding values was shown to have a greater genetic selection differential and reduced future disease risk than traditional selection for resistance only. These findings suggest that if genetic variation in infectivity substantially contributes to disease transmission, then breeding designs which explicitly incorporate IGEs might help reduce disease prevalence. PMID:22768088

Selective inhibition of a multicomponent response can be achieved without cost

PubMed Central

Westrick, Zachary; Ivry, Richard B.

2014-01-01

Behavioral flexibility frequently requires the ability to modify an on-going action. In some situations, optimal performance requires modifying some components of an on-going action without interrupting other components of that action. This form of control has been studied with the selective stop-signal task, in which participants are instructed to abort only one movement of a multicomponent response. Previous studies have shown a transient disruption of the nonaborted component, suggesting limitations in our ability to use selective inhibition. This cost has been attributed to a structural limitation associated with the recruitment of a cortico-basal ganglia pathway that allows for the rapid inhibition of action but operates in a relatively generic manner. Using a model-based approach, we demonstrate that, with a modest amount of training and highly compatible stimulus-response mappings, people can perform a selective-stop task without any cost on the nonaborted component. Prior reports of behavioral costs in selective-stop tasks reflect, at least in part, a sampling bias in the method commonly used to estimate such costs. These results suggest that inhibition can be selectively controlled and present a challenge for models of inhibitory control that posit the operation of generic processes. PMID:25339712

A Graphic Overlay Method for Selection of Osteotomy Site in Chronic Radial Head Dislocation: An Evaluation of 3D-printed Bone Models.

PubMed

Kim, Hui Taek; Ahn, Tae Young; Jang, Jae Hoon; Kim, Kang Hee; Lee, Sung Jae; Jung, Duk Young

2017-03-01

Three-dimensional (3D) computed tomography imaging is now being used to generate 3D models for planning orthopaedic surgery, but the process remains time consuming and expensive. For chronic radial head dislocation, we have designed a graphic overlay approach that employs selected 3D computer images and widely available software to simplify the process of osteotomy site selection. We studied 5 patients (2 traumatic and 3 congenital) with unilateral radial head dislocation. These patients were treated with surgery based on traditional radiographs, but they also had full sets of 3D CT imaging done both before and after their surgery: these 3D CT images form the basis for this study. From the 3D CT images, each patient generated 3 sets of 3D-printed bone models: 2 copies of the preoperative condition, and 1 copy of the postoperative condition. One set of the preoperative models was then actually osteotomized and fixed in the manner suggested by our graphic technique. Arcs of rotation of the 3 sets of 3D-printed bone models were then compared. Arcs of rotation of the 3 groups of bone models were significantly different, with the models osteotomized accordingly to our graphic technique having the widest arcs. For chronic radial head dislocation, our graphic overlay approach simplifies the selection of the osteotomy site(s). Three-dimensional-printed bone models suggest that this approach could improve range of motion of the forearm in actual surgical practice. Level IV-therapeutic study.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

How to Choose--and Use--Motion Picture Projectors

ERIC Educational Resources Information Center

Training, 1976

1976-01-01

Suggests techniques for selecting super 8 and 16mm movie projectors for various training and communication needs. Charts list various characteristics for 17 models of 8mm projectors with built-in screen, 7 models without screen, and 33 models of 16mm projectors. (WL)

Response to Selection in Finite Locus Models with Nonadditive Effects.

PubMed

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

2017-05-01

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 variance can be sustained or even increased when nonadditive genetic effects are present. We tested the hypothesis that finite-locus models with both additive and nonadditive genetic effects maintain more additive genetic variance (VA) and realize larger medium- to long-term genetic gains than models with only additive effects when the trait under selection is subject to truncation selection. Four genetic models that included additive, dominance, and additive-by-additive epistatic effects were simulated. The simulated genome for individuals consisted of 25 chromosomes, each with a length of 1 M. One hundred bi-allelic QTL, 4 on each chromosome, were considered. In each generation, 100 sires and 100 dams were mated, producing 5 progeny per mating. The population was selected for a single trait (h2 = 0.1) for 100 discrete generations with selection on phenotype or BLUP-EBV. VA decreased with directional truncation selection even in presence of nonadditive genetic effects. Nonadditive effects influenced long-term response to selection and among genetic models additive gene action had highest response to selection. In addition, in all genetic models, BLUP-EBV resulted in a greater fixation of favorable and unfavorable alleles and higher response than phenotypic selection. In conclusion, for the schemes we simulated, the presence of nonadditive genetic effects had little effect in changes of additive variance and VA decreased by directional selection. © The American Genetic Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection

PubMed Central

Yang, Kai-Fu; Li, Chao-Yi; Li, Yong-Jie

2015-01-01

Both the neurons with orientation-selective and with non-selective surround inhibition have been observed in the primary visual cortex (V1) of primates and cats. Though the inhibition coming from the surround region (named as non-classical receptive field, nCRF) has been considered playing critical role in visual perception, the specific role of orientation-selective and non-selective inhibition in the task of contour detection is less known. To clarify above question, we first carried out computational analysis of the contour detection performance of V1 neurons with different types of surround inhibition, on the basis of which we then proposed two integrated models to evaluate their role in this specific perceptual task by combining the two types of surround inhibition with two different ways. The two models were evaluated with synthetic images and a set of challenging natural images, and the results show that both of the integrated models outperform the typical models with orientation-selective or non-selective inhibition alone. The findings of this study suggest that V1 neurons with different types of center–surround interaction work in cooperative and adaptive ways at least when extracting organized structures from cluttered natural scenes. This work is expected to inspire efficient phenomenological models for engineering applications in field of computational machine-vision. PMID:26136664

Potential roles of the interaction between model V1 neurons with orientation-selective and non-selective surround inhibition in contour detection.

PubMed

Yang, Kai-Fu; Li, Chao-Yi; Li, Yong-Jie

2015-01-01

Both the neurons with orientation-selective and with non-selective surround inhibition have been observed in the primary visual cortex (V1) of primates and cats. Though the inhibition coming from the surround region (named as non-classical receptive field, nCRF) has been considered playing critical role in visual perception, the specific role of orientation-selective and non-selective inhibition in the task of contour detection is less known. To clarify above question, we first carried out computational analysis of the contour detection performance of V1 neurons with different types of surround inhibition, on the basis of which we then proposed two integrated models to evaluate their role in this specific perceptual task by combining the two types of surround inhibition with two different ways. The two models were evaluated with synthetic images and a set of challenging natural images, and the results show that both of the integrated models outperform the typical models with orientation-selective or non-selective inhibition alone. The findings of this study suggest that V1 neurons with different types of center-surround interaction work in cooperative and adaptive ways at least when extracting organized structures from cluttered natural scenes. This work is expected to inspire efficient phenomenological models for engineering applications in field of computational machine-vision.

A Bayesian Approach to Model Selection in Hierarchical Mixtures-of-Experts Architectures.

PubMed

Tanner, Martin A.; Peng, Fengchun; Jacobs, Robert A.

1997-03-01

There does not exist a statistical model that shows good performance on all tasks. Consequently, the model selection problem is unavoidable; investigators must decide which model is best at summarizing the data for each task of interest. This article presents an approach to the model selection problem in hierarchical mixtures-of-experts architectures. These architectures combine aspects of generalized linear models with those of finite mixture models in order to perform tasks via a recursive "divide-and-conquer" strategy. Markov chain Monte Carlo methodology is used to estimate the distribution of the architectures' parameters. One part of our approach to model selection attempts to estimate the worth of each component of an architecture so that relatively unused components can be pruned from the architecture's structure. A second part of this approach uses a Bayesian hypothesis testing procedure in order to differentiate inputs that carry useful information from nuisance inputs. Simulation results suggest that the approach presented here adheres to the dictum of Occam's razor; simple architectures that are adequate for summarizing the data are favored over more complex structures. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

Contemplating the GANE model using an extreme case paradigm.

PubMed

Geva, Ronny

2016-01-01

Early experiences play a crucial role in programming brain function, affecting selective attention, learning, and memory. Infancy literature suggests an extension of the GANE (glutamate amplifies noradrenergic effects) model to conditions with minimal priority-map inputs, yet suggests qualifications by noting that its efficacy is increased when tonic levels of arousal are maintained in an optimal range, in manners that are age and exposure dependent.

Cognitive and Neural Bases of Skilled Performance

DTIC Science & Technology

1989-05-12

Pergamon, 1958. Broadbent , D.F., A mechanical model for human attention and immediate memory. Psychol. Rev., 64: 205-215’ 1957. Cherry, C. On the...material on the efficiency of selective listening. Amer. J. Psychol., 77: 533-546, 1964. Treisman, A. Strategies and models of selective attention ...cortex reveal suong effects of attention , these results suggest that the visual attentional " filter " may be located at a later stage. This is consistent

The importance of selection in the evolution of blindness in cavefish.

PubMed

Cartwright, Reed A; Schwartz, Rachel S; Merry, Alexandra L; Howell, Megan M

2017-02-07

Blindness has evolved repeatedly in cave-dwelling organisms, and many hypotheses have been proposed to explain this observation, including both accumulation of neutral loss-of-function mutations and adaptation to darkness. Investigating the loss of sight in cave dwellers presents an opportunity to understand the operation of fundamental evolutionary processes, including drift, selection, mutation, and migration. Here we model the evolution of blindness in caves. This model captures the interaction of three forces: (1) selection favoring alleles causing blindness, (2) immigration of sightedness alleles from a surface population, and (3) mutations creating blindness alleles. We investigated the dynamics of this model and determined selection-strength thresholds that result in blindness evolving in caves despite immigration of sightedness alleles from the surface. We estimate that the selection coefficient for blindness would need to be at least 0.005 (and maybe as high as 0.5) for blindness to evolve in the model cave-organism, Astyanax mexicanus. Our results indicate that strong selection is required for the evolution of blindness in cave-dwelling organisms, which is consistent with recent work suggesting a high metabolic cost of eye development.

Genetic signatures of natural selection in a model invasive ascidian

NASA Astrophysics Data System (ADS)

Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

2017-03-01

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.

Selective complexation of K+ and Na+ in simple polarizable ion-ligating systems.

PubMed

Bostick, David L; Brooks, Charles L

2010-09-29

An influx of experimental and theoretical studies of ion transport protein structure has inspired efforts to understand underlying determinants of ionic selectivity. Design principles for selective ion binding can be effectively isolated and interrogated using simplified models composed of a single ion surrounded by a set of ion-ligating molecular species. While quantum mechanical treatments of such systems naturally incorporate electronic degrees of freedom, their computational overhead typically prohibits thorough dynamic sampling of configurational space and, thus, requires approximations when determining ion-selective free energy. As an alternative, we employ dynamical simulations with a polarizable force field to probe the structure and K(+)/Na(+) selectivity in simple models composed of one central K(+)/Na(+) ion surrounded by 0-8 identical model compounds: N-methylacetamide, formamide, or water. In the absence of external restraints, these models represent gas-phase clusters displaying relaxed coordination structures with low coordination number. Such systems display Na(+) selectivity when composed of more than ∼3 organic carbonyl-containing compounds and always display K(+) selectivity when composed of water molecules. Upon imposing restraints that solely enforce specific coordination numbers, we find all models are K(+)-selective when ∼7-8-fold ion coordination is achieved. However, when models composed of the organic compounds provide ∼4-6-fold coordination, they retain their Na(+) selectivity. From these trends, design principles emerge that are of basic importance in the behavior of K(+) channel selectivity filters and suggest a basis not only for K(+) selectivity but also for modulation of block and closure by smaller ions.

Some Empirical Evidence for Latent Trait Model Selection.

ERIC Educational Resources Information Center

Hutten, Leah R.

The results of this study suggest that for purposes of estimating ability by latent trait methods, the Rasch model compares favorably with the three-parameter logistic model. Using estimated parameters to make predictions about 25 actual number-correct score distributions with samples of 1,000 cases each, those predicted by the Rasch model fit the…

Does Learning or Instinct Shape Habitat Selection?

PubMed Central

Nielsen, Scott E.; Shafer, Aaron B. A.; Boyce, Mark S.; Stenhouse, Gordon B.

2013-01-01

Habitat selection is an important behavioural process widely studied for its population-level effects. Models of habitat selection are, however, often fit without a mechanistic consideration. Here, we investigated whether patterns in habitat selection result from instinct or learning for a population of grizzly bears (Ursus arctos) in Alberta, Canada. We found that habitat selection and relatedness were positively correlated in female bears during the fall season, with a trend in the spring, but not during any season for males. This suggests that habitat selection is a learned behaviour because males do not participate in parental care: a genetically predetermined behaviour (instinct) would have resulted in habitat selection and relatedness correlations for both sexes. Geographic distance and home range overlap among animals did not alter correlations indicating that dispersal and spatial autocorrelation had little effect on the observed trends. These results suggest that habitat selection in grizzly bears are partly learned from their mothers, which could have implications for the translocation of wildlife to novel environments. PMID:23341983

Does learning or instinct shape habitat selection?

PubMed

Nielsen, Scott E; Shafer, Aaron B A; Boyce, Mark S; Stenhouse, Gordon B

2013-01-01

Habitat selection is an important behavioural process widely studied for its population-level effects. Models of habitat selection are, however, often fit without a mechanistic consideration. Here, we investigated whether patterns in habitat selection result from instinct or learning for a population of grizzly bears (Ursus arctos) in Alberta, Canada. We found that habitat selection and relatedness were positively correlated in female bears during the fall season, with a trend in the spring, but not during any season for males. This suggests that habitat selection is a learned behaviour because males do not participate in parental care: a genetically predetermined behaviour (instinct) would have resulted in habitat selection and relatedness correlations for both sexes. Geographic distance and home range overlap among animals did not alter correlations indicating that dispersal and spatial autocorrelation had little effect on the observed trends. These results suggest that habitat selection in grizzly bears are partly learned from their mothers, which could have implications for the translocation of wildlife to novel environments.

The nearly neutral and selection theories of molecular evolution under the fisher geometrical framework: substitution rate, population size, and complexity.

PubMed

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A

2012-06-01

The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population's phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however, SR does not have the unrealistic properties of previous nearly neutral models such as the narrow window of selection strengths in which they work. In addition, the SR suggests that compensatory mutations cannot explain the high rate of fixations driven by positive selection currently found in DNA sequences, contrary to what has been previously suggested. We also developed a generalization of SR in which the optimum phenotype can change stochastically due to environmental or physiological shifts, which we called the variable regime (VR). VR models evolution as an interplay between adaptive processes and nearly neutral steady-state processes. When strong environmental fluctuations are incorporated, the process becomes a selection model in which evolutionary rate does not depend on population size, but is critically dependent on the complexity of organisms and mutation size. For SR as well as VR we found that key parameters of molecular evolution are linked by biological factors, and we showed that they cannot be fixed independently by arbitrary criteria, as has usually been assumed in previous molecular evolutionary models.

The Nearly Neutral and Selection Theories of Molecular Evolution Under the Fisher Geometrical Framework: Substitution Rate, Population Size, and Complexity

PubMed Central

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A.

2012-01-01

The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population’s phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however, SR does not have the unrealistic properties of previous nearly neutral models such as the narrow window of selection strengths in which they work. In addition, the SR suggests that compensatory mutations cannot explain the high rate of fixations driven by positive selection currently found in DNA sequences, contrary to what has been previously suggested. We also developed a generalization of SR in which the optimum phenotype can change stochastically due to environmental or physiological shifts, which we called the variable regime (VR). VR models evolution as an interplay between adaptive processes and nearly neutral steady-state processes. When strong environmental fluctuations are incorporated, the process becomes a selection model in which evolutionary rate does not depend on population size, but is critically dependent on the complexity of organisms and mutation size. For SR as well as VR we found that key parameters of molecular evolution are linked by biological factors, and we showed that they cannot be fixed independently by arbitrary criteria, as has usually been assumed in previous molecular evolutionary models. PMID:22426879

Model selection and parameter estimation in structural dynamics using approximate Bayesian computation

NASA Astrophysics Data System (ADS)

Ben Abdessalem, Anis; Dervilis, Nikolaos; Wagg, David; Worden, Keith

2018-01-01

This paper will introduce the use of the approximate Bayesian computation (ABC) algorithm for model selection and parameter estimation in structural dynamics. ABC is a likelihood-free method typically used when the likelihood function is either intractable or cannot be approached in a closed form. To circumvent the evaluation of the likelihood function, simulation from a forward model is at the core of the ABC algorithm. The algorithm offers the possibility to use different metrics and summary statistics representative of the data to carry out Bayesian inference. The efficacy of the algorithm in structural dynamics is demonstrated through three different illustrative examples of nonlinear system identification: cubic and cubic-quintic models, the Bouc-Wen model and the Duffing oscillator. The obtained results suggest that ABC is a promising alternative to deal with model selection and parameter estimation issues, specifically for systems with complex behaviours.

Crossing the Threshold Mindfully: Exploring Rites of Passage Models in Adventure Therapy

ERIC Educational Resources Information Center

Norris, Julian

2011-01-01

Rites of passage models, drawing from ethnographic descriptions of ritualized transition, are widespread in adventure therapy programmes. However, critical literature suggests that: (a) contemporary rites of passage models derive from a selective and sometimes misleading use of ethnographic materials, and (b) the appropriation of initiatory…

A Multidimensional Curriculum Model for Heritage or International Language Instruction.

ERIC Educational Resources Information Center

Lazaruk, Wally

1993-01-01

Describes the Multidimension Curriculum Model for developing a language curriculum and suggests a generic approach to selecting and sequencing learning objectives. Alberta Education used this model to design a new French-as-a-Second-Language program. The experience/communication, culture, language, and general language components at the beginning,…

Cultural selection drives the evolution of human communication systems

PubMed Central

Tamariz, Monica; Ellison, T. Mark; Barr, Dale J.; Fay, Nicolas

2014-01-01

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems. PMID:24966310

Cultural selection drives the evolution of human communication systems.

PubMed

Tamariz, Monica; Ellison, T Mark; Barr, Dale J; Fay, Nicolas

2014-08-07

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems.

Development of cortical orientation selectivity in the absence of visual experience with contour

PubMed Central

Hussain, Shaista; Weliky, Michael

2011-01-01

Visual cortical neurons are selective for the orientation of lines, and the full development of this selectivity requires natural visual experience after eye opening. Here we examined whether this selectivity develops without seeing lines and contours. Juvenile ferrets were reared in a dark room and visually trained by being shown a movie of flickering, sparse spots. We found that despite the lack of contour visual experience, the cortical neurons of these ferrets developed strong orientation selectivity and exhibited simple-cell receptive fields. This finding suggests that overt contour visual experience is unnecessary for the maturation of orientation selectivity and is inconsistent with the computational models that crucially require the visual inputs of lines and contours for the development of orientation selectivity. We propose that a correlation-based model supplemented with a constraint on synaptic strength dynamics is able to account for our experimental result. PMID:21753023

Effects of selective fusion on the thermal history of the earth's mantle

USGS Publications Warehouse

Lee, W.H.K.

1968-01-01

A comparative study on the thermal history of the earth's mantle was made by numerical solutions of the heat equation including and excluding selective fusion of silicates. Selective fusion was approximated by melting in a multicomponent system and redistribution of radioactive elements. Effects of selective fusion on the thermal models are (1) lowering (by several hundred degrees centigrade) and stabilizing the internal temperature distribution, and (2) increasing the surface heat-flow. It was found that models with selective fusion gave results more compatible with observations of both present temperature and surface heat-flow. The results therefore suggest continuous differentiation of the earth's mantle throughout geologic time, and support the hypothesis that the earth's atmosphere, oceans, and crust have been accumulated throughout the earth's history by degassing and selective fusion of the mantle. ?? 1968.

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Optimizing selective cutting strategies for maximum carbon stocks and yield of Moso bamboo forest using BIOME-BGC model.

PubMed

Mao, Fangjie; Zhou, Guomo; Li, Pingheng; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

2017-04-15

The selective cutting method currently used in Moso bamboo forests has resulted in a reduction of stand productivity and carbon sequestration capacity. Given the time and labor expense involved in addressing this problem manually, simulation using an ecosystem model is the most suitable approach. The BIOME-BGC model was improved to suit managed Moso bamboo forests, which was adapted to include age structure, specific ecological processes and management measures of Moso bamboo forest. A field selective cutting experiment was done in nine plots with three cutting intensities (high-intensity, moderate-intensity and low-intensity) during 2010-2013, and biomass of these plots was measured for model validation. Then four selective cutting scenarios were simulated by the improved BIOME-BGC model to optimize the selective cutting timings, intervals, retained ages and intensities. The improved model matched the observed aboveground carbon density and yield of different plots, with a range of relative error from 9.83% to 15.74%. The results of different selective cutting scenarios suggested that the optimal selective cutting measure should be cutting 30% culms of age 6, 80% culms of age 7, and all culms thereafter (above age 8) in winter every other year. The vegetation carbon density and harvested carbon density of this selective cutting method can increase by 74.63% and 21.5%, respectively, compared with the current selective cutting measure. The optimized selective cutting measure developed in this study can significantly promote carbon density, yield, and carbon sink capacity in Moso bamboo forests. Copyright © 2017 Elsevier Ltd. All rights reserved.

A model for field toxicity tests

USGS Publications Warehouse

Kaiser, Mark S.; Finger, Susan E.

1996-01-01

Toxicity tests conducted under field conditions present an interesting challenge for statistical modelling. In contrast to laboratory tests, the concentrations of potential toxicants are not held constant over the test. In addition, the number and identity of toxicants that belong in a model as explanatory factors are not known and must be determined through a model selection process. We present one model to deal with these needs. This model takes the record of mortalities to form a multinomial distribution in which parameters are modelled as products of conditional daily survival probabilities. These conditional probabilities are in turn modelled as logistic functions of the explanatory factors. The model incorporates lagged values of the explanatory factors to deal with changes in the pattern of mortalities over time. The issue of model selection and assessment is approached through the use of generalized information criteria and power divergence goodness-of-fit tests. These model selection criteria are applied in a cross-validation scheme designed to assess the ability of a model to both fit data used in estimation and predict data deleted from the estimation data set. The example presented demonstrates the need for inclusion of lagged values of the explanatory factors and suggests that penalized likelihood criteria may not provide adequate protection against overparameterized models in model selection.

Mixed conditional logistic regression for habitat selection studies.

PubMed

Duchesne, Thierry; Fortin, Daniel; Courbin, Nicolas

2010-05-01

1. Resource selection functions (RSFs) are becoming a dominant tool in habitat selection studies. RSF coefficients can be estimated with unconditional (standard) and conditional logistic regressions. While the advantage of mixed-effects models is recognized for standard logistic regression, mixed conditional logistic regression remains largely overlooked in ecological studies. 2. We demonstrate the significance of mixed conditional logistic regression for habitat selection studies. First, we use spatially explicit models to illustrate how mixed-effects RSFs can be useful in the presence of inter-individual heterogeneity in selection and when the assumption of independence from irrelevant alternatives (IIA) is violated. The IIA hypothesis states that the strength of preference for habitat type A over habitat type B does not depend on the other habitat types also available. Secondly, we demonstrate the significance of mixed-effects models to evaluate habitat selection of free-ranging bison Bison bison. 3. When movement rules were homogeneous among individuals and the IIA assumption was respected, fixed-effects RSFs adequately described habitat selection by simulated animals. In situations violating the inter-individual homogeneity and IIA assumptions, however, RSFs were best estimated with mixed-effects regressions, and fixed-effects models could even provide faulty conclusions. 4. Mixed-effects models indicate that bison did not select farmlands, but exhibited strong inter-individual variations in their response to farmlands. Less than half of the bison preferred farmlands over forests. Conversely, the fixed-effect model simply suggested an overall selection for farmlands. 5. Conditional logistic regression is recognized as a powerful approach to evaluate habitat selection when resource availability changes. This regression is increasingly used in ecological studies, but almost exclusively in the context of fixed-effects models. Fitness maximization can imply differences in trade-offs among individuals, which can yield inter-individual differences in selection and lead to departure from IIA. These situations are best modelled with mixed-effects models. Mixed-effects conditional logistic regression should become a valuable tool for ecological research.

Genetic parameters for carcass traits and body weight using a Bayesian approach in the Canchim cattle.

PubMed

Meirelles, S L C; Mokry, F B; Espasandín, A C; Dias, M A D; Baena, M M; de A Regitano, L C

2016-06-10

Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT.

The population dynamics of cancer: a Darwinian perspective.

PubMed

Vineis, Paolo; Berwick, Marianne

2006-10-01

Carcinogenesis, at least for some types of cancer, can be interpreted as the consequence of selection of mutated cells similar to what, in the theory of evolution, occurs at the population level. Instead of considering a population of organisms, we can refer to a population of cells belonging to multicellular organisms. Many carcinogens are mutagens, and the observed geographic distribution of cancer is, at least in part, attributable to environmental mutagens. However, the rapid change in risk for some cancers after migration suggests that carcinogenesis involves--in addition to mutations--some late event that most probably consists of the selection of cells already carrying mutations. We review a few examples of such selective pressures: finasteride in prostate cancer, vitamin supplementation in smokers, acquired resistance to chemotherapy, peripheral resistance to insulin, and sunlight and mutations in melanoma. A disease model for such a hypothesis is represented by Paroxysmal Nocturnal Hemoglobinuria (PNH). Mutations can be present at birth, as in the case of PNH, and can have a frequency much higher than the occurrence of the corresponding disease (PNH or lymphocytic leukaemia in children). However, PNH does not require a mutator phenotype, only a mutant phenotype followed by selection. A characteristic feature of cancer, instead, is likely to be the development of the mutator phenotype. We propose a 'Darwinian' model of carcinogenesis. If the model is correct, it suggests that prevention is more complex than avoiding exposure to mutagens. Mutations and genetic instability can be already present at birth. Mutations can be selected in the course of life if they increase survival advantage of the cell under certain environmental circumstances. In addition, gene-environment interactions cannot be interpreted according to a simplified linear model (based on the 'analysis of variance' concept); experimental work suggests that a more comprehensive non-linear interpretation based on the idea of 'norm of reaction' is needed.

Beyond perceptual load and dilution: a review of the role of working memory in selective attention

PubMed Central

de Fockert, Jan W.

2013-01-01

The perceptual load and dilution models differ fundamentally in terms of the proposed mechanism underlying variation in distractibility during different perceptual conditions. However, both models predict that distracting information can be processed beyond perceptual processing under certain conditions, a prediction that is well-supported by the literature. Load theory proposes that in such cases, where perceptual task aspects do not allow for sufficient attentional selectivity, the maintenance of task-relevant processing depends on cognitive control mechanisms, including working memory. The key prediction is that working memory plays a role in keeping clear processing priorities in the face of potential distraction, and the evidence reviewed and evaluated in a meta-analysis here supports this claim, by showing that the processing of distracting information tends to be enhanced when load on a concurrent task of working memory is high. Low working memory capacity is similarly associated with greater distractor processing in selective attention, again suggesting that the unavailability of working memory during selective attention leads to an increase in distractibility. Together, these findings suggest that selective attention against distractors that are processed beyond perception depends on the availability of working memory. Possible mechanisms for the effects of working memory on selective attention are discussed. PMID:23734139

Beyond perceptual load and dilution: a review of the role of working memory in selective attention.

PubMed

de Fockert, Jan W

2013-01-01

The perceptual load and dilution models differ fundamentally in terms of the proposed mechanism underlying variation in distractibility during different perceptual conditions. However, both models predict that distracting information can be processed beyond perceptual processing under certain conditions, a prediction that is well-supported by the literature. Load theory proposes that in such cases, where perceptual task aspects do not allow for sufficient attentional selectivity, the maintenance of task-relevant processing depends on cognitive control mechanisms, including working memory. The key prediction is that working memory plays a role in keeping clear processing priorities in the face of potential distraction, and the evidence reviewed and evaluated in a meta-analysis here supports this claim, by showing that the processing of distracting information tends to be enhanced when load on a concurrent task of working memory is high. Low working memory capacity is similarly associated with greater distractor processing in selective attention, again suggesting that the unavailability of working memory during selective attention leads to an increase in distractibility. Together, these findings suggest that selective attention against distractors that are processed beyond perception depends on the availability of working memory. Possible mechanisms for the effects of working memory on selective attention are discussed.

A Ranking Approach to Genomic Selection.

PubMed

Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

2015-01-01

Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

Diel habitat selection of largemouth bass following woody structure installation in Table Rock Lake, Missouri

USGS Publications Warehouse

Harris, J.M.; Paukert, Craig P.; Bush, S.C.; Allen, M.J.; Siepker, Michael

2018-01-01

Largemouth bass Micropterus salmoides (Lacepède) use of installed habitat structure was evaluated in a large Midwestern USA reservoir to determine whether or not these structures were used in similar proportion to natural habitats. Seventy largemouth bass (>380 mm total length) were surgically implanted with radio transmitters and a subset was relocated monthly during day and night for one year. The top habitat selection models (based on Akaike's information criterion) suggest largemouth bass select 2–4 m depths during night and 4–7 m during day, whereas littoral structure selection was similar across diel periods. Largemouth bass selected boat docks at twice the rate of other structures. Installed woody structure was selected at similar rates to naturally occurring complex woody structure, whereas both were selected at a higher rate than simple woody structure. The results suggest the addition of woody structure may concentrate largemouth bass and mitigate the loss of woody habitat in a large reservoir.

Could natural selection change the geographic range limits of light brown apple moth (Lepidoptera, Tortricidae) in North America?

Treesearch

Amy C. Morey; Robert C. Venette; William D. Hutchison

2013-01-01

We artificially selected for increased freeze tolerance in the invasive light brown apple moth. Our results suggest that, by not accounting for adaptation to cold, current models of potential geographic distributions could underestimate the areas at risk of exposure to this species.

Program Evaluation: An Overview.

ERIC Educational Resources Information Center

McCluskey, Lawrence

1973-01-01

Various models of educational evaluation are presented. These include: (1) the classical type model, which contains the following guidelines: formulate objectives, classify objectives, define objectives in behavioral terms, suggest situations in which achievement of objectives will be shown, develop or select appraisal techniques, and gather and…

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

USGS Publications Warehouse

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

2010-01-01

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

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

USGS Publications Warehouse

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

2010-01-01

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

Resource selection models are useful in predicting fine-scale distributions of black-footed ferrets in prairie dog colonies

USGS Publications Warehouse

Eads, David A.; Jachowski, David S.; Biggins, Dean E.; Livieri, Travis M.; Matchett, Marc R.; Millspaugh, Joshua J.

2012-01-01

Wildlife-habitat relationships are often conceptualized as resource selection functions (RSFs)—models increasingly used to estimate species distributions and prioritize habitat conservation. We evaluated the predictive capabilities of 2 black-footed ferret (Mustela nigripes) RSFs developed on a 452-ha colony of black-tailed prairie dogs (Cynomys ludovicianus) in the Conata Basin, South Dakota. We used the RSFs to project the relative probability of occurrence of ferrets throughout an adjacent 227-ha colony. We evaluated performance of the RSFs using ferret space use data collected via postbreeding spotlight surveys June–October 2005–2006. In home ranges and core areas, ferrets selected the predicted "very high" and "high" occurrence categories of both RSFs. Count metrics also suggested selection of these categories; for each model in each year, approximately 81% of ferret locations occurred in areas of very high or high predicted occurrence. These results suggest usefulness of the RSFs in estimating the distribution of ferrets throughout a black-tailed prairie dog colony. The RSFs provide a fine-scale habitat assessment for ferrets that can be used to prioritize releases of ferrets and habitat restoration for prairie dogs and ferrets. A method to quickly inventory the distribution of prairie dog burrow openings would greatly facilitate application of the RSFs.

Emotional Bookkeeping and High Partner Selectivity Are Necessary for the Emergence of Partner-Specific Reciprocal Affiliation in an Agent-Based Model of Primate Groups

PubMed Central

Evers, Ellen; de Vries, Han; Spruijt, Berry M.; Sterck, Elisabeth H. M.

2015-01-01

Primate affiliative relationships are differentiated, individual-specific and often reciprocal. However, the required cognitive abilities are still under debate. Recently, we introduced the EMO-model, in which two emotional dimensions regulate social behaviour: anxiety-FEAR and satisfaction-LIKE. Emotional bookkeeping is modelled by providing each individual with partner-specific LIKE attitudes in which the emotional experiences of earlier affiliations with others are accumulated. Individuals also possess fixed partner-specific FEAR attitudes, reflecting the stable dominance hierarchy. In this paper, we focus on one key parameter of the model, namely the degree of partner selectivity, i.e. the extent to which individuals rely on their LIKE attitudes when choosing affiliation partners. Studying the effect of partner selectivity on the emergent affiliative relationships, we found that at high selectivity, individuals restricted their affiliative behaviours more to similar-ranking individuals and that reciprocity of affiliation was enhanced. We compared the emotional bookkeeping model with a control model, in which individuals had fixed LIKE attitudes simply based on the (fixed) rank-distance, instead of dynamic LIKE attitudes based on earlier events. Results from the control model were very similar to the emotional bookkeeping model: high selectivity resulted in preference of similar-ranking partners and enhanced reciprocity. However, only in the emotional bookkeeping model did high selectivity result in the emergence of reciprocal affiliative relationships that were highly partner-specific. Moreover, in the emotional bookkeeping model, LIKE attitude predicted affiliative behaviour better than rank-distance, especially at high selectivity. Our model suggests that emotional bookkeeping is a likely candidate mechanism to underlie partner-specific reciprocal affiliation. PMID:25785601

Levetiracetam: the preclinical profile of a new class of antiepileptic drugs?

PubMed

Klitgaard, H

2001-01-01

Levetiracetam is a new antiepileptic drug (AED) devoid of anticonvulsant activity in the two classic screening models for AEDs, the maximal electroshock and pentylenetetrazol seizure tests in both mice and rats. This contrasts a potent seizure suppression in genetic and kindled mice and rats and against chemoconvulsants inducing partial seizures in rats. The highly selective action in "epileptic" animals distinguishes levetiracetam from classic and other new AEDs that have nearly equipotent effects in normal and "epileptic" animals. Levetiracetam induces minor behavioral alterations in normal and in kindled mice and rats. This results in an unusually high safety margin in animal models reflecting both partial and primary generalized epilepsy. Furthermore, experiments in the kindling model suggest that levetiracetam may possess antiepileptogenic properties due to a potent ability to prevent the development of kindling in mice and rats at doses devoid of adverse effects. Electrophysiologic recordings from different experimental models suggest that levetiracetam exerts a selective action against abnormal patterns of neuronal activity, which probably explains its selective protection in epileptic animals and its unique tolerability. This effect appears to derive from one or more novel mechanisms of action that do not involve a conventional interaction with traditional drug targets implicated in the modulation of inhibitory and excitatory neurotransmission. Instead, ligand-binding assays have disclosed a brain-specific binding site for levetiracetam. These studies reveal a unique preclinical profile of levetiracetam, distinct from that of all known AEDs, suggesting that levetiracetam could represent the first agent in a new class of AEDs.

A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data.

PubMed

Bommert, Andrea; Rahnenführer, Jörg; Lang, Michel

2017-01-01

Finding a good predictive model for a high-dimensional data set can be challenging. For genetic data, it is not only important to find a model with high predictive accuracy, but it is also important that this model uses only few features and that the selection of these features is stable. This is because, in bioinformatics, the models are used not only for prediction but also for drawing biological conclusions which makes the interpretability and reliability of the model crucial. We suggest using three target criteria when fitting a predictive model to a high-dimensional data set: the classification accuracy, the stability of the feature selection, and the number of chosen features. As it is unclear which measure is best for evaluating the stability, we first compare a variety of stability measures. We conclude that the Pearson correlation has the best theoretical and empirical properties. Also, we find that for the stability assessment behaviour it is most important that a measure contains a correction for chance or large numbers of chosen features. Then, we analyse Pareto fronts and conclude that it is possible to find models with a stable selection of few features without losing much predictive accuracy.

The Substitution Augmentation Modification Redefinition (SAMR) Model: A Critical Review and Suggestions for Its Use

ERIC Educational Resources Information Center

Hamilton, Erica R.; Rosenberg, Joshua M.; Akcaoglu, Mete

2016-01-01

The Substitution, Augmentation, Modification, and Redefinition (SAMR) model is a four-level, taxonomy-based approach for selecting, using, and evaluating technology in K-12 settings (Puentedura 2006). Despite its increasing popularity among practitioners, the SAMR model is not currently represented in the extant literature. To focus the ongoing…

Why fruit rots: theoretical support for Janzen's theory of microbe-macrobe competition.

PubMed

Ruxton, Graeme D; Wilkinson, David M; Schaefer, H Martin; Sherratt, Thomas N

2014-05-07

We present a formal model of Janzen's influential theory that competition for resources between microbes and vertebrates causes microbes to be selected to make these resources unpalatable to vertebrates. That is, fruit rots, seeds mould and meat spoils, in part, because microbes gain a selective advantage if they can alter the properties of these resources to avoid losing the resources to vertebrate consumers. A previous model had failed to find circumstances in which such a costly spoilage trait could flourish; here, we present a simple analytic model of a general situation where costly microbial spoilage is selected and persists. We argue that the key difference between the two models lies in their treatments of microbial dispersal. If microbial dispersal is sufficiently spatially constrained that different resource items can have differing microbial communities, then spoilage will be selected; however, if microbial dispersal has a strong homogenizing effect on the microbial community then spoilage will not be selected. We suspect that both regimes will exist in the natural world, and suggest how future empirical studies could explore the influence of microbial dispersal on spoilage.

Estimating the "impact" of out-of-home placement on child well-being: approaching the problem of selection bias.

PubMed

Berger, Lawrence M; Bruch, Sarah K; Johnson, Elizabeth I; James, Sigrid; Rubin, David

2009-01-01

This study used data on 2,453 children aged 4-17 from the National Survey of Child and Adolescent Well-Being and 5 analytic methods that adjust for selection factors to estimate the impact of out-of-home placement on children's cognitive skills and behavior problems. Methods included ordinary least squares (OLS) regressions and residualized change, simple change, difference-in-difference, and fixed effects models. Models were estimated using the full sample and a matched sample generated by propensity scoring. Although results from the unmatched OLS and residualized change models suggested that out-of-home placement is associated with increased child behavior problems, estimates from models that more rigorously adjust for selection bias indicated that placement has little effect on children's cognitive skills or behavior problems.

A selection model for accounting for publication bias in a full network meta-analysis.

PubMed

Mavridis, Dimitris; Welton, Nicky J; Sutton, Alex; Salanti, Georgia

2014-12-30

Copas and Shi suggested a selection model to explore the potential impact of publication bias via sensitivity analysis based on assumptions for the probability of publication of trials conditional on the precision of their results. Chootrakool et al. extended this model to three-arm trials but did not fully account for the implications of the consistency assumption, and their model is difficult to generalize for complex network structures with more than three treatments. Fitting these selection models within a frequentist setting requires maximization of a complex likelihood function, and identification problems are common. We have previously presented a Bayesian implementation of the selection model when multiple treatments are compared with a common reference treatment. We now present a general model suitable for complex, full network meta-analysis that accounts for consistency when adjusting results for publication bias. We developed a design-by-treatment selection model to describe the mechanism by which studies with different designs (sets of treatments compared in a trial) and precision may be selected for publication. We fit the model in a Bayesian setting because it avoids the numerical problems encountered in the frequentist setting, it is generalizable with respect to the number of treatments and study arms, and it provides a flexible framework for sensitivity analysis using external knowledge. Our model accounts for the additional uncertainty arising from publication bias more successfully compared to the standard Copas model or its previous extensions. We illustrate the methodology using a published triangular network for the failure of vascular graft or arterial patency. Copyright © 2014 John Wiley & Sons, Ltd.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

PubMed

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.

Natural selection and inheritance of breeding time and clutch size in the collared flycatcher.

PubMed

Sheldon, B C; Kruuk, L E B; Merilä, J

2003-02-01

Many characteristics of organisms in free-living populations appear to be under directional selection, possess additive genetic variance, and yet show no evolutionary response to selection. Avian breeding time and clutch size are often-cited examples of such characters. We report analyses of inheritance of, and selection on, these traits in a long-term study of a wild population of the collared flycatcher Ficedula albicollis. We used mixed model analysis with REML estimation ("animal models") to make full use of the information in complex multigenerational pedigrees. Heritability of laying date, but not clutch size, was lower than that estimated previously using parent-offspring regressions, although for both traits there was evidence of substantial additive genetic variance (h2 = 0.19 and 0.29, respectively). Laying date and clutch size were negatively genetically correlated (rA = -0.41 +/- 0.09), implying that selection on one of the traits would cause a correlated response in the other, but there was little evidence to suggest that evolution of either trait would be constrained by correlations with other phenotypic characters. Analysis of selection on these traits in females revealed consistent strong directional fecundity selection for earlier breeding at the level of the phenotype (beta = -0.28 +/- 0.03), but little evidence for stabilising selection on breeding time. We found no evidence that clutch size was independently under selection. Analysis of fecundity selection on breeding values for laying date, estimated from an animal model, indicated that selection acts directly on additive genetic variance underlying breeding time (beta = -0.20 +/- 0.04), but not on clutch size (beta = 0.03 +/- 0.05). In contrast, selection on laying date via adult female survival fluctuated in sign between years, and was opposite in sign for selection on phenotypes (negative) and breeding values (positive). Our data thus suggest that any evolutionary response to selection on laying date is partially constrained by underlying life-history trade-offs, and illustrate the difficulties in using purely phenotypic measures and incomplete fitness estimates to assess evolution of life-history trade-offs. We discuss some of the difficulties associated with understanding the evolution of laying date and clutch size in natural populations.

Genetic signatures of natural selection in a model invasive ascidian

PubMed Central

Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

2017-01-01

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta. PMID:28266616

The motivation to care: application and extension of motivation theory to professional nursing work.

PubMed

Moody, Roseanne C; Pesut, Daniel J

2006-01-01

The purpose of this research is to describe a model of nurses' work motivation relevant to the human caring stance of professional nursing work. The model was derived from selected theories of behavioral motivation and work motivation. Evidence-based theory addressing nurses' work motivation and nurses' motivational states and traits in relation to characteristics of organizational culture and patient health outcomes is suggested in an effort to make a distinct contribution to health services research. An integrated review of selected theories of motivation is presented, including conceptual analyses, theory-building techniques, and the evidence supporting the theoretical propositions and linkages among variables intrinsic to nurses' work motivation. The model of the Motivation to Care for Professional Nursing Work is a framework intended for empirical testing and theory building. The model proposes specific leadership and management strategies to support a culture of motivational caring and competence in health care organizations. Attention to motivation theory and research provides insights and suggests relationships among nurses' motivation to care, motivational states and traits, individual differences that influence nurses' work motivation, and the special effects of nurses' work motivation on patient care outcomes. Suggestions for nursing administrative direction and research are proposed.

Teaching topography-based and selection-based verbal behavior to developmentally disabled individuals: Some considerations

PubMed Central

Shafer, Esther

1993-01-01

Augmentative and alternative communication systems are widely recommended for nonvocal developmentally disabled individuals, with selection-based systems becoming increasingly popular. However, theoretical and experimental evidence suggests that topography-based communication systems are easier to learn. This paper discusses research relevant to the ease of acquisition of topography-based and selection-based systems. Additionally, current practices for choosing and designing communication systems are reviewed in order to investigate the extent to which links have been made with available theoretical and experimental knowledge. A stimulus equivalence model is proposed as a clearer direction for practitioners to follow when planning a communication training program. Suggestions for future research are also offered. PMID:22477085

ASSORTATIVE MATING CAN IMPEDE OR FACILITATE FIXATION OF UNDERDOMINANT ALLELES

PubMed Central

NEWBERRY, MITCHELL G; MCCANDLISH, DAVID M; PLOTKIN, JOSHUA B

2017-01-01

Underdominant mutations have fixed between divergent species, yet classical models suggest that rare underdominant alleles are purged quickly except in small or subdivided populations. We predict that underdominant alleles that also influence mate choice, such as those affecting coloration patterns visible to mates and predators alike, can fix more readily. We analyze a mechanistic model of positive assortative mating in which individuals have n chances to sample compatible mates. This one-parameter model naturally spans random mating (n =1) and complete assortment (n → ∞), yet it produces sexual selection whose strength depends non-monotonically on n. This sexual selection interacts with viability selection to either inhibit or facilitate fixation. As mating opportunities increase, underdominant alleles fix as frequently as neutral mutations, even though sexual selection and underdominance independently each suppress rare alleles. This mechanism allows underdominant alleles to fix in large populations and illustrates how life history can affect evolutionary change. PMID:27497738

3D-QSAR and 3D-QSSR models of negative allosteric modulators facilitate the design of a novel selective antagonist of human α4β2 neuronal nicotinic acetylcholine receptors.

PubMed

Henderson, Brandon J; Orac, Crina M; Maciagiewicz, Iwona; Bergmeier, Stephen C; McKay, Dennis B

2012-02-15

Subtype selective molecules for α4β2 neuronal nicotinic acetylcholine receptors (nAChRs) have been sought as novel therapeutics for nicotine cessation. α4β2 nAChRs have been shown to be involved in mediating the addictive properties of nicotine while other subtypes (i.e., α3β4 and α7) are believed to mediate the undesired effects of potential CNS drugs. To obtain selective molecules, it is important to understand the physiochemical features of ligands that affect selectivity and potency on nAChR subtypes. Here we present novel QSAR/QSSR models for negative allosteric modulators of human α4β2 nAChRs and human α3β4 nAChRs. These models support previous homology model and site-directed mutagenesis studies that suggest a novel mechanism of antagonism. Additionally, information from the models presented in this work was used to synthesize novel molecules; which subsequently led to the discovery of a new selective antagonist of human α4β2 nAChRs. Copyright © 2011 Elsevier Ltd. All rights reserved.

3D-QSAR and 3D-QSSR models of negative allosteric modulators facilitate the design of a novel selective antagonist of human α4β2 neuronal nicotinic acetylcholine receptors

PubMed Central

Henderson, Brandon J.; Orac, Crina M.; Maciagiewicz, Iwona; Bergmeier, Stephen C.; McKay, Dennis B.

2011-01-01

Subtype selective molecules for α4β2 neuronal nicotinic acetylcholine receptors (nAChRs) have been sought as novel therapeutics for nicotine cessation. α4β2 nAChRs have been shown to be involved in mediating the addictive properties of nicotine while other subtypes (i.e., α3β4 and α7) are believed to mediate the undesired effects of potential CNS drugs. To obtain selective molecules, it is important to understand the physiochemical features of ligands that affect selectivity and potency on nAChR subtypes. Here we present novel QSAR/QSSR models for negative allosteric modulators of human α4β2 nAChRs and human α3β4 nAChRs. These models support previous homology model and site-directed mutagenesis studies that suggest a novel mechanism of antagonism. Additionally, information from the models presented in this work was used to synthesize novel molecules; which subsequently led to the discovery of a new selective antagonist of human α4β2 nAChRs. PMID:22285942

Possible roles of exceptionally conserved residues around the selectivity filters of sodium and calcium channels.

PubMed

Tikhonov, Denis B; Zhorov, Boris S

2011-01-28

In the absence of x-ray structures of sodium and calcium channels their homology models are used to rationalize experimental data and design new experiments. A challenge is to model the outer-pore region that folds differently from potassium channels. Here we report a new model of the outer-pore region of the NaV1.4 channel, which suggests roles of highly conserved residues around the selectivity filter. The model takes from our previous study (Tikhonov, D. B., and Zhorov, B. S. (2005) Biophys. J. 88, 184-197) the general disposition of the P-helices, selectivity filter residues, and the outer carboxylates, but proposes new intra- and inter-domain contacts that support structural stability of the outer pore. Glycine residues downstream from the selectivity filter are proposed to participate in knob-into-hole contacts with the P-helices and S6s. These contacts explain the adapted tetrodotoxin resistance of snakes that feed on toxic prey through valine substitution of isoleucine in the P-helix of repeat IV. Polar residues five positions upstream from the selectivity filter residues form H-bonds with the ascending-limb backbones. Exceptionally conserved tryptophans are engaged in inter-repeat H-bonds to form a ring whose π-electrons would facilitate passage of ions from the outer carboxylates to the selectivity filter. The outer-pore model of CaV1.2 derived from the NaV1.4 model is also stabilized by the ring of exceptionally conservative tryptophans and H-bonds between the P-helices and ascending limbs. In this model, the exceptionally conserved aspartate downstream from the selectivity-filter glutamate in repeat II facilitates passage of calcium ions to the selectivity-filter ring through the tryptophan ring. Available experimental data are discussed in view of the models.

Breeding site selection by coho salmon (Oncorhynchus kisutch) in relation to large wood additions and factors that influence reproductive success

USGS Publications Warehouse

Clark, Steven M.; Dunham, Jason B.; McEnroe, Jeffery R.; Lightcap, Scott W.

2014-01-01

The fitness of female Pacific salmon (Oncorhynchus spp.) with respect to breeding behavior can be partitioned into at least four fitness components: survival to reproduction, competition for breeding sites, success of egg incubation, and suitability of the local environment near breeding sites for early rearing of juveniles. We evaluated the relative influences of habitat features linked to these fitness components with respect to selection of breeding sites by coho salmon (Oncorhynchus kisutch). We also evaluated associations between breeding site selection and additions of large wood, as the latter were introduced into the study system as a means of restoring habitat conditions to benefit coho salmon. We used a model selection approach to organize specific habitat features into groupings reflecting fitness components and influences of large wood. Results of this work suggest that female coho salmon likely select breeding sites based on a wide range of habitat features linked to all four hypothesized fitness components. More specifically, model parameter estimates indicated that breeding site selection was most strongly influenced by proximity to pool-tail crests and deeper water (mean and maximum depths). Linkages between large wood and breeding site selection were less clear. Overall, our findings suggest that breeding site selection by coho salmon is influenced by a suite of fitness components in addition to the egg incubation environment, which has been the emphasis of much work in the past.

Empirical study of the dependence of the results of multivariable flexible survival analyses on model selection strategy.

PubMed

Binquet, C; Abrahamowicz, M; Mahboubi, A; Jooste, V; Faivre, J; Bonithon-Kopp, C; Quantin, C

2008-12-30

Flexible survival models, which avoid assumptions about hazards proportionality (PH) or linearity of continuous covariates effects, bring the issues of model selection to a new level of complexity. Each 'candidate covariate' requires inter-dependent decisions regarding (i) its inclusion in the model, and representation of its effects on the log hazard as (ii) either constant over time or time-dependent (TD) and, for continuous covariates, (iii) either loglinear or non-loglinear (NL). Moreover, 'optimal' decisions for one covariate depend on the decisions regarding others. Thus, some efficient model-building strategy is necessary.We carried out an empirical study of the impact of the model selection strategy on the estimates obtained in flexible multivariable survival analyses of prognostic factors for mortality in 273 gastric cancer patients. We used 10 different strategies to select alternative multivariable parametric as well as spline-based models, allowing flexible modeling of non-parametric (TD and/or NL) effects. We employed 5-fold cross-validation to compare the predictive ability of alternative models.All flexible models indicated significant non-linearity and changes over time in the effect of age at diagnosis. Conventional 'parametric' models suggested the lack of period effect, whereas more flexible strategies indicated a significant NL effect. Cross-validation confirmed that flexible models predicted better mortality. The resulting differences in the 'final model' selected by various strategies had also impact on the risk prediction for individual subjects.Overall, our analyses underline (a) the importance of accounting for significant non-parametric effects of covariates and (b) the need for developing accurate model selection strategies for flexible survival analyses. Copyright 2008 John Wiley & Sons, Ltd.

Breakdown of single spin-fluid model in the heavily hole-doped superconductor CsFe2As2

NASA Astrophysics Data System (ADS)

Zhao, D.; Li, S. J.; Wang, N. Z.; Li, J.; Song, D. W.; Zheng, L. X.; Nie, L. P.; Luo, X. G.; Wu, T.; Chen, X. H.

