A semiparametric graphical modelling approach for large-scale equity selection

PubMed Central

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption. PMID:28316507

Enzymatic production of trans fatty acid free fat from partially hydrogenated soybean oil (PHSO)--theory, strategy and practicability.

PubMed

Jala, Ram Chandra Reddy; Xu, Xuebing; Guo, Zheng

2013-12-01

Development of an advanced process/production technology for healthful fats constitutes a major interest of plant oil refinery industry. In this work, a strategy to produce trans fatty acid (TFA) free (or low TFA) products from partially hydrogenated soybean oil by lipase-catalysed selective hydrolysis was proposed, where a physically founded mathematic model to delineate the multi-responses of the reaction as a function of selectivity factor was defined for the first time. The practicability of this strategy was assessed with commercial trans-selective Candida antarctica lipase A (CAL-A) as a model biocatalyst based on a parameter study and fitting to the model. CAL-A was found to have a selectivity factor 4.26 and to maximally remove 73.3% of total TFAs at 46.5% hydrolysis degree. Copyright © 2013 Elsevier Ltd. All rights reserved.

Attentional Selection in Object Recognition

DTIC Science & Technology

1993-02-01

order. It also affects the choice of strategies in both the 24 A Computational Model of Attentional Selection filtering and arbiter stages. The set...such processing. In Treisman’s model this was hidden in the concept of the selection filter . Later computational models of attention tried to...This thesis presents a novel approach to the selection problem by propos. ing a computational model of visual attentional selection as a paradigm for

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

PubMed

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

PubMed Central

Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

Strategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)

NASA Astrophysics Data System (ADS)

Mohammadi Nasrabadi, Ali; Hosseinpour, Mohammad Hossein; Ebrahimnejad, Sadoullah

2013-05-01

In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment evaluation and selection. A modular decision support system (DSS) is developed to select an optimum segment with its appropriate strategies. The suggested DSS has two main modules. The first one is SPACE matrix which indicates the risk of each segment. Also, it determines the long-term strategies. The second module finds the most preferred segment-strategies over time. Dynamic network process is applied to prioritize segment-strategies according to five competitive force factors. There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts. To clarify, an example is illustrated by a case study in Iran's coffee market. The results show that success possibility of segments could be different, and choosing the best ones could help companies to be sure in developing their business. Moreover, changing the priority of strategies over time indicates the importance of long-term planning. This fact has been supported by a case study on strategic priority difference in short- and long-term consideration.

Efficiency of a clinical prediction model for selective rapid testing in children with pharyngitis: A prospective, multicenter study

PubMed Central

Cohen, Robert; Bidet, Philippe; Elbez, Annie; Levy, Corinne; Bossuyt, Patrick M.; Chalumeau, Martin

2017-01-01

Background There is controversy whether physicians can rely on signs and symptoms to select children with pharyngitis who should undergo a rapid antigen detection test (RADT) for group A streptococcus (GAS). Our objective was to evaluate the efficiency of signs and symptoms in selectively testing children with pharyngitis. Materials and methods In this multicenter, prospective, cross-sectional study, French primary care physicians collected clinical data and double throat swabs from 676 consecutive children with pharyngitis; the first swab was used for the RADT and the second was used for a throat culture (reference standard). We developed a logistic regression model combining signs and symptoms with GAS as the outcome. We then derived a model-based selective testing strategy, assuming that children with low and high calculated probability of GAS (<0.12 and >0.85) would be managed without the RADT. Main outcomes and measures were performance of the model (c-index and calibration) and efficiency of the model-based strategy (proportion of participants in whom RADT could be avoided). Results Throat culture was positive for GAS in 280 participants (41.4%). Out of 17 candidate signs and symptoms, eight were retained in the prediction model. The model had an optimism-corrected c-index of 0.73; calibration of the model was good. With the model-based strategy, RADT could be avoided in 6.6% of participants (95% confidence interval 4.7% to 8.5%), as compared to a RADT-for-all strategy. Conclusions This study demonstrated that relying on signs and symptoms for selectively testing children with pharyngitis is not efficient. We recommend using a RADT in all children with pharyngitis. PMID:28235012

Efficiency of a clinical prediction model for selective rapid testing in children with pharyngitis: A prospective, multicenter study.

PubMed

Cohen, Jérémie F; Cohen, Robert; Bidet, Philippe; Elbez, Annie; Levy, Corinne; Bossuyt, Patrick M; Chalumeau, Martin

2017-01-01

There is controversy whether physicians can rely on signs and symptoms to select children with pharyngitis who should undergo a rapid antigen detection test (RADT) for group A streptococcus (GAS). Our objective was to evaluate the efficiency of signs and symptoms in selectively testing children with pharyngitis. In this multicenter, prospective, cross-sectional study, French primary care physicians collected clinical data and double throat swabs from 676 consecutive children with pharyngitis; the first swab was used for the RADT and the second was used for a throat culture (reference standard). We developed a logistic regression model combining signs and symptoms with GAS as the outcome. We then derived a model-based selective testing strategy, assuming that children with low and high calculated probability of GAS (<0.12 and >0.85) would be managed without the RADT. Main outcomes and measures were performance of the model (c-index and calibration) and efficiency of the model-based strategy (proportion of participants in whom RADT could be avoided). Throat culture was positive for GAS in 280 participants (41.4%). Out of 17 candidate signs and symptoms, eight were retained in the prediction model. The model had an optimism-corrected c-index of 0.73; calibration of the model was good. With the model-based strategy, RADT could be avoided in 6.6% of participants (95% confidence interval 4.7% to 8.5%), as compared to a RADT-for-all strategy. This study demonstrated that relying on signs and symptoms for selectively testing children with pharyngitis is not efficient. We recommend using a RADT in all children with pharyngitis.

How motivation affects academic performance: a structural equation modelling analysis.

PubMed

Kusurkar, R A; Ten Cate, Th J; Vos, C M P; Westers, P; Croiset, G

2013-03-01

Few studies in medical education have studied effect of quality of motivation on performance. Self-Determination Theory based on quality of motivation differentiates between Autonomous Motivation (AM) that originates within an individual and Controlled Motivation (CM) that originates from external sources. To determine whether Relative Autonomous Motivation (RAM, a measure of the balance between AM and CM) affects academic performance through good study strategy and higher study effort and compare this model between subgroups: males and females; students selected via two different systems namely qualitative and weighted lottery selection. Data on motivation, study strategy and effort was collected from 383 medical students of VU University Medical Center Amsterdam and their academic performance results were obtained from the student administration. Structural Equation Modelling analysis technique was used to test a hypothesized model in which high RAM would positively affect Good Study Strategy (GSS) and study effort, which in turn would positively affect academic performance in the form of grade point averages. This model fit well with the data, Chi square = 1.095, df = 3, p = 0.778, RMSEA model fit = 0.000. This model also fitted well for all tested subgroups of students. Differences were found in the strength of relationships between the variables for the different subgroups as expected. In conclusion, RAM positively correlated with academic performance through deep strategy towards study and higher study effort. This model seems valid in medical education in subgroups such as males, females, students selected by qualitative and weighted lottery selection.

Optimal feature selection using a modified differential evolution algorithm and its effectiveness for prediction of heart disease.

PubMed

Vivekanandan, T; Sriman Narayana Iyengar, N Ch

2017-11-01

Enormous data growth in multiple domains has posed a great challenge for data processing and analysis techniques. In particular, the traditional record maintenance strategy has been replaced in the healthcare system. It is vital to develop a model that is able to handle the huge amount of e-healthcare data efficiently. In this paper, the challenging tasks of selecting critical features from the enormous set of available features and diagnosing heart disease are carried out. Feature selection is one of the most widely used pre-processing steps in classification problems. A modified differential evolution (DE) algorithm is used to perform feature selection for cardiovascular disease and optimization of selected features. Of the 10 available strategies for the traditional DE algorithm, the seventh strategy, which is represented by DE/rand/2/exp, is considered for comparative study. The performance analysis of the developed modified DE strategy is given in this paper. With the selected critical features, prediction of heart disease is carried out using fuzzy AHP and a feed-forward neural network. Various performance measures of integrating the modified differential evolution algorithm with fuzzy AHP and a feed-forward neural network in the prediction of heart disease are evaluated in this paper. The accuracy of the proposed hybrid model is 83%, which is higher than that of some other existing models. In addition, the prediction time of the proposed hybrid model is also evaluated and has shown promising results. Copyright © 2017 Elsevier Ltd. All rights reserved.

More efficient evolutionary strategies for model calibration with watershed model for demonstration

NASA Astrophysics Data System (ADS)

Baggett, J. S.; Skahill, B. E.

2008-12-01

Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. pp. 75-102, Springer Kern, S., N. Hansen and P. Koumoutsakos (2006). Local Meta-Models for Optimization Using Evolution Strategies. In Ninth International Conference on Parallel Problem Solving from Nature PPSN IX, Proceedings, pp.939-948, Berlin: Springer. Tahk, M., Woo, H., and Park. M, (2007). A hybrid optimization of evolutionary and gradient search. Engineering Optimization, (39), 87-104.