2018-01-01

Although Fe-based superconductors are correlated electronic systems with multiorbital, previous nuclear magnetic resonance (NMR) measurement suggests that a single spin-fluid model is sufficient to describe its spin behavior. Here, we first observed the breakdown of single spin-fluid model in a heavily hole-doped Fe-based superconductor CsFe2As2 by site-selective NMR measurement. At high-temperature regime, both Knight shift and nuclear spin-lattice relaxation at 133Cs and 75As nuclei exhibit distinct temperature-dependent behavior, suggesting the breakdown of the single spin-fluid model in CsFe2As2 . This is ascribed to the coexistence of both localized and itinerant spin degree of freedom at 3 d orbitals, which is consistent with the orbital-selective Mott phase. With decreasing temperature, the single spin-fluid behavior is recovered below T*˜75 K due to a coherent state among 3 d orbitals. The Kondo liquid scenario is proposed to understand the low-temperature coherent state.

A Critique of Selected References on Educational Cost Effectiveness with a Resource - Utility Model To Improve Resource Allocation.

ERIC Educational Resources Information Center

Cleckner, John

The author reviews five cost-effectiveness basic models including log-log correlational, general utility theory, simultaneous equations, nonlinear theoretical, and feedback. Several suggestions are made to improve the models and increase the domain of problems that can be considered by the models. In the second part of the paper, the author…

Feature Selection Methods for Zero-Shot Learning of Neural Activity.

PubMed

Caceres, Carlos A; Roos, Matthew J; Rupp, Kyle M; Milsap, Griffin; Crone, Nathan E; Wolmetz, Michael E; Ratto, Christopher R

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

NASA Astrophysics Data System (ADS)

Xiang, Lin

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8 th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on natural selection implemented in a charter school of a major California city during spring semester of 2009. Eight 8th grade students, two boys and six girls, participated in this study. All of them were low socioeconomic status (SES). English was a second language for all of them, but they had been identified as fluent English speakers at least a year before the study. None of them had learned either natural selection or programming before the study. The study spanned over 7 weeks and was comprised of two study phases. In phase one the subject students learned natural selection in science classroom and how to do programming in NetLogo, an ABPM tool, in a computer lab; in phase two, the subject students were asked to program a simulation of adaptation based on the natural selection model in NetLogo. Both qualitative and quantitative data were collected in this study. The data resources included (1) pre and post test questionnaire, (2) student in-class worksheet, (3) programming planning sheet, (4) code-conception matching sheet, (5) student NetLogo projects, (6) videotaped programming processes, (7) final interview, and (8) investigator's field notes. Both qualitative and quantitative approaches were applied to analyze the gathered data. The findings suggested that students made progress on understanding adaptation phenomena and natural selection at the end of ABPM-supported MBI learning but the progress was limited. These students still held some misconceptions in their conceptual models, such as the idea that animals need to "learn" to adapt into the environment. Besides, their models of natural selection appeared to be incomplete and many relationships among the model ideas had not been well established by the end of the study. Most of them did not treat the natural selection model as a whole but only focused on some ideas within the model. Very few of them could scientifically apply the natural selection model to interpret other evolutionary phenomena. The findings about participating students' programming processes revealed these processes were composed of consecutive programming cycles. The cycle typically included posing a task, constructing and running program codes, and examining the resulting simulation. Students held multiple ideas and applied various programming strategies in these cycles. Students were involved in MBI at each step of a cycle. Three types of ideas, six programming strategies and ten MBI actions were identified out of the processes. The relationships among these ideas, strategies and actions were also identified and described. Findings suggested that ABPM activities could support MBI by (1) exposing students' personal models and understandings, (2) provoking and supporting a series of model-based inquiry activities, such as elaborating target phenomena, abstracting patterns, and revising conceptual models, and (3) provoking and supporting tangible and productive conversations among students, as well as between the instructor and students. Findings also revealed three programming behaviors that appeared to impede productive MBI, including (1) solely phenomenon-orientated programming, (2) transplanting program codes, and (3) blindly running procedures. Based on the findings, I propose a general modeling process in ABPM activities, summarize the ways in which MBI can be supported in ABPM activities and constrained by multiple factors, and suggest the implications of this study in the future ABPM-assisted science instructional design and research.

Fatigue crack growth and life prediction under mixed-mode loading

NASA Astrophysics Data System (ADS)

Sajith, S.; Murthy, K. S. R. K.; Robi, P. S.

2018-04-01

Fatigue crack growth life as a function of crack length is essential for the prevention of catastrophic failures from damage tolerance perspective. In damage tolerance design approach, principles of fracture mechanics are usually applied to predict the fatigue life of structural components. Numerical prediction of crack growth versus number of cycles is essential in damage tolerance design. For cracks under mixed mode I/II loading, modified Paris law (d/a d N =C (ΔKe q ) m ) along with different equivalent stress intensity factor (ΔKeq) model is used for fatigue crack growth rate prediction. There are a large number of ΔKeq models available for the mixed mode I/II loading, the selection of proper ΔKeq model has significant impact on fatigue life prediction. In the present investigation, the performance of ΔKeq models in fatigue life prediction is compared with respect to the experimental findings as there are no guidelines/suggestions available on the selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempt to outline models that would provide accurate and conservative life predictions. Such a study aid the numerical analysts or engineers in the proper selection of the model for numerical simulation of the fatigue life. Moreover, the present investigation also suggests a procedure to enhance the accuracy of life prediction using Paris law.

Wind scatterometry with improved ambiguity selection and rain modeling

NASA Astrophysics Data System (ADS)

Draper, David Willis

Although generally accurate, the quality of SeaWinds on QuikSCAT scatterometer ocean vector winds is compromised by certain natural phenomena and retrieval algorithm limitations. This dissertation addresses three main contributors to scatterometer estimate error: poor ambiguity selection, estimate uncertainty at low wind speeds, and rain corruption. A quality assurance (QA) analysis performed on SeaWinds data suggests that about 5% of SeaWinds data contain ambiguity selection errors and that scatterometer estimation error is correlated with low wind speeds and rain events. Ambiguity selection errors are partly due to the "nudging" step (initialization from outside data). A sophisticated new non-nudging ambiguity selection approach produces generally more consistent wind than the nudging method in moderate wind conditions. The non-nudging method selects 93% of the same ambiguities as the nudged data, validating both techniques, and indicating that ambiguity selection can be accomplished without nudging. Variability at low wind speeds is analyzed using tower-mounted scatterometer data. According to theory, below a threshold wind speed, the wind fails to generate the surface roughness necessary for wind measurement. A simple analysis suggests the existence of the threshold in much of the tower-mounted scatterometer data. However, the backscatter does not "go to zero" beneath the threshold in an uncontrolled environment as theory suggests, but rather has a mean drop and higher variability below the threshold. Rain is the largest weather-related contributor to scatterometer error, affecting approximately 4% to 10% of SeaWinds data. A simple model formed via comparison of co-located TRMM PR and SeaWinds measurements characterizes the average effect of rain on SeaWinds backscatter. The model is generally accurate to within 3 dB over the tropics. The rain/wind backscatter model is used to simultaneously retrieve wind and rain from SeaWinds measurements. The simultaneous wind/rain (SWR) estimation procedure can improve wind estimates during rain, while providing a scatterometer-based rain rate estimate. SWR also affords improved rain flagging for low to moderate rain rates. QuikSCAT-retrieved rain rates correlate well with TRMM PR instantaneous measurements and TMI monthly rain averages. SeaWinds rain measurements can be used to supplement data from other rain-measuring instruments, filling spatial and temporal gaps in coverage.

Backward Response-Level Crosstalk in the Psychological Refractory Period Paradigm

ERIC Educational Resources Information Center

Miller, Jeff; Alderton, Mark

2006-01-01

Bottleneck models of psychological refractory period (PRP) tasks suggest that a Task 1 response should be unaffected by the Task 2 response in the same trial, because selection of the former finishes before selection of the latter begins. Contrary to this conception, the authors found backward response-level crosstalk effects in which Task 2…

Changes in Attitudes Toward Environmental Education and Selected Teaching Behaviors of Teachers Participating in Environmental Education Workshops.

ERIC Educational Resources Information Center

Myer, Teresa A.

This study examined four teacher in-service environmental education programs to: (1) suggest a workable evaluative model for such programs; (2) assess their content with respect to stated activities and objectives; and (3) determine whether or not the experiences correlated with changes in selected teaching behaviors. The research design included…

Models of Cultural Niche Construction with Selection and Assortative Mating

PubMed Central

Feldman, Marcus W.

2012-01-01

Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits. PMID:22905167

Expression-Linked Patterns of Codon Usage, Amino Acid Frequency, and Protein Length in the Basally Branching Arthropod Parasteatoda tepidariorum

PubMed Central

Whittle, Carrie A.; Extavour, Cassandra G.

2016-01-01

Abstract Spiders belong to the Chelicerata, the most basally branching arthropod subphylum. The common house spider, Parasteatoda tepidariorum, is an emerging model and provides a valuable system to address key questions in molecular evolution in an arthropod system that is distinct from traditionally studied insects. Here, we provide evidence suggesting that codon usage, amino acid frequency, and protein lengths are each influenced by expression-mediated selection in P. tepidariorum. First, highly expressed genes exhibited preferential usage of T3 codons in this spider, suggestive of selection. Second, genes with elevated transcription favored amino acids with low or intermediate size/complexity (S/C) scores (glycine and alanine) and disfavored those with large S/C scores (such as cysteine), consistent with the minimization of biosynthesis costs of abundant proteins. Third, we observed a negative correlation between expression level and coding sequence length. Together, we conclude that protein-coding genes exhibit signals of expression-related selection in this emerging, noninsect, arthropod model. PMID:27017527

The role of growth hormone in lines of mice divergently selected on body weight.

PubMed

Hastings, I M; Bootland, L H; Hill, W G

1993-04-01

An understanding of the physiological and genetic changes which determine the response to selection is critical for both evolutionary theory and to assess the application of new molecular techniques to commercial animal breeding. We investigated an aspect of physiology, growth hormone (GH) metabolism, which might a priori have been expected to play a large part in the response of mouse lines selected for high or low body weight. Disruption of endogenous GH or addition of exogenous GH had similar proportionate effects on body weight in both lines of mice (although differences in body composition arose) suggesting that neither the production of GH nor receptor sensitivity to GH had been altered as a result of selection. This supports a 'pleiotropic model' of the response to selection: that many genes with diverse metabolic roles all contribute to the divergent phenotype. This result has significant commercial implications as it suggests that artificial selection, transgenic technology and environmental manipulation may be synergistic rather than antagonistic strategies.

Using suggestion to model different types of automatic writing.

PubMed

Walsh, E; Mehta, M A; Oakley, D A; Guilmette, D N; Gabay, A; Halligan, P W; Deeley, Q

2014-05-01

Our sense of self includes awareness of our thoughts and movements, and our control over them. This feeling can be altered or lost in neuropsychiatric disorders as well as in phenomena such as "automatic writing" whereby writing is attributed to an external source. Here, we employed suggestion in highly hypnotically suggestible participants to model various experiences of automatic writing during a sentence completion task. Results showed that the induction of hypnosis, without additional suggestion, was associated with a small but significant reduction of control, ownership, and awareness for writing. Targeted suggestions produced a double dissociation between thought and movement components of writing, for both feelings of control and ownership, and additionally, reduced awareness of writing. Overall, suggestion produced selective alterations in the control, ownership, and awareness of thought and motor components of writing, thus enabling key aspects of automatic writing, observed across different clinical and cultural settings, to be modelled. Copyright © 2014. Published by Elsevier Inc.

The Multilingual Lexicon: Modelling Selection and Control

ERIC Educational Resources Information Center

de Bot, Kees

2004-01-01

In this paper an overview of research on the multilingual lexicon is presented as the basis for a model for processing multiple languages. With respect to specific issues relating to the processing of more than two languages, it is suggested that there is no need to develop a specific model for such multilingual processing, but at the same time we…

The Revised Hierarchical Model: A Critical Review and Assessment

ERIC Educational Resources Information Center

Kroll, Judith F.; van Hell, Janet G.; Tokowicz, Natasha; Green, David W.

2010-01-01

Brysbaert and Duyck (this issue) suggest that it is time to abandon the Revised Hierarchical Model (Kroll and Stewart, 1994) in favor of connectionist models such as BIA+ (Dijkstra and Van Heuven, 2002) that more accurately account for the recent evidence on non-selective access in bilingual word recognition. In this brief response, we first…

Evaluation of Vocational Technical Education. Phase II. A Skeletal Model with Suggested Research and Development Activities.

ERIC Educational Resources Information Center

New Educational Directions, Crawfordsville, IN.

Phase 2 of this project presents a skeletal model for evaluating vocational education programs which can be applied to secondary, post-secondary, and adult education programs. The model addresses 13 main components of the vocational education system: descriptive information, demonstration of need, student recruitment and selection, curriculum,…

Suzaku  Observations of Heavily Obscured (Compton-thick) Active Galactic Nuclei Selected by the Swift/BAT Hard X-Ray Survey

NASA Astrophysics Data System (ADS)

Tanimoto, Atsushi; Ueda, Yoshihiro; Kawamuro, Taiki; Ricci, Claudio; Awaki, Hisamitsu; Terashima, Yuichi

2018-02-01

We present a uniform broadband X-ray (0.5–100.0 keV) spectral analysis of 12 Swift/Burst Alert Telescope selected Compton-thick ({log}{N}{{H}}/{{cm}}-2≥slant 24) active galactic nuclei (CTAGNs) observed with Suzaku. The Suzaku data of three objects are published here for the first time. We fit the Suzaku and Swift spectra with models utilizing an analytic reflection code and those utilizing the Monte-Carlo-based model from an AGN torus by Ikeda et al. The main results are as follows: (1) The estimated intrinsic luminosity of a CTAGN strongly depends on the model; applying Compton scattering to the transmitted component in an analytic model may largely overestimate the intrinsic luminosity at large column densities. (2) Unabsorbed reflection components are commonly observed, suggesting that the tori are clumpy. (3) Most of CTAGNs show small scattering fractions (<0.5%), implying a buried AGN nature. (4) Comparison with the results obtained for Compton-thin AGNs suggests that the properties of these CTAGNs can be understood as a smooth extension from Compton-thin AGNs with heavier obscuration; we find no evidence that the bulk of the population of hard-X-ray-selected CTAGNs are different from less obscured objects.

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

PubMed Central

Bean, William T.; Stafford, Robert; Butterfield, H. Scott; Brashares, Justin S.

2014-01-01

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define “available” habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining “available” habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists. PMID:25237807

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

USGS Publications Warehouse

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.

AIC and the challenge of complexity: A case study from ecology.

PubMed

Moll, Remington J; Steel, Daniel; Montgomery, Robert A

2016-12-01

Philosophers and scientists alike have suggested Akaike's Information Criterion (AIC), and other similar model selection methods, show predictive accuracy justifies a preference for simplicity in model selection. This epistemic justification of simplicity is limited by an assumption of AIC which requires that the same probability distribution must generate the data used to fit the model and the data about which predictions are made. This limitation has been previously noted but appears to often go unnoticed by philosophers and scientists and has not been analyzed in relation to complexity. If predictions are about future observations, we argue that this assumption is unlikely to hold for models of complex phenomena. That in turn creates a practical limitation for simplicity's AIC-based justification because scientists modeling such phenomena are often interested in predicting the future. We support our argument with an ecological case study concerning the reintroduction of wolves into Yellowstone National Park, U.S.A. We suggest that AIC might still lend epistemic support for simplicity by leading to better explanations of complex phenomena. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Systematics of Strong Lens Modeling Quantified: The Effects of Constraint Selection and Redshift Information on Magnification, Mass, and Multiple Image Predictability

NASA Astrophysics Data System (ADS)

Johnson, Traci L.; Sharon, Keren

2016-11-01

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading as to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.

A three-layer model of natural image statistics.

PubMed

Gutmann, Michael U; Hyvärinen, Aapo

2013-11-01

An important property of visual systems is to be simultaneously both selective to specific patterns found in the sensory input and invariant to possible variations. Selectivity and invariance (tolerance) are opposing requirements. It has been suggested that they could be joined by iterating a sequence of elementary selectivity and tolerance computations. It is, however, unknown what should be selected or tolerated at each level of the hierarchy. We approach this issue by learning the computations from natural images. We propose and estimate a probabilistic model of natural images that consists of three processing layers. Two natural image data sets are considered: image patches, and complete visual scenes downsampled to the size of small patches. For both data sets, we find that in the first two layers, simple and complex cell-like computations are performed. In the third layer, we mainly find selectivity to longer contours; for patch data, we further find some selectivity to texture, while for the downsampled complete scenes, some selectivity to curvature is observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Selective updating of working memory content modulates meso-cortico-striatal activity.

PubMed

Murty, Vishnu P; Sambataro, Fabio; Radulescu, Eugenia; Altamura, Mario; Iudicello, Jennifer; Zoltick, Bradley; Weinberger, Daniel R; Goldberg, Terry E; Mattay, Venkata S

2011-08-01

Accumulating evidence from non-human primates and computational modeling suggests that dopaminergic signals arising from the midbrain (substantia nigra/ventral tegmental area) mediate striatal gating of the prefrontal cortex during the selective updating of working memory. Using event-related functional magnetic resonance imaging, we explored the neural mechanisms underlying the selective updating of information stored in working memory. Participants were scanned during a novel working memory task that parses the neurophysiology underlying working memory maintenance, overwriting, and selective updating. Analyses revealed a functionally coupled network consisting of a midbrain region encompassing the substantia nigra/ventral tegmental area, caudate, and dorsolateral prefrontal cortex that was selectively engaged during working memory updating compared to the overwriting and maintenance of working memory content. Further analysis revealed differential midbrain-dorsolateral prefrontal interactions during selective updating between low-performing and high-performing individuals. These findings highlight the role of this meso-cortico-striatal circuitry during the selective updating of working memory in humans, which complements previous research in behavioral neuroscience and computational modeling. Published by Elsevier Inc.

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

PubMed

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.

The genetic architecture of normal variation in human pigmentation: an evolutionary perspective and model.

PubMed

McEvoy, Brian; Beleza, Sandra; Shriver, Mark D

2006-10-15

Skin pigmentation varies substantially across human populations in a manner largely coincident with ultraviolet radiation intensity. This observation suggests that natural selection in response to sunlight is a major force in accounting for pigmentation variability. We review recent progress in identifying the genes controlling this variation with a particular focus on the trait's evolutionary past and the potential role of testing for signatures of selection in aiding the discovery of functionally important genes. We have analyzed SNP data from the International HapMap project in 77 pigmentation candidate genes for such signatures. On the basis of these results and other similar work, we provide a tentative three-population model (West Africa, East Asia and North Europe) of the evolutionary-genetic architecture of human pigmentation. These results suggest a complex evolutionary history, with selection acting on different gene targets at different times and places in the human past. Some candidate genes may have been selected in the ancestral human population, others in the 'out of Africa' proto European-Asian population, whereas most appear to have selectively evolved solely in either Europeans or East Asians separately despite the pigmentation similarities between these two populations. Selection signatures can provide important clues to aid gene discovery. However, these should be viewed as complements, rather than replacements of, functional studies including linkage and association analyses, which can directly refine our understanding of the trait.

Population Genomics of Inversion Polymorphisms in Drosophila melanogaster

PubMed Central

Corbett-Detig, Russell B.; Hartl, Daniel L.

2012-01-01

Chromosomal inversions have been an enduring interest of population geneticists since their discovery in Drosophila melanogaster. Numerous lines of evidence suggest powerful selective pressures govern the distributions of polymorphic inversions, and these observations have spurred the development of many explanatory models. However, due to a paucity of nucleotide data, little progress has been made towards investigating selective hypotheses or towards inferring the genealogical histories of inversions, which can inform models of inversion evolution and suggest selective mechanisms. Here, we utilize population genomic data to address persisting gaps in our knowledge of D. melanogaster's inversions. We develop a method, termed Reference-Assisted Reassembly, to assemble unbiased, highly accurate sequences near inversion breakpoints, which we use to estimate the age and the geographic origins of polymorphic inversions. We find that inversions are young, and most are African in origin, which is consistent with the demography of the species. The data suggest that inversions interact with polymorphism not only in breakpoint regions but also chromosome-wide. Inversions remain differentiated at low levels from standard haplotypes even in regions that are distant from breakpoints. Although genetic exchange appears fairly extensive, we identify numerous regions that are qualitatively consistent with selective hypotheses. Finally, we show that In(1)Be, which we estimate to be ∼60 years old (95% CI 5.9 to 372.8 years), has likely achieved high frequency via sex-ratio segregation distortion in males. With deeper sampling, it will be possible to build on our inferences of inversion histories to rigorously test selective models—particularly those that postulate that inversions achieve a selective advantage through the maintenance of co-adapted allele complexes. PMID:23284285

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

USGS Publications Warehouse

Brennan, Angela; Hanks, EM; Merkle, JA; Cole, EK; Dewey, SR; Courtemanch, AB; Cross, Paul C.

2018-01-01

Context: Landscape 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. Objective: To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection. Methods: Using 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. Results: All 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 algorithms. Conclusions: CTMC 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.

Simulation modeling to understand how selective foraging by beaver can drive the structure and function of a willow community

USGS Publications Warehouse

Peinetti, H.R.; Baker, B.W.; Coughenour, M.B.

2009-01-01

Beaver-willow (Castor-Salix) communities are a unique and vital component of healthy wetlands throughout the Holarctic region. Beaver selectively forage willow to provide fresh food, stored winter food, and construction material. The effects of this complex foraging behavior on the structure and function of willow communities is poorly understood. Simulation modeling may help ecologists understand these complex interactions. In this study, a modified version of the SAVANNA ecosystem model was developed to better understand how beaver foraging affects the structure and function of a willow community in a simulated riparian ecosystem in Rocky Mountain National Park, Colorado (RMNP). The model represents willow in terms of plant and stem dynamics and beaver foraging in terms of the quantity and quality of stems cut to meet the energetic and life history requirements of beaver. Given a site where all stems were equally available, the model suggested a simulated beaver family of 2 adults, 2 yearlings, and 2 kits required a minimum of 4 ha of willow (containing about10 stems m-2) to persist in a steady-state condition. Beaver created a willow community where the annual net primary productivity (ANPP) was 2 times higher and plant architecture was more diverse than the willow community without beaver. Beaver foraging created a plant architecture dominated by medium size willow plants, which likely explains how beaver can increase ANPP. Long-term simulations suggested that woody biomass stabilized at similar values even though availability differed greatly at initial condition. Simulations also suggested that willow ANPP increased across a range of beaver densities until beaver became food limited. Thus, selective foraging by beaver increased productivity, decreased biomass, and increased structural heterogeneity in a simulated willow community.

Excellent Teachers' Thinking Model: Implications for Effective Teaching

ERIC Educational Resources Information Center

Hamzah, Sahandri G.; Mohamad, Hapidah; Ghorbani, Mohammad R.

2008-01-01

This study aimed to suggest an Excellent Teacher Thinking Model that has the potential to be utilized in the development of excellent teachers. Interaction survey method using survey questions, observation, document review and interview was conducted in this study. One hundred and five excellent teachers were selected randomly as research…

Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Wang, Quanchao; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai

2017-09-01

Genomic selection (GS) can be used to accelerate genetic improvement by shortening the selection interval. The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value (GEBV). This study is a first attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits. The performance of GS models in L. vannamei was evaluated in a population consisting of 205 individuals, which were genotyped for 6 359 single nucleotide polymorphism (SNP) markers by specific length amplified fragment sequencing (SLAF-seq) and phenotyped for body length and body weight. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to obtain the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by the different models was 0.296 and 0.411, respectively. For each trait, the performances of the three models were very similar to each other with respect to predictability. The regression coefficients estimated by the three models were close to one, suggesting near to zero bias for the predictions. Therefore, when GS was applied in a L. vannamei population for the studied scenarios, all three models appeared practicable. Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Prisoner's dilemma posed by fitness-associated recombination strategies.

PubMed

Wexler, Ydo; Rokhlenko, Oleg

2007-07-07

Genetic recombination is a central and repeated topic of study in the evolution of life. However, along with the influence of recombination on evolution, we understand surprisingly little of how selection shapes the nature of recombination. One explanation for recombination is that it allows organisms to escape from perilous situations where they experience very low fitness. As a corollary, it has been suggested that selection should favor recombination at low fitness and not at high fitness (fitness-associated recombination, FAR), and theory suggests that such strategies can indeed be selected. Here we develop models to further investigate the evolution of FAR. Consistent with previous works, we find that FAR can invade and dominate over a strategy of uniform recombination that is independent of fitness. However, our simulation results suggest that extreme FAR strategies, known as group-elitism, are not necessarily superior to other FAR strategies. Moreover, we argue that FAR domination will often occur with a net loss of mean population fitness. Interestingly, this suggests that the strategy of not recombining at high fitness will sometimes be analogous to a defector strategy from the famous "prisoner's dilemma" game: a selfish strategy that is selected but leads to a loss of mean fitness for all players.

Where to deliver baits for deworming urban red foxes for Echinococcus multilocularis control: new protocol for micro-habitat modeling of fox denning requirements.

PubMed

Ikeda, Takako; Yoshimura, Masashi; Onoyama, Keiichi; Oku, Yuzaburo; Nonaka, Nariaki; Katakura, Ken

2014-08-06

Deworming wild foxes by baiting with the anthelmintic praziquantel is being established as a preventive technique against environmental contamination with Echinococcus multilocularis eggs. Improvement of the cost-benefit performance of baiting treatment is required urgently to raise and maintain the efficacy of deworming. We established a spatial model of den site selection by urban red foxes, the definitive host, to specify the optimal micro-habitats for delivering baits in a new modeling approach modified for urban fox populations. The model was established for two cities (Obihiro and Sapporo) in Hokkaido, Japan, in which a sylvatic cycle of E. multilocularis is maintained. The two cities have different degrees of urbanization. The modeling process was designed to detect the best combination of key environmental factors and spatial scale that foxes pay attention to most (here named 'heeding range') when they select den sites. All possible models were generated using logistic regression analysis, with "presence" or "absence" of fox den as the objective variable, and nine landscape categories customized for urban environments as predictor variables to detect the best subset of predictors. This procedure was conducted for each of ten sizes of concentric circles from dens and control points to detect the best circle size. Out of all models generated, the most parsimonious model was selected using Akaike's Information Criterion (AIC) inspection. Our models suggest that fox dens in Obihiro are located at the center of a circle with 500 m radius including low percentages of wide roads, narrow roads, and occupied buildings, but high percentages of green covered areas; the dens in Sapporo within 300 m radius with low percentages of wide roads, occupied buildings, but high percentages of riverbeds and green covered areas. The variation of the models suggests the necessity of accumulating models for various types of cities in order to reveal the patterns of the model. Our denning models indicating suitable sites for delivering baits will improve the cost-benefit performance of the campaign. Our modeling protocol is suitable for the urban landscapes, and for extracting the heeding range when they select the den sites.

Free Language Selection in the Bilingual Brain: An Event-Related fMRI Study

PubMed Central

Zhang, Yong; Wang, Tao; Huang, Peiyu; Li, Dan; Qiu, Jiang; Shen, Tong; Xie, Peng

2015-01-01

Bilingual speakers may select between two languages either on demand (forced language selection) or on their own volition (free language selection). However, the neural substrates underlying free and forced language selection may differ. While the neural substrates underlying forced language selection have been well-explored with language switching paradigms, those underlying free language selection have remained unclear. Using a modified digit-naming switching paradigm, we addressed the neural substrates underlying free language selection by contrasting free language switching with forced language switching. For a digit-pair trial, Chinese-English bilinguals named each digit in Chinese or English either on demand under forced language selection condition or on their own volition under free language selection condition. The results revealed activation in the frontoparietal regions that mediate volition of language selection. Furthermore, a comparison of free and forced language switching demonstrated differences in the patterns of brain activation. Additionally, free language switching showed reduced switching costs as compared to forced language switching. These findings suggest differences between the mechanism(s) underlying free and forced language switching. As such, the current study suggests interactivity between control of volition and control of language switching in free language selection, providing insights into a model of bilingual language control. PMID:26177885

Happy but still focused: failures to find evidence for a mood-induced widening of visual attention.

PubMed

Bruyneel, Lynn; van Steenbergen, Henk; Hommel, Bernhard; Band, Guido P H; De Raedt, Rudi; Koster, Ernst H W

2013-05-01

In models of affect and cognition, it is held that positive affect broadens the scope of attention. Consistent with this claim, previous research has indeed suggested that positive affect is associated with impaired selective attention as evidenced by increased interference of spatially distant distractors. However, several recent findings cast doubt on the reliability of this observation. In the present study, we examined whether selective attention in a visual flanker task is influenced by positive mood induction. Across three experiments, positive affect consistently failed to exert any impact on selective attention. The implications of this null-finding for theoretical models of affect and cognition are discussed.

Evolution of dosage compensation under sexual selection differs between X and Z chromosomes

PubMed Central

Mullon, Charles; Wright, Alison E.; Reuter, Max; Pomiankowski, Andrew; Mank, Judith E.

2015-01-01

Complete sex chromosome dosage compensation has more often been observed in XY than ZW species. In this study, using a population genetic model and the chicken transcriptome, we assess whether sexual conflict can account for this difference. Sexual conflict over expression is inevitable when mutation effects are correlated across the sexes, as compensatory mutations in the heterogametic sex lead to hyperexpression in the homogametic sex. Coupled with stronger selection and greater reproductive variance in males, this results in slower and less complete evolution of Z compared with X dosage compensation. Using expression variance as a measure of selection strength, we find that, as predicted by the model, dosage compensation in the chicken is most pronounced in genes that are under strong selection biased towards females. Our study explains the pattern of weak dosage compensation in ZW systems, and suggests that sexual selection plays a major role in shaping sex chromosome dosage compensation. PMID:26212613

Contribution of correlated noise and selective decoding to choice probability measurements in extrastriate visual cortex.

PubMed

Gu, Yong; Angelaki, Dora E; DeAngelis, Gregory C

2014-07-01

Trial by trial covariations between neural activity and perceptual decisions (quantified by choice Probability, CP) have been used to probe the contribution of sensory neurons to perceptual decisions. CPs are thought to be determined by both selective decoding of neural activity and by the structure of correlated noise among neurons, but the respective roles of these factors in creating CPs have been controversial. We used biologically-constrained simulations to explore this issue, taking advantage of a peculiar pattern of CPs exhibited by multisensory neurons in area MSTd that represent self-motion. Although models that relied on correlated noise or selective decoding could both account for the peculiar pattern of CPs, predictions of the selective decoding model were substantially more consistent with various features of the neural and behavioral data. While correlated noise is essential to observe CPs, our findings suggest that selective decoding of neuronal signals also plays important roles.

Distributed and Dynamic Storage of Working Memory Stimulus Information in Extrastriate Cortex

PubMed Central

Sreenivasan, Kartik K.; Vytlacil, Jason; D'Esposito, Mark

2015-01-01

The predominant neurobiological model of working memory (WM) posits that stimulus information is stored via stable elevated activity within highly selective neurons. Based on this model, which we refer to as the canonical model, the storage of stimulus information is largely associated with lateral prefrontal cortex (lPFC). A growing number of studies describe results that cannot be fully explained by the canonical model, suggesting that it is in need of revision. In the present study, we directly test key elements of the canonical model. We analyzed functional MRI data collected as participants performed a task requiring WM for faces and scenes. Multivariate decoding procedures identified patterns of activity containing information about the items maintained in WM (faces, scenes, or both). While information about WM items was identified in extrastriate visual cortex (EC) and lPFC, only EC exhibited a pattern of results consistent with a sensory representation. Information in both regions persisted even in the absence of elevated activity, suggesting that elevated population activity may not represent the storage of information in WM. Additionally, we observed that WM information was distributed across EC neural populations that exhibited a broad range of selectivity for the WM items rather than restricted to highly selective EC populations. Finally, we determined that activity patterns coding for WM information were not stable, but instead varied over the course of a trial, indicating that the neural code for WM information is dynamic rather than static. Together, these findings challenge the canonical model of WM. PMID:24392897

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony

PubMed Central

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S.

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity, the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations. PMID:28154616

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony.

PubMed

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity , the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations.

Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

PubMed Central

Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.

2013-01-01

Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933

Monte Carlo simulations of parapatric speciation

NASA Astrophysics Data System (ADS)

Schwämmle, V.; Sousa, A. O.; de Oliveira, S. M.

2006-06-01

Parapatric speciation is studied using an individual-based model with sexual reproduction. We combine the theory of mutation accumulation for biological ageing with an environmental selection pressure that varies according to the individuals geographical positions and phenotypic traits. Fluctuations and genetic diversity of large populations are crucial ingredients to model the features of evolutionary branching and are intrinsic properties of the model. Its implementation on a spatial lattice gives interesting insights into the population dynamics of speciation on a geographical landscape and the disruptive selection that leads to the divergence of phenotypes. Our results suggest that assortative mating is not an obligatory ingredient to obtain speciation in large populations at low gene flow.

Improving the geomagnetic field modeling with a selection of high-quality archaeointensity data

NASA Astrophysics Data System (ADS)

Pavon-Carrasco, Francisco Javier; Gomez-Paccard, Miriam; Herve, Gwenael; Osete, Maria Luisa; Chauvin, Annick

2014-05-01

Geomagnetic field reconstructions for the last millennia are based on archeomagnetic data. However, the scatter of the archaeointensity data is very puzzling and clearly suggests that some of the intensity data might not be reliable. In this work we apply different selection criteria to the European and Western Asian archaeointensity data covering the last three millennia in order to investigate if the data selection affects geomagnetic field models results. Thanks to the recently developed archeomagnetic databases, new valuable information related to the methodology used to determine the archeointensity data is now available. We therefore used this information to rank the archaeointensity data in four quality categories depending on the methodology used during the laboratory treatment of the samples and on the number of specimens retained to calculate the mean intensities. Results show how the intensity geomagnetic field component given by the regional models hardly depends on the selected quality data used. When all the available data are used a different behavior of the geomagnetic field is observed in Western and Eastern Europe. However, when the regional model is obtained from a selection of high-quality intensity data the same features are observed at the European scale.

A Simple Approach to Account for Climate Model Interdependence in Multi-Model Ensembles

NASA Astrophysics Data System (ADS)

Herger, N.; Abramowitz, G.; Angelil, O. M.; Knutti, R.; Sanderson, B.

2016-12-01

Multi-model ensembles are an indispensable tool for future climate projection and its uncertainty quantification. Ensembles containing multiple climate models generally have increased skill, consistency and reliability. Due to the lack of agreed-on alternatives, most scientists use the equally-weighted multi-model mean as they subscribe to model democracy ("one model, one vote").Different research groups are known to share sections of code, parameterizations in their model, literature, or even whole model components. Therefore, individual model runs do not represent truly independent estimates. Ignoring this dependence structure might lead to a false model consensus, wrong estimation of uncertainty and effective number of independent models.Here, we present a way to partially address this problem by selecting a subset of CMIP5 model runs so that its climatological mean minimizes the RMSE compared to a given observation product. Due to the cancelling out of errors, regional biases in the ensemble mean are reduced significantly.Using a model-as-truth experiment we demonstrate that those regional biases persist into the future and we are not fitting noise, thus providing improved observationally-constrained projections of the 21st century. The optimally selected ensemble shows significantly higher global mean surface temperature projections than the original ensemble, where all the model runs are considered. Moreover, the spread is decreased well beyond that expected from the decreased ensemble size.Several previous studies have recommended an ensemble selection approach based on performance ranking of the model runs. Here, we show that this approach can perform even worse than randomly selecting ensemble members and can thus be harmful. We suggest that accounting for interdependence in the ensemble selection process is a necessary step for robust projections for use in impact assessments, adaptation and mitigation of climate change.

Evolution of female multiple mating: A quantitative model of the “sexually selected sperm” hypothesis

PubMed Central

Bocedi, Greta; Reid, Jane M

2015-01-01

Explaining the evolution and maintenance of polyandry remains a key challenge in evolutionary ecology. One appealing explanation is the sexually selected sperm (SSS) hypothesis, which proposes that polyandry evolves due to indirect selection stemming from positive genetic covariance with male fertilization efficiency, and hence with a male's success in postcopulatory competition for paternity. However, the SSS hypothesis relies on verbal analogy with “sexy-son” models explaining coevolution of female preferences for male displays, and explicit models that validate the basic SSS principle are surprisingly lacking. We developed analogous genetically explicit individual-based models describing the SSS and “sexy-son” processes. We show that the analogy between the two is only partly valid, such that the genetic correlation arising between polyandry and fertilization efficiency is generally smaller than that arising between preference and display, resulting in less reliable coevolution. Importantly, indirect selection was too weak to cause polyandry to evolve in the presence of negative direct selection. Negatively biased mutations on fertilization efficiency did not generally rescue runaway evolution of polyandry unless realized fertilization was highly skewed toward a single male, and coevolution was even weaker given random mating order effects on fertilization. Our models suggest that the SSS process is, on its own, unlikely to generally explain the evolution of polyandry. PMID:25330405

A computational model of selection by consequences: log survivor plots.

PubMed

Kulubekova, Saule; McDowell, J J

2008-06-01

[McDowell, J.J, 2004. A computational model of selection by consequences. J. Exp. Anal. Behav. 81, 297-317] instantiated the principle of selection by consequences in a virtual organism with an evolving repertoire of possible behaviors undergoing selection, reproduction, and mutation over many generations. The process is based on the computational approach, which is non-deterministic and rules-based. The model proposes a causal account for operant behavior. McDowell found that the virtual organism consistently showed a hyperbolic relationship between response and reinforcement rates according to the quantitative law of effect. To continue validation of the computational model, the present study examined its behavior on the molecular level by comparing the virtual organism's IRT distributions in the form of log survivor plots to findings from live organisms. Log survivor plots did not show the "broken-stick" feature indicative of distinct bouts and pauses in responding, although the bend in slope of the plots became more defined at low reinforcement rates. The shape of the virtual organism's log survivor plots was more consistent with the data on reinforced responding in pigeons. These results suggest that log survivor plot patterns of the virtual organism were generally consistent with the findings from live organisms providing further support for the computational model of selection by consequences as a viable account of operant behavior.

Relations between 18-month-olds' gaze pattern and target action performance: a deferred imitation study with eye tracking.

PubMed

Óturai, Gabriella; Kolling, Thorsten; Knopf, Monika

2013-12-01

Deferred imitation studies are used to assess infants' declarative memory performance. These studies have found that deferred imitation performance improves with age, which is usually attributed to advancing memory capabilities. Imitation studies, however, are also used to assess infants' action understanding. In this second research program it has been observed that infants around the age of one year imitate selectively, i.e., they imitate certain kinds of target actions and omit others. In contrast to this, two-year-olds usually imitate the model's exact actions. 18-month-olds imitate more exactly than one-year-olds, but more selectively than two-year-olds, a fact which makes this age group especially interesting, since the processes underlying selective vs. exact imitation are largely debated. The question, for example, if selective attention to certain kinds of target actions accounts for preferential imitation of these actions in young infants is still open. Additionally, relations between memory capabilities and selective imitation processes, as well as their role in shaping 18-month-olds' neither completely selective, nor completely exact imitation have not been thoroughly investigated yet. The present study, therefore, assessed 18-month-olds' gaze toward two types of actions (functional vs. arbitrary target actions) and the model's face during target action demonstration, as well as infants' deferred imitation performance. Although infants' fixation times to functional target actions were not longer than to arbitrary target actions, they imitated the functional target actions more frequently than the arbitrary ones. This suggests that selective imitation does not rely on selective gaze toward functional target actions during the demonstration phase. In addition, a post hoc analysis of interindividual differences suggested that infants' attention to the model's social-communicative cues might play an important role in exact imitation, meaning the imitation of both functional and arbitrary target actions. Copyright © 2013 Elsevier Inc. All rights reserved.

Do males pay for sex? Sex-specific selection coefficients suggest not.

PubMed

Prokop, Zofia M; Prus, Monika A; Gaczorek, Tomasz S; Sychta, Karolina; Palka, Joanna K; Plesnar-Bielak, Agata; Skarboń, Magdalena

2017-03-01

Selection acting on males can reduce mutation load of sexual relative to asexual populations, thus mitigating the twofold cost of sex, provided that it seeks and destroys the same mutations as selection acting on females, but with higher efficiency. This could happen due to sexual selection-a potent evolutionary force that in most systems predominantly affects males. We used replicate populations of red flour beetles (Tribolium castaneum) to study sex-specific selection against deleterious mutations introduced with ionizing radiation. We found no evidence for selection being stronger in males than in females; in fact, we observed a nonsignificant trend in the opposite direction. This suggests that selection on males does not reduce mutation load below the level expected under the (hypothetical) scenario of asexual reproduction. Additionally, we employed a novel approach, based on a simple model, to quantify the relative contributions of sexual and offspring viability selection to the overall selection observed in males. We found them to be similar in magnitude; however, only the offspring viability component was statistically significant. In summary, we found no support for the hypothesis that selection on males in general, and sexual selection in particular, contributes to the evolutionary maintenance of sex. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Feature Selection Methods for Zero-Shot Learning of Neural Activity

PubMed Central

Caceres, Carlos A.; Roos, Matthew J.; Rupp, Kyle M.; Milsap, Griffin; Crone, Nathan E.; Wolmetz, Michael E.; Ratto, Christopher R.

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy. PMID:28690513

Strong Selection at MHC in Mexicans since Admixture

PubMed Central

Zhou, Quan; Zhao, Liang; Guan, Yongtao

2016-01-01

Mexicans are a recent admixture of Amerindians, Europeans, and Africans. We performed local ancestry analysis of Mexican samples from two genome-wide association studies obtained from dbGaP, and discovered that at the MHC region Mexicans have excessive African ancestral alleles compared to the rest of the genome, which is the hallmark of recent selection for admixed samples. The estimated selection coefficients are 0.05 and 0.07 for two datasets, which put our finding among the strongest known selections observed in humans, namely, lactase selection in northern Europeans and sickle-cell trait in Africans. Using inaccurate Amerindian training samples was a major concern for the credibility of previously reported selection signals in Latinos. Taking advantage of the flexibility of our statistical model, we devised a model fitting technique that can learn Amerindian ancestral haplotype from the admixed samples, which allows us to infer local ancestries for Mexicans using only European and African training samples. The strong selection signal at the MHC remains without Amerindian training samples. Finally, we note that medical history studies suggest such a strong selection at MHC is plausible in Mexicans. PMID:26863142

Selection and response bias as determinants of priming of pop-out search: Revelations from diffusion modeling.

PubMed

Burnham, Bryan R

2018-05-03

During visual search, both top-down factors and bottom-up properties contribute to the guidance of visual attention, but selection history can influence attention independent of bottom-up and top-down factors. For example, priming of pop-out (PoP) is the finding that search for a singleton target is faster when the target and distractor features repeat than when those features trade roles between trials. Studies have suggested that such priming (selection history) effects on pop-out search manifest either early, by biasing the selection of the preceding target feature, or later in processing, by facilitating response and target retrieval processes. The present study was designed to examine the influence of selection history on pop-out search by introducing a speed-accuracy trade-off manipulation in a pop-out search task. Ratcliff diffusion modeling (RDM) was used to examine how selection history influenced both attentional bias and response execution processes. The results support the hypothesis that selection history biases attention toward the preceding target's features on the current trial and also influences selection of the response to the target.

Modeling and simulation to support dose selection and clinical development of SC-75416, a selective COX-2 inhibitor for the treatment of acute and chronic pain.

PubMed

Kowalski, K G; Olson, S; Remmers, A E; Hutmacher, M M

2008-06-01

Pharmacokinetic/pharmacodynamic (PK/PD) models were developed and clinical trial simulations were conducted to recommend a study design to test the hypothesis that a dose of SC-75416, a selective cyclooxygenase-2 inhibitor, can be identified that achieves superior pain relief (PR) compared to 400 mg ibuprofen in a post-oral surgery pain model. PK/PD models were developed for SC-75416, rofecoxib, valdecoxib, and ibuprofen relating plasma concentrations to PR scores using a nonlinear logistic-normal model. Clinical trial simulations conducted using these models suggested that 360 mg SC-75416 could achieve superior PR compared to 400 mg ibuprofen. A placebo- and positive-controlled parallel-group post-oral surgery pain study was conducted evaluating placebo, 60, 180, and 360 mg SC-75416 oral solution, and 400 mg ibuprofen. The study results confirmed the hypothesis that 360 mg SC-75416 achieved superior PR relative to 400 mg ibuprofen (DeltaTOTPAR6=3.3, P<0.05) and demonstrated the predictive performance of the PK/PD models.

Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.

Direction selectivity of blowfly motion-sensitive neurons is computed in a two-stage process.

PubMed Central

Borst, A; Egelhaaf, M

1990-01-01

Direction selectivity of motion-sensitive neurons is generally thought to result from the nonlinear interaction between the signals derived from adjacent image points. Modeling of motion-sensitive networks, however, reveals that such elements may still respond to motion in a rather poor directionally selective way. Direction selectivity can be significantly enhanced if the nonlinear interaction is followed by another processing stage in which the signals of elements with opposite preferred directions are subtracted from each other. Our electrophysiological experiments in the fly visual system suggest that here direction selectivity is acquired in such a two-stage process. Images PMID:2251278

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

PubMed

Van Steen, Kristel; Curran, Desmond; Kramer, Jocelyn; Molenberghs, Geert; Van Vreckem, Ann; Bottomley, Andrew; Sylvester, Richard

2002-12-30

Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before. Copyright 2002 John Wiley & Sons, Ltd.

Model Selection Approach Suggests Causal Association between 25-Hydroxyvitamin D and Colorectal Cancer

PubMed Central

Theodoratou, Evropi; Farrington, Susan M.; Tenesa, Albert; Dunlop, Malcolm G.; McKeigue, Paul; Campbell, Harry

2013-01-01

Introduction 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. Methods 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. Results 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. Conclusion Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations. PMID:23717431

Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch Hoverflies as a case study.

PubMed

Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C

2013-01-01

Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data characteristics (i.e. sample size, spatial distribution).

THE SYSTEMATICS OF STRONG LENS MODELING QUANTIFIED: THE EFFECTS OF CONSTRAINT SELECTION AND REDSHIFT INFORMATION ON MAGNIFICATION, MASS, AND MULTIPLE IMAGE PREDICTABILITY

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

Johnson, Traci L.; Sharon, Keren, E-mail: tljohn@umich.edu

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading asmore » to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.« less

Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

PubMed

Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

2014-12-01

Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Early and late selection processes have separable influences on the neural substrates of attention.

PubMed

Drisdelle, Brandi Lee; Jolicoeur, Pierre

2018-05-01

To improve our understanding of the mechanisms of target selection, we examined how the spatial separation of salient items and their similarity to a pre-defined target interact using lateralised electrophysiological correlates of visual spatial attention (N2pc component) and visual short-term memory (VSTM; SPCN component). Using these features of target selection, we sought to expand on previous work proposing a model of early and late selection, where the N2pc is suggested to reflect the selection probability of visual stimuli (Aubin and Jolicoeur, 2016). The authors suggested that early-selection processes could be enhanced when items are adjacent. In the present work, the stimuli were short oriented lines, all of which were grey except for two that were blue and hence salient. A decrease in N2pc amplitude with decreasing spatial separation between salient items was observed. The N2pc increased in amplitude with increasing similarity of salient distractors to the target template, but only in target-absent trials. There was no interaction between these two factors, suggesting that separable attentional mechanisms influenced the N2pc. The findings suggest that selection is initially based on easily-distinguished attributes (i.e., both blue items) followed by a later identification-based process (if necessary), which depends on feature similarity to a target template. For the SPCN component, the results were in line with previous work: for target-present trials, an increase in similarity of salient distractors was associated with an increase in SPCN amplitude, suggesting more information was maintained in VSTM. In sum, results suggest there is a need for further inspection of salient distractors when they are similar to the target, increasing the need for focal attention, demonstrated by an increase in N2pc amplitude, followed by a higher probability of transfer to VSTM, demonstrated by an increase in SPCN amplitude. Copyright © 2018 Elsevier B.V. All rights reserved.

SIGNALING EFFICACY DRIVES THE EVOLUTION OF LARGER SEXUAL ORNAMENTS BY SEXUAL SELECTION

PubMed Central

Tazzyman, Samuel J; Iwasa, Yoh; Pomiankowski, Andrew

2014-01-01

Why are there so few small secondary sexual characters? Theoretical models predict that sexual selection should lead to reduction as often as exaggeration, and yet we mainly associate secondary sexual ornaments with exaggerated features such as the peacock's tail. We review the literature on mate choice experiments for evidence of reduced sexual traits. This shows that reduced ornamentation is effectively impossible in certain types of ornamental traits (behavioral, pheromonal, or color-based traits, and morphological ornaments for which the natural selection optimum is no trait), but that there are many examples of morphological traits that would permit reduction. Yet small sexual traits are very rarely seen. We analyze a simple mathematical model of Fisher's runaway process (the null model for sexual selection). Our analysis shows that the imbalance cannot be wholly explained by larger ornaments being less costly than smaller ornaments, nor by preferences for larger ornaments being less costly than preferences for smaller ornaments. Instead, we suggest that asymmetry in signaling efficacy limits runaway to trait exaggeration. PMID:24099137

Assortative mating can impede or facilitate fixation of underdominant alleles.

PubMed

Newberry, Mitchell G; McCandlish, David M; Plotkin, Joshua B

2016-12-01

Underdominant mutations have fixed between divergent species, yet classical models suggest that rare underdominant alleles are purged quickly except in small or subdivided populations. We predict that underdominant alleles that also influence mate choice, such as those affecting coloration patterns visible to mates and predators alike, can fix more readily. We analyze a mechanistic model of positive assortative mating in which individuals have n chances to sample compatible mates. This one-parameter model naturally spans random mating (n=1) and complete assortment (n→∞), yet it produces sexual selection whose strength depends non-monotonically on n. This sexual selection interacts with viability selection to either inhibit or facilitate fixation. As mating opportunities increase, underdominant alleles fix as frequently as neutral mutations, even though sexual selection and underdominance independently each suppress rare alleles. This mechanism allows underdominant alleles to fix in large populations and illustrates how life history can affect evolutionary change. Copyright © 2016 Elsevier Inc. All rights reserved.

The Matching Relation and Situation-Specific Bias Modulation in Professional Football Play Selection

PubMed Central

Stilling, Stephanie T; Critchfield, Thomas S

2010-01-01

The utility of a quantitative model depends on the extent to which its fitted parameters vary systematically with environmental events of interest. Professional football statistics were analyzed to determine whether play selection (passing versus rushing plays) could be accounted for with the generalized matching equation, and in particular whether variations in play selection across game situations would manifest as changes in the equation's fitted parameters. Statistically significant changes in bias were found for each of five types of game situations; no systematic changes in sensitivity were observed. Further analyses suggested relationships between play selection bias and both turnover probability (which can be described in terms of punishment) and yards-gained variance (which can be described in terms of variable-magnitude reinforcement schedules). The present investigation provides a useful demonstration of association between face-valid, situation-specific effects in a domain of everyday interest, and a theoretically important term of a quantitative model of behavior. Such associations, we argue, are an essential focus in translational extensions of quantitative models. PMID:21119855

Implications of allometric model selection for county-level biomass mapping.

PubMed

Duncanson, Laura; Huang, Wenli; Johnson, Kristofer; Swatantran, Anu; McRoberts, Ronald E; Dubayah, Ralph

2017-10-18

Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend on the application of allometric models, which often have unknown and unreported uncertainties outside of the size class or environment in which they were developed. Here, we test three popular allometric approaches to field biomass estimation, and explore the implications of allometric model selection for county-level biomass mapping in Sonoma County, California. We test three allometric models: Jenkins et al. (For Sci 49(1): 12-35, 2003), Chojnacky et al. (Forestry 87(1): 129-151, 2014) and the US Forest Service's Component Ratio Method (CRM). We found that Jenkins and Chojnacky models perform comparably, but that at both a field plot level and a total county level there was a ~ 20% difference between these estimates and the CRM estimates. Further, we show that discrepancies are greater in high biomass areas with high canopy covers and relatively moderate heights (25-45 m). The CRM models, although on average ~ 20% lower than Jenkins and Chojnacky, produce higher estimates in the tallest forests samples (> 60 m), while Jenkins generally produces higher estimates of biomass in forests < 50 m tall. Discrepancies do not continually increase with increasing forest height, suggesting that inclusion of height in allometric models is not primarily driving discrepancies. Models developed using all three allometric models underestimate high biomass and overestimate low biomass, as expected with random forest biomass modeling. However, these deviations were generally larger using the Jenkins and Chojnacky allometries, suggesting that the CRM approach may be more appropriate for biomass mapping with lidar. These results confirm that allometric model selection considerably impacts biomass maps and estimates, and that allometric model errors remain poorly understood. Our findings that allometric model discrepancies are not explained by lidar heights suggests that allometric model form does not drive these discrepancies. A better understanding of the sources of allometric model errors, particularly in high biomass systems, is essential for improved forest biomass mapping.

Peer Influence, Peer Selection and Adolescent Alcohol Use: a Simulation Study Using a Dynamic Network Model of Friendship Ties and Alcohol Use.

PubMed

Wang, Cheng; Hipp, John R; Butts, Carter T; Jose, Rupa; Lakon, Cynthia M

2017-05-01

While studies suggest that peer influence can in some cases encourage adolescent substance use, recent work demonstrates that peer influence may be on average protective for cigarette smoking, raising questions about whether this effect occurs for other substance use behaviors. Herein, we focus on adolescent drinking, which may follow different social dynamics than smoking. We use a data-calibrated Stochastic Actor-Based (SAB) Model of adolescent friendship tie choice and drinking behavior to explore the impact of manipulating the size of peer influence and selection effects on drinking in two school-based networks. We first fit a SAB Model to data on friendship tie choice and adolescent drinking behavior within two large schools (n = 2178 and n = 976) over three time points using data from the National Longitudinal Study of Adolescent to Adult Health. We then alter the size of the peer influence and selection parameters with all other effects fixed at their estimated values and simulate the social systems forward 1000 times under varying conditions. Whereas peer selection appears to contribute to drinking behavior similarity among adolescents, there is no evidence that it leads to higher levels of drinking at the school level. A stronger peer influence effect lowers the overall level of drinking in both schools. There are many similarities in the patterning of findings between this study of drinking and previous work on smoking, suggesting that peer influence and selection may function similarly with respect to these substances.

Assessing the effectiveness of a hybrid-flipped model of learning on fluid mechanics instruction: overall course performance, homework, and far- and near-transfer of learning

NASA Astrophysics Data System (ADS)

Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge

2017-11-01

To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity score method entailing a two-stage regression analysis that considered eight covariates to address the potential bias of treatment selection. First, we estimated the probability score based on the eight covariates, and second, we used the inverse of the probability score as a regression weight on the performance of learners who did not select into the hybrid course. Results suggest that enrolment in the hybrid-flipped section had a marginally significant negative impact on the total course score and a significant negative impact on homework performance, possibly because of poor video usage by the hybrid-flipped learners. Suggested considerations are also discussed.

Philosophical Models of Man: With Special Reference to the Teaching of ESN Children.

ERIC Educational Resources Information Center

Burnwood, Les. R. V.; Brady, Carol A.

1981-01-01

Two opposing models of man: deterministic and libertarian are outlined and contrasted, and certain selected practical and ethical consequences for the teaching of children are drawn out. Reasons are given for suggesting that the problems are especially acute for the teacher of educationally sub-normal children. (Author)

Using Two Models in Optics: Students' Difficulties and Suggestions for Teaching.

ERIC Educational Resources Information Center

Colin, P.; Viennot, L.

2001-01-01

Focuses on difficulties linked to situations in physics involving two models--geometrical optics and wave optics. Presents content analysis underlining two important features required for addressing such situations: (1) awareness of the status of the drawings; and (2) the 'backward selection' of paths of light. (Contains 24 references.)…

Conference Model: Guidelines...for Science Supervisors on How to Conduct a Successful Leadership Conference.

ERIC Educational Resources Information Center

DeBlasi, Robert V.

Guidelines of a four-phase model for conducting leadership conferences are outlined. Phase I focuses on initial conference planning, including (1) identifying need and purpose for the conference; (2) selecting a conference chairperson; (3) forming the conference planning committee, listing suggested committees and their responsibilities (program,…

Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

PubMed

Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

2015-01-01

It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

An integrated model for adolescent inpatient group therapy.

PubMed

Garrick, D; Ewashen, C

2001-04-01

This paper proposes an integrated group therapy model to be utilized by psychiatric and mental health nurses; one innovatively designed to meet the therapeutic needs of adolescents admitted to inpatient psychiatric programs. The writers suggest a model of group therapy primarily comprised of interpersonal approaches within a feminist perspective. The proposed group focus is on active therapeutic engagement with adolescents to further interpersonal learning and to critically examine their contextualized lived experiences. Specific client and setting factors relevant to the selection of therapeutic techniques are reviewed. Selected theoretical models of group therapy are critiqued in relation to group therapy with adolescents. This integrated model of group therapy provides a safe and therapeutic forum that enriches clients' personal and interpersonal experiences as well as promotes healthy exploration, change, and empowerment.

Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.

PubMed

Gerdessen, Johanna C; Souverein, Olga W; van 't Veer, Pieter; de Vries, Jeanne Hm

2015-01-01

To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium. The food lists generated by the MILP model have good performance in terms of length, coverage and R 2 (explained variance) of all nutrients. MILP-generated food lists were 32-40 % shorter than a benchmark food list, whereas their quality in terms of R 2 was similar to that of the benchmark. The results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.

Complex patterns of divergence among green-sensitive (RH2a) African cichlid opsins revealed by Clade model analyses

PubMed Central

2012-01-01

Background Gene duplications play an important role in the evolution of functional protein diversity. Some models of duplicate gene evolution predict complex forms of paralog divergence; orthologous proteins may diverge as well, further complicating patterns of divergence among and within gene families. Consequently, studying the link between protein sequence evolution and duplication requires the use of flexible substitution models that can accommodate multiple shifts in selection across a phylogeny. Here, we employed a variety of codon substitution models, primarily Clade models, to explore how selective constraint evolved following the duplication of a green-sensitive (RH2a) visual pigment protein (opsin) in African cichlids. Past studies have linked opsin divergence to ecological and sexual divergence within the African cichlid adaptive radiation. Furthermore, biochemical and regulatory differences between the RH2aα and RH2aβ paralogs have been documented. It thus seems likely that selection varies in complex ways throughout this gene family. Results Clade model analysis of African cichlid RH2a opsins revealed a large increase in the nonsynonymous-to-synonymous substitution rate ratio (ω) following the duplication, as well as an even larger increase, one consistent with positive selection, for Lake Tanganyikan cichlid RH2aβ opsins. Analysis using the popular Branch-site models, by contrast, revealed no such alteration of constraint. Several amino acid sites known to influence spectral and non-spectral aspects of opsin biochemistry were found to be evolving divergently, suggesting that orthologous RH2a opsins may vary in terms of spectral sensitivity and response kinetics. Divergence appears to be occurring despite intronic gene conversion among the tandemly-arranged duplicates. Conclusions Our findings indicate that variation in selective constraint is associated with both gene duplication and divergence among orthologs in African cichlid RH2a opsins. At least some of this variation may reflect an adaptive response to differences in light environment. Interestingly, these patterns only became apparent through the use of Clade models, not through the use of the more widely employed Branch-site models; we suggest that this difference stems from the increased flexibility associated with Clade models. Our results thus bear both on studies of cichlid visual system evolution and on studies of gene family evolution in general. PMID:23078361

Accounting for animal movement in estimation of resource selection functions: sampling and data analysis.

PubMed

Forester, James D; Im, Hae Kyung; Rathouz, Paul J

2009-12-01

Patterns of resource selection by animal populations emerge as a result of the behavior of many individuals. Statistical models that describe these population-level patterns of habitat use can miss important interactions between individual animals and characteristics of their local environment; however, identifying these interactions is difficult. One approach to this problem is to incorporate models of individual movement into resource selection models. To do this, we propose a model for step selection functions (SSF) that is composed of a resource-independent movement kernel and a resource selection function (RSF). We show that standard case-control logistic regression may be used to fit the SSF; however, the sampling scheme used to generate control points (i.e., the definition of availability) must be accommodated. We used three sampling schemes to analyze simulated movement data and found that ignoring sampling and the resource-independent movement kernel yielded biased estimates of selection. The level of bias depended on the method used to generate control locations, the strength of selection, and the spatial scale of the resource map. Using empirical or parametric methods to sample control locations produced biased estimates under stronger selection; however, we show that the addition of a distance function to the analysis substantially reduced that bias. Assuming a uniform availability within a fixed buffer yielded strongly biased selection estimates that could be corrected by including the distance function but remained inefficient relative to the empirical and parametric sampling methods. As a case study, we used location data collected from elk in Yellowstone National Park, USA, to show that selection and bias may be temporally variable. Because under constant selection the amount of bias depends on the scale at which a resource is distributed in the landscape, we suggest that distance always be included as a covariate in SSF analyses. This approach to modeling resource selection is easily implemented using common statistical tools and promises to provide deeper insight into the movement ecology of animals.

Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

PubMed Central

Abdul-Kreem, Luma Issa; Neumann, Heiko

2015-01-01

The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells. PMID:26554589

Extending Data Worth Analyses to Select Multiple Observations Targeting Multiple Forecasts.

PubMed

Vilhelmsen, Troels N; Ferré, Ty P A

2018-05-01

Hydrological models are often set up to provide specific forecasts of interest. Owing to the inherent uncertainty in data used to derive model structure and used to constrain parameter variations, the model forecasts will be uncertain. Additional data collection is often performed to minimize this forecast uncertainty. Given our common financial restrictions, it is critical that we identify data with maximal information content with respect to forecast of interest. In practice, this often devolves to qualitative decisions based on expert opinion. However, there is no assurance that this will lead to optimal design, especially for complex hydrogeological problems. Specifically, these complexities include considerations of multiple forecasts, shared information among potential observations, information content of existing data, and the assumptions and simplifications underlying model construction. In the present study, we extend previous data worth analyses to include: simultaneous selection of multiple new measurements and consideration of multiple forecasts of interest. We show how the suggested approach can be used to optimize data collection. This can be used in a manner that suggests specific measurement sets or that produces probability maps indicating areas likely to be informative for specific forecasts. Moreover, we provide examples documenting that sequential measurement election approaches often lead to suboptimal designs and that estimates of data covariance should be included when selecting future measurement sets. © 2017, National Ground Water Association.

Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska

USGS Publications Warehouse

Roffler, Gretchen H.; Adams, Layne G.; Hebblewhite, Mark

2017-01-01

Sexual segregation occurs frequently in sexually dimorphic species, and it may be influenced by differential habitat requirements between sexes or by social or evolutionary mechanisms that maintain separation of sexes regardless of habitat selection. Understanding the degree of sex-specific habitat specialization is important for management of wildlife populations and the design of monitoring and research programs. Using mid-summer aerial survey data for Dall’s sheep (Ovis dalli dalli) in southern Alaska during 1983–2011, we assessed differences in summer habitat selection by sex and reproductive status at the landscape scale in Wrangell-St. Elias National Park and Preserve (WRST). Males and females were highly segregated socially, as were females with and without young. Resource selection function (RSF) models containing rugged terrain, intermediate values of the normalized difference vegetation index (NDVI), and open landcover types best explained resource selection by each sex, female reproductive classes, and all sheep combined. For male and all female models, most coefficients were similar, suggesting little difference in summer habitat selection between sexes at the landscape scale. A combined RSF model therefore may be used to predict the relative probability of resource selection by Dall’s sheep in WRST regardless of sex or reproductive status.

Structural equation models to estimate risk of infection and tolerance to bovine mastitis.

PubMed

Detilleux, Johann; Theron, Léonard; Duprez, Jean-Noël; Reding, Edouard; Humblet, Marie-France; Planchon, Viviane; Delfosse, Camille; Bertozzi, Carlo; Mainil, Jacques; Hanzen, Christian

2013-03-06

One method to improve durably animal welfare is to select, as reproducers, animals with the highest ability to resist or tolerate infection. To do so, it is necessary to distinguish direct and indirect mechanisms of resistance and tolerance because selection on these traits is believed to have different epidemiological and evolutionary consequences. We propose structural equation models with latent variables (1) to quantify the latent risk of infection and to identify, among the many potential mediators of infection, the few ones that influence it significantly and (2) to estimate direct and indirect levels of tolerance of animals infected naturally with pathogens. We applied the method to two surveys of bovine mastitis in the Walloon region of Belgium, in which we recorded herd management practices, mastitis frequency, and results of bacteriological analyses of milk samples. Structural equation models suggested that, among more than 35 surveyed herd characteristics, only nine (age, addition of urea in the rations, treatment of subclinical mastitis, presence of dirty liner, cows with hyperkeratotic teats, machine stripping, pre- and post-milking teat disinfection, and housing of milking cows in cubicles) were directly and significantly related to a latent measure of bovine mastitis, and that treatment of subclinical mastitis was involved in the pathway between post-milking teat disinfection and latent mastitis. These models also allowed the separation of direct and indirect effects of bacterial infection on milk productivity. Results suggested that infected cows were tolerant but not resistant to mastitis pathogens. We revealed the advantages of structural equation models, compared to classical models, for dissecting measurements of resistance and tolerance to infectious diseases, here bovine mastitis. Using our method, we identified nine major risk factors that were directly associated with an increased risk of mastitis and suggested that cows were tolerant but not resistant to mastitis. Selection should aim at improved resistance to infection by mastitis pathogens, although further investigations are needed due to the limitations of the data used in this study.

Risk Profiling May Improve Lung Cancer Screening

Cancer.gov

A new modeling study suggests that individualized, risk-based selection of ever-smokers for lung cancer screening may prevent more lung cancer deaths and improve the effectiveness and efficiency of screening compared with current screening recommendations

Population mitogenomics provides insights into evolutionary history, source of invasions and diversifying selection in the House Crow (Corvus splendens).

PubMed

Krzemińska, Urszula; Morales, Hernán E; Greening, Chris; Nyári, Árpád S; Wilson, Robyn; Song, Beng Kah; Austin, Christopher M; Sunnucks, Paul; Pavlova, Alexandra; Rahman, Sadequr

2018-04-01

The House Crow (Corvus splendens) is a useful study system for investigating the genetic basis of adaptations underpinning successful range expansion. The species originates from the Indian subcontinent, but has successfully spread through a variety of thermal environments across Asia, Africa and Europe. Here, population mitogenomics was used to investigate the colonisation history and to test for signals of molecular selection on the mitochondrial genome. We sequenced the mitogenomes of 89 House Crows spanning four native and five invasive populations. A Bayesian dated phylogeny, based on the 13 mitochondrial protein-coding genes, supports a mid-Pleistocene (~630,000 years ago) divergence between the most distant genetic lineages. Phylogeographic patterns suggest that northern South Asia is the likely centre of origin for the species. Codon-based analyses of selection and assessments of changes in amino acid properties provide evidence of positive selection on the ND2 and ND5 genes against a background of purifying selection across the mitogenome. Protein homology modelling suggests that four amino acid substitutions inferred to be under positive selection may modulate coupling efficiency and proton translocation mediated by OXPHOS complex I. The identified substitutions are found within native House Crow lineages and ecological niche modelling predicts suitable climatic areas for the establishment of crow populations within the invasive range. Mitogenomic patterns in the invasive range of the species are more strongly associated with introduction history than climate. We speculate that invasions of the House Crow have been facilitated by standing genetic variation that accumulated due to diversifying selection within the native range.

Likelihood analysis of the chalcone synthase genes suggests the role of positive selection in morning glories (Ipomoea).

PubMed

Yang, Ji; Gu, Hongya; Yang, Ziheng

2004-01-01

Chalcone synthase (CHS) is a key enzyme in the biosynthesis of flavonoides, which are important for the pigmentation of flowers and act as attractants to pollinators. Genes encoding CHS constitute a multigene family in which the copy number varies among plant species and functional divergence appears to have occurred repeatedly. In morning glories (Ipomoea), five functional CHS genes (A-E) have been described. Phylogenetic analysis of the Ipomoea CHS gene family revealed that CHS A, B, and C experienced accelerated rates of amino acid substitution relative to CHS D and E. To examine whether the CHS genes of the morning glories underwent adaptive evolution, maximum-likelihood models of codon substitution were used to analyze the functional sequences in the Ipomoea CHS gene family. These models used the nonsynonymous/synonymous rate ratio (omega = d(N)/ d(S)) as an indicator of selective pressure and allowed the ratio to vary among lineages or sites. Likelihood ratio test suggested significant variation in selection pressure among amino acid sites, with a small proportion of them detected to be under positive selection along the branches ancestral to CHS A, B, and C. Positive Darwinian selection appears to have promoted the divergence of subfamily ABC and subfamily DE and is at least partially responsible for a rate increase following gene duplication.

Mitochondrial ASncmtRNA-1 and ASncmtRNA-2 as potent targets to inhibit tumor growth and metastasis in the RenCa murine renal adenocarcinoma model

PubMed Central

Borgna, Vincenzo; Villegas, Jaime; Burzio, Verónica A.; Belmar, Sebastián; Araya, Mariela; Jeldes, Emanuel; Lobos-González, Lorena; Silva, Verónica; Villota, Claudio; Oliveira-Cruz, Luciana; Lopez, Constanza; Socias, Teresa; Castillo, Octavio; Burzio, Luis O.

2017-01-01

Knockdown of antisense noncoding mitochondrial RNAs (ASncmtRNAs) induces apoptosis in several human and mouse tumor cell lines, but not normal cells, suggesting this approach for a selective therapy against different types of cancer. Here we show that in vitro knockdown of murine ASncmtRNAs induces apoptotic death of mouse renal adenocarcinoma RenCa cells, but not normal murine kidney epithelial cells. In a syngeneic subcutaneous RenCa model, treatment delayed and even reversed tumor growth. Since the subcutaneous model does not reflect the natural microenviroment of renal cancer, we used an orthotopic model of RenCa cells inoculated under the renal capsule. These studies showed inhibition of tumor growth and metastasis. Direct metastasis assessment by tail vein injection of RenCa cells also showed a drastic reduction in lung metastatic nodules. In vivo treatment reduces survivin, N-cadherin and P-cadherin levels, providing a molecular basis for metastasis inhibition. In consequence, the treatment significantly enhanced mouse survival in these models. Our results suggest that the ASncmtRNAs could be potent and selective targets for therapy against human renal cell carcinoma. PMID:28620146

Mitochondrial ASncmtRNA-1 and ASncmtRNA-2 as potent targets to inhibit tumor growth and metastasis in the RenCa murine renal adenocarcinoma model.

PubMed

Borgna, Vincenzo; Villegas, Jaime; Burzio, Verónica A; Belmar, Sebastián; Araya, Mariela; Jeldes, Emanuel; Lobos-González, Lorena; Silva, Verónica; Villota, Claudio; Oliveira-Cruz, Luciana; Lopez, Constanza; Socias, Teresa; Castillo, Octavio; Burzio, Luis O

2017-07-04

Knockdown of antisense noncoding mitochondrial RNAs (ASncmtRNAs) induces apoptosis in several human and mouse tumor cell lines, but not normal cells, suggesting this approach for a selective therapy against different types of cancer. Here we show that in vitro knockdown of murine ASncmtRNAs induces apoptotic death of mouse renal adenocarcinoma RenCa cells, but not normal murine kidney epithelial cells. In a syngeneic subcutaneous RenCa model, treatment delayed and even reversed tumor growth. Since the subcutaneous model does not reflect the natural microenviroment of renal cancer, we used an orthotopic model of RenCa cells inoculated under the renal capsule. These studies showed inhibition of tumor growth and metastasis. Direct metastasis assessment by tail vein injection of RenCa cells also showed a drastic reduction in lung metastatic nodules. In vivo treatment reduces survivin, N-cadherin and P-cadherin levels, providing a molecular basis for metastasis inhibition. In consequence, the treatment significantly enhanced mouse survival in these models. Our results suggest that the ASncmtRNAs could be potent and selective targets for therapy against human renal cell carcinoma.

The genetic consequences of selection in natural populations.

PubMed

Thurman, Timothy J; Barrett, Rowan D H

2016-04-01

The selection coefficient, s, quantifies the strength of selection acting on a genetic variant. Despite this parameter's central importance to population genetic models, until recently we have known relatively little about the value of s in natural populations. With the development of molecular genetic techniques in the late 20th century and the sequencing technologies that followed, biologists are now able to identify genetic variants and directly relate them to organismal fitness. We reviewed the literature for published estimates of natural selection acting at the genetic level and found over 3000 estimates of selection coefficients from 79 studies. Selection coefficients were roughly exponentially distributed, suggesting that the impact of selection at the genetic level is generally weak but can occasionally be quite strong. We used both nonparametric statistics and formal random-effects meta-analysis to determine how selection varies across biological and methodological categories. Selection was stronger when measured over shorter timescales, with the mean magnitude of s greatest for studies that measured selection within a single generation. Our analyses found conflicting trends when considering how selection varies with the genetic scale (e.g., SNPs or haplotypes) at which it is measured, suggesting a need for further research. Besides these quantitative conclusions, we highlight key issues in the calculation, interpretation, and reporting of selection coefficients and provide recommendations for future research. © 2016 John Wiley & Sons Ltd.

Safety belt promotion: theory and practice.

PubMed

Nelson, G D; Moffit, P B

1988-02-01

The purpose of this paper is to provide practitioners a rationale and description of selected theoretically based approaches to safety belt promotion. Theory failure is a threat to the integrity and effectiveness of safety belt promotion. The absence of theory driven programs designed to promote safety belt use is a concern of this paper. Six theoretical models from the social and behavioral sciences are reviewed with suggestions for application to promoting safety belt use and include Theory of Reasoned Action, the Health Belief Model, Fear Arousal, Operant Learning, Social Learning Theory, and Diffusion of Innovations. Guidelines for the selection and utilization of theory are discussed.

Evaluation of Target Specificity of Antibacterial Agents Using Staphylococcus aureus ddlA Mutants and d-Cycloserine in a Silkworm Infection Model▿

PubMed Central

Kurokawa, Kenji; Hamamoto, Hiroshi; Matsuo, Miki; Nishida, Satoshi; Yamane, Noriko; Lee, Bok Luel; Murakami, Kazuhisa; Maki, Hideki; Sekimizu, Kazuhisa

2009-01-01

The availability of a silkworm larva infection model to evaluate the therapeutic effectiveness of antibiotics was examined. The 50% effective doses (ED50) of d-cycloserine against the Staphylococcus aureus ddlA mutant-mediated killing of larvae were remarkably lower than those against the parental strain-mediated killing of larvae. Changes in MICs and ED50 of other antibiotics were negligible, suggesting that these alterations are d-cycloserine selective. Therefore, this model is useful for selecting desired compounds based on their therapeutic effectiveness during antibiotic development. PMID:19546371

Hierarchical competitions subserving multi-attribute choice

PubMed Central

Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy EJ

2015-01-01

Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest competitive inhibition may occur in early valuation stages, before option selection. Here, we show behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

USGS Publications Warehouse

Waite, Ian R.

2014-01-01

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Changing how I feel about the food: experimentally manipulated affective associations with fruits change fruit choice behaviors.

PubMed

Walsh, Erin M; Kiviniemi, Marc T

2014-04-01

Fewer than half of Americans meet current recommendations for fruit and vegetable intake. The behavioral affective associations model posits that feelings and emotions associated with a behavior are a proximal influence on decision making. Cross-sectional evidence supports the model and suggests that affective associations predict fruit and vegetable consumption. The purpose of this study was to test whether a causal relation exists between affective associations about fruits and future fruit consumption behavior, as measured by a snack selection task. Following a baseline assessment of cognitive and affective variables, participants' (N = 161) affective associations about fruits were experimentally manipulated with an implicit priming paradigm. Images of fruits were repeatedly paired with positive, negative, or neutral affective stimuli. The key outcome measure was a behavioral choice task in which participants chose between fruit and a granola bar. Participants in the positive prime condition were three times more likely than those in the negative condition to select a piece of fruit over the granola bar alternative in the snack selection task. They were also twice as likely as those in the neutral condition to select fruit. There were no changes in self-reported affective associations or cognitive beliefs. These findings provide further evidence of the implicit and direct influence of affective associations on behavior, suggesting the need to both incorporate the role of affect in health decision making models, as well as the potential utility of intervention strategies targeting affective associations with health-related behaviors.

Changing how I feel about the food: experimentally manipulated affective associations with fruits change fruit choice behaviors

PubMed Central

Kiviniemi, Marc T.

2013-01-01

Fewer than half of Americans meet current recommendations for fruit and vegetable intake. The behavioral affective associations model posits that feelings and emotions associated with a behavior are a proximal influence on decision making. Cross-sectional evidence supports the model and suggests that affective associations predict fruit and vegetable consumption. The purpose of this study was to test whether a causal relation exists between affective associations about fruits and future fruit consumption behavior, as measured by a snack selection task. Following a baseline assessment of cognitive and affective variables, participants’ (N = 161) affective associations about fruits were experimentally manipulated with an implicit priming paradigm. Images of fruits were repeatedly paired with positive, negative, or neutral affective stimuli. The key outcome measure was a behavioral choice task in which participants chose between fruit and a granola bar. Participants in the positive prime condition were three times more likely than those in the negative condition to select a piece of fruit over the granola bar alternative in the snack selection task. They were also twice as likely as those in the neutral condition to select fruit. There were no changes in self-reported affective associations or cognitive beliefs. These findings provide further evidence of the implicit and direct influence of affective associations on behavior, suggesting the need to both incorporate the role of affect in health decision making models, as well as the potential utility of intervention strategies targeting affective associations with health-related behaviors. PMID:23299831

Elucidating spatially explicit behavioral landscapes in the Willow Flycatcher

USGS Publications Warehouse

Bakian, Amanda V.; Sullivan, Kimberly A.; Paxton, Eben H.

2012-01-01

Animal resource selection is a complex, hierarchical decision-making process, yet resource selection studies often focus on the presence and absence of an animal rather than the animal's behavior at resource use locations. In this study, we investigate foraging and vocalization resource selection in a population of Willow Flycatchers, Empidonax traillii adastus, using Bayesian spatial generalized linear models. These models produce “behavioral landscapes” in which space use and resource selection is linked through behavior. Radio telemetry locations were collected from 35 adult Willow Flycatchers (n = 14 males, n = 13 females, and n = 8 unknown sex) over the 2003 and 2004 breeding seasons at Fish Creek, Utah. Results from the 2-stage modeling approach showed that habitat type, perch position, and distance from the arithmetic mean of the home range (in males) or nest site (in females) were important factors influencing foraging and vocalization resource selection. Parameter estimates from the individual-level models indicated high intraspecific variation in the use of the various habitat types and perch heights for foraging and vocalization. On the population level, Willow Flycatchers selected riparian habitat over other habitat types for vocalizing but used multiple habitat types for foraging including mountain shrub, young riparian, and upland forest. Mapping of observed and predicted foraging and vocalization resource selection indicated that the behavior often occurred in disparate areas of the home range. This suggests that multiple core areas may exist in the home ranges of individual flycatchers, and demonstrates that the behavioral landscape modeling approach can be applied to identify spatially and behaviorally distinct core areas. The behavioral landscape approach is applicable to a wide range of animal taxa and can be used to improve our understanding of the spatial context of behavior and resource selection.

A hydrophobic filter confers the cation selectivity of Zygosaccharomyces rouxii plasma-membrane Na+/H+ antiporter.

PubMed

Kinclova-Zimmermannova, Olga; Falson, Pierre; Cmunt, Denis; Sychrova, Hana

2015-04-24

Na(+)/H(+) antiporters may recognize all alkali-metal cations as substrates but may transport them selectively. Plasma-membrane Zygosaccharomyces rouxii Sod2-22 antiporter exports Na(+) and Li(+), but not K(+). The molecular basis of this selectivity is unknown. We combined protein structure modeling, site-directed mutagenesis, phenotype analysis and cation efflux measurements to localize and characterize the cation selectivity region. A three-dimensional model of the ZrSod2-22 transmembrane domain was generated based on the X-ray structure of the Escherichia coli NhaA antiporter and primary sequence alignments with homologous yeast antiporters. The model suggested a close proximity of Thr141, Ala179 and Val375 from transmembrane segments 4, 5 and 11, respectively, forming a hydrophobic hole in the putative cation pathway's core. A series of mutagenesis experiments verified the model and showed that structural modifications of the hole resulted in altered cation selectivity and transport activity. The triple ZrSod2-22 mutant T141S-A179T-V375I gained K(+) transport capacity. The point mutation A179T restricted the antiporter substrate specificity to Li(+) and reduced its transport activity, while serine at this position preserved the native cation selectivity. The negative effect of the A179T mutation can be eliminated by introducing a second mutation, T141S or T141A, in the preceding transmembrane domain. Our experimental results confirm that the three residues found through modeling play a central role in the determination of cation selectivity and transport activity in Z. rouxii Na(+)/H(+) antiporter and that the cation selectivity can be modulated by repositioning a single local methyl group. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.

PubMed

Resende, R T; Resende, M D V; Silva, F F; Azevedo, C F; Takahashi, E K; Silva-Junior, O B; Grattapaglia, D

2017-10-01

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F 2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

Evidence of long-term gene flow and selection during domestication from analyses of Eurasian wild and domestic pig genomes.

PubMed

Frantz, Laurent A F; Schraiber, Joshua G; Madsen, Ole; Megens, Hendrik-Jan; Cagan, Alex; Bosse, Mirte; Paudel, Yogesh; Crooijmans, Richard P M A; Larson, Greger; Groenen, Martien A M

2015-10-01

Traditionally, the process of domestication is assumed to be initiated by humans, involve few individuals and rely on reproductive isolation between wild and domestic forms. We analyzed pig domestication using over 100 genome sequences and tested whether pig domestication followed a traditional linear model or a more complex, reticulate model. We found that the assumptions of traditional models, such as reproductive isolation and strong domestication bottlenecks, are incompatible with the genetic data. In addition, our results show that, despite gene flow, the genomes of domestic pigs have strong signatures of selection at loci that affect behavior and morphology. We argue that recurrent selection for domestic traits likely counteracted the homogenizing effect of gene flow from wild boars and created 'islands of domestication' in the genome. Our results have major ramifications for the understanding of animal domestication and suggest that future studies should employ models that do not assume reproductive isolation.

Learning to choose: Cognitive aging and strategy selection learning in decision making.

PubMed

Mata, Rui; von Helversen, Bettina; Rieskamp, Jörg

2010-06-01

Decision makers often have to learn from experience. In these situations, people must use the available feedback to select the appropriate decision strategy. How does the ability to select decision strategies on the basis of experience change with age? We examined younger and older adults' strategy selection learning in a probabilistic inference task using a computational model of strategy selection learning. Older adults showed poorer decision performance compared with younger adults. In particular, older adults performed poorly in an environment favoring the use of a more cognitively demanding strategy. The results suggest that the impact of cognitive aging on strategy selection learning depends on the structure of the decision environment. (c) 2010 APA, all rights reserved

FlexPepDock lessons from CAPRI peptide-protein rounds and suggested new criteria for assessment of model quality and utility.

PubMed

Marcu, Orly; Dodson, Emma-Joy; Alam, Nawsad; Sperber, Michal; Kozakov, Dima; Lensink, Marc F; Schueler-Furman, Ora

2017-03-01

CAPRI rounds 28 and 29 included, for the first time, peptide-receptor targets of three different systems, reflecting increased appreciation of the importance of peptide-protein interactions. The CAPRI rounds allowed us to objectively assess the performance of Rosetta FlexPepDock, one of the first protocols to explicitly include peptide flexibility in docking, accounting for peptide conformational changes upon binding. We discuss here successes and challenges in modeling these targets: we obtain top-performing, high-resolution models of the peptide motif for cases with known binding sites but there is a need for better modeling of flanking regions, as well as better selection criteria, in particular for unknown binding sites. These rounds have also provided us the opportunity to reassess the success criteria, to better reflect the quality of a peptide-protein complex model. Using all models submitted to CAPRI, we analyze the correlation between current classification criteria and the ability to retrieve critical interface features, such as hydrogen bonds and hotspots. We find that loosening the backbone (and ligand) RMSD threshold, together with a restriction on the side chain RMSD measure, allows us to improve the selection of high-accuracy models. We also suggest a new measure to assess interface hydrogen bond recovery, which is not assessed by the current CAPRI criteria. Finally, we find that surprisingly much can be learned from rather inaccurate models about binding hotspots, suggesting that the current status of peptide-protein docking methods, as reflected by the submitted CAPRI models, can already have a significant impact on our understanding of protein interactions. Proteins 2017; 85:445-462. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Lineage Selection and the Maintenance of Sex.

PubMed

de Vienne, Damien M; Giraud, Tatiana; Gouyon, Pierre-Henri

2013-01-01

Sex predominates in eukaryotes, despite its short-term disadvantage when compared to asexuality. Myriad models have suggested that short-term advantages of sex may be sufficient to counterbalance its twofold costs. However, despite decades of experimental work seeking such evidence, no evolutionary mechanism has yet achieved broad recognition as explanation for the maintenance of sex. We explore here, through lineage-selection models, the conditions favouring the maintenance of sex. In the first model, we allowed the rate of transition to asexuality to evolve, to determine whether lineage selection favoured species with the strongest constraints preventing the loss of sex. In the second model, we simulated more explicitly the mechanisms underlying the higher extinction rates of asexual lineages than of their sexual counterparts. We linked extinction rates to the ecological and/or genetic features of lineages, thereby providing a formalisation of the only figure included in Darwin's "The origin of species". Our results reinforce the view that the long-term advantages of sex and lineage selection may provide the most satisfactory explanations for the maintenance of sex in eukaryotes, which is still poorly recognized, and provide figures and a simulation website for training and educational purposes. Short-term benefits may play a role, but it is also essential to take into account the selection of lineages for a thorough understanding of the maintenance of sex.

Determining the Number of Component Clusters in the Standard Multivariate Normal Mixture Model Using Model-Selection Criteria.

DTIC Science & Technology

1983-06-16

has been advocated by Gnanadesikan and 𔃾ilk (1969), and others in the literature. This suggests that, if we use the formal signficance test type...American Statistical Asso., 62, 1159-1178. Gnanadesikan , R., and Wilk, M..B. (1969). Data Analytic Methods in Multi- variate Statistical Analysis. In

Fluctuating selection across years and phenotypic variation in food-deceptive orchids.

PubMed

Scopece, Giovanni; Juillet, Nicolas; Lexer, Christian; Cozzolino, Salvatore

2017-01-01

Nectarless flowers that deceive pollinators offer an opportunity to study asymmetric plant-insect interactions. Orchids are a widely used model for studying these interactions because they encompass several thousand species adopting deceptive pollination systems. High levels of intra-specific phenotypic variation have been reported in deceptive orchids, suggesting a reduced consistency of pollinator-mediated selection on their floral traits. Nevertheless, several studies report on widespread directional selection mediated by pollinators even in these deceptive orchids. In this study we test the hypothesis that the observed selection can fluctuate across years in strength and direction thus likely contributing to the phenotypic variability of this orchid group. We performed a three-year study estimating selection differentials and selection gradients for nine phenotypic traits involved in insect attraction in two Mediterranean orchid species, namely Orchis mascula and O. pauciflora , both relying on a well-described food-deceptive pollination strategy. We found weak directional selection and marginally significant selection gradients in the two investigated species with significant intra-specific differences in selection differentials across years. Our data do not link this variation with a specific environmental cause, but our results suggest that pollinator-mediated selection in food-deceptive orchids can change in strength and in direction over time. In perennial plants, such as orchids, different selection differentials in the same populations in different flowering seasons can contribute to the maintenance of phenotypic variation often reported in deceptive orchids.

Natural selection and sex differences in morbidity and mortality in early life.

PubMed

Wells, J C

2000-01-07

Both morbidity and mortality are consistently reported to be higher in males than in females in early life, but no explanation for these findings has been offered. This paper argues that the sex difference in early vulnerability can be attributed to the natural selection of optimal maternal strategies for maximizing lifetime reproductive success, as modelled previously by Trivers and Willard. These authors theorized that males and females offer different returns on parental investment depending on the state of the environment. Natural selection has therefore favoured maternal ability to manipulate offspring sex in response to environmental conditions in early life, as shown in variation in the sex ratio at birth. This argument can be extended to the whole period of parental investment until weaning. Male vulnerability in response to environmental stress in early life is predicted to have been favoured by natural selection. This vulnerability is most evident in the harsh conditions resulting from pre-term birth, but can also be seen in term infants, and manifests as greater morbidity and mortality persisting into early childhood. Malnutrition, interacting with infection after birth, is suggested as the fundamental trigger mechanism. The model suggests that whatever improvements are made in medical care, any environmental stress will always affect males more severely than females in early life. Copyright 2000 Academic Press.

Flood prevention dams for arid regions at a micro-scale sub-catchment, case study: Tabuk, Saudi Arabia.

PubMed

Abushandi, Eyad

2016-12-01

Unexpected flash flooding is one of the periodic hydrological problems affecting the city of Tabuk in Saudi Arabia. The region has high potential for floods as it suffers high rainfall intensity in a short time and also has high urbanization rates and topographic complexity. Constructing flood prevention dams is one option to solve this problem. A cost-effective design requires a detailed feasibility study and analysis for the selection of suitable sites. The aim of this study was to develop a method for selecting a suitable site for flood protection dams in the Abu Saba'a district, the most affected part of the city of Tabuk during the flash flood in January 2013. Spatial analysis was applied using Landsat Thematic Mapper images and Shuttle Radar Topography Mission digital elevation model to select a site in the Abu Saba'a area. A simple model using ArcGIS was built including all suggested parameters. The results showed the best site for a dam was 2 km distance backfrom the area, where all parameter values matched. The results showed that the dynamic properties of land cover can affect site selection. It is therefore suggested that more field and hydrological data should be gathered for greater accuracy.

Human behavior. Sex equality can explain the unique social structure of hunter-gatherer bands.

PubMed

Dyble, M; Salali, G D; Chaudhary, N; Page, A; Smith, D; Thompson, J; Vinicius, L; Mace, R; Migliano, A B

2015-05-15

The social organization of mobile hunter-gatherers has several derived features, including low within-camp relatedness and fluid meta-groups. Although these features have been proposed to have provided the selective context for the evolution of human hypercooperation and cumulative culture, how such a distinctive social system may have emerged remains unclear. We present an agent-based model suggesting that, even if all individuals in a community seek to live with as many kin as possible, within-camp relatedness is reduced if men and women have equal influence in selecting camp members. Our model closely approximates observed patterns of co-residence among Agta and Mbendjele BaYaka hunter-gatherers. Our results suggest that pair-bonding and increased sex egalitarianism in human evolutionary history may have had a transformative effect on human social organization. Copyright © 2015, American Association for the Advancement of Science.

Image statistics underlying natural texture selectivity of neurons in macaque V4

PubMed Central

Okazawa, Gouki; Tajima, Satohiro; Komatsu, Hidehiko

2015-01-01

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception. PMID:25535362

Contribution of correlated noise and selective decoding to choice probability measurements in extrastriate visual cortex

PubMed Central

Gu, Yong; Angelaki, Dora E; DeAngelis, Gregory C

2014-01-01

Trial by trial covariations between neural activity and perceptual decisions (quantified by choice Probability, CP) have been used to probe the contribution of sensory neurons to perceptual decisions. CPs are thought to be determined by both selective decoding of neural activity and by the structure of correlated noise among neurons, but the respective roles of these factors in creating CPs have been controversial. We used biologically-constrained simulations to explore this issue, taking advantage of a peculiar pattern of CPs exhibited by multisensory neurons in area MSTd that represent self-motion. Although models that relied on correlated noise or selective decoding could both account for the peculiar pattern of CPs, predictions of the selective decoding model were substantially more consistent with various features of the neural and behavioral data. While correlated noise is essential to observe CPs, our findings suggest that selective decoding of neuronal signals also plays important roles. DOI: http://dx.doi.org/10.7554/eLife.02670.001 PMID:24986734

A decision modeling for phasor measurement unit location selection in smart grid systems

NASA Astrophysics Data System (ADS)

Lee, Seung Yup

As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.

Solid pulmonary nodule risk assessment and decision analysis: comparison of four prediction models in 285 cases.

PubMed

Perandini, Simone; Soardi, Gian Alberto; Motton, Massimiliano; Rossi, Arianna; Signorini, Manuel; Montemezzi, Stefania

2016-09-01

The aim of this study was to compare classification results from four major risk prediction models in a wide population of incidentally detected solitary pulmonary nodules (SPNs) which were selected to crossmatch inclusion criteria for the selected models. A total of 285 solitary pulmonary nodules with a definitive diagnosis were evaluated by means of four major risk assessment models developed from non-screening populations, namely the Mayo, Gurney, PKUPH and BIMC models. Accuracy was evaluated by receiver operating characteristic (ROC) area under the curve (AUC) analysis. Each model's fitness to provide reliable help in decision analysis was primarily assessed by adopting a surgical threshold of 65 % and an observation threshold of 5 % as suggested by ACCP guidelines. ROC AUC values, false positives, false negatives and indeterminate nodules were respectively 0.775, 3, 8, 227 (Mayo); 0.794, 41, 6, 125 (Gurney); 0.889, 42, 0, 144 (PKUPH); 0.898, 16, 0, 118 (BIMC). Resultant data suggests that the BIMC model may be of greater help than Mayo, Gurney and PKUPH models in preoperative SPN characterization when using ACCP risk thresholds because of overall better accuracy and smaller numbers of indeterminate nodules and false positive results. • The BIMC and PKUPH models offer better characterization than older prediction models • Both the PKUPH and BIMC models completely avoided false negative results • The Mayo model suffers from a large number of indeterminate results.

A Two-Step Method to Select Major Surge-Producing Extratropical Cyclones from a 10,000-Year Stochastic Catalog

NASA Astrophysics Data System (ADS)

Keshtpoor, M.; Carnacina, I.; Yablonsky, R. M.

2016-12-01

Extratropical cyclones (ETCs) are the primary driver of storm surge events along the UK and northwest mainland Europe coastlines. In an effort to evaluate the storm surge risk in coastal communities in this region, a stochastic catalog is developed by perturbing the historical storm seeds of European ETCs to account for 10,000 years of possible ETCs. Numerical simulation of the storm surge generated by the full 10,000-year stochastic catalog, however, is computationally expensive and may take several months to complete with available computational resources. A new statistical regression model is developed to select the major surge-generating events from the stochastic ETC catalog. This regression model is based on the maximum storm surge, obtained via numerical simulations using a calibrated version of the Delft3D-FM hydrodynamic model with a relatively coarse mesh, of 1750 historical ETC events that occurred over the past 38 years in Europe. These numerically-simulated surge values were regressed to the local sea level pressure and the U and V components of the wind field at the location of 196 tide gauge stations near the UK and northwest mainland Europe coastal areas. The regression model suggests that storm surge values in the area of interest are highly correlated to the U- and V-component of wind speed, as well as the sea level pressure. Based on these correlations, the regression model was then used to select surge-generating storms from the 10,000-year stochastic catalog. Results suggest that roughly 105,000 events out of 480,000 stochastic storms are surge-generating events and need to be considered for numerical simulation using a hydrodynamic model. The selected stochastic storms were then simulated in Delft3D-FM, and the final refinement of the storm population was performed based on return period analysis of the 1750 historical event simulations at each of the 196 tide gauges in preparation for Delft3D-FM fine mesh simulations.

Similarity Theory of Withdrawn Water Temperature Experiment

PubMed Central

2015-01-01

Selective withdrawal from a thermal stratified reservoir has been widely utilized in managing reservoir water withdrawal. Besides theoretical analysis and numerical simulation, model test was also necessary in studying the temperature of withdrawn water. However, information on the similarity theory of the withdrawn water temperature model remains lacking. Considering flow features of selective withdrawal, the similarity theory of the withdrawn water temperature model was analyzed theoretically based on the modification of governing equations, the Boussinesq approximation, and some simplifications. The similarity conditions between the model and the prototype were suggested. The conversion of withdrawn water temperature between the model and the prototype was proposed. Meanwhile, the fundamental theory of temperature distribution conversion was firstly proposed, which could significantly improve the experiment efficiency when the basic temperature of the model was different from the prototype. Based on the similarity theory, an experiment was performed on the withdrawn water temperature which was verified by numerical method. PMID:26065020

Quantum vision in three dimensions

NASA Astrophysics Data System (ADS)

Roth, Yehuda

We present four models for describing a 3-D vision. Similar to the mirror scenario, our models allow 3-D vision with no need for additional accessories such as stereoscopic glasses or a hologram film. These four models are based on brain interpretation rather than pure objective encryption. We consider the observer "subjective" selection of a measuring device and the corresponding quantum collapse into one of his selected states, as a tool for interpreting reality in according to the observer concepts. This is the basic concept of our study and it is introduced in the first model. Other models suggests "soften" versions that might be much easier to implement. Our quantum interpretation approach contribute to the following fields. In technology the proposed models can be implemented into real devices, allowing 3-D vision without additional accessories. Artificial intelligence: In the desire to create a machine that exchange information by using human terminologies, our interpretation approach seems to be appropriate.

Microsatellites as targets of natural selection.

PubMed

Haasl, Ryan J; Payseur, Bret A

2013-02-01

The ability to survey polymorphism on a genomic scale has enabled genome-wide scans for the targets of natural selection. Theory that connects patterns of genetic variation to evidence of natural selection most often assumes a diallelic locus and no recurrent mutation. Although these assumptions are suitable to selection that targets single nucleotide variants, fundamentally different types of mutation generate abundant polymorphism in genomes. Moreover, recent empirical results suggest that mutationally complex, multiallelic loci including microsatellites and copy number variants are sometimes targeted by natural selection. Given their abundance, the lack of inference methods tailored to the mutational peculiarities of these types of loci represents a notable gap in our ability to interrogate genomes for signatures of natural selection. Previous theoretical investigations of mutation-selection balance at multiallelic loci include assumptions that limit their application to inference from empirical data. Focusing on microsatellites, we assess the dynamics and population-level consequences of selection targeting mutationally complex variants. We develop general models of a multiallelic fitness surface, a realistic model of microsatellite mutation, and an efficient simulation algorithm. Using these tools, we explore mutation-selection-drift equilibrium at microsatellites and investigate the mutational history and selective regime of the microsatellite that causes Friedreich's ataxia. We characterize microsatellite selective events by their duration and cost, note similarities to sweeps from standing point variation, and conclude that it is premature to label microsatellites as ubiquitous agents of efficient adaptive change. Together, our models and simulation algorithm provide a powerful framework for statistical inference, which can be used to test the neutrality of microsatellites and other multiallelic variants.

Microsatellites as Targets of Natural Selection

PubMed Central

Haasl, Ryan J.; Payseur, Bret A.

2013-01-01

The ability to survey polymorphism on a genomic scale has enabled genome-wide scans for the targets of natural selection. Theory that connects patterns of genetic variation to evidence of natural selection most often assumes a diallelic locus and no recurrent mutation. Although these assumptions are suitable to selection that targets single nucleotide variants, fundamentally different types of mutation generate abundant polymorphism in genomes. Moreover, recent empirical results suggest that mutationally complex, multiallelic loci including microsatellites and copy number variants are sometimes targeted by natural selection. Given their abundance, the lack of inference methods tailored to the mutational peculiarities of these types of loci represents a notable gap in our ability to interrogate genomes for signatures of natural selection. Previous theoretical investigations of mutation-selection balance at multiallelic loci include assumptions that limit their application to inference from empirical data. Focusing on microsatellites, we assess the dynamics and population-level consequences of selection targeting mutationally complex variants. We develop general models of a multiallelic fitness surface, a realistic model of microsatellite mutation, and an efficient simulation algorithm. Using these tools, we explore mutation-selection-drift equilibrium at microsatellites and investigate the mutational history and selective regime of the microsatellite that causes Friedreich’s ataxia. We characterize microsatellite selective events by their duration and cost, note similarities to sweeps from standing point variation, and conclude that it is premature to label microsatellites as ubiquitous agents of efficient adaptive change. Together, our models and simulation algorithm provide a powerful framework for statistical inference, which can be used to test the neutrality of microsatellites and other multiallelic variants. PMID:23104080

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

PubMed

Billiard, Sylvain; Castric, Vincent; Vekemans, Xavier

2007-03-01

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

Growth models of Rhizophora mangle L. seedlings in tropical southwestern Atlantic

NASA Astrophysics Data System (ADS)

Lima, Karen Otoni de Oliveira; Tognella, Mônica Maria Pereira; Cunha, Simone Rabelo; Andrade, Humber Agrelli de

2018-07-01

The present study selected and compared regression models that best describe the growth curves of Rhizophora mangle seedlings based on the height (cm) and time (days) variables. The Linear, Exponential, Power Law, Monomolecular, Logistic, and Gompertz models were adjusted with non-linear formulations and minimization of the sum of the squares of the residues. The Akaike Information Criterion was used to select the best model for each seedling. After this selection, the determination coefficient, which evaluates how well a model describes height variation as a time function, was inspected. Differing from the classic population ecology studies, the Monomolecular, Three-parameter Logistic, and Gompertz models presented the best performance in describing growth, suggesting they are the most adequate options for long-term studies. The different growth curves reflect the complexity of stem growth at the seedling stage for R. mangle. The analysis of the joint distribution of the parameters initial height, growth rate, and, asymptotic size allowed the study of the species ecological attributes and to observe its intraspecific variability in each model. Our results provide a basis for interpretation of the dynamics of seedlings growth during their establishment in a mature forest, as well as its regeneration processes.

Statistical model selection for better prediction and discovering science mechanisms that affect reliability

DOE PAGES

Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

2015-08-19

Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore » inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less

Introgression of a Block of Genome Under Infinitesimal Selection.

PubMed

Sachdeva, Himani; Barton, Nicholas H

2018-06-12

Adaptive introgression is common in nature and can be driven by selection acting on multiple, linked genes. We explore the effects of polygenic selection on introgression under the infinitesimal model with linkage. This model assumes that the introgressing block has an effectively infinite number of loci, each with an infinitesimal effect on the trait under selection. The block is assumed to introgress under directional selection within a native population that is genetically homogeneous. We use individual-based simulations and a branching process approximation to compute various statistics of the introgressing block, and explore how these depend on parameters such as the map length and initial trait value associated with the introgressing block, the genetic variability along the block, and the strength of selection. Our results show that the introgression dynamics of a block under infinitesimal selection are qualitatively different from the dynamics of neutral introgression. We also find that in the long run, surviving descendant blocks are likely to have intermediate lengths, and clarify how their length is shaped by the interplay between linkage and infinitesimal selection. Our results suggest that it may be difficult to distinguish the long-term introgression of a block of genome with a single strongly selected locus from the introgression of a block with multiple, tightly linked and weakly selected loci. Copyright © 2018, Genetics.

Full Length Human Mutant Huntingtin with a Stable Polyglutamine Repeat Can Elicit Progressive and Selective Neuropathogenesis in BACHD Mice

PubMed Central

Gray, Michelle; Shirasaki, Dyna I.; Cepeda, Carlos; Andre, Veronique M.; Wilburn, Brian; Lu, Xiao-Hong; Tao, Jifang; Yamazaki, Irene; Li, Shi-Hua; Sun, Yi E.; Li, Xiao-Jiang; Levine, Michael S.; William Yang, X

2008-01-01

To elucidate the pathogenic mechanisms in Huntington’s disease (HD) elicited by expression of full-length human mutant huntingtin (fl-mhtt), a Bacterial Artificial Chromosome (BAC)-mediated transgenic mouse model (BACHD) was developed expressing fl-mhtt with 97 glutamine repeats under the control of endogenous htt regulatory machinery on the BAC. BACHD mice exhibit progressive motor deficits, neuronal synaptic dysfunction, and late-onset selective neuropathology, which includes significant cortical and striatal atrophy and striatal dark neuron degeneration. Power analyses reveal the robustness of the behavioral and neuropathological phenotypes, suggesting BACHD as a suitable fl-mhtt mouse model for preclinical studies. Further analyses of BACHD mice provide additional insights into how mhtt may elicit neuropathogenesis. First, unlike prior fl-mhtt mouse models, BACHD mice reveal that the slowly progressive and selective pathogenic process in HD mouse brains can occur without early and diffuse nuclear accumulation of aggregated mhtt (i.e. as detected by immunostaining with the EM48 antibody). Instead, a relatively steady-state level of predominantly full-length mhtt and a small amount of mhtt N-terminal fragments are sufficient to elicit the disease process. Second, the polyglutamine repeat within fl-mhtt in BACHD mice is encoded by a mixed CAA-CAG repeat, which is stable in both the germline and somatic tissues including the cortex and striatum at the onset of neuropathology. Therefore, our results suggest that somatic repeat instability does not play a necessary role in selective neuropathogenesis in BACHD mice. In summary, the BACHD model constitutes a novel and robust in vivo paradigm for the investigation of HD pathogenesis and treatment. PMID:18550760

Selective gas capture via kinetic trapping

DOE PAGES

Kundu, Joyjit; Pascal, Tod; Prendergast, David; ...