Competitive seeds-selection in complex networks

NASA Astrophysics Data System (ADS)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2017-02-01

This paper investigates a competitive diffusion model where two competitors simultaneously select a set of nodes (seeds) in the network to influence. We focus on the problem of how to select these seeds such that, when the diffusion process terminates, a competitor can obtain more supports than its opponent. Instead of studying this problem in the game-theoretic framework as in the existing work, in this paper we design several heuristic seed-selection strategies inspired by commonly used centrality measures-Betweenness Centrality (BC), Closeness Centrality (CC), Degree Centrality (DC), Eigenvector Centrality (EC), and K-shell Centrality (KS). We mainly compare three centrality-based strategies, which have better performances in competing with the random selection strategy, through simulations on both real and artificial networks. Even though network structure varies across different networks, we find certain common trend appearing in all of these networks. Roughly speaking, BC-based strategy and DC-based strategy are better than CC-based strategy. Moreover, if a competitor adopts CC-based strategy, then BC-based strategy is a better strategy than DC-based strategy for his opponent, and the superiority of BC-based strategy decreases as the heterogeneity of the network decreases.

Health information technology vendor selection strategies and total factor productivity.

PubMed

Ford, Eric W; Huerta, Timothy R; Menachemi, Nir; Thompson, Mark A; Yu, Feliciano

2013-01-01

The aim of this study was to compare health information technology (HIT) adoption strategies' relative performance on hospital-level productivity measures. The American Hospital Association's Annual Survey and Healthcare Information and Management Systems Society Analytics for fiscal years 2002 through 2007 were used for this study. A two-stage approach is employed. First, a Malmquist model is specified to calculate hospital-level productivity measures. A logistic regression model is then estimated to compare the three HIT adoption strategies' relative performance on the newly constructed productivity measures. The HIT vendor selection strategy impacts the amount of technological change required of an organization but does not appear to have either a positive or adverse impact on technical efficiency or total factor productivity. The higher levels in technological change experienced by hospitals using the best of breed and best of suite HIT vendor selection strategies may have a more direct impact on the organization early on in the process. However, these gains did not appear to translate into either increased technical efficiency or total factor productivity during the period studied. Over a longer period, one HIT vendor selection strategy may yet prove to be more effective at improving efficiency and productivity.

Evolution of cooperative strategies from first principles.

PubMed

Burtsev, Mikhail; Turchin, Peter

2006-04-20

One of the greatest challenges in the modern biological and social sciences is to understand the evolution of cooperative behaviour. General outlines of the answer to this puzzle are currently emerging as a result of developments in the theories of kin selection, reciprocity, multilevel selection and cultural group selection. The main conceptual tool used in probing the logical coherence of proposed explanations has been game theory, including both analytical models and agent-based simulations. The game-theoretic approach yields clear-cut results but assumes, as a rule, a simple structure of payoffs and a small set of possible strategies. Here we propose a more stringent test of the theory by developing a computer model with a considerably extended spectrum of possible strategies. In our model, agents are endowed with a limited set of receptors, a set of elementary actions and a neural net in between. Behavioural strategies are not predetermined; instead, the process of evolution constructs and reconstructs them from elementary actions. Two new strategies of cooperative attack and defence emerge in simulations, as well as the well-known dove, hawk and bourgeois strategies. Our results indicate that cooperative strategies can evolve even under such minimalist assumptions, provided that agents are capable of perceiving heritable external markers of other agents.

Processes in arithmetic strategy selection: a fMRI study.

PubMed

Taillan, Julien; Ardiale, Eléonore; Anton, Jean-Luc; Nazarian, Bruno; Félician, Olivier; Lemaire, Patrick

2015-01-01

This neuroimaging (functional magnetic resonance imaging) study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 × 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up (RU) strategy (i.e., doing 60 × 80 = 4,800) or rounding-down (RD) strategy (i.e., doing 50 × 70 = 3,500 to estimate product of 54 × 78). In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40 × 50). Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC), dorso-lateral prefrontal cortex (DLPFC), and angular gyrus (ANG), when selecting (relative to executing) the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modeling cognitive processes underlying strategy selection.

Processes in arithmetic strategy selection: a fMRI study

PubMed Central

Taillan, Julien; Ardiale, Eléonore; Anton, Jean-Luc; Nazarian, Bruno; Félician, Olivier; Lemaire, Patrick

2015-01-01

This neuroimaging (functional magnetic resonance imaging) study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 × 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up (RU) strategy (i.e., doing 60 × 80 = 4,800) or rounding-down (RD) strategy (i.e., doing 50 × 70 = 3,500 to estimate product of 54 × 78). In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40 × 50). Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC), dorso-lateral prefrontal cortex (DLPFC), and angular gyrus (ANG), when selecting (relative to executing) the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modeling cognitive processes underlying strategy selection. PMID:25698995

Strategies to intervene on causal systems are adaptively selected.

PubMed

Coenen, Anna; Rehder, Bob; Gureckis, Todd M

2015-06-01

How do people choose interventions to learn about causal systems? Here, we considered two possibilities. First, we test an information sampling model, information gain, which values interventions that can discriminate between a learner's hypotheses (i.e. possible causal structures). We compare this discriminatory model to a positive testing strategy that instead aims to confirm individual hypotheses. Experiment 1 shows that individual behavior is described best by a mixture of these two alternatives. In Experiment 2 we find that people are able to adaptively alter their behavior and adopt the discriminatory model more often after experiencing that the confirmatory strategy leads to a subjective performance decrement. In Experiment 3, time pressure leads to the opposite effect of inducing a change towards the simpler positive testing strategy. These findings suggest that there is no single strategy that describes how intervention decisions are made. Instead, people select strategies in an adaptive fashion that trades off their expected performance and cognitive effort. Copyright © 2015 Elsevier Inc. All rights reserved.

Strategy selection as rational metareasoning.

PubMed

Lieder, Falk; Griffiths, Thomas L

2017-11-01

Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question of how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost-benefit tradeoff by learning a predictive model of each strategy's performance. We found that our model can provide a unifying explanation for classic findings from domains ranging from decision-making to arithmetic by capturing the variability of people's strategy choices, their dependence on task and context, and their development over time. Systematic model comparisons supported our theory, and 4 new experiments confirmed its distinctive predictions. Our findings suggest that people gradually learn to make increasingly more rational use of fallible heuristics. This perspective reconciles the 2 poles of the debate about human rationality by integrating heuristics and biases with learning and rationality. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Rethinking volitional control over task choice in multitask environments: use of a stimulus set selection strategy in voluntary task switching.

PubMed

Arrington, Catherine M; Weaver, Starla M

2015-01-01

Under conditions of volitional control in multitask environments, subjects may engage in a variety of strategies to guide task selection. The current research examines whether subjects may sometimes use a top-down control strategy of selecting a task-irrelevant stimulus dimension, such as location, to guide task selection. We term this approach a stimulus set selection strategy. Using a voluntary task switching procedure, subjects voluntarily switched between categorizing letter and number stimuli that appeared in two, four, or eight possible target locations. Effects of stimulus availability, manipulated by varying the stimulus onset asynchrony between the two target stimuli, and location repetition were analysed to assess the use of a stimulus set selection strategy. Considered across position condition, Experiment 1 showed effects of both stimulus availability and location repetition on task choice suggesting that only in the 2-position condition, where selection based on location always results in a target at the selected location, subjects may have been using a stimulus set selection strategy on some trials. Experiment 2 replicated and extended these findings in a visually more cluttered environment. These results indicate that, contrary to current models of task selection in voluntary task switching, the top-down control of task selection may occur in the absence of the formation of an intention to perform a particular task.

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

PubMed Central

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

2016-01-01

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

Predicting distant failure in early stage NSCLC treated with SBRT using clinical parameters.

PubMed

Zhou, Zhiguo; Folkert, Michael; Cannon, Nathan; Iyengar, Puneeth; Westover, Kenneth; Zhang, Yuanyuan; Choy, Hak; Timmerman, Robert; Yan, Jingsheng; Xie, Xian-J; Jiang, Steve; Wang, Jing

2016-06-01

The aim of this study is to predict early distant failure in early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT) using clinical parameters by machine learning algorithms. The dataset used in this work includes 81 early stage NSCLC patients with at least 6months of follow-up who underwent SBRT between 2006 and 2012 at a single institution. The clinical parameters (n=18) for each patient include demographic parameters, tumor characteristics, treatment fraction schemes, and pretreatment medications. Three predictive models were constructed based on different machine learning algorithms: (1) artificial neural network (ANN), (2) logistic regression (LR) and (3) support vector machine (SVM). Furthermore, to select an optimal clinical parameter set for the model construction, three strategies were adopted: (1) clonal selection algorithm (CSA) based selection strategy; (2) sequential forward selection (SFS) method; and (3) statistical analysis (SA) based strategy. 5-cross-validation is used to validate the performance of each predictive model. The accuracy was assessed by area under the receiver operating characteristic (ROC) curve (AUC), sensitivity and specificity of the system was also evaluated. The AUCs for ANN, LR and SVM were 0.75, 0.73, and 0.80, respectively. The sensitivity values for ANN, LR and SVM were 71.2%, 72.9% and 83.1%, while the specificity values for ANN, LR and SVM were 59.1%, 63.6% and 63.6%, respectively. Meanwhile, the CSA based strategy outperformed SFS and SA in terms of AUC, sensitivity and specificity. Based on clinical parameters, the SVM with the CSA optimal parameter set selection strategy achieves better performance than other strategies for predicting distant failure in lung SBRT patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis.