2016-07-13

Conventional approaches to the capture of CO 2 by metal-organic frameworks focus on equilibrium conditions, and frameworks that contain little CO 2 in equilibrium are often rejected as carbon-capture materials. Here we use a statistical mechanical model, parameterized by quantum mechanical data, to suggest that metal-organic frameworks can be used to separate CO 2 from a typical flue gas mixture when used under nonequilibrium conditions. The origin of this selectivity is an emergent gas-separation mechanism that results from the acquisition by different gas types of different mobilities within a crowded framework. The resulting distribution of gas types within the frameworkmore » is in general spatially and dynamically heterogeneous. Our results suggest that relaxing the requirement of equilibrium can substantially increase the parameter space of conditions and materials for which selective gas capture can be effected.« less

Detecting site-specific physicochemical selective pressures: applications to the Class I HLA of the human major histocompatibility complex and the SRK of the plant sporophytic self-incompatibility system.

PubMed

Sainudiin, Raazesh; Wong, Wendy Shuk Wan; Yogeeswaran, Krithika; Nasrallah, June B; Yang, Ziheng; Nielsen, Rasmus

2005-03-01

Models of codon substitution are developed that incorporate physicochemical properties of amino acids. When amino acid sites are inferred to be under positive selection, these models suggest the nature and extent of the physicochemical properties under selection. This is accomplished by first partitioning the codons on the basis of some property of the encoded amino acids. This partition is used to parametrize the rates of property-conserving and property-altering base substitutions at the codon level by means of finite mixtures of Markov models that also account for codon and transition:transversion biases. Here, we apply this method to two positively selected receptors involved in ligand-recognition: the class I alleles of the human major histocompatibility complex (MHC) of known structure and the S-locus receptor kinase (SRK) of the sporophytic self-incompatibility system (SSI) in cruciferous plants (Brassicaceae), whose structure is unknown. Through likelihood ratio tests we demonstrate that at some sites, the positively selected MHC and SRK proteins are under physicochemical selective pressures to alter polarity, volume, polarity and/or volume, and charge to various extents. An empirical Bayes approach is used to identify sites that may be important for ligand recognition in these proteins.

Applications of step-selection functions in ecology and conservation.

PubMed

Thurfjell, Henrik; Ciuti, Simone; Boyce, Mark S

2014-01-01

Recent progress in positioning technology facilitates the collection of massive amounts of sequential spatial data on animals. This has led to new opportunities and challenges when investigating animal movement behaviour and habitat selection. Tools like Step Selection Functions (SSFs) are relatively new powerful models for studying resource selection by animals moving through the landscape. SSFs compare environmental attributes of observed steps (the linear segment between two consecutive observations of position) with alternative random steps taken from the same starting point. SSFs have been used to study habitat selection, human-wildlife interactions, movement corridors, and dispersal behaviours in animals. SSFs also have the potential to depict resource selection at multiple spatial and temporal scales. There are several aspects of SSFs where consensus has not yet been reached such as how to analyse the data, when to consider habitat covariates along linear paths between observations rather than at their endpoints, how many random steps should be considered to measure availability, and how to account for individual variation. In this review we aim to address all these issues, as well as to highlight weak features of this modelling approach that should be developed by further research. Finally, we suggest that SSFs could be integrated with state-space models to classify behavioural states when estimating SSFs.

Variance-based selection may explain general mating patterns in social insects.

PubMed

Rueppell, Olav; Johnson, Nels; Rychtár, Jan

2008-06-23

Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.

Virulence evolution in response to anti-infection resistance: toxic food plants can select for virulent parasites of monarch butterflies.

PubMed

de Roode, J C; de Castillejo, C Lopez Fernandez; Faits, T; Alizon, S

2011-04-01

Host resistance to parasites can come in two main forms: hosts may either reduce the probability of parasite infection (anti-infection resistance) or reduce parasite growth after infection has occurred (anti-growth resistance). Both resistance mechanisms are often imperfect, meaning that they do not fully prevent or clear infections. Theoretical work has suggested that imperfect anti-growth resistance can select for higher parasite virulence by favouring faster-growing and more virulent parasites that overcome this resistance. In contrast, imperfect anti-infection resistance is thought not to select for increased parasite virulence, because it is assumed that it reduces the number of hosts that become infected, but not the fitness of parasites in successfully infected hosts. Here, we develop a theoretical model to show that anti-infection resistance can in fact select for higher virulence when such resistance reduces the effective parasite dose that enters a host. Our model is based on a monarch butterfly-parasite system in which larval food plants confer resistance to the monarch host. We carried out an experiment and showed that this environmental resistance is most likely a form of anti-infection resistance, through which toxic food plants reduce the effective dose of parasites that initiates an infection. We used these results to build a mathematical model to investigate the evolutionary consequences of food plant-induced resistance. Our model shows that when the effective infectious dose is reduced, parasites can compensate by evolving a higher per-parasite growth rate, and consequently a higher intrinsic virulence. Our results are relevant to many insect host-parasite systems, in which larval food plants often confer imperfect anti-infection resistance. Our results also suggest that - for parasites where the infectious dose affects the within-host dynamics - vaccines that reduce the effective infectious dose can select for increased parasite virulence. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task

PubMed Central

Miconi, Thomas; Groomes, Laura; Kreiman, Gabriel

2016-01-01

When searching for an object in a scene, how does the brain decide where to look next? Visual search theories suggest the existence of a global “priority map” that integrates bottom-up visual information with top-down, target-specific signals. We propose a mechanistic model of visual search that is consistent with recent neurophysiological evidence, can localize targets in cluttered images, and predicts single-trial behavior in a search task. This model posits that a high-level retinotopic area selective for shape features receives global, target-specific modulation and implements local normalization through divisive inhibition. The normalization step is critical to prevent highly salient bottom-up features from monopolizing attention. The resulting activity pattern constitues a priority map that tracks the correlation between local input and target features. The maximum of this priority map is selected as the locus of attention. The visual input is then spatially enhanced around the selected location, allowing object-selective visual areas to determine whether the target is present at this location. This model can localize objects both in array images and when objects are pasted in natural scenes. The model can also predict single-trial human fixations, including those in error and target-absent trials, in a search task involving complex objects. PMID:26092221

Identification of landscape features influencing gene flow: How useful are habitat selection models?

USGS Publications Warehouse

Roffler, Gretchen H.; Schwartz, Michael K.; Pilgrim, Kristy L.; Talbot, Sandra L.; Sage, Kevin; Adams, Layne G.; Luikart, Gordon

2016-01-01

Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider explicit assumptions and spatial scales of measurement. We calculated pairwise genetic distance among 301 Dall's sheep (Ovis dalli dalli) in southcentral Alaska using an intensive noninvasive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important during summer (rugged terrain, mid-range elevation) were not influential to effective dispersal. This work underscores that consideration of both habitat selection and landscape genetics models may be useful in developing management strategies to both meet the immediate survival of a species and allow for long-term genetic connectivity.

Measuring cognition in teams: a cross-domain review.

PubMed

Wildman, Jessica L; Salas, Eduardo; Scott, Charles P R

2014-08-01

The purpose of this article is twofold: to provide a critical cross-domain evaluation of team cognition measurement options and to provide novice researchers with practical guidance when selecting a measurement method. A vast selection of measurement approaches exist for measuring team cognition constructs including team mental models, transactive memory systems, team situation awareness, strategic consensus, and cognitive processes. Empirical studies and theoretical articles were reviewed to identify all of the existing approaches for measuring team cognition. These approaches were evaluated based on theoretical perspective assumed, constructs studied, resources required, level of obtrusiveness, internal consistency reliability, and predictive validity. The evaluations suggest that all existing methods are viable options from the point of view of reliability and validity, and that there are potential opportunities for cross-domain use. For example, methods traditionally used only to measure mental models may be useful for examining transactive memory and situation awareness. The selection of team cognition measures requires researchers to answer several key questions regarding the theoretical nature of team cognition and the practical feasibility of each method. We provide novice researchers with guidance regarding how to begin the search for a team cognition measure and suggest several new ideas regarding future measurement research. We provide (1) a broad overview and evaluation of existing team cognition measurement methods, (2) suggestions for new uses of those methods across research domains, and (3) critical guidance for novice researchers looking to measure team cognition.

Discovery of Selective, Substrate-Competitive, and Passive Membrane Permeable Glycogen Synthase Kinase-3β Inhibitors: Synthesis, Biological Evaluation, and Molecular Modeling of New C-Glycosylflavones.

PubMed

Liang, Zhibin; Li, Qing X

2018-05-16

Glycogen synthase kinase-3β (GSK-3β) is a key enzyme responsible for tau hyperphosphorylation and is a viable therapeutic target of Alzheimer's disease (AD). We developed a new class of GSK-3β inhibitors based on the 6- C-glycosylflavone isoorientin (1). The new inhibitors are passive membrane permeable and constitutively attenuate GSK-3β mediated tau hyperphosphorylation and amyloid neurotoxicity in an AD cellular model. Enzymatic assays and kinetic studies demonstrated that compound 30 is a GSK-3β substrate-competitive inhibitor with distinct kinase selectivity, isoform-selectivity and over 310-fold increased potency as compared to 1. Structure-activity relationship analyses and in silico modeling suggest the mechanism of actions by which the hydrophobic, π-cation, and orthogonal multipolar interactions of 30 with the substrate site are critical for the GSK-3β inhibition and selectivity. The results provide new insights into GSK-3β drug discovery. The new inhibitors are valuable chemical probes and drug leads with therapeutic potential to tackle AD and other GSK-3β relevant diseases.

Two different mechanisms support selective attention at different phases of training.

PubMed

Itthipuripat, Sirawaj; Cha, Kexin; Byers, Anna; Serences, John T

2017-06-01

Selective attention supports the prioritized processing of relevant sensory information to facilitate goal-directed behavior. Studies in human subjects demonstrate that attentional gain of cortical responses can sufficiently account for attention-related improvements in behavior. On the other hand, studies using highly trained nonhuman primates suggest that reductions in neural noise can better explain attentional facilitation of behavior. Given the importance of selective information processing in nearly all domains of cognition, we sought to reconcile these competing accounts by testing the hypothesis that extensive behavioral training alters the neural mechanisms that support selective attention. We tested this hypothesis using electroencephalography (EEG) to measure stimulus-evoked visual responses from human subjects while they performed a selective spatial attention task over the course of ~1 month. Early in training, spatial attention led to an increase in the gain of stimulus-evoked visual responses. Gain was apparent within ~100 ms of stimulus onset, and a quantitative model based on signal detection theory (SDT) successfully linked the magnitude of this gain modulation to attention-related improvements in behavior. However, after extensive training, this early attentional gain was eliminated even though there were still substantial attention-related improvements in behavior. Accordingly, the SDT-based model required noise reduction to account for the link between the stimulus-evoked visual responses and attentional modulations of behavior. These findings suggest that training can lead to fundamental changes in the way attention alters the early cortical responses that support selective information processing. Moreover, these data facilitate the translation of results across different species and across experimental procedures that employ different behavioral training regimes.

Two different mechanisms support selective attention at different phases of training

PubMed Central

Cha, Kexin; Byers, Anna; Serences, John T.

2017-01-01

Selective attention supports the prioritized processing of relevant sensory information to facilitate goal-directed behavior. Studies in human subjects demonstrate that attentional gain of cortical responses can sufficiently account for attention-related improvements in behavior. On the other hand, studies using highly trained nonhuman primates suggest that reductions in neural noise can better explain attentional facilitation of behavior. Given the importance of selective information processing in nearly all domains of cognition, we sought to reconcile these competing accounts by testing the hypothesis that extensive behavioral training alters the neural mechanisms that support selective attention. We tested this hypothesis using electroencephalography (EEG) to measure stimulus-evoked visual responses from human subjects while they performed a selective spatial attention task over the course of ~1 month. Early in training, spatial attention led to an increase in the gain of stimulus-evoked visual responses. Gain was apparent within ~100 ms of stimulus onset, and a quantitative model based on signal detection theory (SDT) successfully linked the magnitude of this gain modulation to attention-related improvements in behavior. However, after extensive training, this early attentional gain was eliminated even though there were still substantial attention-related improvements in behavior. Accordingly, the SDT-based model required noise reduction to account for the link between the stimulus-evoked visual responses and attentional modulations of behavior. These findings suggest that training can lead to fundamental changes in the way attention alters the early cortical responses that support selective information processing. Moreover, these data facilitate the translation of results across different species and across experimental procedures that employ different behavioral training regimes. PMID:28654635

Selective sweeps of mitochondrial DNA can drive the evolution of uniparental inheritance.

PubMed

Christie, Joshua R; Beekman, Madeleine

2017-08-01

Although the uniparental (or maternal) inheritance of mitochondrial DNA (mtDNA) is widespread, the reasons for its evolution remain unclear. Two main hypotheses have been proposed: selection against individuals containing different mtDNAs (heteroplasmy) and selection against "selfish" mtDNA mutations. Recently, uniparental inheritance was shown to promote adaptive evolution in mtDNA, potentially providing a third hypothesis for its evolution. Here, we explore this hypothesis theoretically and ask if the accumulation of beneficial mutations provides a sufficient fitness advantage for uniparental inheritance to invade a population in which mtDNA is inherited biparentally. In a deterministic model, uniparental inheritance increases in frequency but cannot replace biparental inheritance if only a single beneficial mtDNA mutation sweeps through the population. When we allow successive selective sweeps of mtDNA, however, uniparental inheritance can replace biparental inheritance. Using a stochastic model, we show that a combination of selection and drift facilitates the fixation of uniparental inheritance (compared to a neutral trait) when there is only a single selective mtDNA sweep. When we consider multiple mtDNA sweeps in a stochastic model, uniparental inheritance becomes even more likely to replace biparental inheritance. Our findings thus suggest that selective sweeps of beneficial mtDNA haplotypes can drive the evolution of uniparental inheritance. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Pervasive adaptive protein evolution apparent in diversity patterns around amino acid substitutions in Drosophila simulans.

PubMed

Sattath, Shmuel; Elyashiv, Eyal; Kolodny, Oren; Rinott, Yosef; Sella, Guy

2011-02-10

In Drosophila, multiple lines of evidence converge in suggesting that beneficial substitutions to the genome may be common. All suffer from confounding factors, however, such that the interpretation of the evidence-in particular, conclusions about the rate and strength of beneficial substitutions-remains tentative. Here, we use genome-wide polymorphism data in D. simulans and sequenced genomes of its close relatives to construct a readily interpretable characterization of the effects of positive selection: the shape of average neutral diversity around amino acid substitutions. As expected under recurrent selective sweeps, we find a trough in diversity levels around amino acid but not around synonymous substitutions, a distinctive pattern that is not expected under alternative models. This characterization is richer than previous approaches, which relied on limited summaries of the data (e.g., the slope of a scatter plot), and relates to underlying selection parameters in a straightforward way, allowing us to make more reliable inferences about the prevalence and strength of adaptation. Specifically, we develop a coalescent-based model for the shape of the entire curve and use it to infer adaptive parameters by maximum likelihood. Our inference suggests that ∼13% of amino acid substitutions cause selective sweeps. Interestingly, it reveals two classes of beneficial fixations: a minority (approximately 3%) that appears to have had large selective effects and accounts for most of the reduction in diversity, and the remaining 10%, which seem to have had very weak selective effects. These estimates therefore help to reconcile the apparent conflict among previously published estimates of the strength of selection. More generally, our findings provide unequivocal evidence for strongly beneficial substitutions in Drosophila and illustrate how the rapidly accumulating genome-wide data can be leveraged to address enduring questions about the genetic basis of adaptation.

A neurocomputational model of figure-ground discrimination and target tracking.

PubMed

Sun, H; Liu, L; Guo, A

1999-01-01

A neurocomputational model is presented for figureground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.

Dream interpretation, affect, and the theory of neuronal group selection: Freud, Winnicott, Bion, and Modell.

PubMed

Shields, Walker

2006-12-01

The author uses a dream specimen as interpreted during psychoanalysis to illustrate Modell's hypothesis that Edelman's theory of neuronal group selection (TNGS) may provide a valuable neurobiological model for Freud's dynamic unconscious, imaginative processes in the mind, the retranscription of memory in psychoanalysis, and intersubjective processes in the analytic relationship. He draws parallels between the interpretation of the dream material with keen attention to affect-laden meanings in the evolving analytic relationship in the domain of psychoanalysis and the principles of Edelman's TNGS in the domain of neurobiology. The author notes how this correlation may underscore the importance of dream interpretation in psychoanalysis. He also suggests areas for further investigation in both realms based on study of their interplay.

A Symmetric Two-Locus Fertility Model

PubMed Central

Feldman, Marcus W.; Liberman, Uri

1985-01-01

A model in which selection is mediated by differential fertilities among the genotypes at two diallelic loci is proposed. Fertility depends only on the number of heterozygous loci participating in the mating. Classes analogous to symmetric equilibria in symmetric viability models are determined explicitly and shown to exhibit stability behavior very different from the viability results. Linkage equilibrium is shown to occur in a relatively asymmetric fashion and to overlap in stability with linkage disequilibrium. In many cases single-locus or two-locus polymorphism is shown to be stable simultaneously with chromosome fixation even under very tight linkage. It is suggested that historical effects may be of great significance in the evolution of systems in which fertility is the primary agent of natural selection. PMID:3967817

Altruistic self-removal of health-compromised honey bee workers from their hive.

PubMed

Rueppell, O; Hayworth, M K; Ross, N P

2010-07-01

Social insect colonies represent distinct units of selection. Most individuals evolve by kin selection and forgo individual reproduction. Instead, they display altruistic food sharing, nest maintenance and self-sacrificial colony defence. Recently, altruistic self-removal of diseased worker ants from their colony was described as another important kin-selected behaviour. Here, we report corroborating experimental evidence from honey bee foragers and theoretical analyses. We challenged honey bee foragers with prolonged CO(2) narcosis or by feeding with the cytostatic drug hydroxyurea. Both treatments resulted in increased mortality but also caused the surviving foragers to abandon their social function and remove themselves from their colony, resulting in altruistic suicide. A simple model suggests that altruistic self-removal by sick social insect workers to prevent disease transmission is expected under most biologically plausible conditions. The combined theoretical and empirical support for altruistic self-removal suggests that it may be another important kin-selected behaviour and a potentially widespread mechanism of social immunity.

Crew Interface Analysis: Selected Articles on Space Human Factors Research, 1987 - 1991

DTIC Science & Technology

1993-07-01

recognitions to that distractor ) suggest that the perceptual type of the graph has a strong representation in memory . We found that both training with... processing strategy. If my goal were to compare the value of variables or (possibly) to compare a trend, I would select a perceptual strategy. If...be needed to determine specific processing models for different questions using the perceptual strategy. In addition, predictions about the memory

Divergent positive selection in rhodopsin from lake and riverine cichlid fishes.

PubMed

Schott, Ryan K; Refvik, Shannon P; Hauser, Frances E; López-Fernández, Hernán; Chang, Belinda S W

2014-05-01

Studies of cichlid evolution have highlighted the importance of visual pigment genes in the spectacular radiation of the African rift lake cichlids. Recent work, however, has also provided strong evidence for adaptive diversification of riverine cichlids in the Neotropics, which inhabit environments of markedly different spectral properties from the African rift lakes. These ecological and/or biogeographic differences may have imposed divergent selective pressures on the evolution of the cichlid visual system. To test these hypotheses, we investigated the molecular evolution of the dim-light visual pigment, rhodopsin. We sequenced rhodopsin from Neotropical and African riverine cichlids and combined these data with published sequences from African cichlids. We found significant evidence for positive selection using random sites codon models in all cichlid groups, with the highest levels in African lake cichlids. Tests using branch-site and clade models that partitioned the data along ecological (lake, river) and/or biogeographic (African, Neotropical) boundaries found significant evidence of divergent selective pressures among cichlid groups. However, statistical comparisons among these models suggest that ecological, rather than biogeographic, factors may be responsible for divergent selective pressures that have shaped the evolution of the visual system in cichlids. We found that branch-site models did not perform as well as clade models for our data set, in which there was evidence for positive selection in the background. One of our most intriguing results is that the amino acid sites found to be under positive selection in Neotropical and African lake cichlids were largely nonoverlapping, despite falling into the same three functional categories: spectral tuning, retinal uptake/release, and rhodopsin dimerization. Taken together, these results would imply divergent selection across cichlid clades, but targeting similar functions. This study highlights the importance of molecular investigations of ecologically important groups and the flexibility of clade models in explicitly testing ecological hypotheses.

Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas

PubMed Central

Lescroart, Mark D.; Stansbury, Dustin E.; Gallant, Jack L.

2015-01-01

Perception of natural visual scenes activates several functional areas in the human brain, including the Parahippocampal Place Area (PPA), Retrosplenial Complex (RSC), and the Occipital Place Area (OPA). It is currently unclear what specific scene-related features are represented in these areas. Previous studies have suggested that PPA, RSC, and/or OPA might represent at least three qualitatively different classes of features: (1) 2D features related to Fourier power; (2) 3D spatial features such as the distance to objects in a scene; or (3) abstract features such as the categories of objects in a scene. To determine which of these hypotheses best describes the visual representation in scene-selective areas, we applied voxel-wise modeling (VM) to BOLD fMRI responses elicited by a set of 1386 images of natural scenes. VM provides an efficient method for testing competing hypotheses by comparing predictions of brain activity based on encoding models that instantiate each hypothesis. Here we evaluated three different encoding models that instantiate each of the three hypotheses listed above. We used linear regression to fit each encoding model to the fMRI data recorded from each voxel, and we evaluated each fit model by estimating the amount of variance it predicted in a withheld portion of the data set. We found that voxel-wise models based on Fourier power or the subjective distance to objects in each scene predicted much of the variance predicted by a model based on object categories. Furthermore, the response variance explained by these three models is largely shared, and the individual models explain little unique variance in responses. Based on an evaluation of previous studies and the data we present here, we conclude that there is currently no good basis to favor any one of the three alternative hypotheses about visual representation in scene-selective areas. We offer suggestions for further studies that may help resolve this issue. PMID:26594164

Convergence in parameters and predictions using computational experimental design.

PubMed

Hagen, David R; White, Jacob K; Tidor, Bruce

2013-08-06

Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

PubMed

Mina, Marco; Raynaud, Franck; Tavernari, Daniele; Battistello, Elena; Sungalee, Stephanie; Saghafinia, Sadegh; Laessle, Titouan; Sanchez-Vega, Francisco; Schultz, Nikolaus; Oricchio, Elisa; Ciriello, Giovanni

2017-08-14

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response. Copyright © 2017 Elsevier Inc. All rights reserved.

Intense natural selection preceded the invasion of new adaptive zones during the radiation of New World leaf-nosed bats.

PubMed

Rossoni, Daniela M; Assis, Ana Paula A; Giannini, Norberto P; Marroig, Gabriel

2017-09-11

The family Phyllostomidae, which evolved in the New World during the last 30 million years, represents one of the largest and most morphologically diverse mammal families. Due to its uniquely diverse functional morphology, the phyllostomid skull is presumed to have evolved under strong directional selection; however, quantitative estimation of the strength of selection in this extraordinary lineage has not been reported. Here, we used comparative quantitative genetics approaches to elucidate the processes that drove cranial evolution in phyllostomids. We also quantified the strength of selection and explored its association with dietary transitions and specialization along the phyllostomid phylogeny. Our results suggest that natural selection was the evolutionary process responsible for cranial diversification in phyllostomid bats. Remarkably, the strongest selection in the phyllostomid phylogeny was associated with dietary specialization and the origination of novel feeding habits, suggesting that the adaptive diversification of phyllostomid bats was triggered by ecological opportunities. These findings are consistent with Simpson's quantum evolutionary model of transitions between adaptive zones. The multivariate analyses used in this study provides a powerful tool for understanding the role of evolutionary processes in shaping phenotypic diversity in any group on both micro- and macroevolutionary scales.

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

Model Selection with Strong-lensing Systems

NASA Astrophysics Data System (ADS)

Leaf, Kyle; Melia, Fulvio

2018-05-01

In this paper, we use an unprecedentedly large sample (158) of confirmed strong lens systems for model selection, comparing five well studied Friedmann-Robertson-Walker cosmologies: ΛCDM, wCDM (the standard model with a variable dark-energy equation of state), the Rh = ct universe, the (empty) Milne cosmology, and the classical Einstein-de Sitter (matter dominated) universe. We first use these sources to optimize the parameters in the standard model and show that they are consistent with Planck, though the quality of the best fit is not satisfactory. We demonstrate that this is likely due to under-reported errors, or to errors yet to be included in this kind of analysis. We suggest that the missing dispersion may be due to scatter about a pure single isothermal sphere (SIS) model that is often assumed for the mass distribution in these lenses. We then use the Bayes information criterion, with the inclusion of a suggested SIS dispersion, to calculate the relative likelihoods and ranking of these models, showing that Milne and Einstein-de Sitter are completely ruled out, while Rh = ct is preferred over ΛCDM/wCDM with a relative probability of ˜73% versus ˜24%. The recently reported sample of new strong lens candidates by the Dark Energy Survey, if confirmed, may be able to demonstrate which of these two models is favoured over the other at a level exceeding 3σ.

A coarse-grained biophysical model of sequence evolution and the population size dependence of the speciation rate

PubMed Central

Khatri, Bhavin S.; Goldstein, Richard A.

2015-01-01

Speciation is fundamental to understanding the huge diversity of life on Earth. Although still controversial, empirical evidence suggests that the rate of speciation is larger for smaller populations. Here, we explore a biophysical model of speciation by developing a simple coarse-grained theory of transcription factor-DNA binding and how their co-evolution in two geographically isolated lineages leads to incompatibilities. To develop a tractable analytical theory, we derive a Smoluchowski equation for the dynamics of binding energy evolution that accounts for the fact that natural selection acts on phenotypes, but variation arises from mutations in sequences; the Smoluchowski equation includes selection due to both gradients in fitness and gradients in sequence entropy, which is the logarithm of the number of sequences that correspond to a particular binding energy. This simple consideration predicts that smaller populations develop incompatibilities more quickly in the weak mutation regime; this trend arises as sequence entropy poises smaller populations closer to incompatible regions of phenotype space. These results suggest a generic coarse-grained approach to evolutionary stochastic dynamics, allowing realistic modelling at the phenotypic level. PMID:25936759

Ground penetrating radar: a case study for estimating root bulking rate in cassava (Manihot esculenta Crantz).

PubMed

Delgado, Alfredo; Hays, Dirk B; Bruton, Richard K; Ceballos, Hernán; Novo, Alexandre; Boi, Enrico; Selvaraj, Michael Gomez

2017-01-01

Understanding root traits is a necessary research front for selection of favorable genotypes or cultivation practices. Root and tuber crops having most of their economic potential stored below ground are favorable candidates for such studies. The ability to image and quantify subsurface root structure would allow breeders to classify root traits for rapid selection and allow agronomist the ability to derive effective cultivation practices. In spite of the huge role of Cassava ( Manihot esculenta Crantz), for food security and industrial uses, little progress has been made in understanding the onset and rate of the root-bulking process and the factors that influence it. The objective of this research was to determine the capability of ground penetrating radar (GPR) to predict root-bulking rates through the detection of total root biomass during its growth cycle. Our research provides the first application of GPR for detecting below ground biomass in cassava. Through an empirical study, linear regressions were derived to model cassava bulking rates. The linear equations derived suggest that GPR is a suitable measure of root biomass ( r  = .79). The regression analysis developed accounts for 63% of the variability in cassava biomass below ground. When modeling is performed at the variety level, it is evident that the variety models for SM 1219-9 and TMS 60444 outperform the HMC-1 variety model (r 2  = .77, .63 and .51 respectively). Using current modeling methods, it is possible to predict below ground biomass and estimate root bulking rates for selection of early root bulking in cassava. Results of this approach suggested that the general model was over predicting at early growth stages but became more precise in later root development.

Spectral ageing in the era of big data: integrated versus resolved models

NASA Astrophysics Data System (ADS)

Harwood, Jeremy J.

2017-04-01

Continuous injection models of spectral ageing have long been used to determine the age of radio galaxies from their integrated spectrum; however, many questions about their reliability remain unanswered. With various large area surveys imminent (e.g. LOw Frequency ARray, MeerKAT, Murchison Widefield Array) and planning for the next generation of radio interferometers are well underway (e.g. next generation VLA, Square Kilometre Array), investigations of radio galaxy physics are set to shift away from studies of individual sources to the population as a whole. Determining if and how integrated models of spectral ageing can be applied in the era of big data is therefore crucial. In this paper, I compare classical integrated models of spectral ageing to recent well-resolved studies that use modern analysis techniques on small spatial scales to determine their robustness and validity as a source selection method. I find that integrated models are unable to recover key parameters and, even when known a priori, provide a poor, frequency-dependent description of a source's spectrum. I show a disparity of up to a factor of 6 in age between the integrated and resolved methods but suggest, even with these inconsistencies, such models still provide a potential method of candidate selection in the search for remnant radio galaxies and in providing a cleaner selection of high redshift radio galaxies in z - α selected samples.

CE Needs in Geriatrics and Gerontology for Selected Health Professionals.

ERIC Educational Resources Information Center

Robinson, Betsy C.

1981-01-01

Describes a needs assessment model that offers practical suggestions to program planners in a multidisciplinary area of inquiry that is relatively new to continuing education in health sciences. (Available from University of California Press, Berkeley, CA 94720.) (Author/CT)

Wise Purchasing.

ERIC Educational Resources Information Center

Bridgman, Anne

1990-01-01

Recent events in Florida, California, and other states suggest that school equipment purchasing is fraught with scandal and risk. This article recommends putting district policies in writing, carefully selecting bidders, timing bids to avoid peak periods, and resisting personalized incentives. Sidebars detail model purchasing guidelines and…

Model-based predictions for dopamine.

PubMed

Langdon, Angela J; Sharpe, Melissa J; Schoenbaum, Geoffrey; Niv, Yael

2018-04-01

Phasic dopamine responses are thought to encode a prediction-error signal consistent with model-free reinforcement learning theories. However, a number of recent findings highlight the influence of model-based computations on dopamine responses, and suggest that dopamine prediction errors reflect more dimensions of an expected outcome than scalar reward value. Here, we review a selection of these recent results and discuss the implications and complications of model-based predictions for computational theories of dopamine and learning. Copyright © 2017. Published by Elsevier Ltd.

Models of microbiome evolution incorporating host and microbial selection.

PubMed

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 parental contribution, when host-mediated selection acts on microbes concomitantly. We present a computational framework that integrates different selective processes acting on the evolution of microbiomes. Our framework demonstrates that selection acting on microbes can have a strong effect on microbial diversities and fitnesses, whereas selection on hosts can have weaker outcomes.

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach

USGS Publications Warehouse

Row, Jeff R; Oyler-McCance, Sara J.; Fike, Jennifer; O'Donnell, Michael; Doherty, Kevin E.; Aldridge, Cameron L.; Bowen, Zachary H.; Fedy, Brad C.

2015-01-01

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.

Systematic Identification and Evolutionary Analysis of Catalytically Versatile Cytochrome P450 Monooxygenase Families Enriched in Model Basidiomycete Fungi

PubMed Central

Syed, Khajamohiddin; Shale, Karabo; Pagadala, Nataraj Sekhar; Tuszynski, Jack

2014-01-01

Genome sequencing of basidiomycetes, a group of fungi capable of degrading/mineralizing plant material, revealed the presence of numerous cytochrome P450 monooxygenases (P450s) in their genomes, with some exceptions. Considering the large repertoire of P450s found in fungi, it is difficult to identify P450s that play an important role in fungal metabolism and the adaptation of fungi to diverse ecological niches. In this study, we followed Sir Charles Darwin’s theory of natural selection to identify such P450s in model basidiomycete fungi showing a preference for different types of plant components degradation. Any P450 family comprising a large number of member P450s compared to other P450 families indicates its natural selection over other P450 families by its important role in fungal physiology. Genome-wide comparative P450 analysis in the basidiomycete species, Phanerochaete chrysosporium, Phanerochaete carnosa, Agaricus bisporus, Postia placenta, Ganoderma sp. and Serpula lacrymans, revealed enrichment of 11 P450 families (out of 68 P450 families), CYP63, CYP512, CYP5035, CYP5037, CYP5136, CYP5141, CYP5144, CYP5146, CYP5150, CYP5348 and CYP5359. Phylogenetic analysis of the P450 family showed species-specific alignment of P450s across the P450 families with the exception of P450s of Phanerochaete chrysosporium and Phanerochaete carnosa, suggesting paralogous evolution of P450s in model basidiomycetes. P450 gene-structure analysis revealed high conservation in the size of exons and the location of introns. P450s with the same gene structure were found tandemly arranged in the genomes of selected fungi. This clearly suggests that extensive gene duplications, particularly tandem gene duplications, led to the enrichment of selective P450 families in basidiomycetes. Functional analysis and gene expression profiling data suggest that members of the P450 families are catalytically versatile and possibly involved in fungal colonization of plant material. To our knowledge, this is the first report on the identification and comparative-evolutionary analysis of P450 families enriched in model basidiomycetes. PMID:24466198

Use of a least absolute shrinkage and selection operator (LASSO) model to selected ion flow tube mass spectrometry (SIFT-MS) analysis of exhaled breath to predict the efficacy of dialysis: a pilot study.

PubMed

Wang, Maggie Haitian; Chong, Ka Chun; Storer, Malina; Pickering, John W; Endre, Zoltan H; Lau, Steven Yf; Kwok, Chloe; Lai, Maria; Chung, Hau Yin; Ying Zee, Benny Chung

2016-09-28

Selected ion flow tube-mass spectrometry (SIFT-MS) provides rapid, non-invasive measurements of a full-mass scan of volatile compounds in exhaled breath. Although various studies have suggested that breath metabolites may be indicators of human disease status, many of these studies have included few breath samples and large numbers of compounds, limiting their power to detect significant metabolites. This study employed a least absolute shrinkage and selective operator (LASSO) approach to SIFT-MS data of breath samples to preliminarily evaluate the ability of exhaled breath findings to monitor the efficacy of dialysis in hemodialysis patients. A process of model building and validation showed that blood creatinine and urea concentrations could be accurately predicted by LASSO-selected masses. Using various precursors, the LASSO models were able to predict creatinine and urea concentrations with high adjusted R-square (>80%) values. The correlation between actual concentrations and concentrations predicted by the LASSO model (using precursor H 3 O + ) was high (Pearson correlation coefficient  =  0.96). Moreover, use of full mass scan data provided a better prediction than compounds from selected ion mode. These findings warrant further investigations in larger patient cohorts. By employing a more powerful statistical approach to predict disease outcomes, breath analysis using SIFT-MS technology could be applicable in future to daily medical diagnoses.

Individual differences in the Simon effect are underpinned by differences in the competitive dynamics in the basal ganglia: An experimental verification and a computational model.

PubMed

Stocco, Andrea; Murray, Nicole L; Yamasaki, Brianna L; Renno, Taylor J; Nguyen, Jimmy; Prat, Chantel S

2017-07-01

Cognitive control is thought to be made possible by the activity of the prefrontal cortex, which selectively uses task-specific representations to bias the selection of task-appropriate responses over more automated, but inappropriate, ones. Recent models have suggested, however, that prefrontal representations are in turn controlled by the basal ganglia. In particular, neurophysiological considerations suggest that the basal ganglia's indirect pathway plays a pivotal role in preventing irrelevant information from being incorporated into a task, thus reducing response interference due to the processing of inappropriate stimuli dimensions. Here, we test this hypothesis by showing that individual differences in a non-verbal cognitive control task (the Simon task) are correlated with performance on a decision-making task (the Probabilistic Stimulus Selection task) that tracks the contribution of the indirect pathway. Specifically, the higher the effect of the indirect pathway, the smaller was the behavioral costs associated with suppressing interference in incongruent trials. Additionally, it was found that this correlation was driven by individual differences in incongruent trials only (with little effect on congruent ones) and specific to the indirect pathway (with almost no correlation with the effect of the direct pathways). Finally, it is shown that this pattern of results is precisely what is predicted when competitive dynamics of the basal ganglia are added to the selective attention component of a simple model of the Simon task, thus showing that our experimental results can be fully explained by our initial hypothesis. Published by Elsevier B.V.

The effects of aging on the interaction between reinforcement learning and attention.

PubMed

Radulescu, Angela; Daniel, Reka; Niv, Yael

2016-11-01

Reinforcement learning (RL) in complex environments relies on selective attention to uncover those aspects of the environment that are most predictive of reward. Whereas previous work has focused on age-related changes in RL, it is not known whether older adults learn differently from younger adults when selective attention is required. In 2 experiments, we examined how aging affects the interaction between RL and selective attention. Younger and older adults performed a learning task in which only 1 stimulus dimension was relevant to predicting reward, and within it, 1 "target" feature was the most rewarding. Participants had to discover this target feature through trial and error. In Experiment 1, stimuli varied on 1 or 3 dimensions and participants received hints that revealed the target feature, the relevant dimension, or gave no information. Group-related differences in accuracy and RTs differed systematically as a function of the number of dimensions and the type of hint available. In Experiment 2 we used trial-by-trial computational modeling of the learning process to test for age-related differences in learning strategies. Behavior of both young and older adults was explained well by a reinforcement-learning model that uses selective attention to constrain learning. However, the model suggested that older adults restricted their learning to fewer features, employing more focused attention than younger adults. Furthermore, this difference in strategy predicted age-related deficits in accuracy. We discuss these results suggesting that a narrower filter of attention may reflect an adaptation to the reduced capabilities of the reinforcement learning system. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Developmental stage related patterns of codon usage and genomic GC content: searching for evolutionary fingerprints with models of stem cell differentiation

PubMed Central

2007-01-01

Background The usage of synonymous codons shows considerable variation among mammalian genes. How and why this usage is non-random are fundamental biological questions and remain controversial. It is also important to explore whether mammalian genes that are selectively expressed at different developmental stages bear different molecular features. Results In two models of mouse stem cell differentiation, we established correlations between codon usage and the patterns of gene expression. We found that the optimal codons exhibited variation (AT- or GC-ending codons) in different cell types within the developmental hierarchy. We also found that genes that were enriched (developmental-pivotal genes) or specifically expressed (developmental-specific genes) at different developmental stages had different patterns of codon usage and local genomic GC (GCg) content. Moreover, at the same developmental stage, developmental-specific genes generally used more GC-ending codons and had higher GCg content compared with developmental-pivotal genes. Further analyses suggest that the model of translational selection might be consistent with the developmental stage-related patterns of codon usage, especially for the AT-ending optimal codons. In addition, our data show that after human-mouse divergence, the influence of selective constraints is still detectable. Conclusion Our findings suggest that developmental stage-related patterns of gene expression are correlated with codon usage (GC3) and GCg content in stem cell hierarchies. Moreover, this paper provides evidence for the influence of natural selection at synonymous sites in the mouse genome and novel clues for linking the molecular features of genes to their patterns of expression during mammalian ontogenesis. PMID:17349061

Variation in the Intensity of Selection on Codon Bias over Time Causes Contrasting Patterns of Base Composition Evolution in Drosophila

PubMed Central

Jackson, Benjamin C.; Campos, José L.; Haddrill, Penelope R.; Charlesworth, Brian

2017-01-01

Four-fold degenerate coding sites form a major component of the genome, and are often used to make inferences about selection and demography, so that understanding their evolution is important. Despite previous efforts, many questions regarding the causes of base composition changes at these sites in Drosophila remain unanswered. To shed further light on this issue, we obtained a new whole-genome polymorphism data set from D. simulans. We analyzed samples from the putatively ancestral range of D. simulans, as well as an existing polymorphism data set from an African population of D. melanogaster. By using D. yakuba as an outgroup, we found clear evidence for selection on 4-fold sites along both lineages over a substantial period, with the intensity of selection increasing with GC content. Based on an explicit model of base composition evolution, we suggest that the observed AT-biased substitution pattern in both lineages is probably due to an ancestral reduction in selection intensity, and is unlikely to be the result of an increase in mutational bias towards AT alone. By using two polymorphism-based methods for estimating selection coefficients over different timescales, we show that the selection intensity on codon usage has been rather stable in D. simulans in the recent past, but the long-term estimates in D. melanogaster are much higher than the short-term ones, indicating a continuing decline in selection intensity, to such an extent that the short-term estimates suggest that selection is only active in the most GC-rich parts of the genome. Finally, we provide evidence for complex evolutionary patterns in the putatively neutral short introns, which cannot be explained by the standard GC-biased gene conversion model. These results reveal a dynamic picture of base composition evolution. PMID:28082609

Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy

DOE PAGES

Rosewater, David; Ferreira, Summer; Schoenwald, David; ...

2018-01-25

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational datamore » is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.« less

Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy

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

Rosewater, David; Ferreira, Summer; Schoenwald, David

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational datamore » is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.« less

Speciation in rapidly diverging systems: lessons from Lake Malawi.

PubMed

Danley, P D; Kocher, T D

2001-05-01

Rapid evolutionary radiations provide insight into the fundamental processes involved in species formation. Here we examine the diversification of one such group, the cichlid fishes of Lake Malawi, which have radiated from a single ancestor into more than 400 species over the past 700 000 years. The phylogenetic history of this group suggests: (i) that their divergence has proceeded in three major bursts of cladogenesis; and (ii) that different selective forces have dominated each cladogenic event. The first episode resulted in the divergence of two major lineages, the sand- and rock-dwellers, each adapted to a major benthic macrohabitat. Among the rock-dwellers, competition for trophic resources then drove a second burst of cladogenesis, which resulted in the differentiation of trophic morphology. The third episode of cladogenesis is associated with differentiation of male nuptial colouration, most likely in response to divergent sexual selection. We discuss models of speciation in relation to this observed pattern. We advocate a model, divergence with gene flow, which reconciles the disparate selective forces responsible for the diversification of this group and suggest that the nonadaptive nature of the tertiary episode has significantly contributed to the extraordinary species richness of this group.

A framework for multi-criteria assessment of model enhancements

NASA Astrophysics Data System (ADS)

Francke, Till; Foerster, Saskia; Brosinsky, Arlena; Delgado, José; Güntner, Andreas; López-Tarazón, José A.; Bronstert, Axel

2016-04-01

Modellers are often faced with unsatisfactory model performance for a specific setup of a hydrological model. In these cases, the modeller may try to improve the setup by addressing selected causes for the model errors (i.e. data errors, structural errors). This leads to adding certain "model enhancements" (MEs), e.g. climate data based on more monitoring stations, improved calibration data, modifications in process formulations. However, deciding on which MEs to implement remains a matter of expert knowledge, guided by some sensitivity analysis at best. When multiple MEs have been implemented, a resulting improvement in model performance is not easily attributed, especially when considering different aspects of this improvement (e.g. better performance dynamics vs. reduced bias). In this study we present an approach for comparing the effect of multiple MEs in the face of multiple improvement aspects. A stepwise selection approach and structured plots help in addressing the multidimensionality of the problem. The approach is applied to a case study, which employs the meso-scale hydrosedimentological model WASA-SED for a sub-humid catchment. The results suggest that the effect of the MEs is quite diverse, with some MEs (e.g. augmented rainfall data) cause improvements for almost all aspects, while the effect of other MEs is restricted to few aspects or even deteriorate some. These specific results may not be generalizable. However, we suggest that based on studies like this, identifying the most promising MEs to implement may be facilitated.

Influence of monitoring data selection for optimization of a steady state multimedia model on the magnitude and nature of the model prediction bias.

PubMed

Kim, Hee Seok; Lee, Dong Soo

2017-11-01

SimpleBox is an important multimedia model used to estimate the predicted environmental concentration for screening-level exposure assessment. The main objectives were (i) to quantitatively assess how the magnitude and nature of prediction bias of SimpleBox vary with the selection of observed concentration data set for optimization and (ii) to present the prediction performance of the optimized SimpleBox. The optimization was conducted using a total of 9604 observed multimedia data for 42 chemicals of four groups (i.e., polychlorinated dibenzo-p-dioxins/furans (PCDDs/Fs), polybrominated diphenyl ethers (PBDEs), phthalates, and polycyclic aromatic hydrocarbons (PAHs)). The model performance was assessed based on the magnitude and skewness of prediction bias. Monitoring data selection in terms of number of data and kind of chemicals plays a significant role in optimization of the model. The coverage of the physicochemical properties was found to be very important to reduce the prediction bias. This suggests that selection of observed data should be made such that the physicochemical property (such as vapor pressure, octanol-water partition coefficient, octanol-air partition coefficient, and Henry's law constant) range of the selected chemical groups be as wide as possible. With optimization, about 55%, 90%, and 98% of the total number of the observed concentration ratios were predicted within factors of three, 10, and 30, respectively, with negligible skewness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Morphine-induced antinociception in the rat: supra-additive interactions with imidazoline I₂ receptor ligands.

PubMed

Li, Jun-Xu; Zhang, Yanan; Winter, Jerrold C

2011-11-01

Pain remains a significant clinical challenge and currently available analgesics are not adequate to meet clinical needs. Emerging evidence suggests the role of imidazoline I(2) receptors in pain modulation primarily from studies of the non-selective imidazoline receptor ligand, agmatine. However, little is known of the generality of the effect to selective I(2) receptor ligands. This study examined the antinociceptive effects of two selective I(2) receptor ligands 2-BFI and BU224 (>2000-fold selectivity for I(2) receptors over α(2) adrenoceptors) in a hypertonic (5%) saline-induced writhing test and analyzed their interaction with morphine using a dose-addition analysis. Morphine, 2-BFI and BU224 but not agmatine produced a dose-dependent antinociceptive effect. Both composite additive curve analyses and isobolographical plots revealed a supra-additive interaction between morphine and 2-BFI or BU224, whereas the interaction between 2-BFI and BU224 was additive. The antinociceptive effect of 2-BFI and BU224 was attenuated by the I(2) receptor antagonist/α(2) adrenoceptor antagonist idazoxan but not by the selective α(2) adrenoceptor antagonist yohimbine, suggesting an I(2) receptor-mediated mechanism. Agmatine enhanced the antinociceptive effect of morphine, 2-BFI and BU224 and the enhancement was prevented by yohimbine, suggesting that the effect was mediated by α(2) adrenoceptors. Taken together, these data represent the first report that selective I(2) receptor ligands have substantial antinociceptive activity and produce antinociceptive synergy with opioids in a rat model of acute pain. These data suggest that drugs acting on imidazoline I(2) receptors may be useful either alone or in combination with opioids for the treatment of pain. Copyright © 2011 Elsevier B.V. All rights reserved.

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

PubMed

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Assessing the role of metabotropic glutamate receptor 5 in multiple nociceptive modalities.

PubMed

Zhu, Chang Z; Wilson, Sonya G; Mikusa, Joseph P; Wismer, Carol T; Gauvin, Donna M; Lynch, James J; Wade, Carrie L; Decker, Michael W; Honore, Prisca

2004-12-15

Preclinical data, performed in a limited number of pain models, suggest that functional blockade of metabotropic glutamate (mGlu) receptors may be beneficial for pain management. In the present study, effects of 2-methyl-6-(phenylethynyl)-pyridine (MPEP), a potent, selective mGlu5 receptor antagonist, were examined in a wide variety of rodent nociceptive and hypersensitivity models in order to fully characterize the potential analgesic profile of mGlu5 receptor blockade. Effects of 3-[(2-methyl-1,3-thiazol-4-yl)ethynyl]pyridine (MTEP), as potent and selective as MPEP at mGlu5/mGlu1 receptors but more selective than MPEP at N-methyl-aspartate (NMDA) receptors, were also evaluated in selected nociceptive and side effect models. MPEP (3-30 mg/kg, i.p.) produced a dose-dependent reversal of thermal and mechanical hyperalgesia following complete Freund's adjuvant (CFA)-induced inflammatory hypersensitivity. Additionally, MPEP (3-30 mg/kg, i.p.) decreased thermal hyperalgesia observed in carrageenan-induced inflammatory hypersensitivity without affecting paw edema, abolished acetic acid-induced writhing activity in mice, and was shown to reduce mechanical allodynia and thermal hyperalgesia observed in a model of post-operative hypersensitivity and formalin-induced spontaneous pain. Furthermore, at 30 mg/kg, i.p., MPEP significantly attenuated mechanical allodynia observed in three neuropathic pain models, i.e. spinal nerve ligation, sciatic nerve constriction and vincristine-induced neuropathic pain. MTEP (3-30 mg/kg, i.p.) also potently reduced CFA-induced thermal hyperalgesia. However, at 100 mg/kg, i.p., MPEP and MTEP produced central nerve system (CNS) side effects as measured by rotarod performance and exploratory locomotor activity. These results suggest a role for mGlu5 receptors in multiple nociceptive modalities, though CNS side effects may be a limiting factor in developing mGlu5 receptor analgesic compounds.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

PubMed Central

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

Selection and Socialization Effects in Early Adolescent Alcohol Use: A Propensity Score Analysis

PubMed Central

Scalco, Matthew D.; Trucco, Elisa M.; Coffman, Donna L.; Colder, Craig R.

2015-01-01

The robust correlation between peer and adolescent alcohol use (AU) has been taken as evidence for both socialization and selection processes in the etiology of adolescent AU. Accumulating evidence from studies using a diverse range of methodological and statistical approaches suggests that both processes are involved. A major challenge in testing whether peer AU predicts an adolescent's drinking (socialization) or whether an adolescent's drinking predicts peer AU (selection) is the myriad of potentially confounding factors that might lead to an overestimation of socialization and selection effects. After creating AU transition groups based on peer and adolescent AU across two waves (N = 765; age = 10-15; 53% female), we test whether transitions into AU by adolescents and peers predict later peer and adolescent AU respectively, using (1) propensity score analysis to balance transition groups on 26 potential confounds, (2) a longitudinal design with three waves to establish temporal precedence, and (3) both adolescent (target) and peer self-report of peer AU to disentangle effects attributable to shared reporter bias. Both selection and socialization were supported using both peer self-report of AU and adolescent-report of peer AU. Although cross-sectional analyses suggested peer self-reported models were associated with smaller effects than perceived peer AU, longitudinal analyses suggest a similar sized effect across reporter of peer AU for both selection and socialization. The implications of these findings for the etiology and treatment of adolescent AU are discussed. PMID:25601099

Cardiac HDAC6 Catalytic Activity is Induced in Response to Chronic Hypertension

PubMed Central

Lemon, Douglas D.; Horn, Todd R.; Cavasin, Maria A.; Jeong, Mark Y.; Haubold, Kurt W.; Long, Carlin S.; Irwin, David C.; McCune, Sylvia A.; Chung, Eunhee; Leinwand, Leslie A.; McKinsey, Timothy A.