PubMed

Tran-Duy, An; Boonen, Annelies; van de Laar, Mart A F J; Franke, Angelinus C; Severens, Johan L

2011-12-01

To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Discrete event simulation paradigm was selected for model development. Drug efficacy was modelled as changes in disease activity (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI)) and functional status (Bath Ankylosing Spondylitis Functional Index (BASFI)), which were linked to costs and health utility using statistical models fitted based on an observational AS cohort. Published clinical data were used to estimate drug efficacy and time to events. Two strategies were compared: (1) five available non-steroidal anti-inflammatory drugs (strategy 1) and (2) same as strategy 1 plus two tumour necrosis factor α inhibitors (strategy 2). 13,000 patients were followed up individually until death. For probability sensitivity analysis, Monte Carlo simulations were performed with 1000 sets of parameters sampled from the appropriate probability distributions. The models successfully generated valid data on treatments, BASDAI, BASFI, utility, quality-adjusted life years (QALYs) and costs at time points with intervals of 1-3 months during the simulation length of 70 years. Incremental cost per QALY gained in strategy 2 compared with strategy 1 was €35,186. At a willingness-to-pay threshold of €80,000, it was 99.9% certain that strategy 2 was cost-effective. The modelling framework provides great flexibility to implement complex algorithms representing treatment selection, disease progression and changes in costs and utilities over time of patients with AS. Results obtained from the simulation are plausible.

Multi-criteria, personalized route planning using quantifier-guided ordered weighted averaging operators

NASA Astrophysics Data System (ADS)

Nadi, S.; Delavar, M. R.

2011-06-01

This paper presents a generic model for using different decision strategies in multi-criteria, personalized route planning. Some researchers have considered user preferences in navigation systems. However, these prior studies typically employed a high tradeoff decision strategy, which used a weighted linear aggregation rule, and neglected other decision strategies. The proposed model integrates a pairwise comparison method and quantifier-guided ordered weighted averaging (OWA) aggregation operators to form a personalized route planning method that incorporates different decision strategies. The model can be used to calculate the impedance of each link regarding user preferences in terms of the route criteria, criteria importance and the selected decision strategy. Regarding the decision strategy, the calculated impedance lies between aggregations that use a logical "and" (which requires all the criteria to be satisfied) and a logical "or" (which requires at least one criterion to be satisfied). The calculated impedance also includes taking the average of the criteria scores. The model results in multiple alternative routes, which apply different decision strategies and provide users with the flexibility to select one of them en-route based on the real world situation. The model also defines the robust personalized route under different decision strategies. The influence of different decision strategies on the results are investigated in an illustrative example. This model is implemented in a web-based geographical information system (GIS) for Isfahan in Iran and verified in a tourist routing scenario. The results demonstrated, in real world situations, the validity of the route planning carried out in the model.

Nonequivalence of updating rules in evolutionary games under high mutation rates.

PubMed

Kaiping, G A; Jacobs, G S; Cox, S J; Sluckin, T J

2014-10-01

Moran processes are often used to model selection in evolutionary simulations. The updating rule in Moran processes is a birth-death process, i. e., selection according to fitness of an individual to give birth, followed by the death of a random individual. For well-mixed populations with only two strategies this updating rule is known to be equivalent to selecting unfit individuals for death and then selecting randomly for procreation (biased death-birth process). It is, however, known that this equivalence does not hold when considering structured populations. Here we study whether changing the updating rule can also have an effect in well-mixed populations in the presence of more than two strategies and high mutation rates. We find, using three models from different areas of evolutionary simulation, that the choice of updating rule can change model results. We show, e. g., that going from the birth-death process to the death-birth process can change a public goods game with punishment from containing mostly defectors to having a majority of cooperative strategies. From the examples given we derive guidelines indicating when the choice of the updating rule can be expected to have an impact on the results of the model.

Nonequivalence of updating rules in evolutionary games under high mutation rates

NASA Astrophysics Data System (ADS)

Kaiping, G. A.; Jacobs, G. S.; Cox, S. J.; Sluckin, T. J.

2014-10-01

Moran processes are often used to model selection in evolutionary simulations. The updating rule in Moran processes is a birth-death process, i. e., selection according to fitness of an individual to give birth, followed by the death of a random individual. For well-mixed populations with only two strategies this updating rule is known to be equivalent to selecting unfit individuals for death and then selecting randomly for procreation (biased death-birth process). It is, however, known that this equivalence does not hold when considering structured populations. Here we study whether changing the updating rule can also have an effect in well-mixed populations in the presence of more than two strategies and high mutation rates. We find, using three models from different areas of evolutionary simulation, that the choice of updating rule can change model results. We show, e. g., that going from the birth-death process to the death-birth process can change a public goods game with punishment from containing mostly defectors to having a majority of cooperative strategies. From the examples given we derive guidelines indicating when the choice of the updating rule can be expected to have an impact on the results of the model.

Mixed models for selection of Jatropha progenies with high adaptability and yield stability in Brazilian regions.

PubMed

Teodoro, P E; Bhering, L L; Costa, R D; Rocha, R B; Laviola, B G

2016-08-19

The aim of this study was to estimate genetic parameters via mixed models and simultaneously to select Jatropha progenies grown in three regions of Brazil that meet high adaptability and stability. From a previous phenotypic selection, three progeny tests were installed in 2008 in the municipalities of Planaltina-DF (Midwest), Nova Porteirinha-MG (Southeast), and Pelotas-RS (South). We evaluated 18 families of half-sib in a randomized block design with three replications. Genetic parameters were estimated using restricted maximum likelihood/best linear unbiased prediction. Selection was based on the harmonic mean of the relative performance of genetic values method in three strategies considering: 1) performance in each environment (with interaction effect); 2) performance in each environment (with interaction effect); and 3) simultaneous selection for grain yield, stability and adaptability. Accuracy obtained (91%) reveals excellent experimental quality and consequently safety and credibility in the selection of superior progenies for grain yield. The gain with the selection of the best five progenies was more than 20%, regardless of the selection strategy. Thus, based on the three selection strategies used in this study, the progenies 4, 11, and 3 (selected in all environments and the mean environment and by adaptability and phenotypic stability methods) are the most suitable for growing in the three regions evaluated.

The use of modelling to evaluate and adapt strategies for animal disease control.

PubMed

Saegerman, C; Porter, S R; Humblet, M F

2011-08-01

Disease is often associated with debilitating clinical signs, disorders or production losses in animals and/or humans, leading to severe socio-economic repercussions. This explains the high priority that national health authorities and international organisations give to selecting control strategies for and the eradication of specific diseases. When a control strategy is selected and implemented, an effective method of evaluating its efficacy is through modelling. To illustrate the usefulness of models in evaluating control strategies, the authors describe several examples in detail, including three examples of classification and regression tree modelling to evaluate and improve the early detection of disease: West Nile fever in equids, bovine spongiform encephalopathy (BSE) and multifactorial diseases, such as colony collapse disorder (CCD) in the United States. Also examined are regression modelling to evaluate skin test practices and the efficacy of an awareness campaign for bovine tuberculosis (bTB); mechanistic modelling to monitor the progress of a control strategy for BSE; and statistical nationwide modelling to analyse the spatio-temporal dynamics of bTB and search for potential risk factors that could be used to target surveillance measures more effectively. In the accurate application of models, an interdisciplinary rather than a multidisciplinary approach is required, with the fewest assumptions possible.

Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models.

PubMed

Oizumi, Ryo; Kuniya, Toshikazu; Enatsu, Yoichi

2016-01-01

Despite the fact that density effects and individual differences in life history are considered to be important for evolution, these factors lead to several difficulties in understanding the evolution of life history, especially when population sizes reach the carrying capacity. r/K selection theory explains what types of life strategies evolve in the presence of density effects and individual differences. However, the relationship between the life schedules of individuals and population size is still unclear, even if the theory can classify life strategies appropriately. To address this issue, we propose a few equations on adaptive life strategies in r/K selection where density effects are absent or present. The equations detail not only the adaptive life history but also the population dynamics. Furthermore, the equations can incorporate temporal individual differences, which are referred to as internal stochasticity. Our framework reveals that maximizing density effects is an evolutionarily stable strategy related to the carrying capacity. A significant consequence of our analysis is that adaptive strategies in both selections maximize an identical function, providing both population growth rate and carrying capacity. We apply our method to an optimal foraging problem in a semelparous species model and demonstrate that the adaptive strategy yields a lower intrinsic growth rate as well as a lower basic reproductive number than those obtained with other strategies. This study proposes that the diversity of life strategies arises due to the effects of density and internal stochasticity.

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

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

Microgenetic Patterns of Children's Multiplication Learning: Confirming the Overlapping Waves Model by Latent Growth Modeling

ERIC Educational Resources Information Center

van der Ven, Sanne H. G.; Boom, Jan; Kroesbergen, Evelyn H.; Leseman, Paul P. M.

2012-01-01

Variability in strategy selection is an important characteristic of learning new skills such as mathematical skills. Strategies gradually come and go during this development. In 1996, Siegler described this phenomenon as ''overlapping waves.'' In the current microgenetic study, we attempted to model these overlapping waves statistically. In…

Modeling of lighting behaviour of a hybrid lighting system in inner spaces of Building of Electrical Engineering

NASA Astrophysics Data System (ADS)

Amado, L.; Osma, G.; Villamizar, R.

2016-07-01

This paper presents the modelling of lighting behaviour of a hybrid lighting system - HLS in inner spaces for tropical climate. HLS aims to mitigate the problem of high electricity consumption used by artificial lighting in buildings. These systems integrate intelligently the daylight and artificial light through control strategies. However, selection of these strategies usually depends on expertise of designer and of available budget. In order to improve the selection process of the control strategies, this paper analyses the Electrical Engineering Building (EEB) case, initially modelling of lighting behaviour is established for the HLS of a classroom and an office. This allows estimating the illuminance level of the mixed lighting in the space, and energy consumption by artificial light according to different lighting control techniques, a control strategy based on occupancy and a combination of them. The model considers the concept of Daylight Factor (DF) for the estimating of daylight illuminance on the work plane for tropical climatic conditions. The validation of the model was carried out by comparing the measured and model-estimated indoor illuminances.

Methods of increasing efficiency and maintainability of pipeline systems

NASA Astrophysics Data System (ADS)

Ivanov, V. A.; Sokolov, S. M.; Ogudova, E. V.

2018-05-01

This study is dedicated to the issue of pipeline transportation system maintenance. The article identifies two classes of technical-and-economic indices, which are used to select an optimal pipeline transportation system structure. Further, the article determines various system maintenance strategies and strategy selection criteria. Meanwhile, the maintenance strategies turn out to be not sufficiently effective due to non-optimal values of maintenance intervals. This problem could be solved by running the adaptive maintenance system, which includes a pipeline transportation system reliability improvement algorithm, especially an equipment degradation computer model. In conclusion, three model building approaches for determining optimal technical systems verification inspections duration were considered.

Disclosing Mental Illness Information to a Friend: Exploring How the Disclosure Decision-Making Model Informs Strategy Selection.

PubMed

Venetis, Maria K; Chernichky-Karcher, Skye; Gettings, Patricia E

2018-06-01

Within the context of mental illness disclosure between friends, this study tested the disclosure decision-making model (DD-MM; Greene, 2009) to comprehensively investigate factors that predict disclosure enactment strategies. The DD-MM describes how individuals determine whether they will reveal or conceal non-visible health information. Processes of revealing, called disclosures, take various forms including preparation and rehearsal, directness, third-party disclosure, incremental disclosures, entrapment, and indirect mediums (Afifi & Steuber, 2009). We explore the disclosure decision-making process to understand how college students select to disclose their mental illness information with a friend. Participants were 144 students at a Midwestern university who had disclosed their mental illness information to a friend. Structural equation modeling analyses revealed that college students choose strategies based on their evaluation of information assessment and closeness, and that for some strategies, efficacy mediates the relationship between information assessment and strategy. This manuscript discusses implications of findings and suggests direction for future research.

The difference between energy consumption and energy cost: Modelling energy tariff structures for water resource recovery facilities.

PubMed

Aymerich, I; Rieger, L; Sobhani, R; Rosso, D; Corominas, Ll

2015-09-15

The objective of this paper is to demonstrate the importance of incorporating more realistic energy cost models (based on current energy tariff structures) into existing water resource recovery facilities (WRRFs) process models when evaluating technologies and cost-saving control strategies. In this paper, we first introduce a systematic framework to model energy usage at WRRFs and a generalized structure to describe energy tariffs including the most common billing terms. Secondly, this paper introduces a detailed energy cost model based on a Spanish energy tariff structure coupled with a WRRF process model to evaluate several control strategies and provide insights into the selection of the contracted power structure. The results for a 1-year evaluation on a 115,000 population-equivalent WRRF showed monthly cost differences ranging from 7 to 30% when comparing the detailed energy cost model to an average energy price. The evaluation of different aeration control strategies also showed that using average energy prices and neglecting energy tariff structures may lead to biased conclusions when selecting operating strategies or comparing technologies or equipment. The proposed framework demonstrated that for cost minimization, control strategies should be paired with a specific optimal contracted power. Hence, the design of operational and control strategies must take into account the local energy tariff. Copyright © 2015 Elsevier Ltd. All rights reserved.

Model building strategy for logistic regression: purposeful selection.

PubMed

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

An Evaluation of Some Models for Culture-Fair Selection.

ERIC Educational Resources Information Center

Petersen, Nancy S.; Novick, Melvin R.

Models proposed by Cleary, Thorndike, Cole, Linn, Einhorn and Bass, Darlington, and Gross and Su for analyzing bias in the use of tests in a selection strategy are surveyed. Several additional models are also introduced. The purpose is to describe, compare, contrast, and evaluate these models while extracting such useful ideas as may be found in…

Selective attention in multi-chip address-event systems.

PubMed

Bartolozzi, Chiara; Indiveri, Giacomo

2009-01-01

Selective attention is the strategy used by biological systems to cope with the inherent limits in their available computational resources, in order to efficiently process sensory information. The same strategy can be used in artificial systems that have to process vast amounts of sensory data with limited resources. In this paper we present a neuromorphic VLSI device, the "Selective Attention Chip" (SAC), which can be used to implement these models in multi-chip address-event systems. We also describe a real-time sensory-motor system, which integrates the SAC with a dynamic vision sensor and a robotic actuator. We present experimental results from each component in the system, and demonstrate how the complete system implements a real-time stimulus-driven selective attention model.

A Grounded Theory of Behavior Management Strategy Selection, Implementation, and Perceived Effectiveness Reported by First-Year Elementary Teachers

ERIC Educational Resources Information Center

Smart, Julie B.; Igo, L. Brent

2010-01-01

In this grounded theory study, 19 teachers were interviewed and then, in constant comparative fashion, the interview data were analyzed. The theoretical model that emerged from the data describes novice teachers' tendencies to select and implement differing strategies related to the severity of student behavior. When confronting mild student…

'Chain pooling' model selection as developed for the statistical analysis of a rotor burst protection experiment

NASA Technical Reports Server (NTRS)

Holms, A. G.

1977-01-01

A statistical decision procedure called chain pooling had been developed for model selection in fitting the results of a two-level fixed-effects full or fractional factorial experiment not having replication. The basic strategy included the use of one nominal level of significance for a preliminary test and a second nominal level of significance for the final test. The subject has been reexamined from the point of view of using as many as three successive statistical model deletion procedures in fitting the results of a single experiment. The investigation consisted of random number studies intended to simulate the results of a proposed aircraft turbine-engine rotor-burst-protection experiment. As a conservative approach, population model coefficients were chosen to represent a saturated 2 to the 4th power experiment with a distribution of parameter values unfavorable to the decision procedures. Three model selection strategies were developed.

Determining the Ideal Strategy for Ventilator-associated Pneumonia Prevention. Cost-Benefit Analysis.

PubMed

Branch-Elliman, Westyn; Wright, Sharon B; Howell, Michael D

2015-07-01

Ventilator-associated pneumonia (VAP) is a common healthcare-associated infection with high associated cost and poor patient outcomes. Many strategies for VAP reduction have been evaluated. However, the combination of strategies with the optimal cost-benefit ratio remains unknown. To determine the preferred VAP prevention strategy, both from the hospital and societal perspectives. A cost-benefit decision model with a Markov model was constructed. Baseline probability of VAP, death, reintubation, and discharge from the intensive care unit (ICU) alive were ascertained from clinical trial data. Model inputs were obtained from the medical literature and the U.S. Department of Labor; a device cost was obtained from the manufacturer. Sensitivity analyses were completed to test the robustness of model results. Overall least expensive strategy and the strategy with the best cost-benefit ratio, up to a willingness to pay threshold of $50,000-100,000 per case of VAP averted was sought. We examined a total of 120 unique combinations of VAP prevention strategies. The preferred strategy from the hospital perspective included subglottic suction endotracheal tubes, probiotics, and the Institute for Healthcare Improvement VAP Prevention Bundle. The preferred strategy from the point of view of society also included additional prevention measures (oral care with chlorhexidine and selective oral decontamination). No preferred strategies included silver endotracheal tubes or selective gut decontamination. Despite their infrequent use, current data suggest that the use of prophylactic probiotics and subglottic endotracheal tubes are cost-effective for preventing VAP from the societal and hospital perspectives.

Cooperation and charity in spatial public goods game under different strategy update rules

NASA Astrophysics Data System (ADS)

Li, Yixiao; Jin, Xiaogang; Su, Xianchuang; Kong, Fansheng; Peng, Chengbin

2010-03-01

Human cooperation can be influenced by other human behaviors and recent years have witnessed the flourishing of studying the coevolution of cooperation and punishment, yet the common behavior of charity is seldom considered in game-theoretical models. In this article, we investigate the coevolution of altruistic cooperation and egalitarian charity in spatial public goods game, by considering charity as the behavior of reducing inter-individual payoff differences. Our model is that, in each generation of the evolution, individuals play games first and accumulate payoff benefits, and then each egalitarian makes a charity donation by payoff transfer in its neighborhood. To study the individual-level evolutionary dynamics, we adopt different strategy update rules and investigate their effects on charity and cooperation. These rules can be classified into two global rules: random selection rule in which individuals randomly update strategies, and threshold selection rule where only those with payoffs below a threshold update strategies. Simulation results show that random selection enhances the cooperation level, while threshold selection lowers the threshold of the multiplication factor to maintain cooperation. When charity is considered, it is incapable in promoting cooperation under random selection, whereas it promotes cooperation under threshold selection. Interestingly, the evolution of charity strongly depends on the dispersion of payoff acquisitions of the population, which agrees with previous results. Our work may shed light on understanding human egalitarianism.

Prediction of hydrographs and flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?