2011-01-01

Small molecule histone deacetylase (HDAC) inhibitors block adverse cardiac remodeling in animal models of heart failure. The efficacious compounds target class I, class IIb and, to a lesser extent, class IIa HDACs. It is hypothesized that a selective inhibitor of a specific HDAC class (or an isoform within that class) will provide a favorable therapeutic window for the treatment of heart failure, although the optimal selectivity profile for such a compound remains unknown. Genetic studies have suggested that class I HDACs promote pathological cardiac remodeling, while class IIa HDACs are protective. In contrast, nothing is known about the function or regulation of class IIb HDACs in the heart. We developed assays to quantify catalytic activity of distinct HDAC classes in left and right ventricular cardiac tissue from animal models of hypertensive heart disease. Class I and IIa HDAC activity was elevated in some but not all diseased tissues. In contrast, catalytic activity of the class IIb HDAC, HDAC6, was consistently increased in stressed myocardium, but not in a model of physiologic hypertrophy. HDAC6 catalytic activity was also induced by diverse extracellular stimuli in cultured cardiac myocytes and fibroblasts. These findings suggest an unforeseen role for HDAC6 in the heart, and highlight the need for pre-clinical evaluation of HDAC6-selective inhibitors to determine whether this HDAC isoform is pathological or protective in the setting of cardiovascular disease. PMID:21539845

Lineage Selection and the Maintenance of Sex

PubMed Central

de Vienne, Damien M.; Giraud, Tatiana; Gouyon, Pierre-Henri

2013-01-01

Sex predominates in eukaryotes, despite its short-term disadvantage when compared to asexuality. Myriad models have suggested that short-term advantages of sex may be sufficient to counterbalance its twofold costs. However, despite decades of experimental work seeking such evidence, no evolutionary mechanism has yet achieved broad recognition as explanation for the maintenance of sex. We explore here, through lineage-selection models, the conditions favouring the maintenance of sex. In the first model, we allowed the rate of transition to asexuality to evolve, to determine whether lineage selection favoured species with the strongest constraints preventing the loss of sex. In the second model, we simulated more explicitly the mechanisms underlying the higher extinction rates of asexual lineages than of their sexual counterparts. We linked extinction rates to the ecological and/or genetic features of lineages, thereby providing a formalisation of the only figure included in Darwin's “The origin of species”. Our results reinforce the view that the long-term advantages of sex and lineage selection may provide the most satisfactory explanations for the maintenance of sex in eukaryotes, which is still poorly recognized, and provide figures and a simulation website for training and educational purposes. Short-term benefits may play a role, but it is also essential to take into account the selection of lineages for a thorough understanding of the maintenance of sex. PMID:23825582

Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States

NASA Astrophysics Data System (ADS)

Martinez, Guillermo F.; Gupta, Hoshin V.

2011-12-01

Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a "principle of hydrologic consistency," meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

Inaccurate Color Discrimination by Pollinators Promotes Evolution of Discrete Color Polymorphism in Food-Deceptive Flowers.

PubMed

Kagawa, Kotaro; Takimoto, Gaku

2016-02-01

Many plant species employing a food-deceptive pollination strategy show discrete or continuous floral polymorphism within their populations. Previous studies have suggested that negative frequency-dependent selection (NFDS) caused by the learning behavior of pollinators was responsible for the maintenance of floral polymorphism. However, NFDS alone does not explain why and when discrete or continuous polymorphism evolves. In this study, we use an evolutionary simulation model to propose that inaccurate discrimination of flower colors by pollinators results in evolution of discrete flower color polymorphism. Simulations showed that associative learning based on inaccurate discrimination in pollinators caused disruptive selection of flower colors. The degree of inaccuracy determined the number of discrete flower colors that evolved. Our results suggest that animal behavior based on inaccurate discrimination may be a general cause of disruptive selection that promotes discrete trait polymorphism.

Selective Enhancement of Nucleases by Polyvalent DNA-Functionalized Gold Nanoparticles

PubMed Central

Prigodich, Andrew E.; Alhasan, Ali H.

2011-01-01

We demonstrate that polyvalent DNA-functionalized gold nanoparticles (DNA-Au NPs) selectively enhance Ribonuclease H (RNase H) activity, while inhibiting most biologically relevant nucleases. This combination of properties is particularly interesting in the context of gene regulation, since high RNase H activity results in rapid mRNA degradation and general nuclease inhibition results in high biological stability. We investigate the mechanism of selective RNase H activation and find that the high DNA density of DNA-Au NPs is responsible for this unusual behavior. This work adds to our understanding of polyvalent DNA-Au NPs as gene regulation agents, and suggests a new model for selectively controlling protein-nanoparticle interactions. PMID:21268581

A study of the selection of microcomputer architectures to automate planetary spacecraft power systems

NASA Technical Reports Server (NTRS)

Nauda, A.

1982-01-01

Performance and reliability models of alternate microcomputer architectures as a methodology for optimizing system design were examined. A methodology for selecting an optimum microcomputer architecture for autonomous operation of planetary spacecraft power systems was developed. Various microcomputer system architectures are analyzed to determine their application to spacecraft power systems. It is suggested that no standardization formula or common set of guidelines exists which provides an optimum configuration for a given set of specifications.

Effects of spatial disturbance on common loon nest site selection and territory success

USGS Publications Warehouse

McCarthy, K.P.; DeStefano, S.

2011-01-01

The common loon (Gavia immer) breeds during the summer on northern lakes and water bodies that are also often desirable areas for aquatic recreation and human habitation. In northern New England, we assessed how the spatial nature of disturbance affects common loon nest site selection and territory success. We found through classification and regression analysis that distance to and density of disturbance factors can be used to classify observed nest site locations versus random points, suggesting that these factors affect loon nest site selection (model 1: Correct classification = 75%, null = 50%, K = 0.507, P < 0.001; model 2: Correct classification = 78%, null = 50%, K = 0.551, P < 0.001). However, in an exploratory analysis, we were unable to show a relation between spatial disturbance variables and breeding success (P = 0.595, R 2 = 0.436), possibly because breeding success was so low during the breeding seasons of 2007-2008. We suggest that by selecting nest site locations that avoid disturbance factors, loons thereby limit the effect that disturbance will have on their breeding success. Still, disturbance may force loons to use sub-optimal nesting habitat, limiting the available number of territories, and overall productivity. We advise that management efforts focus on limiting disturbance factors to allow breeding pairs access to the best nesting territories, relieving disturbance pressures that may force sub-optimal nest placement. ?? 2011 The Wildlife Society.

A study of quantum mechanical probabilities in the classical Hodgkin-Huxley model.

PubMed

Moradi, N; Scholkmann, F; Salari, V

2015-03-01

The Hodgkin-Huxley (HH) model is a powerful model to explain different aspects of spike generation in excitable cells. However, the HH model was proposed in 1952 when the real structure of the ion channel was unknown. It is now common knowledge that in many ion-channel proteins the flow of ions through the pore is governed by a gate, comprising a so-called "selectivity filter" inside the ion channel, which can be controlled by electrical interactions. The selectivity filter (SF) is believed to be responsible for the selection and fast conduction of particular ions across the membrane of an excitable cell. Other (generally larger) parts of the molecule such as the pore-domain gate control the access of ions to the channel protein. In fact, two types of gates are considered here for ion channels: the "external gate", which is the voltage sensitive gate, and the "internal gate" which is the selectivity filter gate (SFG). Some quantum effects are expected in the SFG due to its small dimensions, which may play an important role in the operation of an ion channel. Here, we examine parameters in a generalized model of HH to see whether any parameter affects the spike generation. Our results indicate that the previously suggested semi-quantum-classical equation proposed by Bernroider and Summhammer (BS) agrees strongly with the HH equation under different conditions and may even provide a better explanation in some cases. We conclude that the BS model can refine the classical HH model substantially.

Women's Preferences for Penis Size: A New Research Method Using Selection among 3D Models

PubMed Central

Park, Jaymie; Leung, Shannon

2015-01-01

Women’s preferences for penis size may affect men’s comfort with their own bodies and may have implications for sexual health. Studies of women’s penis size preferences typically have relied on their abstract ratings or selecting amongst 2D, flaccid images. This study used haptic stimuli to allow assessment of women’s size recall accuracy for the first time, as well as examine their preferences for erect penis sizes in different relationship contexts. Women (N = 75) selected amongst 33, 3D models. Women recalled model size accurately using this method, although they made more errors with respect to penis length than circumference. Women preferred a penis of slightly larger circumference and length for one-time (length = 6.4 inches/16.3 cm, circumference = 5.0 inches/12.7 cm) versus long-term (length = 6.3 inches/16.0 cm, circumference = 4.8 inches/12.2 cm) sexual partners. These first estimates of erect penis size preferences using 3D models suggest women accurately recall size and prefer penises only slightly larger than average. PMID:26332467

Machinability assessment of commercially pure titanium (CP-Ti) during turning operation: Application potential of GRA method

NASA Astrophysics Data System (ADS)

Khan, Akhtar; Maity, Kalipada

2018-03-01

This paper explores some of the vital machinability characteristics of commercially pure titanium (CP-Ti) grade 2. Experiments were conducted based on Taguchi’s L9 orthogonal array. The selected material was machined on a heavy duty lathe (Model: HMT NH26) using uncoated carbide inserts in dry cutting environment. The selected inserts were designated by ISO as SNMG 120408 (Model: K313) and manufactured by Kennametal. These inserts were rigidly mounted on a right handed tool holder PSBNR 2020K12. Cutting speed, feed rate and depth of cut were selected as three input variables whereas tool wear (VBc) and surface roughness (Ra) were the major attentions. In order to confirm an appreciable machinability of the work part, an optimal parametric combination was attained with the help of grey relational analysis (GRA) approach. Finally, a mathematical model was developed to exhibit the accuracy and acceptability of the proposed methodology using multiple regression equations. The results indicated that, the suggested model is capable of predicting overall grey relational grade within acceptable range.

Women's Preferences for Penis Size: A New Research Method Using Selection among 3D Models.

PubMed

Prause, Nicole; Park, Jaymie; Leung, Shannon; Miller, Geoffrey

2015-01-01

Women's preferences for penis size may affect men's comfort with their own bodies and may have implications for sexual health. Studies of women's penis size preferences typically have relied on their abstract ratings or selecting amongst 2D, flaccid images. This study used haptic stimuli to allow assessment of women's size recall accuracy for the first time, as well as examine their preferences for erect penis sizes in different relationship contexts. Women (N = 75) selected amongst 33, 3D models. Women recalled model size accurately using this method, although they made more errors with respect to penis length than circumference. Women preferred a penis of slightly larger circumference and length for one-time (length = 6.4 inches/16.3 cm, circumference = 5.0 inches/12.7 cm) versus long-term (length = 6.3 inches/16.0 cm, circumference = 4.8 inches/12.2 cm) sexual partners. These first estimates of erect penis size preferences using 3D models suggest women accurately recall size and prefer penises only slightly larger than average.

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

PubMed

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Binding Energy Calculation of Patchouli Alcohol Isomer Cyclooxygenase Complexes Suggested as COX-1/COX-2 Selective Inhibitor

PubMed Central

Mahdi, Chanif; Nurdiana, Nurdiana; Kikuchi, Takheshi; Fatchiyah, Fatchiyah

2014-01-01

To understand the structural features that dictate the selectivity of the two isoforms of the prostaglandin H2 synthase (PGHS/COX), the three-dimensional (3D) structure of COX-1/COX-2 was assessed by means of binding energy calculation of virtual molecular dynamic with using ligand alpha-Patchouli alcohol isomers. Molecular interaction studies with COX-1 and COX-2 were done using the molecular docking tools by Hex 8.0. Interactions were further visualized by using Discovery Studio Client 3.5 software tool. The binding energy of molecular interaction was calculated by AMBER12 and Virtual Molecular Dynamic 1.9.1 software. The analysis of the alpha-Patchouli alcohol isomer compounds showed that all alpha-Patchouli alcohol isomers were suggested as inhibitor of COX-1 and COX-2. Collectively, the scoring binding energy calculation (with PBSA Model Solvent) of alpha-Patchouli alcohol isomer compounds (CID442384, CID6432585, CID3080622, CID10955174, and CID56928117) was suggested as candidate for a selective COX-1 inhibitor and CID521903 as nonselective COX-1/COX-2. PMID:25484897

Optimisation of environmental remediation: how to select and use the reference levels.

PubMed

Balonov, M; Chipiga, L; Kiselev, S; Sneve, M; Yankovich, T; Proehl, G

2018-06-01

A number of past industrial activities and accidents have resulted in the radioactive contamination of large areas at many sites around the world, giving rise to a need for remediation. According to the International Commission on Radiological Protection (ICRP) and International Atomic Energy Agency (IAEA), such situations should be managed as existing exposure situations (ExESs). Control of exposure to the public in ExESs is based on the application of appropriate reference levels (RLs) for residual doses. The implementation of this potentially fruitful concept for the optimisation of remediation in various regions is hampered by a lack of practical experience and relevant guidance. This paper suggests a generic methodology for the selection of numeric values of relevant RLs both in terms of residual annual effective dose and derived RLs (DRLs) based on an appropriate dose assessment. The value for an RL should be selected in the range of the annual residual effective dose of 1-20 mSv, depending on the prevailing circumstances for the exposure under consideration. Within this range, RL values should be chosen by the following assessment steps: (a) assessment of the projected dose, i.e. the dose to a representative person without remedial actions by means of a realistic model as opposed to a conservative model; (b) modelling of the residual dose to a representative person following application of feasible remedial actions; and (c) selection of an RL value between the projected and residual doses, taking account of the prevailing social and economic conditions. This paper also contains some recommendations for practical implementation of the selected RLs for the optimisation of public protection. The suggested methodology used for the selection of RLs (in terms of dose) and the calculation of DRLs (in terms of activity concentration in food, ambient dose rate, etc) has been illustrated by a retrospective analysis of post-Chernobyl monitoring and modelling data from the Bryansk region, Russia, 2001. From this example, it follows that analysis of real data leads to the selection of an RL from a relatively narrow annual dose range (in this case, about 2-3 mSv), from which relevant DRLs can be calculated and directly used for optimisation of the remediation programme.

Self-esteem, narcissism, and stressful life events: Testing for selection and socialization.

PubMed

Orth, Ulrich; Luciano, Eva C

2015-10-01

We examined whether self-esteem and narcissism predict the occurrence of stressful life events (i.e., selection) and whether stressful life events predict change in self-esteem and narcissism (i.e., socialization). The analyses were based on longitudinal data from 2 studies, including samples of 328 young adults (Study 1) and 371 adults (Study 2). The effects of self-esteem and narcissism were mutually controlled for each other and, moreover, controlled for effects of depression. After conducting the study-level analyses, we meta-analytically aggregated the findings. Self-esteem had a selection effect, suggesting that low self-esteem led to the occurrence of stressful life events; however, this effect became nonsignificant when depression was controlled for. Regardless of whether depression was controlled for or not, narcissism had a selection effect, suggesting that high narcissism led to the occurrence of stressful life events. Moreover, stressful life events had a socialization effect on self-esteem, but not on narcissism, suggesting that the occurrence of stressful life events decreased self-esteem. Analyses of trait-state models indicated that narcissism consisted almost exclusively of perfectly stable trait variance, providing a possible explanation for the absence of socialization effects on narcissism. The findings have significant implications because they suggest that a person's level of narcissism influences whether stressful life events occur, and that self-esteem is shaped by the occurrence of stressful life events. Moreover, we discuss the possibility that depression mediates the selection effect of low self-esteem on stressful life events. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

New Universal Rules of Eukaryotic Translation Initiation Fidelity

PubMed Central

Zur, Hadas; Tuller, Tamir

2013-01-01

The accepted model of eukaryotic translation initiation begins with the scanning of the transcript by the pre-initiation complex from the 5′end until an ATG codon with a specific nucleotide (nt) context surrounding it is recognized (Kozak rule). According to this model, ATG codons upstream to the beginning of the ORF should affect translation. We perform for the first time, a genome-wide statistical analysis, uncovering a new, more comprehensive and quantitative, set of initiation rules for improving the cost of translation and its efficiency. Analyzing dozens of eukaryotic genomes, we find that in all frames there is a universal trend of selection for low numbers of ATG codons; specifically, 16–27 codons upstream, but also 5–11 codons downstream of the START ATG, include less ATG codons than expected. We further suggest that there is selection for anti optimal ATG contexts in the vicinity of the START ATG. Thus, the efficiency and fidelity of translation initiation is encoded in the 5′UTR as required by the scanning model, but also at the beginning of the ORF. The observed nt patterns suggest that in all the analyzed organisms the pre-initiation complex often misses the START ATG of the ORF, and may start translation from an alternative initiation start-site. Thus, to prevent the translation of undesired proteins, there is selection for nucleotide sequences with low affinity to the pre-initiation complex near the beginning of the ORF. With the new suggested rules we were able to obtain a twice higher correlation with ribosomal density and protein levels in comparison to the Kozak rule alone (e.g. for protein levels r = 0.7 vs. r = 0.31; p<10−12). PMID:23874179

Training versus engagement as paths to cognitive enrichment with aging.

PubMed

Stine-Morrow, Elizabeth A L; Payne, Brennan R; Roberts, Brent W; Kramer, Arthur F; Morrow, Daniel G; Payne, Laura; Hill, Patrick L; Jackson, Joshua J; Gao, Xuefei; Noh, Soo Rim; Janke, Megan C; Parisi, Jeanine M

2014-12-01

While a training model of cognitive intervention targets the improvement of particular skills through instruction and practice, an engagement model is based on the idea that being embedded in an intellectually and socially complex environment can impact cognition, perhaps even broadly, without explicit instruction. We contrasted these 2 models of cognitive enrichment by randomly assigning healthy older adults to a home-based inductive reasoning training program, a team-based competitive program in creative problem solving, or a wait-list control. As predicted, those in the training condition showed selective improvement in inductive reasoning. Those in the engagement condition, on the other hand, showed selective improvement in divergent thinking, a key ability exercised in creative problem solving. On average, then, both groups appeared to show ability-specific effects. However, moderators of change differed somewhat for those in the engagement and training interventions. Generally, those who started either intervention with a more positive cognitive profile showed more cognitive growth, suggesting that cognitive resources enabled individuals to take advantage of environmental enrichment. Only in the engagement condition did initial levels of openness and social network size moderate intervention effects on cognition, suggesting that comfort with novelty and an ability to manage social resources may be additional factors contributing to the capacity to take advantage of the environmental complexity associated with engagement. Collectively, these findings suggest that training and engagement models may offer alternative routes to cognitive resilience in late life. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

PrPC Governs Susceptibility to Prion Strains in Bank Vole, While Other Host Factors Modulate Strain Features

PubMed Central

Espinosa, J. C.; Nonno, R.; Di Bari, M.; Aguilar-Calvo, P.; Pirisinu, L.; Fernández-Borges, N.; Vanni, I.; Vaccari, G.; Marín-Moreno, A.; Frassanito, P.; Lorenzo, P.; Agrimi, U.

2016-01-01

ABSTRACT Bank vole is a rodent species that shows differential susceptibility to the experimental transmission of different prion strains. In this work, the transmission features of a panel of diverse prions with distinct origins were assayed both in bank vole expressing methionine at codon 109 (Bv109M) and in transgenic mice expressing physiological levels of bank vole PrPC (the BvPrP-Tg407 mouse line). This work is the first systematic comparison of the transmission features of a collection of prion isolates, representing a panel of diverse prion strains, in a transgenic-mouse model and in its natural counterpart. The results showed very similar transmission properties in both the natural species and the transgenic-mouse model, demonstrating the key role of the PrP amino acid sequence in prion transmission susceptibility. However, differences in the PrPSc types propagated by Bv109M and BvPrP-Tg407 suggest that host factors other than PrPC modulate prion strain features. IMPORTANCE The differential susceptibility of bank voles to prion strains can be modeled in transgenic mice, suggesting that this selective susceptibility is controlled by the vole PrP sequence alone rather than by other species-specific factors. Differences in the phenotypes observed after prion transmissions in bank voles and in the transgenic mice suggest that host factors other than the PrPC sequence may affect the selection of the substrain replicating in the animal model. PMID:27654300

Training versus Engagement as Paths to Cognitive Enrichment with Aging

PubMed Central

Stine-Morrow, Elizabeth A. L.; Payne, Brennan R.; Roberts, Brent W.; Kramer, Arthur F.; Morrow, Daniel G.; Payne, Laura; Hill, Patrick L.; Jackson, Joshua J.; Gao, Xuefei; Noh, Soo Rim; Janke, Megan C.; Parisi, Jeanine M.

2015-01-01

While a training model of cognitive intervention targets the improvement of particular skills through instruction and practice, an engagement model is based on the idea that being embedded in an intellectually and socially complex environment can impact cognition, perhaps even broadly, without explicit instruction. We contrasted these two models of cognitive enrichment by randomly assigning healthy older adults to a home-based inductive reasoning training program, a team-based competitive program in creative problem solving, or to a wait-list control. As predicted, those in the training condition showed selective improvement in inductive reasoning. Those in the engagement condition, on the other hand, showed selective improvement in divergent thinking, a key ability exercised in creative problem solving. On average, then, both groups appeared to show ability-specific effects. However, moderators of change differed somewhat for those in the engagement and training interventions. Generally, those who started either intervention with a more positive cognitive profile showed more cognitive growth, suggesting that cognitive resources enabled individuals to take advantage of environmental enrichment. Only in the engagement condition did initial levels of openness and social network size moderate intervention effects on cognition, suggesting that comfort with novelty and an ability to manage social resources may be additional factors contributing to the capacity to take advantage of the environmental complexity associated with engagement. Collectively, these findings suggest that training and engagement models may offer alternative routes to cognitive resilience in late life. PMID:25402337

How does epistasis influence the response to selection?

PubMed Central

Barton, N H

2017-01-01

Much of quantitative genetics is based on the ‘infinitesimal model', under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4Ne by the ‘drift load', and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large Nes, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects. PMID:27901509

How does epistasis influence the response to selection?

PubMed

Barton, N H

2017-01-01

Much of quantitative genetics is based on the 'infinitesimal model', under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4N e by the 'drift load', and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large N e s, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects.

Dynamic causal modelling of effective connectivity from fMRI: Are results reproducible and sensitive to Parkinson's disease and its treatment?

PubMed Central

Rowe, J.B.; Hughes, L.E.; Barker, R.A.; Owen, A.M.

2010-01-01

Dynamic causal modelling (DCM) of functional magnetic resonance imaging (fMRI) data offers new insights into the pathophysiology of neurological disease and mechanisms of effective therapies. Current applications can be used both to identify the most likely functional brain network underlying observed data and estimate the networks' connectivity parameters. We examined the reproducibility of DCM in healthy subjects (young 18–48 years, n = 27; old 50–80 years, n = 15) in the context of action selection. We then examined the effects of Parkinson's disease (50–78 years, Hoehn and Yahr stage 1–2.5, n = 16) and dopaminergic therapy. Forty-eight models were compared, for each of 90 sessions from 58 subjects. Model-evidences clustered according to sets of structurally similar models, with high correlations over two sessions in healthy older subjects. The same model was identified as most likely in healthy controls on both sessions and in medicated patients. In this most likely network model, the selection of action was associated with enhanced coupling between prefrontal cortex and the pre-supplementary motor area. However, the parameters for intrinsic connectivity and contextual modulation in this model were poorly correlated across sessions. A different model was identified in patients with Parkinson's disease after medication withdrawal. In “off” patients, action selection was associated with enhanced connectivity from prefrontal to lateral premotor cortex. This accords with independent evidence of a dopamine-dependent functional disconnection of the SMA in Parkinson's disease. Together, these results suggest that DCM model selection is robust and sensitive enough to study clinical populations and their pharmacological treatment. For critical inferences, model selection may be sufficient. However, caution is required when comparing groups or drug effects in terms of the connectivity parameter estimates, if there are significant posterior covariances among parameters. PMID:20056151

Evaluation of Intradural Stimulation Efficiency and Selectivity in a Computational Model of Spinal Cord Stimulation

PubMed Central

Howell, Bryan; Lad, Shivanand P.; Grill, Warren M.

2014-01-01

Spinal cord stimulation (SCS) is an alternative or adjunct therapy to treat chronic pain, a prevalent and clinically challenging condition. Although SCS has substantial clinical success, the therapy is still prone to failures, including lead breakage, lead migration, and poor pain relief. The goal of this study was to develop a computational model of SCS and use the model to compare activation of neural elements during intradural and extradural electrode placement. We constructed five patient-specific models of SCS. Stimulation thresholds predicted by the model were compared to stimulation thresholds measured intraoperatively, and we used these models to quantify the efficiency and selectivity of intradural and extradural SCS. Intradural placement dramatically increased stimulation efficiency and reduced the power required to stimulate the dorsal columns by more than 90%. Intradural placement also increased selectivity, allowing activation of a greater proportion of dorsal column fibers before spread of activation to dorsal root fibers, as well as more selective activation of individual dermatomes at different lateral deviations from the midline. Further, the results suggest that current electrode designs used for extradural SCS are not optimal for intradural SCS, and a novel azimuthal tripolar design increased stimulation selectivity, even beyond that achieved with an intradural paddle array. Increased stimulation efficiency is expected to increase the battery life of implantable pulse generators, increase the recharge interval of rechargeable implantable pulse generators, and potentially reduce stimulator volume. The greater selectivity of intradural stimulation may improve the success rate of SCS by mitigating the sensitivity of pain relief to malpositioning of the electrode. The outcome of this effort is a better quantitative understanding of how intradural electrode placement can potentially increase the selectivity and efficiency of SCS, which, in turn, provides predictions that can be tested in future clinical studies assessing the potential therapeutic benefits of intradural SCS. PMID:25536035

Archaeological data reveal slow rates of evolution during plant domestication.

PubMed

Purugganan, Michael D; Fuller, Dorian Q

2011-01-01

Domestication is an evolutionary process of species divergence in which morphological and physiological changes result from the cultivation/tending of plant or animal species by a mutualistic partner, most prominently humans. Darwin used domestication as an analogy to evolution by natural selection although there is strong debate on whether this process of species evolution by human association is an appropriate model for evolutionary study. There is a presumption that selection under domestication is strong and most models assume rapid evolution of cultivated species. Using archaeological data for 11 species from 60 archaeological sites, we measure rates of evolution in two plant domestication traits--nonshattering and grain/seed size increase. Contrary to previous assumptions, we find the rates of phenotypic evolution during domestication are slow, and significantly lower or comparable to those observed among wild species subjected to natural selection. Our study indicates that the magnitudes of the rates of evolution during the domestication process, including the strength of selection, may be similar to those measured for wild species. This suggests that domestication may be driven by unconscious selection pressures similar to that observed for natural selection, and the study of the domestication process may indeed prove to be a valid model for the study of evolutionary change. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

PubMed

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

The signature of positive selection at randomly chosen loci.

PubMed

Przeworski, Molly

2002-03-01

In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.

Is hyporheic flow an indicator for salmonid spawning site selection?

NASA Astrophysics Data System (ADS)

Benjankar, R. M.; Tonina, D.; Marzadri, A.; McKean, J. A.; Isaak, D.

2015-12-01

Several studies have investigated the role of hydraulic variables in the selection of spawning sites by salmonids. Some recent studies suggest that the intensity of the ambient hyporheic flow, that present without a salmon egg pocket, is a cue for spawning site selection, but others have argued against it. We tested this hypothesis by using a unique dataset of field surveyed spawning site locations and an unprecedented meter-scale resolution bathymetry of a 13.5 km long reach of Bear Valley Creek (Idaho, USA), an important Chinook salmon spawning stream. We used a two-dimensional surface water model to quantify stream hydraulics and a three-dimensional hyporheic model to quantify the hyporheic flows. Our results show that the intensity of ambient hyporheic flows is not a statistically significant variable for spawning site selection. Conversely, the intensity of the water surface curvature and the habitat quality, quantified as a function of stream hydraulics and morphology, are the most important variables for salmonid spawning site selection. KEY WORDS: Salmonid spawning habitat, pool-riffle system, habitat quality, surface water curvature, hyporheic flow

Selection against Heteroplasmy Explains the Evolution of Uniparental Inheritance of Mitochondria

PubMed Central

Christie, Joshua R.; Schaerf, Timothy M.; Beekman, Madeleine

2015-01-01

Why are mitochondria almost always inherited from one parent during sexual reproduction? Current explanations for this evolutionary mystery include conflict avoidance between the nuclear and mitochondrial genomes, clearing of deleterious mutations, and optimization of mitochondrial-nuclear coadaptation. Mathematical models, however, fail to show that uniparental inheritance can replace biparental inheritance under any existing hypothesis. Recent empirical evidence indicates that mixing two different but normal mitochondrial haplotypes within a cell (heteroplasmy) can cause cell and organism dysfunction. Using a mathematical model, we test if selection against heteroplasmy can lead to the evolution of uniparental inheritance. When we assume selection against heteroplasmy and mutations are neither advantageous nor deleterious (neutral mutations), uniparental inheritance replaces biparental inheritance for all tested parameter values. When heteroplasmy involves mutations that are advantageous or deleterious (non-neutral mutations), uniparental inheritance can still replace biparental inheritance. We show that uniparental inheritance can evolve with or without pre-existing mating types. Finally, we show that selection against heteroplasmy can explain why some organisms deviate from strict uniparental inheritance. Thus, we suggest that selection against heteroplasmy explains the evolution of uniparental inheritance. PMID:25880558

Functional Imaging of Audio-Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed

Rinne, Teemu; Muers, Ross S; Salo, Emma; Slater, Heather; Petkov, Christopher I

2017-06-01

The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio-visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio-visual selective attention modulates the primate brain, identify sources for "lost" attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. © The Author 2017. Published by Oxford University Press.

Functional Imaging of Audio–Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed Central

Muers, Ross S.; Salo, Emma; Slater, Heather; Petkov, Christopher I.

2017-01-01

Abstract The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio–visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio–visual selective attention modulates the primate brain, identify sources for “lost” attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. PMID:28419201

Tumor evolution in space: the effects of competition colonization tradeoffs on tumor invasion dynamics.

PubMed

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations.

MARRIAGE, BMI, AND WAGES: A DOUBLE SELECTION APPROACH

PubMed Central

Brown, Heather

2011-01-01

Obesity rates have been rising over the past decade. As more people become obese, the social stigma of obesity may be reduced. Marriage has typically been used as a positive signal to employers. If obese individuals possess other characteristics that are valued in the labour market they may no longer face a wage penalty for their physical appearance. This paper investigates the relationship between marital status, body mass index (BMI), and wages by estimating a double selection model that controls for selection into the labour and marriage markets using waves 14 and 16 (2004 and 2006) of the British Household Panel Survey. Results suggest that unobserved characteristics related to marriage and labour market participation are causing an upward bias onthe BMI coefficients. The BMI coefficient is positive and significant for married men only in the double selection model. The findings provide evidence that unobserved characteristics related to success in the marriage and labour market may influence the relationship between BMI and wages. PMID:21910281

Tumor Evolution in Space: The Effects of Competition Colonization Tradeoffs on Tumor Invasion Dynamics

PubMed Central

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations. PMID:23508890

Discrete choice modeling of shovelnose sturgeon habitat selection in the Lower Missouri River

USGS Publications Warehouse

Bonnot, T.W.; Wildhaber, M.L.; Millspaugh, J.J.; DeLonay, A.J.; Jacobson, R.B.; Bryan, J.L.

2011-01-01

Substantive changes to physical habitat in the Lower Missouri River, resulting from intensive management, have been implicated in the decline of pallid (Scaphirhynchus albus) and shovelnose (S. platorynchus) sturgeon. To aid in habitat rehabilitation efforts, we evaluated habitat selection of gravid, female shovelnose sturgeon during the spawning season in two sections (lower and upper) of the Lower Missouri River in 2005 and in the upper section in 2007. We fit discrete choice models within an information theoretic framework to identify selection of means and variability in three components of physical habitat. Characterizing habitat within divisions around fish better explained selection than habitat values at the fish locations. In general, female shovelnose sturgeon were negatively associated with mean velocity between them and the bank and positively associated with variability in surrounding depths. For example, in the upper section in 2005, a 0.5 m s-1 decrease in velocity within 10 m in the bank direction increased the relative probability of selection 70%. In the upper section fish also selected sites with surrounding structure in depth (e.g., change in relief). Differences in models between sections and years, which are reinforced by validation rates, suggest that changes in habitat due to geomorphology, hydrology, and their interactions over time need to be addressed when evaluating habitat selection. Because of the importance of variability in surrounding depths, these results support an emphasis on restoring channel complexity as an objective of habitat restoration for shovelnose sturgeon in the Lower Missouri River.

Making stronger causal inferences: Accounting for selection bias in associations between high performance work systems, leadership, and employee and customer satisfaction.

PubMed

Schmidt, Joseph A; Pohler, Dionne M

2018-05-17

We develop competing hypotheses about the relationship between high performance work systems (HPWS) with employee and customer satisfaction. Drawing on 8 years of employee and customer survey data from a financial services firm, we used a recently developed empirical technique-covariate balanced propensity score (CBPS) weighting-to examine if the proposed relationships between HPWS and satisfaction outcomes can be explained by reverse causality, selection effects, or commonly omitted variables such as leadership behavior. The results provide support for leader behaviors as a primary driver of customer satisfaction, rather than HPWS, and also suggest that the problem of reverse causality requires additional attention in future human resource (HR) systems research. Model comparisons suggest that the estimates and conclusions vary across CBPS, meta-analytic, cross-sectional, and time-lagged models (with and without a lagged dependent variable as a control). We highlight the theoretical and methodological implications of the findings for HR systems research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Attraction of position preference by spatial attention throughout human visual cortex.

PubMed

Klein, Barrie P; Harvey, Ben M; Dumoulin, Serge O

2014-10-01

Voluntary spatial attention concentrates neural resources at the attended location. Here, we examined the effects of spatial attention on spatial position selectivity in humans. We measured population receptive fields (pRFs) using high-field functional MRI (fMRI) (7T) while subjects performed an attention-demanding task at different locations. We show that spatial attention attracts pRF preferred positions across the entire visual field, not just at the attended location. This global change in pRF preferred positions systematically increases up the visual hierarchy. We model these pRF preferred position changes as an interaction between two components: an attention field and a pRF without the influence of attention. This computational model suggests that increasing effects of attention up the hierarchy result primarily from differences in pRF size and that the attention field is similar across the visual hierarchy. A similar attention field suggests that spatial attention transforms different neural response selectivities throughout the visual hierarchy in a similar manner. Copyright © 2014 Elsevier Inc. All rights reserved.

Simulation and Experimental Studies on Grain Selection and Structure Design of the Spiral Selector for Casting Single Crystal Ni-Based Superalloy.

PubMed

Zhang, Hang; Xu, Qingyan

2017-10-27

Grain selection is an important process in single crystal turbine blades manufacturing. Selector structure is a control factor of grain selection, as well as directional solidification (DS). In this study, the grain selection and structure design of the spiral selector were investigated through experimentation and simulation. A heat transfer model and a 3D microstructure growth model were established based on the Cellular automaton-Finite difference (CA-FD) method for the grain selector. Consequently, the temperature field, the microstructure and the grain orientation distribution were simulated and further verified. The average error of the temperature result was less than 1.5%. The grain selection mechanisms were further analyzed and validated through simulations. The structural design specifications of the selector were suggested based on the two grain selection effects. The structural parameters of the spiral selector, namely, the spiral tunnel diameter ( d w ), the spiral pitch ( h b ) and the spiral diameter ( h s ), were studied and the design criteria of these parameters were proposed. The experimental and simulation results demonstrated that the improved selector could accurately and efficiently produce a single crystal structure.

Simulation and Experimental Studies on Grain Selection and Structure Design of the Spiral Selector for Casting Single Crystal Ni-Based Superalloy

PubMed Central

Zhang, Hang; Xu, Qingyan

2017-01-01

Grain selection is an important process in single crystal turbine blades manufacturing. Selector structure is a control factor of grain selection, as well as directional solidification (DS). In this study, the grain selection and structure design of the spiral selector were investigated through experimentation and simulation. A heat transfer model and a 3D microstructure growth model were established based on the Cellular automaton-Finite difference (CA-FD) method for the grain selector. Consequently, the temperature field, the microstructure and the grain orientation distribution were simulated and further verified. The average error of the temperature result was less than 1.5%. The grain selection mechanisms were further analyzed and validated through simulations. The structural design specifications of the selector were suggested based on the two grain selection effects. The structural parameters of the spiral selector, namely, the spiral tunnel diameter (dw), the spiral pitch (hb) and the spiral diameter (hs), were studied and the design criteria of these parameters were proposed. The experimental and simulation results demonstrated that the improved selector could accurately and efficiently produce a single crystal structure. PMID:29077067

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise.

PubMed

Ahveninen, Jyrki; Hämäläinen, Matti; Jääskeläinen, Iiro P; Ahlfors, Seppo P; Huang, Samantha; Lin, Fa-Hsuan; Raij, Tommi; Sams, Mikko; Vasios, Christos E; Belliveau, John W

2011-03-08

How can we concentrate on relevant sounds in noisy environments? A "gain model" suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A "tuning model" suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMRI) while subjects attended to tones delivered to one ear and ignored opposite-ear inputs. The attended ear was switched every 30 s to quantify how quickly the effects evolve. To produce overlapping inputs, the tones were presented alone vs. during white-noise masking notch-filtered ±1/6 octaves around the tone center frequencies. Amplitude modulation (39 vs. 41 Hz in opposite ears) was applied for "frequency tagging" of attention effects on maskers. Noise masking reduced early (50-150 ms; N1) auditory responses to unattended tones. In support of the tuning model, selective attention canceled out this attenuating effect but did not modulate the gain of 50-150 ms activity to nonmasked tones or steady-state responses to the maskers themselves. These tuning effects originated at nonprimary auditory cortices, purportedly occupied by neurons that, without attention, have wider frequency tuning than ±1/6 octaves. The attentional tuning evolved rapidly, during the first few seconds after attention switching, and correlated with behavioral discrimination performance. In conclusion, a simple gain model alone cannot explain auditory selective attention. In nonprimary auditory cortices, attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise.

Multi-scale habitat selection of the endangered Hawaiian Goose

USGS Publications Warehouse

Leopold, Christina R.; Hess, Steven C.

2013-01-01

After a severe population reduction during the mid-20th century, the endangered Hawaiian Goose (Branta sandvicensis), or Nēnē, has only recently re-established its seasonal movement patterns on Hawai‘i Island. Little is currently understood about its movements and habitat use during the nonbreeding season. The objectives of this research were to identify habitats preferred by two subpopulations of the Nēnē and how preferences shift seasonally at both meso-and fine scales. From 2009 to 2011, ten Nēnē ganders were outfitted with 40-to 45-g satellite transmitters with GPS capability. We used binary logistic regression to compare habitat use versus availability and an information-theoretic approach for model selection. Meso-scale habitat modeling revealed that Nēnē preferred exotic grass and human-modified landscapes during the breeding and molting seasons and native subalpine shrubland during the nonbreeding season. Fine-scale habitat modeling further indicated preference for exotic grass, bunch grass, and absence of trees. Proximity to water was important during molt, suggesting that the presence of water may provide escape from introduced mammalian predators while Nēnē are flightless. Finescale species-composition data added relatively little to understanding of Nēnē habitat preferences modeled at the meso scale, suggesting that the meso-scale is appropriate for management planning. Habitat selection during our study was consistent with historical records, although dissimilar from more recent studies of other subpopulations. Nēnē make pronounced seasonal movements between existing reserves and use distinct habitat types; understanding annual patterns has implications for the protection and restoration of important seasonal habitats.

Controlling for selection effects in the relationship between child behavior problems and exposure to intimate partner violence.

PubMed

Emery, Clifton R

2011-05-01

This article used the Project on Human Development in Chicago Neighborhoods (PHDCN) data to examine the relationship between exposure to intimate partner violence (IPV) and child behavior problems (externalizing and internalizing), truancy, grade repetition, smoking, drinking, and use of marijuana. Longitudinal data analysis was conducted on 1,816 primary caregivers and their children. Fixed-effects regression models were employed to address concerns with selection bias. IPV was associated with significantly greater internalizing behavior, externalizing behavior, and truancy. Findings from age interaction models suggested that the relationship between IPV and child behavior problems may attenuate as the age of the child at time of exposure increases.

Integrated configurable equipment selection and line balancing for mass production with serial-parallel machining systems

NASA Astrophysics Data System (ADS)

Battaïa, Olga; Dolgui, Alexandre; Guschinsky, Nikolai; Levin, Genrikh

2014-10-01

Solving equipment selection and line balancing problems together allows better line configurations to be reached and avoids local optimal solutions. This article considers jointly these two decision problems for mass production lines with serial-parallel workplaces. This study was motivated by the design of production lines based on machines with rotary or mobile tables. Nevertheless, the results are more general and can be applied to assembly and production lines with similar structures. The designers' objectives and the constraints are studied in order to suggest a relevant mathematical model and an efficient optimization approach to solve it. A real case study is used to validate the model and the developed approach.

Novel 2H-chromen-2-one derivatives of resveratrol: Design, synthesis, modeling and use as human monoamine oxidase inhibitors.

PubMed

Ruan, Ban-Feng; Cheng, Hui-Jie; Ren, Jing; Li, Hong-Lin; Guo, Lu-Lu; Zhang, Xing-Xing; Liao, Chenzhong

2015-10-20

Using a fragment-based drug design strategy, two biomedical interesting fragments, resveratrol and coumarin were linked to design a series of novel human monoamine oxidase (hMAO) inhibitors with a scaffold of 3-((E)-3-(2-((E)-styryl)phenyl)acryloyl)-2H-chromen-2-one, which demonstrated a very interesting selectivity profile against hMAO-A and hMAO-B: some compounds with this scaffold are selective hMAO-A inhibitors, whereas some are selective hMAO-B inhibitors. The small changes in the substituents of the coumarin moiety led to this interesting selectivity profile. The most potent selective hMAO-B inhibitor D7 has a selectivity ratio of 20.93, with an IC₅₀ value of 2.78 μM, similar or better than selegiline (IC₅₀ = 2.89 μM), a selective hMAO-B inhibitor currently in the market for the treatment of Parkinson's disease. Our modeling study indicates that Tyr 326 of hMAO-B (or corresponded Ile 335 of hMAO-A) may be the determinant for the specificity of these compounds. The selectivity profile of compounds reported herein suggests that we can further develop both selective hMAO-A and hMAO-B inhibitors based on this novel scaffold. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

What explains rare and conspicuous colours in a snail? A test of time-series data against models of drift, migration or selection.

PubMed

Johannesson, K; Butlin, R K

2017-01-01

It is intriguing that conspicuous colour morphs of a prey species may be maintained at low frequencies alongside cryptic morphs. Negative frequency-dependent selection by predators using search images ('apostatic selection') is often suggested without rejecting alternative explanations. Using a maximum likelihood approach we fitted predictions from models of genetic drift, migration, constant selection, heterozygote advantage or negative frequency-dependent selection to time-series data of colour frequencies in isolated populations of a marine snail (Littorina saxatilis), re-established with perturbed colour morph frequencies and followed for >20 generations. Snails of conspicuous colours (white, red, banded) are naturally rare in the study area (usually <10%) but frequencies were manipulated to levels of ~50% (one colour per population) in 8 populations at the start of the experiment in 1992. In 2013, frequencies had declined to ~15-45%. Drift alone could not explain these changes. Migration could not be rejected in any population, but required rates much higher than those recorded. Directional selection was rejected in three populations in favour of balancing selection. Heterozygote advantage and negative frequency-dependent selection could not be distinguished statistically, although overall the results favoured the latter. Populations varied idiosyncratically as mild or variable colour selection (3-11%) interacted with demographic stochasticity, and the overall conclusion was that multiple mechanisms may contribute to maintaining the polymorphisms.

Restricted cross-scale habitat selection by American beavers.

PubMed

Francis, Robert A; Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-12-01

Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.

Restricted cross-scale habitat selection by American beavers

PubMed Central

Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-01-01

Abstract Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection. PMID:29492032

Selection for increased voluntary wheel-running affects behavior and brain monoamines in mice

PubMed Central

Waters, R.Parrish; Pringle, R.B.; Forster, G.L.; Renner, K.J.; Malisch, J.L.; Garland, T.; Swallow, J.G.

2013-01-01

Selective-breeding of house mice for increased voluntary wheel-running has resulted in multiple physiological and behavioral changes. Characterizing these differences may lead to experimental models that can elucidate factors involved in human diseases and disorders associated with physical inactivity, or potentially treated by physical activity, such as diabetes, obesity, and depression. Herein, we present ethological data for adult males from a line of mice that has been selectively bred for high levels of voluntary wheel-running and from a non-selected control line, housed with or without wheels. Additionally, we present concentrations of central monoamines in limbic, striatal, and midbrain regions. We monitored wheel-running for 8 weeks, and observed home-cage behavior during the last 5 weeks of the study. Mice from the selected line accumulated more revolutions per day than controls due to increased speed and duration of running. Selected mice exhibited more active behaviors than controls, regardless of wheel access, and exhibited less inactivity and grooming than controls. Selective-breeding also influenced the longitudinal patterns of behavior. We found statistically significant differences in monoamine concentrations and associated metabolites in brain regions that influence exercise and motivational state. These results suggest underlying neurochemical differences between selected and control lines that may influence the observed differences in behavior. Our results bolster the argument that selected mice can provide a useful model of human psychological and physiological diseases and disorders. PMID:23352668

Novel ROCK inhibitors for the treatment of pulmonary arterial hypertension

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

Shaw, Duncan; Hollingworth, Greg; Soldermann, Nicolas

A novel class of selective inhibitors of ROCK1 and ROCK2 has been identified by structural based drug design. PK/PD experiments using a set of highly selective Rho kinase inhibitors suggest that systemic Rho kinase inhibition is linked to a reversible reduction in lymphocyte counts. These results led to the consideration of topical delivery of these molecules, and to the identification of a lead molecule 7 which shows promising PK and PD in a murine model of pulmonary hypertension after intra-tracheal dosing.

Modeling Citation Networks Based on Vigorousness and Dormancy

NASA Astrophysics Data System (ADS)

Wang, Xue-Wen; Zhang, Li-Jie; Yang, Guo-Hong; Xu, Xin-Jian

2013-08-01

In citation networks, the activity of papers usually decreases with age and dormant papers may be discovered and become fashionable again. To model this phenomenon, a competition mechanism is suggested which incorporates two factors: vigorousness and dormancy. Based on this idea, a citation network model is proposed, in which a node has two discrete stage: vigorous and dormant. Vigorous nodes can be deactivated and dormant nodes may be activated and become vigorous. The evolution of the network couples addition of new nodes and state transitions of old ones. Both analytical calculation and numerical simulation show that the degree distribution of nodes in generated networks displays a good right-skewed behavior. Particularly, scale-free networks are obtained as the deactivated vertex is target selected and exponential networks are realized for the random-selected case. Moreover, the measurement of four real-world citation networks achieves a good agreement with the stochastic model.

Creative thought as blind-variation and selective-retention: Combinatorial models of exceptional creativity

NASA Astrophysics Data System (ADS)

Simonton, Dean Keith

2010-06-01

Campbell (1960) proposed that creative thought should be conceived as a blind-variation and selective-retention process (BVSR). This article reviews the developments that have taken place in the half century that has elapsed since his proposal, with special focus on the use of combinatorial models as formal representations of the general theory. After defining the key concepts of blind variants, creative thought, and disciplinary context, the combinatorial models are specified in terms of individual domain samples, variable field size, ideational combination, and disciplinary communication. Empirical implications are then derived with respect to individual, domain, and field systems. These abstract combinatorial models are next provided substantive reinforcement with respect to findings concerning the cognitive processes, personality traits, developmental factors, and social contexts that contribute to creativity. The review concludes with some suggestions regarding future efforts to explicate creativity according to BVSR theory.

The establishment of insulin resistance model in FL83B and L6 cell

NASA Astrophysics Data System (ADS)

Liu, Lanlan; Han, Jizhong; Li, Haoran; Liu, Mengmeng; Zeng, Bin

2017-10-01

The insulin resistance models of mouse liver epithelial and rat myoblasts cells were induced by three kinds of inducers: dexamethasone, high insulin and high glucose. The purpose is to select the optimal insulin resistance model, to provide a simple and reliable TR cell model for the study of the pathogenesis of TR and the improvement of TR drugs and functional foods. The MTT method is used for toxicity screening of three compounds, selecting security and suitable concentration. We performed a Glucose oxidase peroxidase (GOD-POD) method involving FL83B and L6 cell with dexamethasone, high insulin and high glucose-induced insulin resistance. Results suggested that FL83B cells with dexamethasone-induced (0.25uM) were established insulin resistance and L6 cells with high-glucose (30mM) and dexamethasone-induced (0.25uM) were established insulin resistance.

Simultaneous attentional guidance by working-memory and selection history reveals two distinct sources of attention.

PubMed

Schwark, Jeremy D; Dolgov, Igor; Sandry, Joshua; Volkman, C Brooks

2013-10-01

Recent theories of attention have proposed that selection history is a separate, dissociable source of information that influences attention. The current study sought to investigate the simultaneous involvement of selection history and working-memory on attention during visual search. Experiments 1 and 2 used target feature probability to manipulate selection history and found significant effects of both working-memory and selection history, although working-memory dominated selection history when they cued different locations. Experiment 3 eliminated the contribution of voluntary refreshing of working-memory and replicated the main effects, although selection history became dominant. Using the same methodology, but with reduced probability cue validity, both effects were present in Experiment 4 and did not significantly differ in their contribution to attention. Effects of selection history and working-memory never interacted. These results suggest that selection history and working-memory are separate influences on attention and have little impact on each other. Theoretical implications for models of attention are discussed. © 2013.

Methods to Improve the Selection and Tailoring of Implementation Strategies

PubMed Central

Powell, Byron J.; Beidas, Rinad S.; Lewis, Cara C.; Aarons, Gregory A.; McMillen, J. Curtis; Proctor, Enola K.; Khinduka, Shanti K.; Mandell, David S.

2015-01-01

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research. PMID:26289563

The Emotional Gatekeeper: A Computational Model of Attentional Selection and Suppression through the Pathway from the Amygdala to the Inhibitory Thalamic Reticular Nucleus

PubMed Central

Bullock, Daniel; Barbas, Helen

2016-01-01

In a complex environment that contains both opportunities and threats, it is important for an organism to flexibly direct attention based on current events and prior plans. The amygdala, the hub of the brain's emotional system, is involved in forming and signaling affective associations between stimuli and their consequences. The inhibitory thalamic reticular nucleus (TRN) is a hub of the attentional system that gates thalamo-cortical signaling. In the primate brain, a recently discovered pathway from the amygdala sends robust projections to TRN. Here we used computational modeling to demonstrate how the amygdala-TRN pathway, embedded in a wider neural circuit, can mediate selective attention guided by emotions. Our Emotional Gatekeeper model demonstrates how this circuit enables focused top-down, and flexible bottom-up, allocation of attention. The model suggests that the amygdala-TRN projection can serve as a unique mechanism for emotion-guided selection of signals sent to cortex for further processing. This inhibitory selection mechanism can mediate a powerful affective ‘framing’ effect that may lead to biased decision-making in highly charged emotional situations. The model also supports the idea that the amygdala can serve as a relevance detection system. Further, the model demonstrates how abnormal top-down drive and dysregulated local inhibition in the amygdala and in the cortex can contribute to the attentional symptoms that accompany several neuropsychiatric disorders. PMID:26828203

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape.

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.

Evaluation of a black-footed ferret resource utilization function model

USGS Publications Warehouse

Eads, D.A.; Millspaugh, J.J.; Biggins, D.E.; Jachowski, D.S.; Livieri, T.M.

2011-01-01

Resource utilization function (RUF) models permit evaluation of potential habitat for endangered species; ideally such models should be evaluated before use in management decision-making. We evaluated the predictive capabilities of a previously developed black-footed ferret (Mustela nigripes) RUF. Using the population-level RUF, generated from ferret observations at an adjacent yet distinct colony, we predicted the distribution of ferrets within a black-tailed prairie dog (Cynomys ludovicianus) colony in the Conata Basin, South Dakota, USA. We evaluated model performance, using data collected during post-breeding spotlight surveys (2007-2008) by assessing model agreement via weighted compositional analysis and count-metrics. Compositional analysis of home range use and colony-level availability, and core area use and home range availability, demonstrated ferret selection of the predicted Very high and High occurrence categories in 2007 and 2008. Simple count-metrics corroborated these findings and suggested selection of the Very high category in 2007 and the Very high and High categories in 2008. Collectively, these results suggested that the RUF was useful in predicting occurrence and intensity of space use of ferrets at our study site, the 2 objectives of the RUF. Application of this validated RUF would increase the resolution of habitat evaluations, permitting prediction of the distribution of ferrets within distinct colonies. Additional model evaluation at other sites, on other black-tailed prairie dog colonies of varying resource configuration and size, would increase understanding of influences upon model performance and the general utility of the RUF. ?? 2011 The Wildlife Society.