NASA Astrophysics Data System (ADS)

Pool, Sandra; Viviroli, Daniel; Seibert, Jan

2017-11-01

Applications of runoff models usually rely on long and continuous runoff time series for model calibration. However, many catchments around the world are ungauged and estimating runoff for these catchments is challenging. One approach is to perform a few runoff measurements in a previously fully ungauged catchment and to constrain a runoff model by these measurements. In this study we investigated the value of such individual runoff measurements when taken at strategic points in time for applying a bucket-type runoff model (HBV) in ungauged catchments. Based on the assumption that a limited number of runoff measurements can be taken, we sought the optimal sampling strategy (i.e. when to measure the streamflow) to obtain the most informative data for constraining the runoff model. We used twenty gauged catchments across the eastern US, made the assumption that these catchments were ungauged, and applied different runoff sampling strategies. All tested strategies consisted of twelve runoff measurements within one year and ranged from simply using monthly flow maxima to a more complex selection of observation times. In each case the twelve runoff measurements were used to select 100 best parameter sets using a Monte Carlo calibration approach. Runoff simulations using these 'informed' parameter sets were then evaluated for an independent validation period in terms of the Nash-Sutcliffe efficiency of the hydrograph and the mean absolute relative error of the flow-duration curve. Model performance measures were normalized by relating them to an upper and a lower benchmark representing a well-informed and an uninformed model calibration. The hydrographs were best simulated with strategies including high runoff magnitudes as opposed to the flow-duration curves that were generally better estimated with strategies that captured low and mean flows. The choice of a sampling strategy covering the full range of runoff magnitudes enabled hydrograph and flow-duration curve simulations close to a well-informed model calibration. The differences among such strategies covering the full range of runoff magnitudes were small indicating that the exact choice of a strategy might be less crucial. Our study corroborates the information value of a small number of strategically selected runoff measurements for simulating runoff with a bucket-type runoff model in almost ungauged catchments.

Effects of parceling on model selection: Parcel-allocation variability in model ranking.

PubMed

Sterba, Sonya K; Rights, Jason D

2017-03-01

Research interest often lies in comparing structural model specifications implying different relationships among latent factors. In this context parceling is commonly accepted, assuming the item-level measurement structure is well known and, conservatively, assuming items are unidimensional in the population. Under these assumptions, researchers compare competing structural models, each specified using the same parcel-level measurement model. However, little is known about consequences of parceling for model selection in this context-including whether and when model ranking could vary across alternative item-to-parcel allocations within-sample. This article first provides a theoretical framework that predicts the occurrence of parcel-allocation variability (PAV) in model selection index values and its consequences for PAV in ranking of competing structural models. These predictions are then investigated via simulation. We show that conditions known to manifest PAV in absolute fit of a single model may or may not manifest PAV in model ranking. Thus, one cannot assume that low PAV in absolute fit implies a lack of PAV in ranking, and vice versa. PAV in ranking is shown to occur under a variety of conditions, including large samples. To provide an empirically supported strategy for selecting a model when PAV in ranking exists, we draw on relationships between structural model rankings in parcel- versus item-solutions. This strategy employs the across-allocation modal ranking. We developed software tools for implementing this strategy in practice, and illustrate them with an example. Even if a researcher has substantive reason to prefer one particular allocation, investigating PAV in ranking within-sample still provides an informative sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Conducting field studies for testing pesticide leaching models

USGS Publications Warehouse

Smith, Charles N.; Parrish, Rudolph S.; Brown, David S.

1990-01-01

A variety of predictive models are being applied to evaluate the transport and transformation of pesticides in the environment. These include well known models such as the Pesticide Root Zone Model (PRZM), the Risk of Unsaturated-Saturated Transport and Transformation Interactions for Chemical Concentrations Model (RUSTIC) and the Groundwater Loading Effects of Agricultural Management Systems Model (GLEAMS). The potentially large impacts of using these models as tools for developing pesticide management strategies and regulatory decisions necessitates development of sound model validation protocols. This paper offers guidance on many of the theoretical and practical problems encountered in the design and implementation of field-scale model validation studies. Recommendations are provided for site selection and characterization, test compound selection, data needs, measurement techniques, statistical design considerations and sampling techniques. A strategy is provided for quantitatively testing models using field measurements.

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.

Development of a targeted transgenesis strategy in highly differentiated cells: a powerful tool for functional genomic analysis.

PubMed

Puttini, Stefania; Ouvrard-Pascaud, Antoine; Palais, Gael; Beggah, Ahmed T; Gascard, Philippe; Cohen-Tannoudji, Michel; Babinet, Charles; Blot-Chabaud, Marcel; Jaisser, Frederic

2005-03-16

Functional genomic analysis is a challenging step in the so-called post-genomic field. Identification of potential targets using large-scale gene expression analysis requires functional validation to identify those that are physiologically relevant. Genetically modified cell models are often used for this purpose allowing up- or down-expression of selected targets in a well-defined and if possible highly differentiated cell type. However, the generation of such models remains time-consuming and expensive. In order to alleviate this step, we developed a strategy aimed at the rapid and efficient generation of genetically modified cell lines with conditional, inducible expression of various target genes. Efficient knock-in of various constructs, called targeted transgenesis, in a locus selected for its permissibility to the tet inducible system, was obtained through the stimulation of site-specific homologous recombination by the meganuclease I-SceI. Our results demonstrate that targeted transgenesis in a reference inducible locus greatly facilitated the functional analysis of the selected recombinant cells. The efficient screening strategy we have designed makes possible automation of the transfection and selection steps. Furthermore, this strategy could be applied to a variety of highly differentiated cells.

Optimum allocation of test resources and comparison of breeding strategies for hybrid wheat.

PubMed

Longin, C Friedrich H; Mi, Xuefei; Melchinger, Albrecht E; Reif, Jochen C; Würschum, Tobias

2014-10-01

The use of a breeding strategy combining the evaluation of line per se with testcross performance maximizes annual selection gain for hybrid wheat breeding. Recent experimental studies confirmed a high commercial potential for hybrid wheat requiring the design of optimum breeding strategies. Our objectives were to (1) determine the optimum allocation of the type and number of testers, the number of test locations and the number of doubled haploid lines for different breeding strategies, (2) identify the best breeding strategy and (3) elaborate key parameters for an efficient hybrid wheat breeding program. We performed model calculations using the selection gain for grain yield as target variable to optimize the number of lines, testers and test locations in four different breeding strategies. A breeding strategy (BS2) combining the evaluation of line per se performance and general combining ability (GCA) had a far larger annual selection gain across all considered scenarios than a breeding strategy (BS1) focusing only on GCA. In the combined strategy, the production of testcross seed conducted in parallel with the first yield trial for line per se performance (BS2rapid) resulted in a further increase of the annual selection gain. For the current situation in hybrid wheat, this relative superiority of the strategy BS2rapid amounted to 67 % in annual selection gain compared to BS1. Varying a large number of parameters, we identified the high costs for hybrid seed production and the low variance of GCA in hybrid wheat breeding as key parameters limiting selection gain in BS2rapid.

Bet-hedging as a complex interaction among developmental instability, environmental heterogeneity, dispersal, and life-history strategy.

PubMed

Scheiner, Samuel M

2014-02-01

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.

A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection

PubMed Central

Sale, Mark; Sherer, Eric A

2015-01-01

The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection. PMID:23772792

Older partner selection promotes the prevalence of cooperation in evolutionary games.

PubMed

Yang, Guoli; Huang, Jincai; Zhang, Weiming

2014-10-21

Evolutionary games typically come with the interplays between evolution of individual strategy and adaptation to network structure. How these dynamics in the co-evolution promote (or obstruct) the cooperation is regarded as an important topic in social, economic, and biological fields. Combining spatial selection with partner choice, the focus of this paper is to identify which neighbour should be selected as a role to imitate during the process of co-evolution. Age, an internal attribute and kind of local piece of information regarding the survivability of the agent, is a significant consideration for the selection strategy. The analysis and simulations presented, demonstrate that older partner selection for strategy imitation could foster the evolution of cooperation. The younger partner selection, however, may decrease the level of cooperation. Our model highlights the importance of agent׳s age on the promotion of cooperation in evolutionary games, both efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Plausible combinations: An improved method to evaluate the covariate structure of Cormack-Jolly-Seber mark-recapture models

USGS Publications Warehouse

Bromaghin, Jeffrey F.; McDonald, Trent L.; Amstrup, Steven C.

2013-01-01

Mark-recapture models are extensively used in quantitative population ecology, providing estimates of population vital rates, such as survival, that are difficult to obtain using other methods. Vital rates are commonly modeled as functions of explanatory covariates, adding considerable flexibility to mark-recapture models, but also increasing the subjectivity and complexity of the modeling process. Consequently, model selection and the evaluation of covariate structure remain critical aspects of mark-recapture modeling. The difficulties involved in model selection are compounded in Cormack-Jolly- Seber models because they are composed of separate sub-models for survival and recapture probabilities, which are conceptualized independently even though their parameters are not statistically independent. The construction of models as combinations of sub-models, together with multiple potential covariates, can lead to a large model set. Although desirable, estimation of the parameters of all models may not be feasible. Strategies to search a model space and base inference on a subset of all models exist and enjoy widespread use. However, even though the methods used to search a model space can be expected to influence parameter estimation, the assessment of covariate importance, and therefore the ecological interpretation of the modeling results, the performance of these strategies has received limited investigation. We present a new strategy for searching the space of a candidate set of Cormack-Jolly-Seber models and explore its performance relative to existing strategies using computer simulation. The new strategy provides an improved assessment of the importance of covariates and covariate combinations used to model survival and recapture probabilities, while requiring only a modest increase in the number of models on which inference is based in comparison to existing techniques.