Domestication and fitness in the wild: A multivariate view.

PubMed

Tufto, Jarle

2017-09-01

Domesticated species continually escaping and interbreeding with wild relatives impose a migration load on wild populations. As domesticated stocks become increasingly different as a result of artificial and natural selection in captivity, fitness of escapees in the wild is expected to decline, reducing the effective rate of migration into wild populations. Recent theory suggest that this may alleviate and eventually eliminate the resulting migration load. I develop a multivariate model of trait and wild fitness evolution resulting from the joint effects of artificial and natural selection in the captive environment. Initially, the evolutionary trajectory is dominated by the effects of artificial selection causing a fast initial decline in fitness of escapees in the wild. In later phases, through the counteracting effects of correlational multivariate natural selection in captivity, the mean phenotype is pushed in directions of weak stabilizing selection, allowing a sustained response in the trait subject to artificial selection. Provided that there is some alignment between the adaptive landscapes in the wild and in captivity, these phases are associated with slower rates of decline in wild fitness of the domesticated stock, suggesting that detrimental effects on wild populations are likely to remain a concern in the foreseeable future. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

A Goal-Oriented Model of Natural Language Interaction

DTIC Science & Technology

1977-01-01

AHSTKACT This report describes a research program in modeling human communication . The methodology involved selecting a single, naturally-occurring...knowledge is seldom used in the design process. Human communication skills have not bee’’ characferi?ed at a level of detail appropriate for guiding design...necessarily combine to give a complete picture of human communication . Experience over several more dialogues may suggest that one or all be replaced

Honey Bee Location- and Time-Linked Memory Use in Novel Foraging Situations: Floral Color Dependency

PubMed Central

Amaya-Márquez, Marisol; Hill, Peggy S. M.; Abramson, Charles I.; Wells, Harrington

2014-01-01

Learning facilitates behavioral plasticity, leading to higher success rates when foraging. However, memory is of decreasing value with changes brought about by moving to novel resource locations or activity at different times of the day. These premises suggest a foraging model with location- and time-linked memory. Thus, each problem is novel, and selection should favor a maximum likelihood approach to achieve energy maximization results. Alternatively, information is potentially always applicable. This premise suggests a different foraging model, one where initial decisions should be based on previous learning regardless of the foraging site or time. Under this second model, no problem is considered novel, and selection should favor a Bayesian or pseudo-Bayesian approach to achieve energy maximization results. We tested these two models by offering honey bees a learning situation at one location in the morning, where nectar rewards differed between flower colors, and examined their behavior at a second location in the afternoon where rewards did not differ between flower colors. Both blue-yellow and blue-white dimorphic flower patches were used. Information learned in the morning was clearly used in the afternoon at a new foraging site. Memory was not location-time restricted in terms of use when visiting either flower color dimorphism. PMID:26462587

Sex-specific early survival drives adult sex ratio bias in snowy plovers and impacts mating system and population growth

PubMed Central

Küpper, Clemens; Miller, Tom E. X.; Cruz-López, Medardo; Maher, Kathryn H.; dos Remedios, Natalie; Stoffel, Martin A.; Hoffman, Joseph I.; Krüger, Oliver; Székely, Tamás

2017-01-01

Adult sex ratio (ASR) is a central concept in population biology and a key factor in sexual selection, but why do most demographic models ignore sex biases? Vital rates often vary between the sexes and across life history, but their relative contributions to ASR variation remain poorly understood—an essential step to evaluate sex ratio theories in the wild and inform conservation. Here, we combine structured two-sex population models with individual-based mark–recapture data from an intensively monitored polygamous population of snowy plovers. We show that a strongly male-biased ASR (0.63) is primarily driven by sex-specific survival of juveniles rather than adults or dependent offspring. This finding provides empirical support for theories of unbiased sex allocation when sex differences in survival arise after the period of parental investment. Importantly, a conventional model ignoring sex biases significantly overestimated population viability. We suggest that sex-specific population models are essential to understand the population dynamics of sexual organisms: reproduction and population growth are most sensitive to perturbations in survival of the limiting sex. Overall, our study suggests that sex-biased early survival may contribute toward mating system evolution and population persistence, with implications for both sexual selection theory and biodiversity conservation. PMID:28634289

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein.

PubMed

Gebreyesus, G; Lund, M S; Janss, L; Poulsen, N A; Larsen, L B; Bovenhuis, H; Buitenhuis, A J

2016-04-01

Genetic parameters were estimated for the major milk proteins using bivariate and multi-trait models based on genomic relationships between animals. The analyses included, apart from total protein percentage, αS1-casein (CN), αS2-CN, β-CN, κ-CN, α-lactalbumin, and β-lactoglobulin, as well as the posttranslational sub-forms of glycosylated κ-CN and αS1-CN-8P (phosphorylated). Standard errors of the estimates were used to compare the models. In total, 650 Danish Holstein cows across 4 parities and days in milk ranging from 9 to 481d were selected from 21 herds. The multi-trait model generally resulted in lower standard errors of heritability estimates, suggesting that genetic parameters can be estimated with high accuracy using multi-trait analyses with genomic relationships for scarcely recorded traits. The heritability estimates from the multi-trait model ranged from low (0.05 for β-CN) to high (0.78 for κ-CN). Genetic correlations between the milk proteins and the total milk protein percentage were generally low, suggesting the possibility to alter protein composition through selective breeding with little effect on total milk protein percentage. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Male More than Female Infants Imitate Propulsive Motion

ERIC Educational Resources Information Center

Benenson, Joyce F.; Tennyson, Robert; Wrangham, Richard W.

2011-01-01

Few experimental studies investigate the mechanisms by which young children develop sex-typed activity preferences. Gender self-labeling followed by selective imitation of same-sex models currently is considered a primary socialization mechanism. Research with prenatally androgenized girls and non-human primates also suggests an innate male…

Applied Music Teaching Behavior as a Function of Selected Personality Variables.

ERIC Educational Resources Information Center

Schmidt, Charles P.

1989-01-01

Investigates the relationships among applied music teaching behaviors and personality variables as measured by the Myers-Briggs Type Indicator (MBTI). Suggests that personality variables may be important factors underlying four applied music teaching behaviors: approvals, rate of reinforcement, teacher model/performance, and pace. (LS)

COMPARATIVE MICROARRAY EXPRESSION ANALYSIS OF SELECTED CANCER RELEVANT GENES IN HYPERTENSIVE RESISTANT VERSUS SUSCEPTIBLE RODENT STRAINS

EPA Science Inventory

Hypertension and cancer are prevalent diseases. Epidemiological studies suggest that hypertension may increase the long term risk of cancer. Identification of resistance and/or susceptibility genes using rodent models could provide important insights into the management and treat...

Effects of smoking history on selective attention in schizophrenia.

PubMed

Hahn, Constanze; Hahn, Eric; Dettling, Michael; Güntürkün, Onur; Ta, Thi Minh Tam; Neuhaus, Andres H

2012-03-01

Smoking prevalence is highly elevated in schizophrenia compared to the general population and to other psychiatric populations. Evidence suggests that smoking may lead to improvements of schizophrenia-associated attention deficits; however, large-scale studies on this important issue are scarce. We examined whether sustained, selective, and executive attention processes are differentially modulated by long-term nicotine consumption in 104 schizophrenia patients and 104 carefully matched healthy controls. A significant interaction of 'smoking status' × 'diagnostic group' was obtained for the domain of selective attention. Smoking was significantly associated with a detrimental conflict effect in controls, while the opposite effect was revealed for schizophrenia patients. Likewise, a positive correlation between a cumulative measure of nicotine consumption and conflict effect in controls and a negative correlation in patients were found. These results provide evidence for specific directional effects of smoking on conflict processing that critically dissociate with diagnosis. The data supports the self-medication hypothesis of smoking in schizophrenia and suggests selective attention as a specific cognitive domain targeted by nicotine consumption. A potential mechanistic model explaining these findings is discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Selection for predation, not female fecundity, explains sexual size dimorphism in the orchid mantises.

PubMed

Svenson, Gavin J; Brannoch, Sydney K; Rodrigues, Henrique M; O'Hanlon, James C; Wieland, Frank

2016-12-01

Here we reconstruct the evolutionary shift towards floral simulation in orchid mantises and suggest female predatory selection as the likely driving force behind the development of extreme sexual size dimorphism. Through analysis of body size data and phylogenetic modelling of trait evolution, we recovered an ancestral shift towards sexual dimorphisms in both size and appearance in a lineage of flower-associated praying mantises. Sedentary female flower mantises dramatically increased in size prior to a transition from camouflaged, ambush predation to a floral simulation strategy, gaining access to, and visually attracting, a novel resource: large pollinating insects. Male flower mantises, however, remained small and mobile to facilitate mate-finding and reproductive success, consistent with ancestral male life strategy. Although moderate sexual size dimorphisms are common in many arthropod lineages, the predominant explanation is female size increase for increased fecundity. However, sex-dependent selective pressures acting outside of female fecundity have been suggested as mechanisms behind niche dimorphisms. Our hypothesised role of predatory selection acting on females to generate both extreme sexual size dimorphism coupled with niche dimorphism is novel among arthropods.

Selection for predation, not female fecundity, explains sexual size dimorphism in the orchid mantises

PubMed Central

Svenson, Gavin J.; Brannoch, Sydney K.; Rodrigues, Henrique M.; O’Hanlon, James C.; Wieland, Frank

2016-01-01

Here we reconstruct the evolutionary shift towards floral simulation in orchid mantises and suggest female predatory selection as the likely driving force behind the development of extreme sexual size dimorphism. Through analysis of body size data and phylogenetic modelling of trait evolution, we recovered an ancestral shift towards sexual dimorphisms in both size and appearance in a lineage of flower-associated praying mantises. Sedentary female flower mantises dramatically increased in size prior to a transition from camouflaged, ambush predation to a floral simulation strategy, gaining access to, and visually attracting, a novel resource: large pollinating insects. Male flower mantises, however, remained small and mobile to facilitate mate-finding and reproductive success, consistent with ancestral male life strategy. Although moderate sexual size dimorphisms are common in many arthropod lineages, the predominant explanation is female size increase for increased fecundity. However, sex-dependent selective pressures acting outside of female fecundity have been suggested as mechanisms behind niche dimorphisms. Our hypothesised role of predatory selection acting on females to generate both extreme sexual size dimorphism coupled with niche dimorphism is novel among arthropods. PMID:27905469

Race-Related Cognitive Test Bias in the ACTIVE Study: A MIMIC Model Approach

PubMed Central

Aiken Morgan, Adrienne T.; Marsiske, Michael; Dzierzewski, Joseph; Jones, Richard N.; Whitfield, Keith E.; Johnson, Kathy E.; Cresci, Mary K.

2010-01-01

The present study investigated evidence for race-related test bias in cognitive measures used in the baseline assessment of the ACTIVE clinical trial. Test bias against African Americans has been documented in both cognitive aging and early lifespan studies. Despite significant mean performance differences, Multiple Indicators Multiple Causes (MIMIC) models suggested most differences were at the construct level. There was little evidence that specific measures put either group at particular advantage or disadvantage and little evidence of cognitive test bias in this sample. Small group differences in education, cognitive status, and health suggest positive selection may have attenuated possible biases. PMID:20845121

Selective binding and transcytosis of Ulex europaeus 1 lectin by mouse Peyer's patch M-cells in vivo.

PubMed

Clark, M A; Jepson, M A; Simmons, N L; Hirst, B H

1995-12-01

The in vivo interaction of the lectin Ulex europaeus agglutinin 1 with mouse Peyer's patch follicle-associated epithelial cells was studied in the mouse Peyer's patch gut loop model by immunofluorescence and electron microscopy. The lectin targets to mouse Peyer's patch M-cells and is rapidly endocytosed and transcytosed. These processes are accompanied by morphological changes in the M-cell microvilli and by redistribution of polymerised actin. The demonstration of selective binding and uptake of a lectin by intestinal M-cells in vivo suggests that M-cell-specific surface glycoconjugates might act as receptors for the selective adhesion/uptake of microorganisms.

Variable Selection for Nonparametric Quantile Regression via Smoothing Spline AN OVA

PubMed Central

Lin, Chen-Yen; Bondell, Howard; Zhang, Hao Helen; Zou, Hui

2014-01-01

Quantile regression provides a more thorough view of the effect of covariates on a response. Nonparametric quantile regression has become a viable alternative to avoid restrictive parametric assumption. The problem of variable selection for quantile regression is challenging, since important variables can influence various quantiles in different ways. We tackle the problem via regularization in the context of smoothing spline ANOVA models. The proposed sparse nonparametric quantile regression (SNQR) can identify important variables and provide flexible estimates for quantiles. Our numerical study suggests the promising performance of the new procedure in variable selection and function estimation. Supplementary materials for this article are available online. PMID:24554792

The source of dual-task limitations: Serial or parallel processing of multiple response selections?

PubMed Central

Marois, René

2014-01-01

Although it is generally recognized that the concurrent performance of two tasks incurs costs, the sources of these dual-task costs remain controversial. The serial bottleneck model suggests that serial postponement of task performance in dual-task conditions results from a central stage of response selection that can only process one task at a time. Cognitive-control models, by contrast, propose that multiple response selections can proceed in parallel, but that serial processing of task performance is predominantly adopted because its processing efficiency is higher than that of parallel processing. In the present study, we empirically tested this proposition by examining whether parallel processing would occur when it was more efficient and financially rewarded. The results indicated that even when parallel processing was more efficient and was incentivized by financial reward, participants still failed to process tasks in parallel. We conclude that central information processing is limited by a serial bottleneck. PMID:23864266

Preventing the return of smallpox: molecular modeling studies on thymidylate kinase from Variola virus.

PubMed

Guimarães, Ana Paula; Ramalho, Teodorico Castro; França, Tanos Celmar Costa

2014-01-01

Smallpox was one of the most devastating diseases in the human history and still represents a serious menace today due to its potential use by bioterrorists. Considering this threat and the non-existence of effective chemotherapy, we propose the enzyme thymidylate kinase from Variola virus (VarTMPK) as a potential target to the drug design against smallpox. We first built a homology model for VarTMPK and performed molecular docking studies on it in order to investigate the interactions with inhibitors of Vaccinia virus TMPK (VacTMPK). Subsequently, molecular dynamics (MD) simulations of these compounds inside VarTMPK and human TMPK (HssTMPK) were carried out in order to select the most promising and selective compounds as leads for the design of potential VarTMPK inhibitors. Results of the docking and MD simulations corroborated to each other, suggesting selectivity towards VarTMPK and, also, a good correlation with the experimental data.

Aridity and grazing as convergent selective forces: an experiment with an Arid Chaco bunchgrass.

PubMed

Quiroga, R Emiliano; Golluscio, Rodolfo A; Blanco, Lisandro J; Fernández, Roberto J

2010-10-01

It has been proposed that aridity and grazing are convergent selective forces: each one selects for traits conferring resistance to both. However, this conceptual model has not yet been experimentally validated. The aim of this work was to experimentally evaluate the effect of aridity and grazing, as selective forces, on drought and grazing resistance of populations of Trichloris crinita, a native perennial forage grass of the Argentinean Arid Chaco region. We collected seeds in sites with four different combinations of aridity and grazing history (semiarid/ subhumid x heavily grazed/lightly grazed), established them in pots in a common garden, and subjected the resulting plants to different combinations of drought and defoliation. Our results agreed with the convergence model. Aridity has selected T. crinita genotypes that respond better to drought and defoliation in terms of sexual reproduction and leaf growth, and that can evade grazing due to a lower shoot: root ratio and a higher resource allocation to reserves (starch) in stem bases. Similarly, grazing has selected genotypes that respond better to drought and defoliation in terms of sexual reproduction and that can evade grazing due to a lower digestibility of leaf blades. These results allow us to extend concepts of previous models in plant adaptation to herbivory to models on plant adaptation to drought. The only variable in which we obtained a result opposite to predictions was plant height, as plants from semiarid sites were taller (and with more erect tillers) than plants from subhumid sites; we hypothesize that this result might have been a consequence of the selection exerted by the high solar radiation and soil temperatures of semiarid sites. In addition, our work allows for the prediction of the effects of dry or wet growing seasons on the performance of T. crinita plants. Our results suggest that we can rely on dry environments for selecting grazing-resistant genotypes and on high grazing pressure history environments for selecting drought-resistant ones.

Assessing the Utility of Temporally Dynamic Terrain Indices in Alaskan Moose Resource Selection

NASA Astrophysics Data System (ADS)

Jennewein, J. S.; Hebblewhite, M.; Meddens, A. J.; Gilbert, S.; Vierling, L. A.; Boelman, N.; Eitel, J.

2017-12-01

The accelerated warming in arctic and boreal regions impacts ecosystem structure and plant species distribution, which have secondary effects on wildlife. In summer months, moose (Alces alces) are especially vulnerable to changes in the availability and quality of forage and foliage cover due to their thermoregulatory needs and high energetic demands post calving. Resource selection functions (RSFs) have been used with great success to model such tradeoffs in habitat selection. Recently, RSFs have expanded to include more dynamic representations of habitat selection through the use of time-varying covariates such as dynamic habitat indices. However, to date few studies have investigated dynamic terrain indices, which incorporate long-term, highly-dynamic meteorological data (e.g., albedo, air temperature) and their utility in modeling habitat selection. The purpose of this study is to compare two dynamic terrain indices (i.e., solar insolation and topographic wetness) to their static counterparts in Alaskan moose resource selection over a ten-year period (2008-2017). Additionally, the utility of a dynamic wind-shelter index is assessed. Three moose datasets (n=130 total), spanning a north-to-south gradient in Alaska, are analyzed independently to assess location-specific resource selection. The newly-released, high-resolution Arctic Digital Elevation Model (5m2) is used as the terrain input into both dynamic and static indices. Dynamic indices are programmed with meteorological data from the North American Regional Analysis (NARR) and NASA's Goddard Earth Sciences Data and Information Services Center (GES-DISC) databases. Static wetness and solar insolation indices are estimated using only topographic parameters (e.g., slope, aspect). Preliminary results from pilot analyses suggest that dynamic terrain indices may provide novel insights into resource selection of moose that could not be gained when using static counterparts. Future applications of such dynamic terrain indices that incorporate time-varying meteorological data may be increasingly important in modelling habitat selection under continued climate change scenarios.

Rational selection of training and test sets for the development of validated QSAR models

NASA Astrophysics Data System (ADS)

Golbraikh, Alexander; Shen, Min; Xiao, Zhiyan; Xiao, Yun-De; Lee, Kuo-Hsiung; Tropsha, Alexander

2003-02-01

Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors ( kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q 2 for the training set and accuracy of prediction ( R 2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

Incorporating Neighborhood Choice in a Model of Neighborhood Effects on Income.

PubMed

van Ham, Maarten; Boschman, Sanne; Vogel, Matt

2018-05-09

Studies of neighborhood effects often attempt to identify causal effects of neighborhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research, and it has been argued that estimates of neighborhood effects are biased because people nonrandomly select into neighborhoods based on their preferences, income, and the availability of alternative housing. We propose a two-step framework to disentangle selection processes in the relationship between neighborhood deprivation and earnings. We model neighborhood selection using a conditional logit model, from which we derive correction terms. Driven by the recognition that most households prefer certain types of neighborhoods rather than specific areas, we employ a principle components analysis to reduce these terms into eight correction components. We use these to adjust parameter estimates from a model of subsequent neighborhood effects on individual income for the unequal probability that a household chooses to live in a particular type of neighborhood. We apply this technique to administrative data from the Netherlands. After we adjust for the differential sorting of households into certain types of neighborhoods, the effect of neighborhood income on individual income diminishes but remains significant. These results further emphasize that researchers need to be attuned to the role of selection bias when assessing the role of neighborhood effects on individual outcomes. Perhaps more importantly, the persistent effect of neighborhood deprivation on subsequent earnings suggests that neighborhood effects reflect more than the shared characteristics of neighborhood residents: place of residence partially determines economic well-being.

The infinitesimal model: Definition, derivation, and implications.

PubMed

Barton, N H; Etheridge, A M; Véber, A

2017-12-01

Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions

PubMed Central

Wagatsuma, Nobuhiko; Sakai, Ko

2017-01-01

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision. PMID:28163688

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions.

PubMed

Wagatsuma, Nobuhiko; Sakai, Ko

2016-01-01

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision.

Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

PubMed Central

Porfirio, Luciana L.; Harris, Rebecca M. B.; Lefroy, Edward C.; Hugh, Sonia; Gould, Susan F.; Lee, Greg; Bindoff, Nathaniel L.; Mackey, Brendan

2014-01-01

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models. PMID:25420020

Correlation between surface reconstruction and polytypism in InAs nanowire selective area epitaxy

NASA Astrophysics Data System (ADS)

Liu, Ziyang; Merckling, Clement; Rooyackers, Rita; Richard, Olivier; Bender, Hugo; Mols, Yves; Vila, María; Rubio-Zuazo, Juan; Castro, Germán R.; Collaert, Nadine; Thean, Aaron; Vandervorst, Wilfried; Heyns, Marc

2017-12-01

The mechanism of widely observed intermixing of wurtzite and zinc-blende crystal structures in InAs nanowire (NW) grown by selective area epitaxy (SAE) is studied. We demonstrate that the crystal structure in InAs NW grown by SAE can be controlled using basic growth parameters, and wurtzitelike InAs NWs are achieved. We link the polytypic InAs NWs SAE to the reconstruction of the growth front (111)B surface. Surface reconstruction study of InAs (111) substrate and the following homoepitaxy experiment suggest that (111) planar defect nucleation is related to the (1 × 1) reconstruction of InAs (111)B surface. In order to reveal it more clearly, a model is presented to correlate growth temperature and arsenic partial pressure with InAs NW crystal structure. This model considers the transition between (1 × 1) and (2 × 2) surface reconstructions in the frame of adatom atoms adsorption/desorption, and the polytypism is thus linked to reconstruction quantitatively. The experimental data fit well with the model, which highly suggests that surface reconstruction plays an important role in the polytypism phenomenon in InAs NWs SAE.

The Einstein@Home Gamma-ray Pulsar Survey. II. Source Selection, Spectral Analysis, and Multiwavelength Follow-up

NASA Astrophysics Data System (ADS)

Wu, J.; Clark, C. J.; Pletsch, H. J.; Guillemot, L.; Johnson, T. J.; Torne, P.; Champion, D. J.; Deneva, J.; Ray, P. S.; Salvetti, D.; Kramer, M.; Aulbert, C.; Beer, C.; Bhattacharyya, B.; Bock, O.; Camilo, F.; Cognard, I.; Cuéllar, A.; Eggenstein, H. B.; Fehrmann, H.; Ferrara, E. C.; Kerr, M.; Machenschalk, B.; Ransom, S. M.; Sanpa-Arsa, S.; Wood, K.

2018-02-01

We report on the analysis of 13 gamma-ray pulsars discovered in the Einstein@Home blind search survey using Fermi Large Area Telescope (LAT) Pass 8 data. The 13 new gamma-ray pulsars were discovered by searching 118 unassociated LAT sources from the third LAT source catalog (3FGL), selected using the Gaussian Mixture Model machine-learning algorithm on the basis of their gamma-ray emission properties being suggestive of pulsar magnetospheric emission. The new gamma-ray pulsars have pulse profiles and spectral properties similar to those of previously detected young gamma-ray pulsars. Follow-up radio observations have revealed faint radio pulsations from two of the newly discovered pulsars and enabled us to derive upper limits on the radio emission from the others, demonstrating that they are likely radio-quiet gamma-ray pulsars. We also present results from modeling the gamma-ray pulse profiles and radio profiles, if available, using different geometric emission models of pulsars. The high discovery rate of this survey, despite the increasing difficulty of blind pulsar searches in gamma rays, suggests that new systematic surveys such as presented in this article should be continued when new LAT source catalogs become available.

Integrating in silico models to enhance predictivity for developmental toxicity.

PubMed

Marzo, Marco; Kulkarni, Sunil; Manganaro, Alberto; Roncaglioni, Alessandra; Wu, Shengde; Barton-Maclaren, Tara S; Lester, Cathy; Benfenati, Emilio

2016-08-31

Application of in silico models to predict developmental toxicity has demonstrated limited success particularly when employed as a single source of information. It is acknowledged that modelling the complex outcomes related to this endpoint is a challenge; however, such models have been developed and reported in the literature. The current study explored the possibility of integrating the selected public domain models (CAESAR, SARpy and P&G model) with the selected commercial modelling suites (Multicase, Leadscope and Derek Nexus) to assess if there is an increase in overall predictive performance. The results varied according to the data sets used to assess performance which improved upon model integration relative to individual models. Moreover, because different models are based on different specific developmental toxicity effects, integration of these models increased the applicable chemical and biological spaces. It is suggested that this approach reduces uncertainty associated with in silico predictions by achieving a consensus among a battery of models. The use of tools to assess the applicability domain also improves the interpretation of the predictions. This has been verified in the case of the software VEGA, which makes freely available QSAR models with a measurement of the applicability domain. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Selecting a Conservation Surrogate Species for Small Fragmented Habitats Using Ecological Niche Modelling

PubMed Central

Nekaris, K. Anne-Isola; Arnell, Andrew P.; Svensson, Magdalena S.

2015-01-01

Simple Summary Large “charismatic” animals (with widespread popular appeal) are often used as flagship species to raise awareness for conservation. Deforestation and forest fragmentation are among the main threats to biodiversity, and in many places such species are disappearing. In this paper we aim to find a suitable species among the less charismatic animal species left in the fragmented forests of South-western Sri Lanka. We selected ten candidates, using a questionnaire survey along with computer modelling of their distributions. The red slender loris and the fishing cat came out as finalists as they were both appealing to local people, and fulfilled selected ecological criteria. Abstract Flagship species are traditionally large, charismatic animals used to rally conservation efforts. Accepted flagship definitions suggest they need only fulfil a strategic role, unlike umbrella species that are used to shelter cohabitant taxa. The criteria used to select both flagship and umbrella species may not stand up in the face of dramatic forest loss, where remaining fragments may only contain species that do not suit either set of criteria. The Cinderella species concept covers aesthetically pleasing and overlooked species that fulfil the criteria of flagships or umbrellas. Such species are also more likely to occur in fragmented habitats. We tested Cinderella criteria on mammals in the fragmented forests of the Sri Lankan Wet Zone. We selected taxa that fulfilled both strategic and ecological roles. We created a shortlist of ten species, and from a survey of local perceptions highlighted two finalists. We tested these for umbrella characteristics against the original shortlist, utilizing Maximum Entropy (MaxEnt) modelling, and analysed distribution overlap using ArcGIS. The criteria highlighted Loris tardigradus tardigradus and Prionailurus viverrinus as finalists, with the former having highest flagship potential. We suggest Cinderella species can be effective conservation surrogates especially in habitats where traditional flagship species have been extirpated. PMID:26479135

Residential self-selection bias in the estimation of built environment effects on physical activity between adolescence and young adulthood.

PubMed

Boone-Heinonen, Janne; Guilkey, David K; Evenson, Kelly R; Gordon-Larsen, Penny

2010-10-04

Built environment research is dominated by cross-sectional designs, which are particularly vulnerable to residential self-selection bias resulting from health-related attitudes, neighborhood preferences, or other unmeasured characteristics related to both neighborhood choice and health-related outcomes. We used cohort data from the National Longitudinal Study of Adolescent Health (United States; Wave I, 1994-95; Wave III, 2001-02; n = 12,701) and a time-varying geographic information system. Longitudinal relationships between moderate to vigorous physical activity (MVPA) bouts and built and socioeconomic environment measures (landcover diversity, pay and public physical activity facilities per 10,000 population, street connectivity, median household income, and crime rate) from adolescence to young adulthood were estimated using random effects models (biased by unmeasured confounders) and fixed effects models (within-person estimator, which adjusts for unmeasured confounders that are stable over time). Random effects models yielded null associations except for negative crime-MVPA associations [coefficient (95% CI): -0.056 (-0.083, -0.029) in males, -0.061 (-0.090, -0.033) in females]. After controlling for measured and time invariant unmeasured characteristics using within-person estimators, MVPA was higher with greater physical activity pay facilities in males [coefficient (95% CI): 0.024 (0.006, 0.042)], and lower with higher crime rates in males [coefficient (95% CI): -0.107 (-0.140, -0.075)] and females [coefficient (95% CI): -0.046 (-0.083, -0.009)]. Other associations were null or in the counter-intuitive direction. Comparison of within-person estimates to estimates unadjusted for unmeasured characteristics suggest that residential self-selection can bias associations toward the null, as opposed to its typical characterization as a positive confounder. Differential environment-MVPA associations by residential relocation suggest that studies examining changes following residential relocation may be vulnerable to selection bias. The authors discuss complexities of adjusting for residential self-selection and residential relocation, particularly during the adolescent to young adult transition.

BIOCOMPUTATION: some history and prospects.

PubMed

Cull, Paul

2013-06-01

At first glance, biology and computer science are diametrically opposed sciences. Biology deals with carbon based life forms shaped by evolution and natural selection. Computer Science deals with electronic machines designed by engineers and guided by mathematical algorithms. In this brief paper, we review biologically inspired computing. We discuss several models of computation which have arisen from various biological studies. We show what these have in common, and conjecture how biology can still suggest answers and models for the next generation of computing problems. We discuss computation and argue that these biologically inspired models do not extend the theoretical limits on computation. We suggest that, in practice, biological models may give more succinct representations of various problems, and we mention a few cases in which biological models have proved useful. We also discuss the reciprocal impact of computer science on biology and cite a few significant contributions to biological science. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Detecting Directional Selection in the Presence of Recent Admixture in African-Americans

PubMed Central

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

2011-01-01

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. PMID:21196524

Selectivity curves of the capture of mangrove crab (Ucides cordatus) on the northern coast of Brazil using bayesian inference.

PubMed

Furtado-Junior, I; Abrunhosa, F A; Holanda, F C A F; Tavares, M C S

2016-06-01

Fishing selectivity of the mangrove crab Ucides cordatus in the north coast of Brazil can be defined as the fisherman's ability to capture and select individuals from a certain size or sex (or a combination of these factors) which suggests an empirical selectivity. Considering this hypothesis, we calculated the selectivity curves for males and females crabs using the logit function of the logistic model in the formulation. The Bayesian inference consisted of obtaining the posterior distribution by applying the Markov chain Monte Carlo (MCMC) method to software R using the OpenBUGS, BRugs, and R2WinBUGS libraries. The estimated results of width average carapace selection for males and females compared with previous studies reporting the average width of the carapace of sexual maturity allow us to confirm the hypothesis that most mature individuals do not suffer from fishing pressure; thus, ensuring their sustainability.

Genetic Variation of Goat Interferon Regulatory Factor 3 Gene and Its Implication in Goat Evolution

PubMed Central

Shu, Liping; Zhang, Yesheng; Wang, Yangzi; Sanni, Timothy M.; Imumorin, Ikhide G.; Peters, Sunday O.; Zhang, Jiajin; Dong, Yang; Wang, Wen

2016-01-01

The immune systems are fundamentally vital for evolution and survival of species; as such, selection patterns in innate immune loci are of special interest in molecular evolutionary research. The interferon regulatory factor (IRF) gene family control many different aspects of the innate and adaptive immune responses in vertebrates. Among these, IRF3 is known to take active part in very many biological processes. We assembled and evaluated 1356 base pairs of the IRF3 gene coding region in domesticated goats from Africa (Nigeria, Ethiopia and South Africa) and Asia (Iran and China) and the wild goat (Capra aegagrus). Five segregating sites with θ value of 0.0009 for this gene demonstrated a low diversity across the goats’ populations. Fu and Li tests were significantly positive but Tajima’s D test was significantly negative, suggesting its deviation from neutrality. Neighbor joining tree of IRF3 gene in domesticated goats, wild goat and sheep showed that all domesticated goats have a closer relationship than with the wild goat and sheep. Maximum likelihood tree of the gene showed that different domesticated goats share a common ancestor and suggest single origin. Four unique haplotypes were observed across all the sequences, of which, one was particularly common to African goats (MOCH-K14-0425, Poitou and WAD). In assessing the evolution mode of the gene, we found that the codon model dN/dS ratio for all goats was greater than one. Phylogenetic Analysis by Maximum Likelihood (PAML) gave a ω0 (dN/dS) value of 0.067 with LnL value of -6900.3 for the first Model (M1) while ω2 = 1.667 in model M2 with LnL value of -6900.3 with positive selection inferred in 3 codon sites. Mechanistic empirical combination (MEC) model for evaluating adaptive selection pressure on particular codons also confirmed adaptive selection pressure in three codons (207, 358 and 408) in IRF3 gene. Positive diversifying selection inferred with recent evolutionary changes in domesticated goat IRF3 led us to conclude that the gene evolution may have been influenced by domestication processes in goats. PMID:27598391

Genetic Variation of Goat Interferon Regulatory Factor 3 Gene and Its Implication in Goat Evolution.

PubMed

Okpeku, Moses; Esmailizadeh, Ali; Adeola, Adeniyi C; Shu, Liping; Zhang, Yesheng; Wang, Yangzi; Sanni, Timothy M; Imumorin, Ikhide G; Peters, Sunday O; Zhang, Jiajin; Dong, Yang; Wang, Wen

2016-01-01

The immune systems are fundamentally vital for evolution and survival of species; as such, selection patterns in innate immune loci are of special interest in molecular evolutionary research. The interferon regulatory factor (IRF) gene family control many different aspects of the innate and adaptive immune responses in vertebrates. Among these, IRF3 is known to take active part in very many biological processes. We assembled and evaluated 1356 base pairs of the IRF3 gene coding region in domesticated goats from Africa (Nigeria, Ethiopia and South Africa) and Asia (Iran and China) and the wild goat (Capra aegagrus). Five segregating sites with θ value of 0.0009 for this gene demonstrated a low diversity across the goats' populations. Fu and Li tests were significantly positive but Tajima's D test was significantly negative, suggesting its deviation from neutrality. Neighbor joining tree of IRF3 gene in domesticated goats, wild goat and sheep showed that all domesticated goats have a closer relationship than with the wild goat and sheep. Maximum likelihood tree of the gene showed that different domesticated goats share a common ancestor and suggest single origin. Four unique haplotypes were observed across all the sequences, of which, one was particularly common to African goats (MOCH-K14-0425, Poitou and WAD). In assessing the evolution mode of the gene, we found that the codon model dN/dS ratio for all goats was greater than one. Phylogenetic Analysis by Maximum Likelihood (PAML) gave a ω0 (dN/dS) value of 0.067 with LnL value of -6900.3 for the first Model (M1) while ω2 = 1.667 in model M2 with LnL value of -6900.3 with positive selection inferred in 3 codon sites. Mechanistic empirical combination (MEC) model for evaluating adaptive selection pressure on particular codons also confirmed adaptive selection pressure in three codons (207, 358 and 408) in IRF3 gene. Positive diversifying selection inferred with recent evolutionary changes in domesticated goat IRF3 led us to conclude that the gene evolution may have been influenced by domestication processes in goats.

Artificial neural networks in models of specialization, guild evolution and sympatric speciation.

PubMed

Holmgren, Noél M A; Norrström, Niclas; Getz, Wayne M

2007-03-29

Sympatric speciation can arise as a result of disruptive selection with assortative mating as a pleiotropic by-product. Studies on host choice, employing artificial neural networks as models for the host recognition system in exploiters, illustrate how disruptive selection on host choice coupled with assortative mating can arise as a consequence of selection for specialization. Our studies demonstrate that a generalist exploiter population can evolve into a guild of specialists with an 'ideal free' frequency distribution across hosts. The ideal free distribution arises from variability in host suitability and density-dependent exploiter fitness on different host species. Specialists are less subject to inter-phenotypic competition than generalists and to harmful mutations that are common in generalists exploiting multiple hosts. When host signals used as cues by exploiters coevolve with exploiter recognition systems, our studies show that evolutionary changes may be continuous and cyclic. Selection changes back and forth between specialization and generalization in the exploiters, and weak and strong mimicry in the hosts, where non-defended hosts use the host investing in defence as a model. Thus, host signals and exploiter responses are engaged in a red-queen mimicry process that is ultimately cyclic rather then directional. In one phase, evolving signals of exploitable hosts mimic those of hosts less suitable for exploitation (i.e. the model). Signals in the model hosts also evolve through selection to escape the mimic and its exploiters. Response saturation constraints in the model hosts lead to the mimic hosts finally perfecting its mimicry, after which specialization in the exploiter guild is lost. This loss of exploiter specialization provides an opportunity for the model hosts to escape their mimics. Therefore, this cycle then repeats. We suggest that a species can readily evolve sympatrically when disruptive selection for specialization on hosts is the first step. In a sexual reproduction setting, partial reproductive isolation may first evolve by mate choice being confined to individuals on the same host. Secondly, this disruptive selection will favour assortative mate choice on genotype, thereby leading to increased reproductive isolation.

The evolution of life-history variation in fishes, with particular reference to flatfishes

NASA Astrophysics Data System (ADS)

Roff, Derek A.

This paper explores four aspects of the evolution of life-history variation in fish, with particular reference to the flatfishes: 1. genetic variation and evolutionary response; 2. the size and age at first reproduction; 3. adult lifespan and variation in recruitment; 4. the relationship between reproductive effort and age. Evolutionary response may be limited by previous evolutionary pathways (phylogenetic variation) or by lack of genetic variation due to selection for a single trait. Estimates of heritability suggest, as predicted, that selection is stronger on life-history traits than morphological traits; but there is still adequate genetic variation to permit fairly rapid evolutionary changes. Several approaches to the analysis of the optimal age and size at first reproduction are discussed in the light of a general life-history model based on the assumption that natural selection maximizes r or R 0. It is concluded that one of the most important areas of future research is the relationship between reproduction and mortality. Murphy's hypothesis that the reproductive lifespan should increase with variation in spawning success is shown to be incorrect for fish, at least at the level of interspecific comparison. The model of Charlesworth & León predicting the sufficient condition for reproductive effort to increase with age is tested: in 28 of 31 cases the model predicts an increase of reproductive effort with age. These results suggest that, in general, reproductive effort should increase with age in fish. This prediction is confirmed in the 15 species for which adequate data exist.

Post-Domestication Selection in the Maize Starch Pathway

PubMed Central

Fan, Longjiang; Bao, Jiandong; Wang, Yu; Yao, Jianqiang; Gui, Yijie; Hu, Weiming; Zhu, Jinqing; Zeng, Mengqian; Li, Yu; Xu, Yunbi

2009-01-01

Modern crops have usually experienced domestication selection and subsequent genetic improvement (post-domestication selection). Chinese waxy maize, which originated from non-glutinous domesticated maize (Zea mays ssp. mays), provides a unique model for investigating the post-domestication selection of maize. In this study, the genetic diversity of six key genes in the starch pathway was investigated in a glutinous population that included 55 Chinese waxy accessions, and a selective bottleneck that resulted in apparent reductions in diversity in Chinese waxy maize was observed. Significant positive selection in waxy (wx) but not amylose extender1 (ae1) was detected in the glutinous population, in complete contrast to the findings in non-glutinous maize, which indicated a shift in the selection target from ae1 to wx during the improvement of Chinese waxy maize. Our results suggest that an agronomic trait can be quickly improved into a target trait with changes in the selection target among genes in a crop pathway. PMID:19859548

Social interaction with a tutor modulates responsiveness of specific auditory neurons in juvenile zebra finches.

PubMed

Yanagihara, Shin; Yazaki-Sugiyama, Yoko

2018-04-12

Behavioral states of animals, such as observing the behavior of a conspecific, modify signal perception and/or sensations that influence state-dependent higher cognitive behavior, such as learning. Recent studies have shown that neuronal responsiveness to sensory signals is modified when animals are engaged in social interactions with others or in locomotor activities. However, how these changes produce state-dependent differences in higher cognitive function is still largely unknown. Zebra finches, which have served as the premier songbird model, learn to sing from early auditory experiences with tutors. They also learn from playback of recorded songs however, learning can be greatly improved when song models are provided through social communication with tutors (Eales, 1989; Chen et al., 2016). Recently we found a subset of neurons in the higher-level auditory cortex of juvenile zebra finches that exhibit highly selective auditory responses to the tutor song after song learning, suggesting an auditory memory trace of the tutor song (Yanagihara and Yazaki-Sugiyama, 2016). Here we show that auditory responses of these selective neurons became greater when juveniles were paired with their tutors, while responses of non-selective neurons did not change. These results suggest that social interaction modulates cortical activity and might function in state-dependent song learning. Copyright © 2018 Elsevier B.V. All rights reserved.

Biogeographic and bathymetric determinants of brachiopod extinction and survival during the Late Ordovician mass extinction.

PubMed

Finnegan, Seth; Rasmussen, Christian M Ø; Harper, David A T

2016-04-27

The Late Ordovician mass extinction (LOME) coincided with dramatic climate changes, but there are numerous ways in which these changes could have driven marine extinctions. We use a palaeobiogeographic database of rhynchonelliform brachiopods to examine the selectivity of Late Ordovician-Early Silurian genus extinctions and evaluate which extinction drivers are best supported by the data. The first (latest Katian) pulse of the LOME preferentially affected genera restricted to deeper waters or to relatively narrow (less than 35°) palaeolatitudinal ranges. This pattern is only observed in the latest Katian, suggesting that it reflects drivers unique to this interval. Extinction of exclusively deeper-water genera implies that changes in water mass properties such as dissolved oxygen content played an important role. Extinction of genera with narrow latitudinal ranges suggests that interactions between shifting climate zones and palaeobiogeography may also have been important. We test the latter hypothesis by estimating whether each genus would have been able to track habitats within its thermal tolerance range during the greenhouse-icehouse climate transition. Models including these estimates are favoured over alternative models. We argue that the LOME, long regarded as non-selective, is highly selective along biogeographic and bathymetric axes that are not closely correlated with taxonomic identity. © 2016 The Author(s).

Biogeographic and bathymetric determinants of brachiopod extinction and survival during the Late Ordovician mass extinction

PubMed Central

Finnegan, Seth; Rasmussen, Christian M. Ø.; Harper, David A. T.

2016-01-01

The Late Ordovician mass extinction (LOME) coincided with dramatic climate changes, but there are numerous ways in which these changes could have driven marine extinctions. We use a palaeobiogeographic database of rhynchonelliform brachiopods to examine the selectivity of Late Ordovician–Early Silurian genus extinctions and evaluate which extinction drivers are best supported by the data. The first (latest Katian) pulse of the LOME preferentially affected genera restricted to deeper waters or to relatively narrow (less than 35°) palaeolatitudinal ranges. This pattern is only observed in the latest Katian, suggesting that it reflects drivers unique to this interval. Extinction of exclusively deeper-water genera implies that changes in water mass properties such as dissolved oxygen content played an important role. Extinction of genera with narrow latitudinal ranges suggests that interactions between shifting climate zones and palaeobiogeography may also have been important. We test the latter hypothesis by estimating whether each genus would have been able to track habitats within its thermal tolerance range during the greenhouse–icehouse climate transition. Models including these estimates are favoured over alternative models. We argue that the LOME, long regarded as non-selective, is highly selective along biogeographic and bathymetric axes that are not closely correlated with taxonomic identity. PMID:27122567

Limited potential for adaptation to climate change in a broadly distributed marine crustacean.

PubMed

Kelly, Morgan W; Sanford, Eric; Grosberg, Richard K

2012-01-22

The extent to which acclimation and genetic adaptation might buffer natural populations against climate change is largely unknown. Most models predicting biological responses to environmental change assume that species' climatic envelopes are homogeneous both in space and time. Although recent discussions have questioned this assumption, few empirical studies have characterized intraspecific patterns of genetic variation in traits directly related to environmental tolerance limits. We test the extent of such variation in the broadly distributed tidepool copepod Tigriopus californicus using laboratory rearing and selection experiments to quantify thermal tolerance and scope for adaptation in eight populations spanning more than 17° of latitude. Tigriopus californicus exhibit striking local adaptation to temperature, with less than 1 per cent of the total quantitative variance for thermal tolerance partitioned within populations. Moreover, heat-tolerant phenotypes observed in low-latitude populations cannot be achieved in high-latitude populations, either through acclimation or 10 generations of strong selection. Finally, in four populations there was no increase in thermal tolerance between generations 5 and 10 of selection, suggesting that standing variation had already been depleted. Thus, plasticity and adaptation appear to have limited capacity to buffer these isolated populations against further increases in temperature. Our results suggest that models assuming a uniform climatic envelope may greatly underestimate extinction risk in species with strong local adaptation.

Model for Codon Position Bias in RNA Editing

NASA Astrophysics Data System (ADS)

Liu, Tsunglin; Bundschuh, Ralf

2005-08-01

RNA editing can be crucial for the expression of genetic information via inserting, deleting, or substituting a few nucleotides at specific positions in an RNA sequence. Within coding regions in an RNA sequence, editing usually occurs with a certain bias in choosing the positions of the editing sites. In the mitochondrial genes of Physarum polycephalum, many more editing events have been observed at the third codon position than at the first and second, while in some plant mitochondria the second codon position dominates. Here we propose an evolutionary model that explains this bias as the basis of selection at the protein level. The model predicts a distribution of the three positions rather close to the experimental observation in Physarum. This suggests that the codon position bias in Physarum is mainly a consequence of selection at the protein level.

A model for codon position bias in RNA editing

NASA Astrophysics Data System (ADS)

Bundschuh, Ralf; Liu, Tsunglin

2006-03-01

RNA editing can be crucial for the expression of genetic information via inserting, deleting, or substituting a few nucleotides at specific positions in an RNA sequence. Within coding regions in an RNA sequence, editing usually occurs with a certain bias in choosing the positions of the editing sites. In the mitochondrial genes of Physarum polycephalum, many more editing events have been observed at the third codon position than at the first and second, while in some plant mitochondria the second codon position dominates. Here we propose an evolutionary model that explains this bias as the basis of selection at the protein level. The model predicts a distribution of the three positions rather close to the experimental observation in Physarum. This suggests that the codon position bias in Physarum is mainly a consequence of selection at the protein level.

Interspecific competition underlying mutualistic networks.

PubMed

Maeng, Seong Eun; Lee, Jae Woo; Lee, Deok-Sun

2012-03-09

Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.

Interspecific Competition Underlying Mutualistic Networks

NASA Astrophysics Data System (ADS)

Maeng, Seong Eun; Lee, Jae Woo; Lee, Deok-Sun

2012-03-01

Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.

Application of an interactive water simulation model in urban water management: a case study in Amsterdam.

PubMed

Leskens, J G; Brugnach, M; Hoekstra, A Y

2014-01-01

Water simulation models are available to support decision-makers in urban water management. To use current water simulation models, special expertise is required. Therefore, model information is prepared prior to work sessions, in which decision-makers weigh different solutions. However, this model information quickly becomes outdated when new suggestions for solutions arise and are therefore limited in use. We suggest that new model techniques, i.e. fast and flexible computation algorithms and realistic visualizations, allow this problem to be solved by using simulation models during work sessions. A new Interactive Water Simulation Model was applied for two case study areas in Amsterdam and was used in two workshops. In these workshops, the Interactive Water Simulation Model was positively received. It included non-specialist participants in the process of suggesting and selecting possible solutions and made them part of the accompanying discussions and negotiations. It also provided the opportunity to evaluate and enhance possible solutions more often within the time horizon of a decision-making process. Several preconditions proved to be important for successfully applying the Interactive Water Simulation Model, such as the willingness of the stakeholders to participate and the preparation of different general main solutions that can be used for further iterations during a work session.

Kakusan4 and Aminosan: two programs for comparing nonpartitioned, proportional and separate models for combined molecular phylogenetic analyses of multilocus sequence data.

PubMed

Tanabe, Akifumi S

2011-09-01

Proportional and separate models able to apply different combination of substitution rate matrix (SRM) and among-site rate variation model (ASRVM) to each locus are frequently used in phylogenetic studies of multilocus data. A proportional model assumes that branch lengths are proportional among partitions and a separate model assumes that each partition has an independent set of branch lengths. However, the selection from among nonpartitioned (i.e., a common combination of models is applied to all-loci concatenated sequences), proportional and separate models is usually based on the researcher's preference rather than on any information criteria. This study describes two programs, 'Kakusan4' (for DNA sequences) and 'Aminosan' (for amino-acid sequences), which allow the selection of evolutionary models based on several types of information criteria. The programs can handle both multilocus and single-locus data, in addition to providing an easy-to-use wizard interface and a noninteractive command line interface. In the case of multilocus data, SRMs and ASRVMs are compared at each locus and at all-loci concatenated sequences, after which nonpartitioned, proportional and separate models are compared based on information criteria. The programs also provide model configuration files for mrbayes, paup*, phyml, raxml and Treefinder to support further phylogenetic analysis using a selected model. When likelihoods are optimized by Treefinder, the best-fit models were found to differ depending on the data set. Furthermore, differences in the information criteria among nonpartitioned, proportional and separate models were much larger than those among the nonpartitioned models. These findings suggest that selecting from nonpartitioned, proportional and separate models results in a better phylogenetic tree. Kakusan4 and Aminosan are available at http://www.fifthdimension.jp/. They are licensed under gnugpl Ver.2, and are able to run on Windows, MacOS X and Linux. © 2011 Blackwell Publishing Ltd.

Evolution of egg target size: an analysis of selection on correlated characters.

PubMed

Podolsky, R D

2001-12-01

In broadcast-spawning marine organisms, chronic sperm limitation should select for traits that improve chances of sperm-egg contact. One mechanism may involve increasing the size of the physical or chemical target for sperm. However, models of fertilization kinetics predict that increasing egg size can reduce net zygote production due to an associated decline in fecundity. An alternate method for increasing physical target size is through addition of energetically inexpensive external structures, such as the jelly coats typical of eggs in species from several phyla. In selection experiments on eggs of the echinoid Dendraster excentricus, in which sperm was used as the agent of selection, eggs with larger overall targets were favored in fertilization. Actual shifts in target size following selection matched quantitative predictions of a model that assumed fertilization was proportional to target size. Jelly volume and ovum volume, two characters that contribute to target size, were correlated both within and among females. A cross-sectional analysis of selection partitioned the independent effects of these characters on fertilization success and showed that they experience similar direct selection pressures. Coupled with data on relative organic costs of the two materials, these results suggest that, under conditions where fertilization is limited by egg target size, selection should favor investment in low-cost accessory structures and may have a relatively weak effect on the evolution of ovum size.

Foveal analysis and peripheral selection during active visual sampling

PubMed Central

Ludwig, Casimir J. H.; Davies, J. Rhys; Eckstein, Miguel P.

2014-01-01

Human vision is an active process in which information is sampled during brief periods of stable fixation in between gaze shifts. Foveal analysis serves to identify the currently fixated object and has to be coordinated with a peripheral selection process of the next fixation location. Models of visual search and scene perception typically focus on the latter, without considering foveal processing requirements. We developed a dual-task noise classification technique that enables identification of the information uptake for foveal analysis and peripheral selection within a single fixation. Human observers had to use foveal vision to extract visual feature information (orientation) from different locations for a psychophysical comparison. The selection of to-be-fixated locations was guided by a different feature (luminance contrast). We inserted noise in both visual features and identified the uptake of information by looking at correlations between the noise at different points in time and behavior. Our data show that foveal analysis and peripheral selection proceeded completely in parallel. Peripheral processing stopped some time before the onset of an eye movement, but foveal analysis continued during this period. Variations in the difficulty of foveal processing did not influence the uptake of peripheral information and the efficacy of peripheral selection, suggesting that foveal analysis and peripheral selection operated independently. These results provide important theoretical constraints on how to model target selection in conjunction with foveal object identification: in parallel and independently. PMID:24385588

Word Fluency: A Task Analysis.

ERIC Educational Resources Information Center

Laine, Matti

It is suggested that models of human problem solving are useful in the analysis of word fluency (WF) test performance. In problem-solving terms, WF tasks would require the subject to define and clarify the conditions of the task (task acquisition), select and employ appropriate strategies, and monitor one's performance. In modern neuropsychology,…

Teaching Reading to Learning Disabled Children: A Fourth Approach.

ERIC Educational Resources Information Center

Bateman, Barbara

The evidence presented in this paper suggests that deficits in selective skills are primary factors in learning disabilities, and that aptitude/treatment interaction models may be useful in devising teaching methods for the reading instruction of learning disabled children. After reviewing various approaches to teaching reading to learning…

Overprompting Science Students Using Adjunct Study Questions.

ERIC Educational Resources Information Center

Holliday, William G.

1983-01-01

The selective attention model was used to explain effects of overprompting students (N=170) provided with study questions adjunct to a complex flow diagram describing scientific cyclical schema. Strongly prompting students to answers of questions was less effective than an unprompted question treatment, suggesting that prompting techniques be used…

Effects of spatial disturbance on common loon nest site selection and territory success

USGS Publications Warehouse

McCarthy, Kyle P.; DeStefano, Stephen

2011-01-01

The common loon (Gavia immer) breeds during the summer on northern lakes and water bodies that are also often desirable areas for aquatic recreation and human habitation. In northern New England, we assessed how the spatial nature of disturbance affects common loon nest site selection and territory success. We found through classification and regression analysis that distance to and density of disturbance factors can be used to classify observed nest site locations versus random points, suggesting that these factors affect loon nest site selection (model 1: Correct classification = 75%, null = 50%, K = 0.507, P < 0.001; model 2: Correct classification = 78%, null = 50%, K = 0.551, P < 0.001). However, in an exploratory analysis, we were unable to show a relation between spatial disturbance variables and breeding success (P = 0.595, R2 = 0.436), possibly because breeding success was so low during the breeding seasons of 2007–2008. We suggest that by selecting nest site locations that avoid disturbance factors, loons thereby limit the effect that disturbance will have on their breeding success. Still, disturbance may force loons to use sub-optimal nesting habitat, limiting the available number of territories, and overall productivity. We advise that management efforts focus on limiting disturbance factors to allow breeding pairs access to the best nesting territories, relieving disturbance pressures that may force sub-optimal nest placement.

Effects of Food and Pharmaceutical Formulation on Desmopressin Pharmacokinetics in Children.

PubMed

Michelet, Robin; Dossche, Lien; De Bruyne, Pauline; Colin, Pieter; Boussery, Koen; Vande Walle, Johan; Van Bocxlaer, Jan; Vermeulen, An

2016-09-01

Desmopressin is used for treatment of nocturnal enuresis in children. In this study, we investigated the pharmacokinetics of two formulations-a tablet and a lyophilisate-in both fasted and fed children. Previously published data from two studies (one in 22 children aged 6-16 years, and the other in 25 children aged 6-13 years) were analyzed using population pharmacokinetic modeling. A one-compartment model with first-order absorption was fitted to the data. Covariates were selected using a forward selection procedure. The final model was evaluated, and sensitivity analysis was performed to improve future sampling designs. Simulations were subsequently performed to further explore the relative bioavailability of both formulations and the food effect. The final model described the plasma desmopressin concentrations adequately. The formulation and the fed state were included as covariates on the relative bioavailability. The lyophilisate was, on average, 32.1 % more available than the tablet, and fasted children exhibited an average increase in the relative bioavailability of 101 % in comparison with fed children. Body weight was included as a covariate on distribution volume, using a power function with an exponent of 0.402. Simulations suggested that both the formulation and the food effect were clinically relevant. Bioequivalence data on two formulations of the same drug in adults cannot be readily extrapolated to children. This was the first study in children suggesting that the two desmopressin formulations are not bioequivalent in children at the currently approved dose levels. Furthermore, the effect of food intake was found to be clinically relevant. Sampling times for a future study were suggested. This sampling design should result in more informative data and consequently generate a more robust model.

Quantitative thickness prediction of tectonically deformed coal using Extreme Learning Machine and Principal Component Analysis: a case study

NASA Astrophysics Data System (ADS)

Wang, Xin; Li, Yan; Chen, Tongjun; Yan, Qiuyan; Ma, Li

2017-04-01

The thickness of tectonically deformed coal (TDC) has positive correlation associations with gas outbursts. In order to predict the TDC thickness of coal beds, we propose a new quantitative predicting method using an extreme learning machine (ELM) algorithm, a principal component analysis (PCA) algorithm, and seismic attributes. At first, we build an ELM prediction model using the PCA attributes of a synthetic seismic section. The results suggest that the ELM model can produce a reliable and accurate prediction of the TDC thickness for synthetic data, preferring Sigmoid activation function and 20 hidden nodes. Then, we analyze the applicability of the ELM model on the thickness prediction of the TDC with real application data. Through the cross validation of near-well traces, the results suggest that the ELM model can produce a reliable and accurate prediction of the TDC. After that, we use 250 near-well traces from 10 wells to build an ELM predicting model and use the model to forecast the TDC thickness of the No. 15 coal in the study area using the PCA attributes as the inputs. Comparing the predicted results, it is noted that the trained ELM model with two selected PCA attributes yields better predication results than those from the other combinations of the attributes. Finally, the trained ELM model with real seismic data have a different number of hidden nodes (10) than the trained ELM model with synthetic seismic data. In summary, it is feasible to use an ELM model to predict the TDC thickness using the calculated PCA attributes as the inputs. However, the input attributes, the activation function and the number of hidden nodes in the ELM model should be selected and tested carefully based on individual application.

Disentangling Mechanisms That Mediate the Balance Between Stochastic and Deterministic Processes in Microbial Succession

DOE PAGES

Dini-Andreote, Francisco; Stegen, James C.; van Elsas, Jan D.; ...

2015-03-17

Despite growing recognition that deterministic and stochastic factors simultaneously influence bacterial communities, little is known about mechanisms shifting their relative importance. To better understand underlying mechanisms, we developed a conceptual model linking ecosystem development during primary succession to shifts in the stochastic/deterministic balance. To evaluate the conceptual model we coupled spatiotemporal data on soil bacterial communities with environmental conditions spanning 105 years of salt marsh development. At the local scale there was a progression from stochasticity to determinism due to Na accumulation with increasing ecosystem age, supporting a main element of the conceptual model. At the regional-scale, soil organic mattermore » (SOM) governed the relative influence of stochasticity and the type of deterministic ecological selection, suggesting scale-dependency in how deterministic ecological selection is imposed. Analysis of a new ecological simulation model supported these conceptual inferences. Looking forward, we propose an extended conceptual model that integrates primary and secondary succession in microbial systems.« less

Additive-Multiplicative Approximation of Genotype-Environment Interaction

PubMed Central

Gimelfarb, A.

1994-01-01

A model of genotype-environment interaction in quantitative traits is considered. The model represents an expansion of the traditional additive (first degree polynomial) approximation of genotypic and environmental effects to a second degree polynomial incorporating a multiplicative term besides the additive terms. An experimental evaluation of the model is suggested and applied to a trait in Drosophila melanogaster. The environmental variance of a genotype in the model is shown to be a function of the genotypic value: it is a convex parabola. The broad sense heritability in a population depends not only on the genotypic and environmental variances, but also on the position of the genotypic mean in the population relative to the minimum of the parabola. It is demonstrated, using the model, that GXE interaction rectional may cause a substantial non-linearity in offspring-parent regression and a reversed response to directional selection. It is also shown that directional selection may be accompanied by an increase in the heritability. PMID:7896113

Lower- and higher-level models of right hemisphere language. A selective survey.

PubMed

Gainotti, Guido

2016-01-01

The models advanced to explain right hemisphere (RH) language function can be divided into two main types. According to the older (lower-level) models, RH language reflects the ontogenesis of conceptual and semantic-lexical development; the more recent models, on the other hand, suggest that the RH plays an important role in the use of higher-level language functions, such as metaphors, to convey complex, abstract concepts. The hypothesis that the RH may be preferentially involved in processing the semantic-lexical components of language was advanced by Zaidel in splitbrain patients and his model was confirmed by neuropsychological investigations, proving that right brain-damaged patients show selective semanticlexical disorders. The possible links between lower and higher levels of RH language are discussed, as is the hypothesis that the RH may have privileged access to the figurative aspects of novel metaphorical expressions, whereas conventionalization of metaphorical meaning could be a bilaterally-mediated process involving abstract semantic-lexical codes.

[Effect of stock abundance and environmental factors on the recruitment success of small yellow croaker in the East China Sea].

PubMed

Liu, Zun-lei; Yuan, Xing-wei; Yang, Lin-lin; Yan, Li-ping; Zhang, Hui; Cheng, Jia-hua

2015-02-01

Multiple hypotheses are available to explain recruitment rate. Model selection methods can be used to identify the best model that supports a particular hypothesis. However, using a single model for estimating recruitment success is often inadequate for overexploited population because of high model uncertainty. In this study, stock-recruitment data of small yellow croaker in the East China Sea collected from fishery dependent and independent surveys between 1992 and 2012 were used to examine density-dependent effects on recruitment success. Model selection methods based on frequentist (AIC, maximum adjusted R2 and P-values) and Bayesian (Bayesian model averaging, BMA) methods were applied to identify the relationship between recruitment and environment conditions. Interannual variability of the East China Sea environment was indicated by sea surface temperature ( SST) , meridional wind stress (MWS), zonal wind stress (ZWS), sea surface pressure (SPP) and runoff of Changjiang River ( RCR). Mean absolute error, mean squared predictive error and continuous ranked probability score were calculated to evaluate the predictive performance of recruitment success. The results showed that models structures were not consistent based on three kinds of model selection methods, predictive variables of models were spawning abundance and MWS by AIC, spawning abundance by P-values, spawning abundance, MWS and RCR by maximum adjusted R2. The recruitment success decreased linearly with stock abundance (P < 0.01), suggesting overcompensation effect in the recruitment success might be due to cannibalism or food competition. Meridional wind intensity showed marginally significant and positive effects on the recruitment success (P = 0.06), while runoff of Changjiang River showed a marginally negative effect (P = 0.07). Based on mean absolute error and continuous ranked probability score, predictive error associated with models obtained from BMA was the smallest amongst different approaches, while that from models selected based on the P-value of the independent variables was the highest. However, mean squared predictive error from models selected based on the maximum adjusted R2 was highest. We found that BMA method could improve the prediction of recruitment success, derive more accurate prediction interval and quantitatively evaluate model uncertainty.

Multi-indication Pharmacotherapeutic Multicriteria Decision Analytic Model for the Comparative Formulary Inclusion of Proton Pump Inhibitors in Qatar.

PubMed

Al-Badriyeh, Daoud; Alabbadi, Ibrahim; Fahey, Michael; Al-Khal, Abdullatif; Zaidan, Manal

2016-05-01

The formulary inclusion of proton pump inhibitors (PPIs) in the government hospital health services in Qatar is not comparative or restricted. Requests to include a PPI in the formulary are typically accepted if evidence of efficacy and tolerability is presented. There are no literature reports of a PPI scoring model that is based on comparatively weighted multiple indications and no reports of PPI selection in Qatar or the Middle East. This study aims to compare first-line use of the PPIs that exist in Qatar. The economic effect of the study recommendations was also quantified. A comparative, evidence-based multicriteria decision analysis (MCDA) model was constructed to follow the multiple indications and pharmacotherapeutic criteria of PPIs. Literature and an expert panel informed the selection criteria of PPIs. Input from the relevant local clinician population steered the relative weighting of selection criteria. Comparatively scored PPIs, exceeding a defined score threshold, were recommended for selection. Weighted model scores were successfully developed, with 95% CI and 5% margin of error. The model comprised 7 main criteria and 38 subcriteria. Main criteria are indication, dosage frequency, treatment duration, best published evidence, available formulations, drug interactions, and pharmacokinetic and pharmacodynamic properties. Most weight was achieved for the indications selection criteria. Esomeprazole and rabeprazole were suggested as formulary options, followed by lansoprazole for nonformulary use. The estimated effect of the study recommendations was up to a 15.3% reduction in the annual PPI expenditure. Robustness of study conclusions against variabilities in study inputs was confirmed via sensitivity analyses. The implementation of a locally developed PPI-specific comparative MCDA scoring model, which is multiweighted indication and criteria based, into the Qatari formulary selection practices is a successful evidence-based cost-cutting exercise. Esomeprazole and rabeprazole should be the first-line choice from among the PPIs available at the Qatari government hospital health services. Copyright © 2016 Elsevier HS Journals, Inc. All rights reserved.

PrPC Governs Susceptibility to Prion Strains in Bank Vole, While Other Host Factors Modulate Strain Features.

PubMed

Espinosa, J C; Nonno, R; Di Bari, M; Aguilar-Calvo, P; Pirisinu, L; Fernández-Borges, N; Vanni, I; Vaccari, G; Marín-Moreno, A; Frassanito, P; Lorenzo, P; Agrimi, U; Torres, J M

2016-12-01

Bank vole is a rodent species that shows differential susceptibility to the experimental transmission of different prion strains. In this work, the transmission features of a panel of diverse prions with distinct origins were assayed both in bank vole expressing methionine at codon 109 (Bv109M) and in transgenic mice expressing physiological levels of bank vole PrP C (the BvPrP-Tg407 mouse line). This work is the first systematic comparison of the transmission features of a collection of prion isolates, representing a panel of diverse prion strains, in a transgenic-mouse model and in its natural counterpart. The results showed very similar transmission properties in both the natural species and the transgenic-mouse model, demonstrating the key role of the PrP amino acid sequence in prion transmission susceptibility. However, differences in the PrP Sc types propagated by Bv109M and BvPrP-Tg407 suggest that host factors other than PrP C modulate prion strain features. The differential susceptibility of bank voles to prion strains can be modeled in transgenic mice, suggesting that this selective susceptibility is controlled by the vole PrP sequence alone rather than by other species-specific factors. Differences in the phenotypes observed after prion transmissions in bank voles and in the transgenic mice suggest that host factors other than the PrP C sequence may affect the selection of the substrain replicating in the animal model. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Development of a Sigma-2 Receptor affinity filter through a Monte Carlo based QSAR analysis.

PubMed

Rescifina, Antonio; Floresta, Giuseppe; Marrazzo, Agostino; Parenti, Carmela; Prezzavento, Orazio; Nastasi, Giovanni; Dichiara, Maria; Amata, Emanuele

2017-08-30

For the first time in sigma-2 (σ 2 ) receptor field, a quantitative structure-activity relationship (QSAR) model has been built using pK i values of the whole set of known selective σ 2 receptor ligands (548 compounds), taken from the Sigma-2 Receptor Selective Ligands Database (S2RSLDB) (http://www.researchdsf.unict.it/S2RSLDB/), through the Monte Carlo technique and employing the software CORAL. The model has been developed by using a large and structurally diverse set of compounds, allowing for a prediction of different populations of chemical compounds endpoint (σ 2 receptor pK i ). The statistical quality reached, suggested that model for pK i determination is robust and possesses a satisfactory predictive potential. The statistical quality is high for both visible and invisible sets. The screening of the FDA approved drugs, external to our dataset, suggested that sixteen compounds might be repositioned as σ 2 receptor ligands (predicted pK i ≥8). A literature check showed that six of these compounds have already been tested for affinity at σ 2 receptor and, of these, two (Flunarizine and Terbinafine) have shown an experimental σ 2 receptor pK i >7. This suggests that this QSAR model may be used as focusing screening filter in order to prospectively find or repurpose new drugs with high affinity for the σ 2 receptor, and overall allowing for an enhanced hit rate respect to a random screening. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

Quantitative structure–activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods

PubMed Central

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure–activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7−7−1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure–activity relationship model suggested is robust and satisfactory. PMID:26600858

The electrostatics of VDAC: implications for selectivity and gating.

PubMed

Choudhary, Om P; Ujwal, Rachna; Kowallis, William; Coalson, Rob; Abramson, Jeff; Grabe, Michael

2010-02-26

The voltage-dependent anion channel (VDAC) is the major pathway mediating the transfer of metabolites and ions across the mitochondrial outer membrane. Two hallmarks of the channel in the open state are high metabolite flux and anion selectivity, while the partially closed state blocks metabolites and is cation selective. Here we report the results from electrostatics calculations carried out on the recently determined high-resolution structure of murine VDAC1 (mVDAC1). Poisson-Boltzmann calculations show that the ion transfer free energy through the channel is favorable for anions, suggesting that mVDAC1 represents the open state. This claim is buttressed by Poisson-Nernst-Planck calculations that predict a high single-channel conductance indicative of the open state and an anion selectivity of 1.75--nearly a twofold selectivity for anions over cations. These calculations were repeated on mutant channels and gave selectivity changes in accord with experimental observations. We were then able to engineer an in silico mutant channel with three point mutations that converted mVDAC1 into a channel with a preference for cations. Finally, we investigated two proposals for how the channel gates between the open and the closed state. Both models involve the movement of the N-terminal helix, but neither motion produced the observed voltage sensitivity, nor did either model result in a cation-selective channel, which is observed experimentally. Thus, we were able to rule out certain models for channel gating, but the true motion has yet to be determined. Copyright (c) 2009. Elsevier Ltd. All rights reserved.

Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

PubMed

Jin, Mingwu; Deng, Weishu

2018-05-15

There is a spectrum of the progression from healthy control (HC) to mild cognitive impairment (MCI) without conversion to Alzheimer's disease (AD), to MCI with conversion to AD (cMCI), and to AD. This study aims to predict the different disease stages using brain structural information provided by magnetic resonance imaging (MRI) data. The neighborhood component analysis (NCA) is applied to select most powerful features for prediction. The ensemble decision tree classifier is built to predict which group the subject belongs to. The best features and model parameters are determined by cross validation of the training data. Our results show that 16 out of a total of 429 features were selected by NCA using 240 training subjects, including MMSE score and structural measures in memory-related regions. The boosting tree model with NCA features can achieve prediction accuracy of 56.25% on 160 test subjects. Principal component analysis (PCA) and sequential feature selection (SFS) are used for feature selection, while support vector machine (SVM) is used for classification. The boosting tree model with NCA features outperforms all other combinations of feature selection and classification methods. The results suggest that NCA be a better feature selection strategy than PCA and SFS for the data used in this study. Ensemble tree classifier with boosting is more powerful than SVM to predict the subject group. However, more advanced feature selection and classification methods or additional measures besides structural MRI may be needed to improve the prediction performance. Copyright © 2018 Elsevier B.V. All rights reserved.

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

NASA Astrophysics Data System (ADS)

Zhang, Yucheng; Oikonomou, Anastasia; Wong, Alexander; Haider, Masoom A.; Khalvati, Farzad

2017-04-01

Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative features from radiological images. Radiomic features have been shown to provide prognostic value in predicting clinical outcomes in several studies. However, several challenges including feature redundancy, unbalanced data, and small sample sizes have led to relatively low predictive accuracy. In this study, we explore different strategies for overcoming these challenges and improving predictive performance of radiomics-based prognosis for non-small cell lung cancer (NSCLC). CT images of 112 patients (mean age 75 years) with NSCLC who underwent stereotactic body radiotherapy were used to predict recurrence, death, and recurrence-free survival using a comprehensive radiomics analysis. Different feature selection and predictive modeling techniques were used to determine the optimal configuration of prognosis analysis. To address feature redundancy, comprehensive analysis indicated that Random Forest models and Principal Component Analysis were optimum predictive modeling and feature selection methods, respectively, for achieving high prognosis performance. To address unbalanced data, Synthetic Minority Over-sampling technique was found to significantly increase predictive accuracy. A full analysis of variance showed that data endpoints, feature selection techniques, and classifiers were significant factors in affecting predictive accuracy, suggesting that these factors must be investigated when building radiomics-based predictive models for cancer prognosis.

Toward the definition of stereochemical requirements for MT2-selective antagonists and partial agonists by studying 4-phenyl-2-propionamidotetralin derivatives.

PubMed

Bedini, Annalida; Lucarini, Simone; Spadoni, Gilberto; Tarzia, Giorgio; Scaglione, Francesco; Dugnani, Silvana; Pannacci, Marilou; Lucini, Valeria; Carmi, Caterina; Pala, Daniele; Rivara, Silvia; Mor, Marco

2011-12-22

New derivatives of 4-phenyl-2-propionamidotetralin (4-P-PDOT) were prepared and tested on cloned MT1 and MT2 receptors, with the purpose of merging previously reported pharmacophores for nonselective agonists and for MT2-selective antagonists. A 8-methoxy group increases binding affinity of both (±)-cis- and (±)-trans-4-P-PDOT, and it can be bioisosterically replaced by a bromine. Conformational analysis of 8-methoxy-4-P-PDOT by molecular dynamics, supported by NMR data, revealed an energetically favored conformation for the (2S,4S)-cis isomer and a less favorable conformation for the (2R,4S)-trans one, fulfilling the requirements of a pharmacophore model for nonselective melatonin receptor agonists. A new superposition model, including features characteristic of MT2-selective antagonists, suggests that MT1/MT2 agonists and MT2 antagonists can share the same arrangement for their pharmacophoric elements. The model correctly predicted the eutomers of (±)-cis- and (±)-trans-4-P-PDOT. The model was validated by preparing three dihydronaphthalene derivatives, either able or not able to reproduce the putative active conformation of 4-P-PDOT.

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

USGS Publications Warehouse

Muller, Benjamin J.; Cade, Brian S.; Schwarzkoph, Lin

2018-01-01

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads (Rhinella marina) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

Natural allelic variations of xenobiotic-metabolizing enzymes affect sexual dimorphism in Oryzias latipes.

PubMed

Katsumura, Takafumi; Oda, Shoji; Nakagome, Shigeki; Hanihara, Tsunehiko; Kataoka, Hiroshi; Mitani, Hiroshi; Kawamura, Shoji; Oota, Hiroki

2014-12-22

Sexual dimorphisms, which are phenotypic differences between males and females, are driven by sexual selection. Interestingly, sexually selected traits show geographical variations within species despite strong directional selective pressures. This paradox has eluded many evolutionary biologists for some time, and several models have been proposed (e.g. 'indicator model' and 'trade-off model'). However, disentangling which of these theories explains empirical patterns remains difficult, because genetic polymorphisms that cause variation in sexual differences are still unknown. In this study, we show that polymorphisms in cytochrome P450 (CYP) 1B1, which encodes a xenobiotic-metabolizing enzyme, are associated with geographical differences in sexual dimorphism in the anal fin morphology of medaka fish (Oryzias latipes). Biochemical assays and genetic cross experiments show that high- and low-activity CYP1B1 alleles enhanced and declined sex differences in anal fin shapes, respectively. Behavioural and phylogenetic analyses suggest maintenance of the high-activity allele by sexual selection, whereas the low-activity allele possibly has experienced positive selection due to by-product effects of CYP1B1 in inferred ancestral populations. The present data can elucidate evolutionary mechanisms behind genetic variations in sexual dimorphism and indicate trade-off interactions between two distinct mechanisms acting on the two alleles with pleiotropic effects of xenobiotic-metabolizing enzymes. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

PubMed

Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

2003-11-01

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

Modeling Sexual Selection in Túngara Frog and Rationality of Mate Choice.

PubMed

Vargas Bernal, Esteban; Sanabria Malagon, Camilo

2017-12-01

The males of the species of frogs Engystomops pustulosus produce simple and complex calls to lure females, as a way of intersexual selection. Complex calls lead males to a greater reproductive success than what simple calls do. However, the complex calls are also more attractive to their main predator, the bat Trachops cirrhosus. Therefore, as M. Ryan suggests in (The túngara frog: a study in sexual selection and communication. University of Chicago Press, Chicago, 1985), the complexity of the calls lets the frogs keep a trade-off between reproductive success and predation. In this paper, we verify this trade-off from the perspective of game theory. We first model the proportion of simple calls as a symmetric game of two strategies. We also model the effect of adding a third strategy, males that keep quiet and intercept females, which would play a role of intrasexual selection. Under the assumption that the decision of the males takes into account this trade-off between reproductive success and predation, our model reproduces the observed behavior reported in the literature with minimal assumption on the parameters. From the model with three strategies, we verify that the quiet strategy could only coexists with the simple and complex strategies if the rate at which quiet males intercept females is high, which explains the rarity of the quiet strategy. We conclude that the reproductive strategy of the male frog E. pustulosus is rational.

Pharmacophore modeling for identification of anti-IGF-1R drugs and in-vitro validation of fulvestrant as a potential inhibitor

PubMed Central

Hanif, Rumeza; Jabeen, Ishrat; Mansoor, Qaisar; Ismail, Muhammad

2018-01-01

Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE). The best model consisted of three pharmacophore features: aromatic hydrophobic (HyD/Aro), hydrophobic (HyD) and hydrogen bond acceptor (HBA). This model was validated against World drug bank (WDB) database screening to identify 189 hits with the required pharmacophore features and was further screened by using Lipinski positive compounds. Finally, the most effective drug, fulvestrant, was selected. Fulvestrant is a selective estrogen receptor down regulator (SERD). This inhibitor was further studied by using both in-silico and in-vitro approaches that showed the targeted effect of fulvestrant in ER+ MCF-7 cells. Results suggested that fulvestrant has selective cytotoxic effect and a dose dependent response on IRS-1, IGF-1R, PDZK1 and ER-α in MCF-7 cells. PDZK1 can be an important inhibitory target using fulvestrant because it directly regulates IGF-1R. PMID:29787591

Pharmacophore modeling for identification of anti-IGF-1R drugs and in-vitro validation of fulvestrant as a potential inhibitor.

PubMed

Khalid, Samra; Hanif, Rumeza; Jabeen, Ishrat; Mansoor, Qaisar; Ismail, Muhammad

2018-01-01

Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE). The best model consisted of three pharmacophore features: aromatic hydrophobic (HyD/Aro), hydrophobic (HyD) and hydrogen bond acceptor (HBA). This model was validated against World drug bank (WDB) database screening to identify 189 hits with the required pharmacophore features and was further screened by using Lipinski positive compounds. Finally, the most effective drug, fulvestrant, was selected. Fulvestrant is a selective estrogen receptor down regulator (SERD). This inhibitor was further studied by using both in-silico and in-vitro approaches that showed the targeted effect of fulvestrant in ER+ MCF-7 cells. Results suggested that fulvestrant has selective cytotoxic effect and a dose dependent response on IRS-1, IGF-1R, PDZK1 and ER-α in MCF-7 cells. PDZK1 can be an important inhibitory target using fulvestrant because it directly regulates IGF-1R.

Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

PubMed Central

Zhang, Jinming; Cavallari, Jennifer M; Fang, Shona C; Weisskopf, Marc G; Lin, Xihong; Mittleman, Murray A; Christiani, David C

2017-01-01

Background Environmental and occupational exposure to metals is ubiquitous worldwide, and understanding the hazardous metal components in this complex mixture is essential for environmental and occupational regulations. Objective To identify hazardous components from metal mixtures that are associated with alterations in cardiac autonomic responses. Methods Urinary concentrations of 16 types of metals were examined and ‘acceleration capacity’ (AC) and ‘deceleration capacity’ (DC), indicators of cardiac autonomic effects, were quantified from ECG recordings among 54 welders. We fitted linear mixed-effects models with least absolute shrinkage and selection operator (LASSO) to identify metal components that are associated with AC and DC. The Bayesian Information Criterion was used as the criterion for model selection procedures. Results Mercury and chromium were selected for DC analysis, whereas mercury, chromium and manganese were selected for AC analysis through the LASSO approach. When we fitted the linear mixed-effects models with ‘selected’ metal components only, the effect of mercury remained significant. Every 1 µg/L increase in urinary mercury was associated with −0.58 ms (−1.03, –0.13) changes in DC and 0.67 ms (0.25, 1.10) changes in AC. Conclusion Our study suggests that exposure to several metals is associated with impaired cardiac autonomic functions. Our findings should be replicated in future studies with larger sample sizes. PMID:28663305

Using Evolutionary Theory to Guide Mental Health Research.

PubMed

Durisko, Zachary; Mulsant, Benoit H; McKenzie, Kwame; Andrews, Paul W

2016-03-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating "normally" (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. © The Author(s) 2016.

Using Evolutionary Theory to Guide Mental Health Research

PubMed Central

Mulsant, Benoit H.; McKenzie, Kwame; Andrews, Paul W.

2016-01-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating “normally” (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. PMID:27254091

Sequential sensory and decision processing in posterior parietal cortex

PubMed Central

Ibos, Guilhem; Freedman, David J

2017-01-01

Decisions about the behavioral significance of sensory stimuli often require comparing sensory inference of what we are looking at to internal models of what we are looking for. Here, we test how neuronal selectivity for visual features is transformed into decision-related signals in posterior parietal cortex (area LIP). Monkeys performed a visual matching task that required them to detect target stimuli composed of conjunctions of color and motion-direction. Neuronal recordings from area LIP revealed two main findings. First, the sequential processing of visual features and the selection of target-stimuli suggest that LIP is involved in transforming sensory information into decision-related signals. Second, the patterns of color and motion selectivity and their impact on decision-related encoding suggest that LIP plays a role in detecting target stimuli by comparing bottom-up sensory inputs (what the monkeys were looking at) and top-down cognitive encoding inputs (what the monkeys were looking for). DOI: http://dx.doi.org/10.7554/eLife.23743.001 PMID:28418332

Selecting cockpit functions for speech I/O technology

NASA Technical Reports Server (NTRS)

Simpson, C. A.

1985-01-01

A general methodology for the initial selection of functions for speech generation and speech recognition technology is discussed. The SCR (Stimulus/Central-Processing/Response) compatibility model of Wickens et al. (1983) is examined, and its application is demonstrated for a particular cockpit display problem. Some limits of the applicability of that model are illustrated in the context of predicting overall pilot-aircraft system performance. A program of system performance measurement is recommended for the evaluation of candidate systems. It is suggested that no one measure of system performance can necessarily be depended upon to the exclusion of others. Systems response time, system accuracy, and pilot ratings are all important measures. Finally, these measures must be collected in the context of the total flight task environment.

Genomic signals of selection predict climate-driven population declines in a migratory bird.

PubMed

Bay, Rachael A; Harrigan, Ryan J; Underwood, Vinh Le; Gibbs, H Lisle; Smith, Thomas B; Ruegg, Kristen

2018-01-05

The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler ( Setophaga petechia ). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts. Copyright © 2018, American Association for the Advancement of Science.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

PubMed Central

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

Genetic drift and selection in many-allele range expansions.

PubMed

Weinstein, Bryan T; Lavrentovich, Maxim O; Möbius, Wolfram; Murray, Andrew W; Nelson, David R

2017-12-01

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colony's curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics without additional fitting. Our results suggest that the random walk model can act as a useful predictive tool for describing the evolutionary dynamics of range expansions composed of an arbitrary number of genotypes with different fitnesses.

Implications of sex-specific selection for the genetic basis of disease.

PubMed

Morrow, Edward H; Connallon, Tim

2013-12-01

Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.

Caffeine and Selective Adenosine Receptor Antagonists as New Therapeutic Tools for the Motivational Symptoms of Depression

PubMed Central

López-Cruz, Laura; Salamone, John D.; Correa, Mercè

2018-01-01

Major depressive disorder is one of the most common and debilitating psychiatric disorders. Some of the motivational symptoms of depression, such anergia (lack of self-reported energy) and fatigue are relatively resistant to traditional treatments such as serotonin uptake inhibitors. Thus, new pharmacological targets are being investigated. Epidemiological data suggest that caffeine consumption can have an impact on aspects of depressive symptomatology. Caffeine is a non-selective adenosine antagonist for A1/A2A receptors, and has been demonstrated to modulate behavior in classical animal models of depression. Moreover, selective adenosine receptor antagonists are being assessed for their antidepressant effects in animal studies. This review focuses on how caffeine and selective adenosine antagonists can improve different aspects of depression in humans, as well as in animal models. The effects on motivational symptoms of depression such as anergia, fatigue, and psychomotor slowing receive particular attention. Thus, the ability of adenosine receptor antagonists to reverse the anergia induced by dopamine antagonism or depletion is of special interest. In conclusion, although further studies are needed, it appears that caffeine and selective adenosine receptor antagonists could be therapeutic agents for the treatment of motivational dysfunction in depression. PMID:29910727

The Birth-Death-Mutation Process: A New Paradigm for Fat Tailed Distributions

PubMed Central

Maruvka, Yosef E.; Kessler, David A.; Shnerb, Nadav M.

2011-01-01

Fat tailed statistics and power-laws are ubiquitous in many complex systems. Usually the appearance of of a few anomalously successful individuals (bio-species, investors, websites) is interpreted as reflecting some inherent “quality” (fitness, talent, giftedness) as in Darwin's theory of natural selection. Here we adopt the opposite, “neutral”, outlook, suggesting that the main factor explaining success is merely luck. The statistics emerging from the neutral birth-death-mutation (BDM) process is shown to fit marvelously many empirical distributions. While previous neutral theories have focused on the power-law tail, our theory economically and accurately explains the entire distribution. We thus suggest the BDM distribution as a standard neutral model: effects of fitness and selection are to be identified by substantial deviations from it. PMID:22069453

Phenology of Scramble Polygyny in a Wild Population of Chrysolemid Beetles: The Opportunity for and the Strength of Sexual Selection

PubMed Central

Baena, Martha Lucía; Macías-Ordóñez, Rogelio

2012-01-01

Recent debate has highlighted the importance of estimating both the strength of sexual selection on phenotypic traits, and the opportunity for sexual selection. We describe seasonal fluctuations in mating dynamics of Leptinotarsa undecimlineata (Coleoptera: Chrysomelidae). We compared several estimates of the opportunity for, and the strength of, sexual selection and male precopulatory competition over the reproductive season. First, using a null model, we suggest that the ratio between observed values of the opportunity for sexual selections and their expected value under random mating results in unbiased estimates of the actual nonrandom mating behavior of the population. Second, we found that estimates for the whole reproductive season often misrepresent the actual value at any given time period. Third, mating differentials on male size and mobility, frequency of male fighting and three estimates of the opportunity for sexual selection provide contrasting but complementary information. More intense sexual selection associated to male mobility, but not to male size, was observed in periods with high opportunity for sexual selection and high frequency of male fights. Fourth, based on parameters of spatial and temporal aggregation of female receptivity, we describe the mating system of L. undecimlineata as a scramble mating polygyny in which the opportunity for sexual selection varies widely throughout the season, but the strength of sexual selection on male size remains fairly weak, while male mobility inversely covaries with mating success. We suggest that different estimates for the opportunity for, and intensity of, sexual selection should be applied in order to discriminate how different behavioral and demographic factors shape the reproductive dynamic of populations. PMID:22761675

Population genetics of mouse lemur vomeronasal receptors: current versus past selection and demographic inference.

PubMed

Hohenbrink, Philipp; Mundy, Nicholas I; Radespiel, Ute

2017-01-21

A major effort is underway to use population genetic approaches to identify loci involved in adaptation. One issue that has so far received limited attention is whether loci that show a phylogenetic signal of positive selection in the past also show evidence of ongoing positive selection at the population level. We address this issue using vomeronasal receptors (VRs), a diverse gene family in mammals involved in intraspecific communication and predator detection. In mouse lemurs, we previously demonstrated that both subfamilies of VRs (V1Rs and V2Rs) show a strong signal of directional selection in interspecific analyses. We predicted that ongoing sexual selection and/or co-evolution with predators may lead to current directional or balancing selection on VRs. Here, we re-sequence 17 VRs and perform a suite of selection and demographic analyses in sympatric populations of two species of mouse lemurs (Microcebus murinus and M. ravelobensis) in northwestern Madagascar. M. ravelobensis had consistently higher genetic diversity at VRs than M. murinus. In general, we find little evidence for positive selection, with most loci evolving under purifying selection and one locus even showing evidence of functional loss in M. ravelobensis. However, a few loci in M. ravelobensis show potential evidence of positive selection. Using mismatch distributions and expansion models, we infer a more recent colonisation of the habitat by M. murinus than by M. ravelobensis, which most likely speciated in this region earlier on. These findings suggest that the analysis of VR variation is useful in inferring demographic and phylogeographic history of mouse lemurs. In conclusion, this study reveals a substantial heterogeneity over time in selection on VR loci, suggesting that VR evolution is episodic.

Modeling conflict and error in the medial frontal cortex.

PubMed

Mayer, Andrew R; Teshiba, Terri M; Franco, Alexandre R; Ling, Josef; Shane, Matthew S; Stephen, Julia M; Jung, Rex E

2012-12-01

Despite intensive study, the role of the dorsal medial frontal cortex (dMFC) in error monitoring and conflict processing remains actively debated. The current experiment manipulated conflict type (stimulus conflict only or stimulus and response selection conflict) and utilized a novel modeling approach to isolate error and conflict variance during a multimodal numeric Stroop task. Specifically, hemodynamic response functions resulting from two statistical models that either included or isolated variance arising from relatively few error trials were directly contrasted. Twenty-four participants completed the task while undergoing event-related functional magnetic resonance imaging on a 1.5-Tesla scanner. Response times monotonically increased based on the presence of pure stimulus or stimulus and response selection conflict. Functional results indicated that dMFC activity was present during trials requiring response selection and inhibition of competing motor responses, but absent during trials involving pure stimulus conflict. A comparison of the different statistical models suggested that relatively few error trials contributed to a disproportionate amount of variance (i.e., activity) throughout the dMFC, but particularly within the rostral anterior cingulate gyrus (rACC). Finally, functional connectivity analyses indicated that an empirically derived seed in the dorsal ACC/pre-SMA exhibited strong connectivity (i.e., positive correlation) with prefrontal and inferior parietal cortex but was anti-correlated with the default-mode network. An empirically derived seed from the rACC exhibited the opposite pattern, suggesting that sub-regions of the dMFC exhibit different connectivity patterns with other large scale networks implicated in internal mentations such as daydreaming (default-mode) versus the execution of top-down attentional control (fronto-parietal). Copyright © 2011 Wiley Periodicals, Inc.

Breeding novel solutions in the brain: a model of Darwinian neurodynamics.

PubMed

Szilágyi, András; Zachar, István; Fedor, Anna; de Vladar, Harold P; Szathmáry, Eörs

2016-01-01

Background : The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods : We combine known components of the brain - recurrent neural networks (acting as attractors), the action selection loop and implicit working memory - to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results : We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions : Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.

Pharmacokinetics and Pharmacokinetic/Pharmacodynamic Modeling of Filgotinib (GLPG0634), a Selective JAK1 Inhibitor, in Support of Phase IIB Dose Selection.

PubMed

Namour, Florence; Diderichsen, Paul Matthias; Cox, Eugène; Vayssière, Béatrice; Van der Aa, Annegret; Tasset, Chantal; Van't Klooster, Gerben

2015-08-01

Filgotinib (GLPG0634) is a selective inhibitor of Janus kinase 1 (JAK1) currently in development for the treatment of rheumatoid arthritis and Crohn's disease. While less selective JAK inhibitors have shown long-term efficacy in treating inflammatory conditions, this was accompanied by dose-limiting side effects. Here, we describe the pharmacokinetics of filgotinib and its active metabolite in healthy volunteers and the use of pharmacokinetic-pharmacodynamic modeling and simulation to support dose selection for phase IIB in patients with rheumatoid arthritis. Two trials were conducted in healthy male volunteers. In the first trial, filgotinib was administered as single doses from 10 mg up to multiple daily doses of 200 mg. In the second trial, daily doses of 300 and 450 mg for 10 days were evaluated. Non-compartmental analysis was used to determine individual pharmacokinetic parameters for filgotinib and its metabolite. The overall pharmacodynamic activity for the two moieties was assessed in whole blood using interleukin-6-induced phosphorylation of signal-transducer and activator of transcription 1 as a biomarker for JAK1 activity. These data were used to conduct non-linear mixed-effects modeling to investigate a pharmacokinetic/pharmacodynamic relationship. Modeling and simulation on the basis of early clinical data suggest that the pharmacokinetics of filgotinib are dose proportional up to 200 mg, in agreement with observed data, and support that both filgotinib and its metabolite contribute to its pharmacodynamic effects. Simulation of biomarker response supports that the maximum pharmacodynamic effect is reached at a daily dose of 200 mg filgotinib. Based on these results, a daily dose range up to 200 mg has been selected for phase IIB dose-finding studies in patients with rheumatoid arthritis.

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

PubMed

Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

2018-01-01

Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

Natural selection reduced diversity on human y chromosomes.

PubMed

Wilson Sayres, Melissa A; Lohmueller, Kirk E; Nielsen, Rasmus

2014-01-01

The human Y chromosome exhibits surprisingly low levels of genetic diversity. This could result from neutral processes if the effective population size of males is reduced relative to females due to a higher variance in the number of offspring from males than from females. Alternatively, selection acting on new mutations, and affecting linked neutral sites, could reduce variability on the Y chromosome. Here, using genome-wide analyses of X, Y, autosomal and mitochondrial DNA, in combination with extensive population genetic simulations, we show that low observed Y chromosome variability is not consistent with a purely neutral model. Instead, we show that models of purifying selection are consistent with observed Y diversity. Further, the number of sites estimated to be under purifying selection greatly exceeds the number of Y-linked coding sites, suggesting the importance of the highly repetitive ampliconic regions. While we show that purifying selection removing deleterious mutations can explain the low diversity on the Y chromosome, we cannot exclude the possibility that positive selection acting on beneficial mutations could have also reduced diversity in linked neutral regions, and may have contributed to lowering human Y chromosome diversity. Because the functional significance of the ampliconic regions is poorly understood, our findings should motivate future research in this area.

Natural Selection Reduced Diversity on Human Y Chromosomes

PubMed Central

Wilson Sayres, Melissa A.; Lohmueller, Kirk E.; Nielsen, Rasmus

2014-01-01

The human Y chromosome exhibits surprisingly low levels of genetic diversity. This could result from neutral processes if the effective population size of males is reduced relative to females due to a higher variance in the number of offspring from males than from females. Alternatively, selection acting on new mutations, and affecting linked neutral sites, could reduce variability on the Y chromosome. Here, using genome-wide analyses of X, Y, autosomal and mitochondrial DNA, in combination with extensive population genetic simulations, we show that low observed Y chromosome variability is not consistent with a purely neutral model. Instead, we show that models of purifying selection are consistent with observed Y diversity. Further, the number of sites estimated to be under purifying selection greatly exceeds the number of Y-linked coding sites, suggesting the importance of the highly repetitive ampliconic regions. While we show that purifying selection removing deleterious mutations can explain the low diversity on the Y chromosome, we cannot exclude the possibility that positive selection acting on beneficial mutations could have also reduced diversity in linked neutral regions, and may have contributed to lowering human Y chromosome diversity. Because the functional significance of the ampliconic regions is poorly understood, our findings should motivate future research in this area. PMID:24415951

Preschoolers' encoding of rational actions: the role of task features and verbal information.

PubMed

Pfeifer, Caroline; Elsner, Birgit

2013-10-01

In the current study, we first investigated whether preschoolers imitate selectively across three imitation tasks. Second, we examined whether preschoolers' selective imitation is influenced by differences in the modeled actions and/or by the situational context. Finally, we investigated how verbal cues given by the model affect preschoolers' imitation. Participants (3- to 5-year-olds) watched an adult performing an unusual action in three imitation tasks (touch light, house, and obstacle). In two conditions, the model either was or was not restricted by situational constraints. In addition, the model verbalized either the goal that was to be achieved, the movement, or none of the action components. Preschoolers always acted on the objects without constraints. Results revealed differences in preschoolers' selective imitation across the tasks. In the house task, they showed the selective imitation pattern that has been interpreted as rational, imitating the unusual action more often in the no-constraint condition than in the constraint condition. In contrast, in the touch light task, preschoolers imitated the unusual head touch irrespective of the model's constraints or of the verbal cues that had been presented. Finally, in the obstacle task, children mostly emulated the observed goal irrespective of the presence of the constraint, but they increased their imitation of the unusual action when the movement had been emphasized. Overall, our data suggest that preschoolers adjust their imitative behavior to context-specific information about objects, actions, and their interpretations of the model's intention to teach something. Copyright © 2012 Elsevier Inc. All rights reserved.

The host dark matter haloes of [O II] emitters at 0.5 < z < 1.5

NASA Astrophysics Data System (ADS)

Gonzalez-Perez, V.; Comparat, J.; Norberg, P.; Baugh, C. M.; Contreras, S.; Lacey, C.; McCullagh, N.; Orsi, A.; Helly, J.; Humphries, J.

2018-03-01

Emission line galaxies (ELGs) are used in several ongoing and upcoming surveys (SDSS-IV/eBOSS, DESI) as tracers of the dark matter distribution. Using a new galaxy formation model, we explore the characteristics of [O II] emitters, which dominate optical ELG selections at z ≃ 1. Model [O II] emitters at 0.5 < z < 1.5 are selected to mimic the DEEP2, VVDS, eBOSS and DESI surveys. The luminosity functions of model [O II] emitters are in reasonable agreement with observations. The selected [O II] emitters are hosted by haloes with Mhalo ≥ 1010.3h-1M⊙, with ˜90 per cent of them being central star-forming galaxies. The predicted mean halo occupation distributions of [O II] emitters have a shape typical of that inferred for star-forming galaxies, with the contribution from central galaxies, < N > _{[O II] cen}, being far from the canonical step function. The < N > _{[O II] cen}} can be described as the sum of an asymmetric Gaussian for discs and a step function for spheroids, which plateau below unity. The model [O II] emitters have a clustering bias close to unity, which is below the expectations for eBOSS and DESI ELGs. At z ˜ 1, a comparison with observed g-band-selected galaxy, which is expected to be dominated by [O II] emitters, indicates that our model produces too few [O II] emitters that are satellite galaxies. This suggests the need to revise our modelling of hot gas stripping in satellite galaxies.

[Different wavelengths selection methods for identification of early blight on tomato leaves by using hyperspectral imaging technique].

PubMed

Cheng, Shu-Xi; Xie, Chuan-Qi; Wang, Qiao-Nan; He, Yong; Shao, Yong-Ni

2014-05-01

Identification of early blight on tomato leaves by using hyperspectral imaging technique based on different effective wavelengths selection methods (successive projections algorithm, SPA; x-loading weights, x-LW; gram-schmidt orthogonaliza-tion, GSO) was studied in the present paper. Hyperspectral images of seventy healthy and seventy infected tomato leaves were obtained by hyperspectral imaging system across the wavelength range of 380-1023 nm. Reflectance of all pixels in region of interest (ROI) was extracted by ENVI 4. 7 software. Least squares-support vector machine (LS-SVM) model was established based on the full spectral wavelengths. It obtained an excellent result with the highest identification accuracy (100%) in both calibration and prediction sets. Then, EW-LS-SVM and EW-LDA models were established based on the selected wavelengths suggested by SPA, x-LW and GSO, respectively. The results showed that all of the EW-LS-SVM and EW-LDA models performed well with the identification accuracy of 100% in EW-LS-SVM model and 100%, 100% and 97. 83% in EW-LDA model, respectively. Moreover, the number of input wavelengths of SPA-LS-SVM, x-LW-LS-SVM and GSO-LS-SVM models were four (492, 550, 633 and 680 nm), three (631, 719 and 747 nm) and two (533 and 657 nm), respectively. Fewer input variables were beneficial for the development of identification instrument. It demonstrated that it is feasible to identify early blight on tomato leaves by using hyperspectral imaging, and SPA, x-LW and GSO were effective wavelengths selection methods.

Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection

PubMed Central

Hsieh, PingHsun; Veeramah, Krishna R.; Lachance, Joseph; Tishkoff, Sarah A.; Wall, Jeffrey D.; Hammer, Michael F.; Gutenkunst, Ryan N.

2016-01-01

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 yr ago. We also find that bidirectional asymmetric gene flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors. PMID:26888263

Switches in Genomic GC Content Drive Shifts of Optimal Codons under Sustained Selection on Synonymous Sites

PubMed Central

Sun, Yu; Tamarit, Daniel

2017-01-01

Abstract The major codon preference model suggests that codons read by tRNAs in high concentrations are preferentially utilized in highly expressed genes. However, the identity of the optimal codons differs between species although the forces driving such changes are poorly understood. We suggest that these questions can be tackled by placing codon usage studies in a phylogenetic framework and that bacterial genomes with extreme nucleotide composition biases provide informative model systems. Switches in the background substitution biases from GC to AT have occurred in Gardnerella vaginalis (GC = 32%), and from AT to GC in Lactobacillus delbrueckii (GC = 62%) and Lactobacillus fermentum (GC = 63%). We show that despite the large effects on codon usage patterns by these switches, all three species evolve under selection on synonymous sites. In G. vaginalis, the dramatic codon frequency changes coincide with shifts of optimal codons. In contrast, the optimal codons have not shifted in the two Lactobacillus genomes despite an increased fraction of GC-ending codons. We suggest that all three species are in different phases of an on-going shift of optimal codons, and attribute the difference to a stronger background substitution bias and/or longer time since the switch in G. vaginalis. We show that comparative and correlative methods for optimal codon identification yield conflicting results for genomes in flux and discuss possible reasons for the mispredictions. We conclude that switches in the direction of the background substitution biases can drive major shifts in codon preference patterns even under sustained selection on synonymous codon sites. PMID:27540085

A new perspective on the perceptual selectivity of attention under load.

PubMed

Giesbrecht, Barry; Sy, Jocelyn; Bundesen, Claus; Kyllingsbaek, Søren

2014-05-01

The human attention system helps us cope with a complex environment by supporting the selective processing of information relevant to our current goals. Understanding the perceptual, cognitive, and neural mechanisms that mediate selective attention is a core issue in cognitive neuroscience. One prominent model of selective attention, known as load theory, offers an account of how task demands determine when information is selected and an account of the efficiency of the selection process. However, load theory has several critical weaknesses that suggest that it is time for a new perspective. Here we review the strengths and weaknesses of load theory and offer an alternative biologically plausible computational account that is based on the neural theory of visual attention. We argue that this new perspective provides a detailed computational account of how bottom-up and top-down information is integrated to provide efficient attentional selection and allocation of perceptual processing resources. © 2014 New York Academy of Sciences.

Adolescent Friendships, BMI, and Physical Activity: Untangling Selection and Influence Through Longitudinal Social Network Analysis

PubMed Central

Simpkins, Sandra D.; Schaefer, David R.; Price, Chara D.; Vest, Andrea E.

2012-01-01

Bioecological theory suggests that adolescents’ health is a result of selection and socialization processes occurring between adolescents and their microsettings. This study examines the association between adolescents’ friends and health using a social network model and data from the National Longitudinal Study of Adolescent Health (N = 1,896, mean age = 15.97 years). Results indicated evidence of friend influence on BMI and physical activity. Friendships were more likely among adolescents who engaged in greater physical activity and who were similar to one another in BMI and physical activity. These effects emerged after controlling for alternative friend selection factors, such as endogenous social network processes and propinquity through courses and activities. Some selection effects were moderated by gender, popularity, and reciprocity. PMID:24222971

Scale-Dependent Habitat Selection and Size-Based Dominance in Adult Male American Alligators

PubMed Central

Strickland, Bradley A.; Vilella, Francisco J.; Belant, Jerrold L.

2016-01-01

Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators (Alligator mississippiensis; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem. PMID:27588947

Scale-dependent habitat selection and size-based dominance in adult male American alligators

USGS Publications Warehouse

Strickland, Bradley A.; Vilella, Francisco; Belant, Jerrold L.

2016-01-01

Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators (Alligator mississippiensis; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem.