Prestige-Oriented Market Entry Strategy: The Case of Australian Universities

ERIC Educational Resources Information Center

Tayar, Mark; Jack, Robert

2013-01-01

Through an exploratory case study of four Australian universities this article finds that foreign market entry strategies are shaped by prestige-seeking motivations and a culture of risk aversion. From the market selection, entry mode and higher education literature, a conceptual model, embedded with four propositions, is presented. The model sees…

Bet hedging based cooperation can limit kin selection and form a basis for mutualism.

PubMed

Uitdehaag, Joost C M

2011-07-07

Mutualism is a mechanism of cooperation in which partners that differ help each other. As such, mutualism opposes mechanisms of kin selection and tag-based selection (for example the green beard mechanism), which are based on giving exclusive help to partners that are related or carry the same tag. In contrast to kin selection, which is a basis for parochialism and intergroup warfare, mutualism can therefore be regarded as a mechanism that drives peaceful coexistence between different groups and individuals. Here the competition between mutualism and kin (tag) selection is studied. In a model where kin selection and tag-based selection are dominant, mutualism is promoted by introducing environmental fluctuations. These fluctuations cause reduction in reproductive success by the mechanism of variance discount. The best strategy to counter variance discount is to share with agents who experience the most anticorrelated fluctuations, a strategy called bet hedging. In this way, bet hedging stimulates cooperation with the most unrelated partners, which is a basis for mutualism. Analytic results and simulations reveal that, if this effect is large enough, mutualistic strategies can dominate kin selective strategies. In addition, mutants of these mutualistic strategies that experience fluctuations that are more anticorrelated to their partner, can outcompete wild type, which can lead to the evolution of specialization. In this way, the evolutionary success of mutualistic strategies can be explained by bet hedging-based cooperation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Children's selective trust decisions: rational competence and limiting performance factors.

PubMed

Hermes, Jonas; Behne, Tanya; Bich, Anna Elisa; Thielert, Christa; Rakoczy, Hannes

2018-03-01

Recent research has amply documented that even preschoolers learn selectively from others, preferring, for example, reliable over unreliable and competent over incompetent models. It remains unclear, however, what the cognitive foundations of such selective learning are, in particular, whether it builds on rational inferences or on less sophisticated processes. The current study, therefore, was designed to test directly the possibility that children are in principle capable of selective learning based on rational inference, yet revert to simpler strategies such as global impression formation under certain circumstances. Preschoolers (N = 75) were shown pairs of models that either differed in their degree of competence within one domain (strong vs. weak or knowledgeable vs. ignorant) or were both highly competent, but in different domains (e.g., strong vs. knowledgeable model). In the test trials, children chose between the models for strength- or knowledge-related tasks. The results suggest that, in fact, children are capable of rational inference-based selective trust: when both models were highly competent, children preferred the model with the competence most predictive and relevant for a given task. However, when choosing between two models that differed in competence on one dimension, children reverted to halo-style wide generalizations and preferred the competent models for both relevant and irrelevant tasks. These findings suggest that the rational strategies for selective learning, that children master in principle, can get masked by various performance factors. © 2017 John Wiley & Sons Ltd.

The cost-effectiveness of two strategies for vaccinating US veterans with hepatitis C virus infection against hepatitis A and hepatitis B viruses.

PubMed

Jakiche, Rita; Borrego, Matthew E; Raisch, Dennis W; Gupchup, Gireesh V; Pai, Manjunath A; Jakiche, Antoine

2007-01-01

Although hepatitis A and B vaccinations are recommended for patients with chronic hepatitis C virus (HCV), the ideal vaccination strategy has not been determined. Our objective was to model the cost-effectiveness of two strategies for vaccinating patients with HCV infection against hepatitis A (HAV) and hepatitis B (HBV) viruses. The strategies evaluated were: universal vaccination with the combined HAV and HBV vaccine, and selective vaccination based on immunity determined by blood testing. A decision tree model was constructed to compare the cost-effectiveness of the two vaccination strategies from the New Mexico Veterans Affairs Health Care System (NMVAHCS) perspective. A retrospective review of all HCV patients (2517 subjects) at the NMVAHCS was performed to extract prevalence of immunity to HAV and HBV, and prevalence of decompensated liver disease. Literature review was performed to obtain other probabilities for the model. Only direct medical costs were considered; the effectiveness measure was the number of patients immune to both HAV and HBV. Sensitivity analyses were performed to test robustness of the results to changes in input variables. All costs were in 2004 US dollars. The selective strategy was less costly but less effective, with a cost-effectiveness ratio of 105 dollars per patient immune to HAV and HBV. The universal strategy was more effective but more expensive with a cost-effectiveness ratio of 112 dollars per patient immune to HAV and HBV. Compared with the selective strategy, universal strategy was associated with an incremental cost-effectiveness (ICE) ratio of 154 dollars per additional patient immune to HAV and HBV. The universal strategy would become more cost-effective if 1) the cost of combined vaccine was reduced to less than 30.75 dollars (9.7% reduction), 2) the cost of HBV vaccine increased to greater than 34.50 dollars (25% increase), 3) the cost of blood tests for immunity increased to more than 25.25 dollars (23% increase), or (4) the prevalence of anti-HBs decreased to less than 24%. The selective vaccination strategy for HAV and HBV in our sample of patients with HCV is more cost-effective. However, the universal strategy is more effective and its ICE is minimal, thus it may be worth the additional cost.

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

Stability of a Model Explaining Selected Extramusical Influences on Solo and Small-Ensemble Festival Ratings

ERIC Educational Resources Information Center

Bergee, Martin J.; Westfall, Claude R.

2005-01-01

This is the third study in a line of inquiry whose purpose has been to develop a theoretical model of selected extra musical variables' influence on solo and small-ensemble festival ratings. Authors of the second of these (Bergee & McWhirter, 2005) had used binomial logistic regression as the basis for their model-formulation strategy. Their…

Evaluating data worth for ground-water management under uncertainty

USGS Publications Warehouse

Wagner, B.J.

1999-01-01

A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models-a chance-constrained ground-water management model and an integer-programing sampling network design model-to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information-i.e., the projected reduction in management costs-with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models - a chance-constrained ground-water management model and an integer-programming sampling network design model - to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information - i.e., the projected reduction in management costs - with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Ensemble of surrogates-based optimization for identifying an optimal surfactant-enhanced aquifer remediation strategy at heterogeneous DNAPL-contaminated sites

NASA Astrophysics Data System (ADS)

Jiang, Xue; Lu, Wenxi; Hou, Zeyu; Zhao, Haiqing; Na, Jin

2015-11-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

Ensemble of Surrogates-based Optimization for Identifying an Optimal Surfactant-enhanced Aquifer Remediation Strategy at Heterogeneous DNAPL-contaminated Sites

NASA Astrophysics Data System (ADS)

Lu, W., Sr.; Xin, X.; Luo, J.; Jiang, X.; Zhang, Y.; Zhao, Y.; Chen, M.; Hou, Z.; Ouyang, Q.

2015-12-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

An adaptive model order reduction by proper snapshot selection for nonlinear dynamical problems

NASA Astrophysics Data System (ADS)

Nigro, P. S. B.; Anndif, M.; Teixeira, Y.; Pimenta, P. M.; Wriggers, P.

2016-04-01

Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD).

Trophic Strategies of Unicellular Plankton.

PubMed

Chakraborty, Subhendu; Nielsen, Lasse Tor; Andersen, Ken H

2017-04-01

Unicellular plankton employ trophic strategies ranging from pure photoautotrophs over mixotrophy to obligate heterotrophs (phagotrophs), with cell sizes from 10 -8 to 1 μg C. A full understanding of how trophic strategy and cell size depend on resource environment and predation is lacking. To this end, we develop and calibrate a trait-based model for unicellular planktonic organisms characterized by four traits: cell size and investments in phototrophy, nutrient uptake, and phagotrophy. We use the model to predict how optimal trophic strategies depend on cell size under various environmental conditions, including seasonal succession. We identify two mixotrophic strategies: generalist mixotrophs investing in all three investment traits and obligate mixotrophs investing only in phototrophy and phagotrophy. We formulate two conjectures: (1) most cells are limited by organic carbon; however, small unicellulars are colimited by organic carbon and nutrients, and only large photoautotrophs and smaller mixotrophs are nutrient limited; (2) trophic strategy is bottom-up selected by the environment, while optimal size is top-down selected by predation. The focus on cell size and trophic strategies facilitates general insights into the strategies of a broad class of organisms in the size range from micrometers to millimeters that dominate the primary and secondary production of the world's oceans.

A biologically inspired meta-control navigation system for the Psikharpax rat robot.

PubMed

Caluwaerts, K; Staffa, M; N'Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

2012-06-01

A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment-recognized as new contexts-and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics.

Modeling the language learning strategies and English language proficiency of pre-university students in UMS: A case study

NASA Astrophysics Data System (ADS)

Kiram, J. J.; Sulaiman, J.; Swanto, S.; Din, W. A.

2015-10-01

This study aims to construct a mathematical model of the relationship between a student's Language Learning Strategy usage and English Language proficiency. Fifty-six pre-university students of University Malaysia Sabah participated in this study. A self-report questionnaire called the Strategy Inventory for Language Learning was administered to them to measure their language learning strategy preferences before they sat for the Malaysian University English Test (MUET), the results of which were utilised to measure their English language proficiency. We attempted the model assessment specific to Multiple Linear Regression Analysis subject to variable selection using Stepwise regression. We conducted various assessments to the model obtained, including the Global F-test, Root Mean Square Error and R-squared. The model obtained suggests that not all language learning strategies should be included in the model in an attempt to predict Language Proficiency.

Policy Building--An Extension to User Modeling

ERIC Educational Resources Information Center

Yudelson, Michael V.; Brunskill, Emma

2012-01-01

In this paper we combine a logistic regression student model with an exercise selection procedure. As opposed to the body of prior work on strategies for selecting practice opportunities, we are working on an assumption of a finite amount of opportunities to teach the student. Our goal is to prescribe activities that would maximize the amount…

Learning Strategy Selection in the Water Maze and Hippocampal CREB Phosphorylation Differ in Two Inbred Strains of Mice

ERIC Educational Resources Information Center

Sung, Jin-Young; Goo, June-Seo; Lee, Dong-Eun; Jin, Da-Qing; Bizon, Jennifer L.; Gallagher, Michela; Han, Jung-Soo

2008-01-01

Learning strategy selection was assessed in two different inbred strains of mice, C57BL/6 and DBA/2, which are used for developing genetically modified mouse models. Male mice received a training protocol in a water maze using alternating blocks of visible and hidden platform trials, during which mice escaped to a single location. After training,…

A comparison of WEC control strategies

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

Wilson, David G.; Bacelli, Giorgio; Coe, Ryan Geoffrey

2016-04-01

The operation of Wave Energy Converter (WEC) devices can pose many challenging problems to the Water Power Community. A key research question is how to significantly improve the performance of these WEC devices through improving the control system design. This report summarizes an effort to analyze and improve the performance of WEC through the design and implementation of control systems. Controllers were selected to span the WEC control design space with the aim of building a more comprehensive understanding of different controller capabilities and requirements. To design and evaluate these control strategies, a model scale test-bed WEC was designed formore » both numerical and experimental testing (see Section 1.1). Seven control strategies have been developed and applied on a numerical model of the selected WEC. This model is capable of performing at a range of levels, spanning from a fully-linear realization to varying levels of nonlinearity. The details of this model and its ongoing development are described in Section 1.2.« less

Value-added strategy models to provide quality services in senior health business.

PubMed

Yang, Ya-Ting; Lin, Neng-Pai; Su, Shyi; Chen, Ya-Mei; Chang, Yao-Mao; Handa, Yujiro; Khan, Hafsah Arshed Ali; Elsa Hsu, Yi-Hsin

2017-06-20

The rapid population aging is now a global issue. The increase in the elderly population will impact the health care industry and health enterprises; various senior needs will promote the growth of the senior health industry. Most senior health studies are focused on the demand side and scarcely on supply. Our study selected quality enterprises focused on aging health and analyzed different strategies to provide excellent quality services to senior health enterprises. We selected 33 quality senior health enterprises in Taiwan and investigated their excellent quality services strategies by face-to-face semi-structured in-depth interviews with CEO and managers of each enterprise in 2013. A total of 33 senior health enterprises in Taiwan. Overall, 65 CEOs and managers of 33 enterprises were interviewed individually. None. Core values and vision, organization structure, quality services provided, strategies for quality services. This study's results indicated four type of value-added strategy models adopted by senior enterprises to offer quality services: (i) residential care and co-residence model, (ii) home care and living in place model, (iii) community e-business experience model and (iv) virtual and physical portable device model. The common part in these four strategy models is that the services provided are elderly centered. These models offer virtual and physical integrations, and also offer total solutions for the elderly and their caregivers. Through investigation of successful strategy models for providing quality services to seniors, we identified opportunities to develop innovative service models and successful characteristics, also policy implications were summarized. The observations from this study will serve as a primary evidenced base for enterprises developing their senior market and, also for promoting the value co-creation possibility through dialogue between customers and those that deliver service. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Competency criteria and the class inclusion task: modeling judgments and justifications.

PubMed

Thomas, H; Horton, J J

1997-11-01

Preschool age children's class inclusion task responses were modeled as mixtures of different probability distributions. The main idea: Different response strategies are equivalent to different probability distributions. A child displays cognitive strategy s if P (child uses strategy s, given the child's observed score X = x) = p(s) is the most probable strategy. The general approach is widely applicable to many settings. Both judgment and justification questions were asked. Judgment response strategies identified were subclass comparison, guessing, and inclusion logic. Children's justifications lagged their judgments in development. Although justification responses may be useful, C. J. Brainerd was largely correct: If a single response variable is to be selected, a judgments variable is likely the preferable one. But the process must be modeled to identify cognitive strategies, as B. Hodkin has demonstrated.

A game-based decision support methodology for competitive systems design

NASA Astrophysics Data System (ADS)

Briceno, Simon Ignacio

This dissertation describes the development of a game-based methodology that facilitates the exploration and selection of research and development (R&D) projects under uncertain competitive scenarios. The proposed method provides an approach that analyzes competitor positioning and formulates response strategies to forecast the impact of technical design choices on a project's market performance. A critical decision in the conceptual design phase of propulsion systems is the selection of the best architecture, centerline, core size, and technology portfolio. This selection can be challenging when considering evolving requirements from both the airframe manufacturing company and the airlines in the market. Furthermore, the exceedingly high cost of core architecture development and its associated risk makes this strategic architecture decision the most important one for an engine company. Traditional conceptual design processes emphasize performance and affordability as their main objectives. These areas alone however, do not provide decision-makers with enough information as to how successful their engine will be in a competitive market. A key objective of this research is to examine how firm characteristics such as their relative differences in completing R&D projects, differences in the degree of substitutability between different project types, and first/second-mover advantages affect their product development strategies. Several quantitative methods are investigated that analyze business and engineering strategies concurrently. In particular, formulations based on the well-established mathematical field of game theory are introduced to obtain insights into the project selection problem. The use of game theory is explored in this research as a method to assist the selection process of R&D projects in the presence of imperfect market information. The proposed methodology focuses on two influential factors: the schedule uncertainty of project completion times and the uncertainty associated with competitive reactions. A normal-form matrix is created to enumerate players, their moves and payoffs, and to formulate a process by which an optimal decision can be achieved. The non-cooperative model is tested using the concept of a Nash equilibrium to identify potential strategies that are robust to uncertain market fluctuations (e.g: uncertainty in airline demand, airframe requirements and competitor positioning). A first/second-mover advantage parameter is used as a scenario dial to adjust market rewards and firms' payoffs. The methodology is applied to a commercial aircraft engine selection study where engine firms must select an optimal engine project for development. An engine modeling and simulation framework is developed to generate a broad engine project portfolio. The creation of a customer value model enables designers to incorporate airline operation characteristics into the engine modeling and simulation process to improve the accuracy of engine/customer matching. Summary. Several key findings are made that provide recommendations on project selection strategies for firms uncertain as to when they will enter the market. The proposed study demonstrates that within a technical design environment, a rational and analytical means of modeling project development strategies is beneficial in high market risk situations.

Managing burned landscapes: Evaluating future management strategies for resilient forests under a warming climate

Treesearch

K. L. Shive; P. Z. Fule; C. H. Sieg; B. A. Strom; M. E. Hunter

2014-01-01

Climate change effects on forested ecosystems worldwide include increases in drought-related mortality, changes to disturbance regimes and shifts in species distributions. Such climate-induced changes will alter the outcomes of current management strategies, complicating the selection of appropriate strategies to promote forest resilience. We modelled forest growth in...

Use of participatory modeling workshops in a water-stressed basin of northern Mexico to assess sustainable water resources management and conduct community outreach

NASA Astrophysics Data System (ADS)

Vivoni, E. R.; Mayer, A. S.; Halvorsen, K. E.; Robles-Morua, A.; Kossak, D.

2016-12-01

A series of iterative participatory modeling workshops were held in Sonora, México with the goal of developing water resources management strategies in a water-stressed basin subject to hydro-climatic variability and change. A model of the water resources system, consisting of watershed hydrology, water resources infrastructure, and groundwater models, was developed deliberatively in the workshops, along with scenarios of future climate and development. Participants used the final version of the water resources systems model to select from supply-side and demand-side water resources management strategies. The performance of the strategies was based on the reliability of meeting current and future demands at a daily time scale over a year's period. Pre- and post-workshop surveys were developed and administered. The survey questions focused on evaluation of participants' modeling capacity and the utility and accuracy of the models. The selected water resources strategies and the associated, expected reliability varied widely among participants. Most participants could be clustered into three groups with roughly equal numbers of participants that varied in terms of reliance on expanding infrastructure vs. demand modification; expectations of reliability; and perceptions of social, environmental, and economic impacts. The wide range of strategies chosen and associated reliabilities indicate that there is a substantial degree of uncertainty in how future water resources decisions could be made in the region. The pre- and post-survey results indicate that participants believed their modeling abilities increased and beliefs in the utility of models increased as a result of the workshops

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

USGS Publications Warehouse

Bastille-Rousseau, Guillaume; Gibbs, James P.; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Fredy; Rousseau, Louis-Philippe

2016-01-01

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Applying model abstraction techniques to optimize monitoring networks for detecting subsurface contaminant transport

USDA-ARS?s Scientific Manuscript database

Improving strategies for monitoring subsurface contaminant transport includes performance comparison of competing models, developed independently or obtained via model abstraction. Model comparison and parameter discrimination involve specific performance indicators selected to better understand s...