43.1 GENETIC INSIGHTS LEAD TO DISCOVERY OF SELECTIVE ACTIVATORS OF MGLU1 AND MGLU3 METABOTROPIC GLUTAMATE RECEPTORS AS POTENTIAL TREATMENTS FOR SCHIZOPHRENIA

PubMed Central

Conn, P Jeffrey; Yohn, Samantha; Stansley, Branden; Foster, Dan; Plumley, Hyekyung; Lindsley, Craig

2018-01-01

Abstract Background A large number of clinical and preclinical studies suggest that dysfunction at synapses for the excitatory neurotransmitter glutamate may play a critical role in the pathophysiological changes that underlie each of the major symptom clusters observed in schizophrenia patients. Interestingly, recent genetic studies identified multiple nonsynonymous single nucleotide polymorphisms (SNPs) in the human genes encoding two specific subtypes of metabotropic glutamate (mGlu) receptors that are associated with schizophrenia. These include GRM1 and GRM3, the genes encoding for the mGlu1 and mGlu3 receptor subtypes respectively. Furthermore, postmortem studies suggest that expression of these mGlu receptor subtypes is altered brains of schizophrenia patients compared to controls. Mutations in GRM1 were identified a range of schizophrenia patients, whereas SNPs in the human gene encoding mGlu3 (GRM3) are selectively associated with poor performance on cognitive tests that are dependent on function of the prefrontal cortex (PFC) and hippocampus. These studies raise the possibility that disrupted signaling of mGlu1 and/or mGlu3 could contribute to the symptoms of schizophrenia and that selective modulators of these receptors could provide a novel approach to treatment of this disorder. Methods Wild-type and mutant forms of mGlu receptors were expressed in cell lines and used for discovery and optimization of highly selective positive allosteric modulators (PAMs) of mGlu1 and mGlu3. Optimized mGlu1 and mGlu3 PAMs were then used along with mouse genetic studies to evaluate the roles of these receptors in specific basal ganglia and forebrain circuits that have been implicated in schizophrenia. Finally, these compounds were used in animal models to assess potential efficacy in rodent models that are relevant for reducing positive, negative, and cognitive symptoms that are observed in schizophrenia patients. Results GRM1 mutations associated with schizophrenia were found to reduce mGlu1 signaling, suggesting that loss of function of this receptor could contribute to symptoms associated with schizophrenia. Furthermore, we found that highly selective mGlu1 PAMs reverse deficits in mGlu1 signaling observed in these mutant receptors, induced a profound reduction in dopamine release in striatal areas implicated in schizophrenia, and have robust antipsychotic-like effects that are mediated by localized inhibition of dopamine release in striatum. In contrast to existing antipsychotic medications, selective mGlu1 PAMs also improve motivation and reduce anhedonia in animal models. Interestingly, selective mGlu3 PAMs have multiple effects in the prefrontal cortex and hippocampus that would be expected to improve cognitive function. Consistent with this, highly selective mGlu3 PAMs have robust cognition-enhancing effects in rodent models that are relevant for the cognitive deficits observed in schizophrenia patients. Discussion These studies provide exciting new evidence that highly selective activators of two glutamate receptors identified in human genetic studies have potential utility in treatment of positive (mGLu1), negative (mGlu1), and cognitive (mGlu3) symptoms of schizophrenia patients. Furthermore, the novel mGlu1 and mGlu3 PAMs discovered in these studies provide excellent drug leads for further optimization and ultimate clinical testing.

Modeling spring habitat requirements of the endangered brown eared pheasant Crossoptilon mantchuricum in the Huanglong Mountains, Shaanxi Province, China.

PubMed

Li, Hongqun; Yue, Bisong; Lian, Zhenmin; Zhao, Hongfeng; Zhao, Delong; Xiao, Xiangming

2012-09-01

A detailed understanding of the habitat needs of brown eared pheasants (Crossoptilon mantchuricum) is essential for conserving the species. We carried out field surveys in the Huanglong Mountains of Shaanxi Province, China, from March to June in 2007 and 2008. We arrayed a total of 206 grid plots (200 × 200 m) along transects in 2007 and 2008 and quantified a suite of environmental variables for each one. In the optimal logistic regression model, the most important variables for brown eared pheasants were slope degree, tree cover, distance to nearest water, cover and depth of fallen leaves. Hosmer and Leweshow goodness-of-fit tests explained that logistic models for the species were good fits. The model suggested that spring habitat selection of the brown eared pheasant was negatively related to distance to nearest water and slope degree, and positively to cover of trees and cover and depth of fallen leaves. In addition, the observed detected and undetected grids in 2007 did not show significant differences with predictions based on the model. These results showed that the model could well predict the habitat selection of brown eared pheasants. Based on these predictive models, we suggest that habitat management plans incorporating this new information can now focus more effectively on restrictions on the number of tourists entering the nature reserve, prohibition of firewood collection, livestock grazing, and medicinal plant harvesting by local residents in the core areas, protection of mixed forest and sources of the permanent water in the reserve, and use of alternatives to firewood.

A Simulation Modeling Approach Method Focused on the Refrigerated Warehouses Using Design of Experiment

NASA Astrophysics Data System (ADS)

Cho, G. S.

2017-09-01

For performance optimization of Refrigerated Warehouses, design parameters are selected based on the physical parameters such as number of equipment and aisles, speeds of forklift for ease of modification. This paper provides a comprehensive framework approach for the system design of Refrigerated Warehouses. We propose a modeling approach which aims at the simulation optimization so as to meet required design specifications using the Design of Experiment (DOE) and analyze a simulation model using integrated aspect-oriented modeling approach (i-AOMA). As a result, this suggested method can evaluate the performance of a variety of Refrigerated Warehouses operations.

Methods of the working processes modelling of an internal combustion engine by an ANSYS IC Engine module

NASA Astrophysics Data System (ADS)

Kurchatkin, I. V.; Gorshkalev, A. A.; Blagin, E. V.

2017-01-01

This article deals with developed methods of the working processes modelling in the combustion chamber of an internal combustion engine (ICE). Methods includes description of the preparation of a combustion chamber 3-d model, setting of the finite-element mesh, boundary condition setting and solution customization. Aircraft radial engine M-14 was selected for modelling. The cycle of cold blowdown in the ANSYS IC Engine software was carried out. The obtained data were compared to results of known calculation methods. A method of engine’s induction port improvement was suggested.

Ready! Aim! Fire! targeting the right medical science journal.

PubMed

Hardman, Timothy C; Serginson, James M

2017-09-01

Inadvertently submitting a paper to a journal that is unlikely to publish it is a waste of resources and ultimately delays dissemination of one's research. A high proportion of manuscripts are rejected by their author's first-choice journal. The aim of the present work was to review guidance provided within the literature for journal selection that might minimize the chance of manuscript rejection. We also consider papers that encompass more than one main medical science and describe the selection process that we used with a paper that was published in Cardiovascular Endocrinology . A database search (Embase, PubMed and Medworm) was performed for all articles published in the scientific literature providing guidance on journal selection. Articles were identified that either had journal selection as their principal topic or included journal selection as part of a broader discussion of publishing. The relative performance of four free-to-use, web-based applications that claim to provide guidance on journal selection was compared. The searches identified 286 hits, of which 249 were in English. Of these papers, 16 discussed journal selection and a further 10 articles were identified from citations within the original 16 articles. Only one article described a comprehensive model for submission decision-making. Identification of appropriate candidate journals by various web-based applications was erratic, with the Jane database providing the most robust suggestions. Our work suggests that little attention has been focused in the scientific literature on the mechanisms that authors use to select a journal for their work. Nevertheless, scientists for the most part seem to have a good sense of where their papers are most likely to be accepted. Beyond ensuring that a manuscript fulfils all the target journal's requirements, the literature suggests that it is important to have an objective view of the scientific contribution or 'value' of your work.

Ready! Aim! Fire! targeting the right medical science journal

PubMed Central

Serginson, James M.

2017-01-01

Objective Inadvertently submitting a paper to a journal that is unlikely to publish it is a waste of resources and ultimately delays dissemination of one’s research. A high proportion of manuscripts are rejected by their author’s first-choice journal. The aim of the present work was to review guidance provided within the literature for journal selection that might minimize the chance of manuscript rejection. We also consider papers that encompass more than one main medical science and describe the selection process that we used with a paper that was published in Cardiovascular Endocrinology. Methods A database search (Embase, PubMed and Medworm) was performed for all articles published in the scientific literature providing guidance on journal selection. Articles were identified that either had journal selection as their principal topic or included journal selection as part of a broader discussion of publishing. The relative performance of four free-to-use, web-based applications that claim to provide guidance on journal selection was compared. Results The searches identified 286 hits, of which 249 were in English. Of these papers, 16 discussed journal selection and a further 10 articles were identified from citations within the original 16 articles. Only one article described a comprehensive model for submission decision-making. Identification of appropriate candidate journals by various web-based applications was erratic, with the Jane database providing the most robust suggestions. Conclusion Our work suggests that little attention has been focused in the scientific literature on the mechanisms that authors use to select a journal for their work. Nevertheless, scientists for the most part seem to have a good sense of where their papers are most likely to be accepted. Beyond ensuring that a manuscript fulfils all the target journal’s requirements, the literature suggests that it is important to have an objective view of the scientific contribution or ‘value’ of your work. PMID:28884050

Intercohort density dependence drives brown trout habitat selection

NASA Astrophysics Data System (ADS)

Ayllón, Daniel; Nicola, Graciela G.; Parra, Irene; Elvira, Benigno; Almodóvar, Ana

2013-01-01

Habitat selection can be viewed as an emergent property of the quality and availability of habitat but also of the number of individuals and the way they compete for its use. Consequently, habitat selection can change across years due to fluctuating resources or to changes in population numbers. However, habitat selection predictive models often do not account for ecological dynamics, especially density dependent processes. In stage-structured population, the strength of density dependent interactions between individuals of different age classes can exert a profound influence on population trajectories and evolutionary processes. In this study, we aimed to assess the effects of fluctuating densities of both older and younger competing life stages on the habitat selection patterns (described as univariate and multivariate resource selection functions) of young-of-the-year, juvenile and adult brown trout Salmo trutta. We observed all age classes were selective in habitat choice but changed their selection patterns across years consistently with variations in the densities of older but not of younger age classes. Trout of an age increased selectivity for positions highly selected by older individuals when their density decreased, but this pattern did not hold when the density of younger age classes varied. It suggests that younger individuals are dominated by older ones but can expand their range of selected habitats when density of competitors decreases, while older trout do not seem to consider the density of younger individuals when distributing themselves even though they can negatively affect their final performance. Since these results may entail critical implications for conservation and management practices based on habitat selection models, further research should involve a wider range of river typologies and/or longer time frames to fully understand the patterns of and the mechanisms underlying the operation of density dependence on brown trout habitat selection.

Recommending blood glucose monitors, a pharmacy perspective.

PubMed

Carter, Alan

2007-03-01

Selection of what blood glucose monitoring system to utilize has become an issue for physicians, diabetes educators, pharmacists, and patients. The field of competing makes and models of blood glucose monitoring systems has become crowded, with manufacturers touting improvements in accuracy, ease of use/alternate site options, stored results capacity, software evaluation tools, and/or price point. Personal interviews of 12 pharmacists from community and academic practice settings about monitor preference, as well as results from a national survey of pharmacist recommendations, were compared to actual wholesale sales data to estimate the impact of such recommendations on final monitor selection by the patient. Accu-Chek monitors were recommended 34.65% of the time and represented 28.58% of sales, with a success rate of 82.48% of being the monitor selected. OneTouch monitors had 27.72% of recommendations but represented 31.43% of sales, indicating possible patient brand loyalty or formulary preference for that product. FreeStyle(R) monitors came in third for pharmacist recommendations and were selected by the patient 61.68% of the time when recommended. The category of "other monitor" choices was selected 60.89% of the time by patients given those suggestions. Included in the "other monitor" category was the new disposable monitor marketed as the Sidekick. Based on sales data provided, the Sidekick made up 2.87% of "other monitor" category sales, representing 68% of the "other monitor" segment. While patients frequently follow pharmacist monitoring system suggestions, the ultimate deciding factor is most often the final out-of-pocket cost to the patient. As a result, cost of supplies often becomes the most important determining factor in final monitor selection at the patient level. If the patient cannot afford to perform the recommended daily testing intervals, all other determining factors and suggestions become moot.

Topology in two dimensions. IV - CDM models with non-Gaussian initial conditions

NASA Astrophysics Data System (ADS)

Coles, Peter; Moscardini, Lauro; Plionis, Manolis; Lucchin, Francesco; Matarrese, Sabino; Messina, Antonio

1993-02-01

The results of N-body simulations with both Gaussian and non-Gaussian initial conditions are used here to generate projected galaxy catalogs with the same selection criteria as the Shane-Wirtanen counts of galaxies. The Euler-Poincare characteristic is used to compare the statistical nature of the projected galaxy clustering in these simulated data sets with that of the observed galaxy catalog. All the models produce a topology dominated by a meatball shift when normalized to the known small-scale clustering properties of galaxies. Models characterized by a positive skewness of the distribution of primordial density perturbations are inconsistent with the Lick data, suggesting problems in reconciling models based on cosmic textures with observations. Gaussian CDM models fit the distribution of cell counts only if they have a rather high normalization but possess too low a coherence length compared with the Lick counts. This suggests that a CDM model with extra large scale power would probably fit the available data.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

NASA Astrophysics Data System (ADS)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Eggspot number and sexual selection in the cichlid fish Astatotilapia burtoni.

PubMed

Henning, Frederico; Meyer, Axel

2012-01-01

Sexual selection on male coloration is one of the main mechanisms proposed to explain the explosive speciation rates in East African cichlid fish. True eggspots are color patterns characteristic of the most species-rich lineage of cichlids, the Haplochromini, and have been suggested to be causally related to the speciation processes. Eggspots are thought to have originated by sensory exploitation and subsequently gained several roles in sexual advertisement. However, for most of these functions the evidence is equivocal. In addition, the genetic architecture of this trait still is largely unknown. We conducted bidirectional selective breeding experiments for eggspot numbers in the model cichlid, Astatotilapia burtoni. After two generations, low lines responded significantly, whereas the high lines did not. Body size was both phenotypically and genotypically correlated with eggspot number and showed correlated response to selection. Males with higher numbers of eggspots were found to sire larger offspring. Despite the potential to act as honest indicators of fitness, the behavioral experiments showed no evidence of a role in either intra- or inter-sexual selection. Visual-based female preference was instead explained by courtship intensity. The evolution of this trait has been interpreted in light of adaptive theories of sexual selection, however the present and published results suggest the influence of non-adaptive factors such as sensory exploitation, environmental constraints and sexual antagonism.

Prey from the eyes of predators: Color discriminability of aposematic and mimetic butterflies from an avian visual perspective.

PubMed

Su, Shiyu; Lim, Matthew; Kunte, Krushnamegh

2015-11-01

Predation exerts strong selection on mimetic butterfly wing color patterns, which also serve other functions such as sexual selection. Therefore, specific selection pressures may affect the sexes and signal components differentially. We tested three predictions about the evolution of mimetic resemblance by comparing wing coloration of aposematic butterflies and their Batesian mimics: (a) females gain greater mimetic advantage than males and therefore are better mimics, (b) due to intersexual genetic correlations, sexually monomorphic mimics are better mimics than female-limited mimics, and (c) mimetic resemblance is better on the dorsal wing surface that is visible to predators in flight. Using a physiological model of avian color vision, we quantified mimetic resemblance from predators' perspective, which showed that female butterflies were better mimics than males. Mimetic resemblance in female-limited mimics was comparable to that in sexually monomorphic mimics, suggesting that intersexual genetic correlations did not constrain adaptive response to selection for female-limited mimicry. Mimetic resemblance on the ventral wing surface was better than that on the dorsal wing surface, implying stronger natural and sexual selection on ventral and dorsal surfaces, respectively. These results suggest that mimetic resemblance in butterfly mimicry rings has evolved under various selective pressures acting in a sex- and wing surface-specific manner. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Our Selections and Decisions: Inherent Features of the Nervous System?

NASA Astrophysics Data System (ADS)

Rösler, Frank

The chapter summarizes findings on the neuronal bases of decisionmaking. Taking the phenomenon of selection it will be explained that systems built only from excitatory and inhibitory neuron (populations) have the emergent property of selecting between different alternatives. These considerations suggest that there exists a hierarchical architecture with central selection switches. However, in such a system, functions of selection and decision-making are not localized, but rather emerge from an interaction of several participating networks. These are, on the one hand, networks that process specific input and output representations and, on the other hand, networks that regulate the relative activation/inhibition of the specific input and output networks. These ideas are supported by recent empirical evidence. Moreover, other studies show that rather complex psychological variables, like subjective probability estimates, expected gains and losses, prediction errors, etc., do have biological correlates, i.e., they can be localized in time and space as activation states of neural networks and single cells. These findings suggest that selections and decisions are consequences of an architecture which, seen from a biological perspective, is fully deterministic. However, a transposition of such nomothetic functional principles into the idiographic domain, i.e., using them as elements for comprehensive 'mechanistic' explanations of individual decisions, seems not to be possible because of principle limitations. Therefore, individual decisions will remain predictable by means of probabilistic models alone.

A comparison of progestin and androgen receptor binding using the CoMFA technique

NASA Astrophysics Data System (ADS)

Loughney, Deborah A.; Schwender, Charles F.

1992-12-01

A series of 48 steroids has been studied with the SYBYL QSAR module using Relative Binding Affinities (RBAs) to progesterone and androgen receptors obtained from the literature. Models for the progesterone and androgen data were developed. Both models show regions where sterics and electrostatics correlate to binding affinity but are different for androgen and progesterone which suggests differences possibly important for receptor selectivity. The progesterone model is more predictive than the androgen (predictive r2 of 0.725 vs. 0.545 for progesterone and androgen, respectively).

Evidences of local adaptation in quantitative traits in Prosopis alba (Leguminosae).

PubMed

Bessega, C; Pometti, C; Ewens, M; Saidman, B O; Vilardi, J C

2015-02-01

Signals of selection on quantitative traits can be detected by the comparison between the genetic differentiation of molecular (neutral) markers and quantitative traits, by multivariate extensions of the same model and by the observation of the additive covariance among relatives. We studied, by three different tests, signals of occurrence of selection in Prosopis alba populations over 15 quantitative traits: three economically important life history traits: height, basal diameter and biomass, 11 leaf morphology traits that may be related with heat-tolerance and physiological responses and spine length that is very important from silvicultural purposes. We analyzed 172 G1-generation trees growing in a common garden belonging to 32 open pollinated families from eight sampling sites in Argentina. The multivariate phenotypes differ significantly among origins, and the highest differentiation corresponded to foliar traits. Molecular genetic markers (SSR) exhibited significant differentiation and allowed us to provide convincing evidence that natural selection is responsible for the patterns of morphological differentiation. The heterogeneous selection over phenotypic traits observed suggested different optima in each population and has important implications for gene resource management. The results suggest that the adaptive significance of traits should be considered together with population provenance in breeding program as a crucial point prior to any selecting program, especially in Prosopis where the first steps are under development.

Bim-mediated apoptosis is not necessary for thymic negative selection to ubiquitous self-antigens.

PubMed

Hu, Qian; Sader, Alyssa; Parkman, Julia C; Baldwin, Troy A

2009-12-15

T cell education in the thymus is critical for establishing a functional, yet self-tolerant, T cell repertoire. Negative selection is a key process in enforcing self-tolerance. There are many questions that surround the mechanism of negative selection, but it is currently held that apoptosis initiated by Bim and/or Nur77 is critical for negative selection. Recent studies, however, have questioned the necessity of Bim in maintaining both central and peripheral T cell tolerance. To reconcile these apparently contradictory findings, we examined the role of Bim in negative selection in the well-characterized, physiological HY(cd4) mouse model. We found that while Bim expression was required for CD4(+)CD8(+) double-positive thymocyte apoptosis, it was not required for negative selection. Furthermore, Bim deficiency did not alter the frequency or affinity of male reactive cells that escape negative selection in an oligoclonal repertoire. Collectively, these studies indicate that negative selection occurs efficiently in the absence of apoptosis and suggest that the current paradigm of negative selection requiring apoptosis be revisited.

Model of the best-of-N nest-site selection process in honeybees.

PubMed

Reina, Andreagiovanni; Marshall, James A R; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N-1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

The re-emergence of felid camouflage with the decay of predator recognition in deer under relaxed selection

PubMed Central

Stankowich, Theodore; Coss, Richard G

2006-01-01

When a previously common predator disappears owing to local extinction, the strong source of natural selection on prey to visually recognize that predator becomes relaxed. At present, we do not know the extent to which recognition of a specific predator is generalized to similar looking predators or how a specific predator-recognition cue, such as coat pattern, degrades under prolonged relaxed selection. Using predator models, we show that deer exhibit a more rapid and stronger antipredator response to their current predator, the puma, than to a leopard displaying primitive rosettes similar to a locally extinct predator, an early jaguar. Presentation of a novel tiger with a striped coat engendered an intermediate speed of predator recognition and strength of antipredator behaviour. Responses to the leopard model slightly exceeded responses to a non-threatening deer model, suggesting that thousands of years of relaxed selection have led to the loss of recognition of the spotted coat as a jaguar-recognition cue, and that the spotted coat has regained its ability to camouflage the felid form. Our results shed light on the evolutionary arms race between adoption of camouflage to facilitate hunting and the ability of prey to quickly recognize predators by their formerly camouflaging patterns. PMID:17148247

Evaluating the influence of motor control on selective attention through a stochastic model: the paradigm of motor control dysfunction in cerebellar patient.

PubMed

Veneri, Giacomo; Federico, Antonio; Rufa, Alessandra

2014-01-01

Attention allows us to selectively process the vast amount of information with which we are confronted, prioritizing some aspects of information and ignoring others by focusing on a certain location or aspect of the visual scene. Selective attention is guided by two cognitive mechanisms: saliency of the image (bottom up) and endogenous mechanisms (top down). These two mechanisms interact to direct attention and plan eye movements; then, the movement profile is sent to the motor system, which must constantly update the command needed to produce the desired eye movement. A new approach is described here to study how the eye motor control could influence this selection mechanism in clinical behavior: two groups of patients (SCA2 and late onset cerebellar ataxia LOCA) with well-known problems of motor control were studied; patients performed a cognitively demanding task; the results were compared to a stochastic model based on Monte Carlo simulations and a group of healthy subjects. The analytical procedure evaluated some energy functions for understanding the process. The implemented model suggested that patients performed an optimal visual search, reducing intrinsic noise sources. Our findings theorize a strict correlation between the "optimal motor system" and the "optimal stimulus encoders."

Model of the best-of-N nest-site selection process in honeybees

NASA Astrophysics Data System (ADS)

Reina, Andreagiovanni; Marshall, James A. R.; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N -1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Some effects of quiet geomagnetic field changes upon values used for main field modeling

USGS Publications Warehouse

Campbell, W.H.

1987-01-01

The effects of three methods of data selection upon the assumed main field levels for geomagnetic observatory records used in main field modeling were investigated for a year of very low solar-terrestrial activity. The first method concerned the differences between the year's average of quiet day field values and the average of all values during the year. For H these differences were 2-3 gammas, for D they were -0.04 to -0.12???, for Z the differences were negligible. The second method of selection concerned the effects of the daytime internal Sq variations upon the daily mean values of field. The midnight field levels when the Sq currents were a minimum deviated from the daily mean levels by as much as 4-7 gammas in H and Z but were negligible for D. The third method of selection was designed to avoid the annual and semi-annual quiet level changes of field caused by the seasonal changes in the magnetosphere. Contributions from these changes were found to be as much as 4-7 gammas in quiet years and expected to be greater than 10 gammas in active years. Suggestions for improved methods of improved data selection in main field modeling are given. ?? 1987.

Modeling the effect of boost timing in murine irradiated sporozoite prime-boost vaccines

PubMed Central

Zhang, Min; Herrero, Miguel A.; Acosta, Francisco J.; Tsuji, Moriya

2018-01-01

Vaccination with radiation-attenuated sporozoites has been shown to induce CD8+ T cell-mediated protection against pre-erythrocytic stages of malaria. Empirical evidence suggests that successive inoculations often improve the efficacy of this type of vaccines. An initial dose (prime) triggers a specific cellular response, and subsequent inoculations (boost) amplify this response to create a robust CD8+ T cell memory. In this work we propose a model to analyze the effect of T cell dynamics on the performance of prime-boost vaccines. This model suggests that boost doses and timings should be selected according to the T cell response elicited by priming. Specifically, boosting during late stages of clonal contraction would maximize T cell memory production for vaccines using lower doses of irradiated sporozoites. In contrast, single-dose inoculations would be indicated for higher vaccine doses. Experimental data have been obtained that support theoretical predictions of the model. PMID:29329308

A comparative study of two communication models in HIV/AIDS coverage in selected Nigerian newspapers

PubMed Central

Okidu, Onjefu

2013-01-01

The current overriding thought in HIV/AIDS communication in developing countries is the need for a shift from the cognitive model, which emphasises the decision-making of the individual, to the activity model, which emphasises the context of the individual. In spite of the acknowledged media shift from the cognitive to the activity model in some developing countries, some HIV/AIDS communication scholars have felt otherwise. It was against this background that this study examined the content of some selected Nigerian newspapers to ascertain the attention paid to HIV/AIDS cognitive and activity information. Generally, the study found that Nigerian newspapers had shifted from the cognitive to the activity model of communication in their coverage of HIV/AIDS issues. The findings of the study seem inconsistent with the theoretical argument of some scholars that insufficient attention has been paid by mass media in developing countries to the activity model of HIV/AIDS communication. It is suggested that future research replicate the study for Nigerian and other developing countries’ mass media. PMID:23394854

A comparative study of two communication models in HIV/AIDS coverage in selected Nigerian newspapers.

PubMed

Okidu, Onjefu

2013-01-30

The current overriding thought in HIV/AIDS communication in developing countries is the need for a shift from the cognitive model, which emphasises the decision-making of the individual, to the activity model, which emphasises the context of the individual. In spite of the acknowledged media shift from the cognitive to the activity model in some developing countries, some HIV/AIDS communication scholars have felt otherwise. It was against this background that this study examined the content of some selected Nigerian newspapers to ascertain the attention paid to HIV/AIDS cognitive and activity information. Generally, the study found that Nigerian newspapers had shifted from the cognitive to the activity model of communication in their coverage of HIV/AIDS issues. The findings of the study seem inconsistent with the theoretical argument of some scholars that insufficient attention has been paid by mass media in developing countries to the activity model of HIV/AIDS communication. It is suggested that future research replicate the study for Nigerian and other developing countries' mass media.

Maternal hypothyroidism: An overview of current experimental models.

PubMed

Ghanbari, Mahboubeh; Ghasemi, Asghar

2017-10-15

Maternal hypothyroidism (MH) is the most common cause of transient congenital hypothyroidism. Different animal models are used for assessing developmental effects of MH in offspring. The severity and status of hypothyroidism in animal models must be a reflection of the actual conditions in humans. To obtain comparable results with different clinical conditions, which lead to MH in humans, several factors have been suggested for researchers to consider before designing the experimental models. Regarding development of fetal body systems during pregnancy, interference at different times provides different results and the appropriate time for induction of hypothyroidism should be selected based on accurate time of development of the system under assessment. Other factors that should be taken into consideration include, physiological and biochemical differences between humans and other species, thyroid hormone-independent effects of anti-thyroid drugs, circadian rhythms in TSH secretion, sex differences, physical and psychological stress. This review addresses essential guidelines for selecting and managing the optimal animal model for MH as well as discussing the pros and cons of currently used models. Copyright © 2017 Elsevier Inc. All rights reserved.

Sexual differences in microhabitat selection of breeding little bustards Tetrax tetrax: Ecological segregation based on vegetation structure

NASA Astrophysics Data System (ADS)

Morales, M. B.; Traba, J.; Carriles, E.; Delgado, M. P.; de la Morena, E. L. García

2008-11-01

We examined sexual differences in patterns of vegetation structure selection in the sexually dimorphic little bustard. Differences in vegetation structure between male, female and non-used locations during reproduction were examined and used to build a presence/absence model for each sex. Ten variables were measured in each location, extracting two PCA factors (PC1: a visibility-shelter gradient; PC2: a gradient in food availability) used as response variables in GLM explanatory models. Both factors significantly differed between female, male and control locations. Neither study site nor phenology was significant. Logistic regression was used to model male and female presence/absence. Female presence was positively associated to cover of ground by vegetation litter, as well as overall vegetation cover, and negatively to vegetation density over 30 cm above ground. Male presence was positively related to litter cover and short vegetation and negatively to vegetation density over 30 cm above ground. Models showed good global performance and robustness. Female microhabitat selection and distribution seems to be related to the balance between shelter and visibility for surveillance. Male microhabitat selection would be related mainly to the need of conspicuousness for courtship. Accessibility to food resources seems to be equally important for both sexes. Differences suggest ecological sexual segregation resulting from different ecological constraints. These are the first detailed results on vegetation structure selection in both male and female little bustards, and are useful in designing management measures addressing vegetation structure irrespective of landscape composition. Similar microhabitat approaches can be applied to manage the habitat of many declining farmland birds.

A Model of Expertise: A Case Study of a Second Language Teacher Educator

ERIC Educational Resources Information Center

Asaba, Mayumi

2018-01-01

This study investigates the characteristics of an L2 expert teacher educator. The expert participant was selected based on the criteria suggested by educational expertise studies: years of teaching experience, high reputation among multiple constituencies, and evidence of impact on student performance. The data collection included observations,…

Models of expert assessments and their study in problems of choice and decision-making in management of motor transport processes

NASA Astrophysics Data System (ADS)

Belokurov, V. P.; Belokurov, S. V.; Korablev, R. A.; Shtepa, A. A.

2018-05-01

The article deals with decision making concerning transport tasks on search iterations in the management of motor transport processes. An optimal selection of the best option for specific situations is suggested in the management of complex multi-criteria transport processes.

Locus of Semantic Interference in Picture Naming: Evidence from Dual-Task Performance

ERIC Educational Resources Information Center

Piai, Vitória; Roelofs, Ardi; Schriefers, Herbert

2014-01-01

Disagreement exists regarding the functional locus of semantic interference of distractor words in picture naming. This effect is a cornerstone of modern psycholinguistic models of word production, which assume that it arises in lexical response-selection. However, recent evidence from studies of dual-task performance suggests a locus in…

Presentation-Practice-Production and Task-Based Learning in the Light of Second Language Learning Theories.

ERIC Educational Resources Information Center

Ritchie, Graeme

2003-01-01

Features of presentation-practice-production (PPP) and task-based learning (TBL) models for language teaching are discussed with reference to language learning theories. Pre-selection of target structures, use of controlled repetition, and explicit grammar instruction in a PPP lesson are given. Suggests TBL approaches afford greater learning…

Navigating the Parallel Universe: Education for Collection Management in the Electronic Age.

ERIC Educational Resources Information Center

Blake, Virgil L. P.; Surprenant, Thomas T.

2000-01-01

Focuses on the selection and decision-making aspects of the Edelmen model of collection development. Reviews challenges facing library/information studies education and the place of collection development within that context. Considers implications for the library/information center of the rise of a new class of resources. Suggests that a more…

Sustaining Professional and Organizational Growth of the ACTER through the Value of Mentorship

ERIC Educational Resources Information Center

Gordon, Howard R. D.

2016-01-01

The author examines selected aspects of mentorship and its value to the Association for Career and Technical Education Research (ACTER). He describes the Collaborative Mentoring Theory and the key elements of Daloz's Mentoring Model. Highlights of types of mentoring and suggested characteristics of Generation Xers and Millennials are reported. He…

Perceptions of Financial Aid: Black Students at a Predominantly White Institution

ERIC Educational Resources Information Center

Tichavakunda, Antar A.

2017-01-01

This study provides qualitative context for statistics concerning Black college students and financial aid. Using the financial nexus model as a framework, this research draws upon interviews with 29 Black juniors and seniors at a selective, -private, and predominantly White university. The data suggest that students -generally exhibited high…

Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli.

PubMed

Aumentado-Armstrong, Tristan; Metzen, Michael G; Sproule, Michael K J; Chacron, Maurice J

2015-10-01

Neurons that respond selectively but in an invariant manner to a given feature of natural stimuli have been observed across species and systems. Such responses emerge in higher brain areas, thereby suggesting that they occur by integrating afferent input. However, the mechanisms by which such integration occurs are poorly understood. Here we show that midbrain electrosensory neurons can respond selectively and in an invariant manner to heterogeneity in behaviorally relevant stimulus waveforms. Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input. To test this hypothesis, we built a model based on the Hodgkin-Huxley formalism that received realistic afferent input. We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally. Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli. We discuss the implications of our findings for the electrosensory and other systems.

Taxonomic and regional uncertainty in species-area relationships and the identification of richness hotspots

PubMed Central

Guilhaumon, François; Gimenez, Olivier; Gaston, Kevin J.; Mouillot, David

2008-01-01

Species-area relationships (SARs) are fundamental to the study of key and high-profile issues in conservation biology and are particularly widely used in establishing the broad patterns of biodiversity that underpin approaches to determining priority areas for biological conservation. Classically, the SAR has been argued in general to conform to a power-law relationship, and this form has been widely assumed in most applications in the field of conservation biology. Here, using nonlinear regressions within an information theoretical model selection framework, we included uncertainty regarding both model selection and parameter estimation in SAR modeling and conducted a global-scale analysis of the form of SARs for vascular plants and major vertebrate groups across 792 terrestrial ecoregions representing almost 97% of Earth's inhabited land. The results revealed a high level of uncertainty in model selection across biomes and taxa, and that the power-law model is clearly the most appropriate in only a minority of cases. Incorporating this uncertainty into a hotspots analysis using multimodel SARs led to the identification of a dramatically different set of global richness hotspots than when the power-law SAR was assumed. Our findings suggest that the results of analyses that assume a power-law model may be at severe odds with real ecological patterns, raising significant concerns for conservation priority-setting schemes and biogeographical studies. PMID:18832179

The maintenance of single-locus polymorphism. IV. Models with mutation from existing alleles.

PubMed

Spencer, H G; Marks, R W

1992-01-01

The ability of viability selection to maintain allelic polymorphism is investigated using a constructionist approach. In extensions to the models we have previously proposed, a population is bombarded with a series of mutations whose fitnesses in conjunction with other alleles are functions of the corresponding fitnesses with a particular allele, the parent allele, already in the population. Allele frequencies are iterated simultaneously, thus allowing alleles to be driven to extinction by selection. Such models allow very high levels of polymorphism to evolve: up to 38 alleles in one case. Alleles that are lethal as homozygotes can evolve to surprisingly high frequencies. The joint evolution of allele frequencies and viabilities highlights the necessity to consider more than the current morphology of a population. Comparisons are made with the neutral theory of evolution and it is suggested that failure to reject neutrality using the Ewens-Watterson test cannot be regarded as evidence for the neutral theory.

Compensating, resisting, and breaking: a meta-analytic examination of reactions to self-esteem threat.

PubMed

vanDellen, Michelle R; Campbell, W Keith; Hoyle, Rick H; Bradfield, Erin K

2011-02-01

Much research has identified how people react to receiving threatening information about the self. The purpose of this article is to discuss such experiences in the context of a model of state self-esteem regulation. The authors propose that people engage in one of three regulatory responses to threat: compensation, resistance, and breaking. They conduct a meta-analysis aimed to examine when people engage in each of these three responses to threat and how trait self-esteem affects the selection and success of selecting each regulatory response. Furthermore, the authors test six theoretical models that might explain why responses to ego threat vary across level of trait self-esteem. The models for differences between people with low and high trait self-esteem that fit the data best suggest that (a) self-esteem serves as a resource and (b) there is a self-verification motivation.

Intrinsic two-dimensional features as textons

NASA Technical Reports Server (NTRS)

Barth, E.; Zetzsche, C.; Rentschler, I.

1998-01-01

We suggest that intrinsic two-dimensional (i2D) features, computationally defined as the outputs of nonlinear operators that model the activity of end-stopped neurons, play a role in preattentive texture discrimination. We first show that for discriminable textures with identical power spectra the predictions of traditional models depend on the type of nonlinearity and fail for energy measures. We then argue that the concept of intrinsic dimensionality, and the existence of end-stopped neurons, can help us to understand the role of the nonlinearities. Furthermore, we show examples in which models without strong i2D selectivity fail to predict the correct ranking order of perceptual segregation. Our arguments regarding the importance of i2D features resemble the arguments of Julesz and co-workers regarding textons such as terminators and crossings. However, we provide a computational framework that identifies textons with the outputs of nonlinear operators that are selective to i2D features.

Sexual Dimorphism and Sexual Selection: A Unified Economic Analysis1

PubMed Central

Chu, C. Y. Cyrus; Lee, Ronald D.

2012-01-01

We develop a life history model with two sexes, and study the optimal energy allocation strategy of males and females. We join Darwin and others in suggesting that the origin of sexual dimorphism and sexual selection is the difference between male and female reproduction costs. Due to this assumed cost difference, the resulting Bellman equations of gene dynamics in our two-sex life history model imply a large “energy surplus” on the part of males. This allows the male form to devote energy to the development of some costly male traits that help the males to compete for access to females. These costly male traits are sexually dimorphic. Using this life history model, we are able to explain important features of sexual dimorphism, as well as why males often transfer less to their offspring than do females, and why only females have menopause. PMID:22699007

Proposing integrated Shannon's entropy-inverse data envelopment analysis methods for resource allocation problem under a fuzzy environment

NASA Astrophysics Data System (ADS)

Çakır, Süleyman

2017-10-01

In this study, a two-phase methodology for resource allocation problems under a fuzzy environment is proposed. In the first phase, the imprecise Shannon's entropy method and the acceptability index are suggested, for the first time in the literature, to select input and output variables to be used in the data envelopment analysis (DEA) application. In the second step, an interval inverse DEA model is executed for resource allocation in a short run. In an effort to exemplify the practicality of the proposed fuzzy model, a real case application has been conducted involving 16 cement firms listed in Borsa Istanbul. The results of the case application indicated that the proposed hybrid model is a viable procedure to handle input-output selection and resource allocation problems under fuzzy conditions. The presented methodology can also lend itself to different applications such as multi-criteria decision-making problems.

Slack channels expressed in sensory neurons control neuropathic pain in mice.

PubMed

Lu, Ruirui; Bausch, Anne E; Kallenborn-Gerhardt, Wiebke; Stoetzer, Carsten; Debruin, Natasja; Ruth, Peter; Geisslinger, Gerd; Leffler, Andreas; Lukowski, Robert; Schmidtko, Achim

2015-01-21

Slack (Slo2.2) is a sodium-activated potassium channel that regulates neuronal firing activities and patterns. Previous studies identified Slack in sensory neurons, but its contribution to acute and chronic pain in vivo remains elusive. Here we generated global and sensory neuron-specific Slack mutant mice and analyzed their behavior in various animal models of pain. Global ablation of Slack led to increased hypersensitivity in models of neuropathic pain, whereas the behavior in models of inflammatory and acute nociceptive pain was normal. Neuropathic pain behaviors were also exaggerated after ablation of Slack selectively in sensory neurons. Notably, the Slack opener loxapine ameliorated persisting neuropathic pain behaviors. In conclusion, Slack selectively controls the sensory input in neuropathic pain states, suggesting that modulating its activity might represent a novel strategy for management of neuropathic pain. Copyright © 2015 the authors 0270-6474/15/351125-11$15.00/0.

Selective rab11 transport and the intrinsic regenerative ability of CNS axons

PubMed Central

Koseki, Hiroaki; Donegá, Matteo; Lam, Brian YH; Petrova, Veselina; van Erp, Susan; Yeo, Giles SH; Kwok, Jessica CF; ffrench-Constant, Charles

2017-01-01

Neurons lose intrinsic axon regenerative ability with maturation, but the mechanism remains unclear. Using an in-vitro laser axotomy model, we show a progressive decline in the ability of cut CNS axons to form a new growth cone and then elongate. Failure of regeneration was associated with increased retraction after axotomy. Transportation into axons becomes selective with maturation; we hypothesized that selective exclusion of molecules needed for growth may contribute to regeneration decline. With neuronal maturity rab11 vesicles (which carry many molecules involved in axon growth) became selectively targeted to the somatodendritic compartment and excluded from axons by predominant retrograde transport However, on overexpression rab11 was mistrafficked into proximal axons, and these axons showed less retraction and enhanced regeneration after axotomy. These results suggest that the decline of intrinsic axon regenerative ability is associated with selective exclusion of key molecules, and that manipulation of transport can enhance regeneration. PMID:28829741

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

The Role of Attention in Information Processing Implications for the Design of Displays

DTIC Science & Technology

1989-12-01

processing system. Psychological Review, J, 214-255. Neisser , U . (1967). Cognitive Rsycholo&X. New York, NY: Appleton- Century-Crofts. Neisser , U . (1969...in the visual display is now an important part of a number of attention models. A related model suggested by Neisser (1967) is that successful...to filter attenuation theory have been proposed by Neisser (1967, 1969). According to Neisser’s theory, selective attention is an active process of

Modelling gene expression profiles related to prostate tumor progression using binary states

PubMed Central

2013-01-01

Background Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression. Methods We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets. Results We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings. Conclusions Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies. PMID:23721350

Positive selection of digestive Cys proteases in herbivorous Coleoptera.

PubMed

Vorster, Juan; Rasoolizadeh, Asieh; Goulet, Marie-Claire; Cloutier, Conrad; Sainsbury, Frank; Michaud, Dominique

2015-10-01

Positive selection is thought to contribute to the functional diversification of insect-inducible protease inhibitors in plants in response to selective pressures exerted by the digestive proteases of their herbivorous enemies. Here we assessed whether a reciprocal evolutionary process takes place on the insect side, and whether ingestion of a positively selected plant inhibitor may translate into a measurable rebalancing of midgut proteases in vivo. Midgut Cys proteases of herbivorous Coleoptera, including the major pest Colorado potato beetle (Leptinotarsa decemlineata), were first compared using a codon-based evolutionary model to look for the occurrence of hypervariable, positively selected amino acid sites among the tested sequences. Hypervariable sites were found, distributed within -or close to- amino acid regions interacting with Cys-type inhibitors of the plant cystatin protein family. A close examination of L. decemlineata sequences indicated a link between their assignment to protease functional families and amino acid identity at positively selected sites. A function-diversifying role for positive selection was further suggested empirically by in vitro protease assays and a shotgun proteomic analysis of L. decemlineata Cys proteases showing a differential rebalancing of protease functional family complements in larvae fed single variants of a model cystatin mutated at positively selected amino acid sites. These data confirm overall the occurrence of hypervariable, positively selected amino acid sites in herbivorous Coleoptera digestive Cys proteases. They also support the idea of an adaptive role for positive selection, useful to generate functionally diverse proteases in insect herbivores ingesting functionally diverse, rapidly evolving dietary cystatins. Copyright © 2015 Elsevier Ltd. All rights reserved.

The role of genetic background in susceptibility to chemical warfare nerve agents across rodent and non-human primate models.

PubMed

Matson, Liana M; McCarren, Hilary S; Cadieux, C Linn; Cerasoli, Douglas M; McDonough, John H

2018-01-15

Genetics likely play a role in various responses to nerve agent exposure, as genetic background plays an important role in behavioral, neurological, and physiological responses to environmental stimuli. Mouse strains or selected lines can be used to identify susceptibility based on background genetic features to nerve agent exposure. Additional genetic techniques can then be used to identify mechanisms underlying resistance and sensitivity, with the ultimate goal of developing more effective and targeted therapies. Here, we discuss the available literature on strain and selected line differences in cholinesterase activity levels and response to nerve agent-induced toxicity and seizures. We also discuss the available cholinesterase and toxicity literature across different non-human primate species. The available data suggest that robust genetic differences exist in cholinesterase activity, nerve agent-induced toxicity, and chemical-induced seizures. Available cholinesterase data suggest that acetylcholinesterase activity differs across strains, but are limited by the paucity of carboxylesterase data in strains and selected lines. Toxicity and seizures, two outcomes of nerve agent exposure, have not been fully evaluated for genetic differences, and thus further studies are required to understand baseline strain and selected line differences. Published by Elsevier B.V.

The accumulation of reproductive isolation in early stages of divergence supports a role for sexual selection.

PubMed

Martin, M D; Mendelson, T C

2016-04-01

Models of speciation by sexual selection propose that male-female coevolution leads to the rapid evolution of behavioural reproductive isolation. Here, we compare the strength of behavioural isolation to ecological isolation, gametic incompatibility and hybrid inviability in a group of dichromatic stream fishes. In addition, we examine whether any of these individual barriers, or a combined measure of total isolation, is predicted by body shape differences, male colour differences, environmental differences or genetic distance. Behavioural isolation reaches the highest values of any barrier and is significantly greater than ecological isolation. No individual reproductive barrier is associated with any of the predictor variables. However, marginally significant relationships between male colour and body shape differences with ecological and behavioural isolation are discussed. Differences in male colour and body shape predict total reproductive isolation between species; hierarchical partitioning of these two variables' effects suggests a stronger role for male colour differences. Together, these results suggest an important role for divergent sexual selection in darter speciation but raise new questions about the mechanisms of sexual selection at play and the role of male nuptial ornaments. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Forest Succession and Maternity Day roost selection by Myotis septentrionalis in a mesophytic hardwood forest

USGS Publications Warehouse

Silvis, Alexander; Ford, W. Mark; Eric R. Britzke,; Nathan R. Beane,; Joshua B. Johnson,

2012-01-01

Conservation of summer maternity roosts is considered critical for bat management in North America, yet many aspects of the physical and environmental factors that drive roost selection are poorly understood. We tracked 58 female northern bats (Myotis septentrionalis) to 105 roost trees of 21 species on the Fort Knox military reservation in north-central Kentucky during the summer of 2011. Sassafras (Sassafras albidum) was used as a day roost more than expected based on forest stand-level availability and accounted for 48.6% of all observed day roosts. Using logistic regression and an information theoretic approach, we were unable to reliably differentiate between sassafras and other roost species or between day roosts used during different maternity periods using models representative of individual tree metrics, site metrics, topographic location, or combinations of these factors. For northern bats, we suggest that day-roost selection is not a function of differences between individual tree species per se, but rather of forest successional patterns, stand and tree structure. Present successional trajectories may not provide this particular selected structure again without management intervention, thereby suggesting that resource managers take a relatively long retrospective view to manage current and future forest conditions for bats.

Coincidental loss of bacterial virulence in multi-enemy microbial communities.

PubMed

Zhang, Ji; Ketola, Tarmo; Örmälä-Odegrip, Anni-Maria; Mappes, Johanna; Laakso, Jouni

2014-01-01

The coincidental virulence evolution hypothesis suggests that outside-host selection, such as predation, parasitism and resource competition can indirectly affect the virulence of environmentally-growing bacterial pathogens. While there are some examples of coincidental environmental selection for virulence, it is also possible that the resource acquisition and enemy defence is selecting against it. To test these ideas we conducted an evolutionary experiment by exposing the opportunistic pathogen bacterium Serratia marcescens to the particle-feeding ciliate Tetrahymena thermophila, the surface-feeding amoeba Acanthamoeba castellanii, and the lytic bacteriophage Semad11, in all possible combinations in a simulated pond water environment. After 8 weeks the virulence of the 384 evolved clones were quantified with fruit fly Drosophila melanogaster oral infection model, and several other life-history traits were measured. We found that in comparison to ancestor bacteria, evolutionary treatments reduced the virulence in most of the treatments, but this reduction was not clearly related to any changes in other life-history traits. This suggests that virulence traits do not evolve in close relation with these life-history traits, or that different traits might link to virulence in different selective environments, for example via resource allocation trade-offs.

An actor-based model of social network influence on adolescent body size, screen time, and playing sports.

PubMed

Shoham, David A; Tong, Liping; Lamberson, Peter J; Auchincloss, Amy H; Zhang, Jun; Dugas, Lara; Kaufman, Jay S; Cooper, Richard S; Luke, Amy

2012-01-01

Recent studies suggest that obesity may be "contagious" between individuals in social networks. Social contagion (influence), however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves) or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM) framework developed by Snijders and colleagues to data on adolescent body mass index (BMI), screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network) and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health) and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151). Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers' influence on one another, rather than treating "high risk" adolescents in isolation.

Systems thinking, the Swiss Cheese Model and accident analysis: a comparative systemic analysis of the Grayrigg train derailment using the ATSB, AcciMap and STAMP models.

PubMed

Underwood, Peter; Waterson, Patrick

2014-07-01

The Swiss Cheese Model (SCM) is the most popular accident causation model and is widely used throughout various industries. A debate exists in the research literature over whether the SCM remains a viable tool for accident analysis. Critics of the model suggest that it provides a sequential, oversimplified view of accidents. Conversely, proponents suggest that it embodies the concepts of systems theory, as per the contemporary systemic analysis techniques. The aim of this paper was to consider whether the SCM can provide a systems thinking approach and remain a viable option for accident analysis. To achieve this, the train derailment at Grayrigg was analysed with an SCM-based model (the ATSB accident investigation model) and two systemic accident analysis methods (AcciMap and STAMP). The analysis outputs and usage of the techniques were compared. The findings of the study showed that each model applied the systems thinking approach. However, the ATSB model and AcciMap graphically presented their findings in a more succinct manner, whereas STAMP more clearly embodied the concepts of systems theory. The study suggests that, whilst the selection of an analysis method is subject to trade-offs that practitioners and researchers must make, the SCM remains a viable model for accident analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impact of the New U.S. Department of Agriculture School Meal Standards on Food Selection, Consumption, and Waste

PubMed Central

Cohen, Juliana F.W.; Richardson, Scott; Parker, Ellen; Catalano, Paul J.; Rimm, Eric B.

2014-01-01

Background The U.S Department of Agriculture (USDA) recently made substantial changes to the school meal standards. The media and public outcry have suggested that this has led to substantially more food waste. Purpose School meal selection, consumption, and waste were assessed before and after implementation of the new school meal standards. Methods Plate waste data was collected in 4 schools in an urban, low-income school district. Logistic regression and mixed-model ANOVA were used to estimate the differences in selection and consumption of school meals before (fall 2011) and after implementation (fall 2012) of the new standards among 1030 elementary and middle school children. Analyses were conducted in 2013. Results After the new standards were implemented, fruit selection increased by 23.0%, and entrée and vegetable selection remained unchanged. Additionally, post-implementation entrée consumption increased by 15.6%, vegetable consumption increased by 16.2%, and fruit consumption remained the same. Milk selection and consumption decreased owing to an unrelated milk policy change. Conclusions While food waste levels were substantial both pre- and post-implementation, the new guidelines have positively impacted school meal selection and consumption. Despite the increased vegetable portion size requirement, consumption increased and led to significantly more cups of vegetables consumed. Significantly more students selected a fruit, while the overall percentage of fruit consumed remained the same, resulting in more students consuming fruits. Contrary to media reports, these results suggest that the new school meal standards have improved students’ overall diet quality. Legislation to weaken the standards is not warranted. PMID:24650841

From the Cover: Harmane-Induced Selective Dopaminergic Neurotoxicity in Caenorhabditis elegans.

PubMed

Sammi, Shreesh Raj; Agim, Zeynep Sena; Cannon, Jason R

2018-02-01

Parkinson's disease (PD) is a debilitating neurodegenerative disease. Although numerous exposures have been linked to PD etiology, causative factors for most cases remain largely unknown. Emerging data on the neurotoxicity of heterocyclic amines suggest that this class of compounds should be examined for relevance to PD. Here, using Caenorhabditis elegans as a model system, we tested whether harmane exposure produced selective toxicity to dopamine neurons that is potentially relevant to PD. Harmane is a known tremorigenic β-carboline (a type of heterocyclic amine) found in cooked meat, roasted coffee beans, and tobacco. Thus, this compound represents a potentially important exposure. In the nematode model, we observed dopaminergic neurons to be selectively vulnerable, showing significant loss in terms of structure and function at lower doses than other neuronal populations. In examining mechanisms of toxicity, we observed significant harmane-induced decreases in mitochondrial viability and increased reactive oxygen species levels. Blocking transport through the dopamine transporter (DAT) was not neuroprotective, suggesting that harmane is unlikely to enter the cell through DAT. However, a mitochondrial complex I activator did partially ameliorate neurodegeneration. Further, mitochondrial complex I activator treatment reduced harmane-induced dopamine depletion, measured by the 1-nonanol assay. In summary, we have shown that harmane exposure in C. elegans produces selective dopaminergic neurotoxicity that may bear relevance to PD, and that neurotoxicity may be mediated through mitochondrial mechanisms. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.