Reasoning, learning, and creativity: frontal lobe function and human decision-making.

PubMed

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

PubMed Central

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

Systematic review of management strategies to control chronic wasting disease in wild deer populations in North America.

PubMed

Uehlinger, F D; Johnston, A C; Bollinger, T K; Waldner, C L

2016-08-22

Chronic wasting disease (CWD) is a contagious, fatal prion disease affecting cervids in a growing number of regions across North America. Projected deer population declines and concern about potential spread of CWD to other species warrant strategies to manage this disease. Control efforts to date have been largely unsuccessful, resulting in continuing spread and increasing prevalence. This systematic review summarizes peer-reviewed published reports describing field-applicable CWD control strategies in wild deer populations in North America using systematic review methods. Ten databases were searched for peer-reviewed literature. Following deduplication, relevance screening, full-text appraisal, subject matter expert review and qualitative data extraction, nine references were included describing four distinct management strategies. Six of the nine studies used predictive modeling to evaluate control strategies. All six demonstrated one or more interventions to be effective but results were dependant on parameters and assumptions used in the model. Three found preferential removal of CWD infected deer to be effective in reducing CWD prevalence; one model evaluated a test and slaughter strategy, the other selective removal of infected deer by predators and the third evaluated increased harvest of the sex with highest prevalence (males). Three models evaluated non-selective harvest of deer. There were only three reports that examined primary data collected as part of observational studies. Two of these studies supported the effectiveness of intensive non-selective culling; the third study did not find a difference between areas that were subjected to culling and those that were not. Seven of the nine studies were conducted in the United States. This review highlights the paucity of evaluated, field-applicable control strategies for CWD in wild deer populations. Knowledge gaps in the complex epidemiology of CWD and the intricacies inherent to prion diseases currently pose significant challenges to effective control of this disease in wild deer in North America.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Inference from habitat-selection analysis depends on foraging strategies.

PubMed

Bastille-Rousseau, Guillaume; Fortin, Daniel; Dussault, Christian

2010-11-01

1. Several methods have been developed to assess habitat selection, most of which are based on a comparison between habitat attributes in used vs. unused or random locations, such as the popular resource selection functions (RSFs). Spatial evaluation of residency time has been recently proposed as a promising avenue for studying habitat selection. Residency-time analyses assume a positive relationship between residency time within habitat patches and selection. We demonstrate that RSF and residency-time analyses provide different information about the process of habitat selection. Further, we show how the consideration of switching rate between habitat patches (interpatch movements) together with residency-time analysis can reveal habitat-selection strategies. 2. Spatially explicit, individual-based modelling was used to simulate foragers displaying one of six foraging strategies in a heterogeneous environment. The strategies combined one of three patch-departure rules (fixed-quitting-harvest-rate, fixed-time and fixed-amount strategy), together with one of two interpatch-movement rules (random or biased). Habitat selection of simulated foragers was then assessed using RSF, residency-time and interpatch-movement analyses. 3. Our simulations showed that RSFs and residency times are not always equivalent. When foragers move in a non-random manner and do not increase residency time in richer patches, residency-time analysis can provide misleading assessments of habitat selection. This is because the overall time spent in the various patch types not only depends on residency times, but also on interpatch-movement decisions. 4. We suggest that RSFs provide the outcome of the entire selection process, whereas residency-time and interpatch-movement analyses can be used in combination to reveal the mechanisms behind the selection process. 5. We showed that there is a risk in using residency-time analysis alone to infer habitat selection. Residency-time analyses, however, may enlighten the mechanisms of habitat selection by revealing central components of resource-use strategies. Given that management decisions are often based on resource-selection analyses, the evaluation of resource-use strategies can be key information for the development of efficient habitat-management strategies. Combining RSF, residency-time and interpatch-movement analyses is a simple and efficient way to gain a more comprehensive understanding of habitat selection. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.

Efficient design based on perturbed parameter ensembles to identify plausible and diverse variants of a model for climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.; Sexton, D.; Murphy, J.

2017-12-01

We present exploratory work towards developing an efficient strategy to select variants of a state-of-the-art but expensive climate model suitable for climate projection studies. The strategy combines information from a set of idealized perturbed parameter ensemble (PPE) and CMIP5 multi-model ensemble (MME) experiments, and uses two criteria as basis to select model variants for a PPE suitable for future projections: a) acceptable model performance at two different timescales, and b) maintaining diversity in model response to climate change. We demonstrate that there is a strong relationship between model errors at weather and climate timescales for a variety of key variables. This relationship is used to filter out parts of parameter space that do not give credible simulations of historical climate, while minimizing the impact on ranges in forcings and feedbacks that drive model responses to climate change. We use statistical emulation to explore the parameter space thoroughly, and demonstrate that about 90% can be filtered out without affecting diversity in global-scale climate change responses. This leads to identification of plausible parts of parameter space from which model variants can be selected for projection studies.

Decision method for optimal selection of warehouse material handling strategies by production companies

NASA Astrophysics Data System (ADS)

Dobos, P.; Tamás, P.; Illés, B.

2016-11-01

Adequate establishment and operation of warehouse logistics determines the companies’ competitiveness significantly because it effects greatly the quality and the selling price of the goods that the production companies produce. In order to implement and manage an adequate warehouse system, adequate warehouse position, stock management model, warehouse technology, motivated work force committed to process improvement and material handling strategy are necessary. In practical life, companies have paid small attantion to select the warehouse strategy properly. Although it has a major influence on the production in the case of material warehouse and on smooth costumer service in the case of finished goods warehouse because this can happen with a huge loss in material handling. Due to the dynamically changing production structure, frequent reorganization of warehouse activities is needed, on what the majority of the companies react basically with no reactions. This work presents a simulation test system frames for eligible warehouse material handling strategy selection and also the decision method for selection.

An Experimental Test of a Model for Decision Strategy Selection

DTIC Science & Technology

1977-12-01

University of Washington, Seattle, WA 98195 1l. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE Organizational Effectiveness Research Programg... Controlling Office) IS. SECURITY CLASS, (of this report) UNCLASSI FIED 15. DECLASSIFICATION/DOWNGRADING SCHEDULE 16. DISTRIBUTION STATEMENT (of this Report... Equivalence Interval Decision Maker Cost Curve Strategy Cost Expected Net Utility Effect of the Value of the Perceived Strategy Da ision Strategies Decision on

Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

PubMed Central

Osinga, Hinke M.; Marshall, James A. R.

2015-01-01

It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

PubMed

Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

2018-01-01

Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

A behavioural and neural evaluation of prospective decision-making under risk

PubMed Central

Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J.

2010-01-01

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single choice contexts there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal pre-determined strategy, irrespective of the particular order in which options are presented. An alternative model involves continuously re-evaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of re-evaluating decision utilities, where available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously-acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes. PMID:20980595

A behavioral and neural evaluation of prospective decision-making under risk.

PubMed

Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J

2010-10-27

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single-choice contexts, there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal predetermined strategy, regardless of the particular order in which options are presented. An alternative model involves continuously reevaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of reevaluating decision utilities, in which available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance, and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes.

A model-based 'varimax' sampling strategy for a heterogeneous population.

PubMed

Akram, Nuzhat A; Farooqi, Shakeel R

2014-01-01

Sampling strategies are planned to enhance the homogeneity of a sample, hence to minimize confounding errors. A sampling strategy was developed to minimize the variation within population groups. Karachi, the largest urban agglomeration in Pakistan, was used as a model population. Blood groups ABO and Rh factor were determined for 3000 unrelated individuals selected through simple random sampling. Among them five population groups, namely Balochi, Muhajir, Pathan, Punjabi and Sindhi, based on paternal ethnicity were identified. An index was designed to measure the proportion of admixture at parental and grandparental levels. Population models based on index score were proposed. For validation, 175 individuals selected through stratified random sampling were genotyped for the three STR loci CSF1PO, TPOX and TH01. ANOVA showed significant differences across the population groups for blood groups and STR loci distribution. Gene diversity was higher across the sub-population model than in the agglomerated population. At parental level gene diversities are significantly higher across No admixture models than Admixture models. At grandparental level the difference was not significant. A sub-population model with no admixture at parental level was justified for sampling the heterogeneous population of Karachi.

Space Operations Center orbit altitude selection strategy

NASA Technical Reports Server (NTRS)

Indrikis, J.; Myers, H. L.

1982-01-01

The strategy for the operational altitude selection has to respond to the Space Operation Center's (SOC) maintenance requirements and the logistics demands of the missions to be supported by the SOC. Three orbit strategies are developed: two are constant altitude, and one variable altitude. In order to minimize the effect of atmospheric uncertainty the dynamic altitude method is recommended. In this approach the SOC will operate at the optimum altitude for the prevailing atmospheric conditions and logistics model, provided that mission safety constraints are not violated. Over a typical solar activity cycle this method produces significant savings in the overall logistics cost.

Feature selection in feature network models: finding predictive subsets of features with the Positive Lasso.

PubMed

Frank, Laurence E; Heiser, Willem J

2008-05-01

A set of features is the basis for the network representation of proximity data achieved by feature network models (FNMs). Features are binary variables that characterize the objects in an experiment, with some measure of proximity as response variable. Sometimes features are provided by theory and play an important role in the construction of the experimental conditions. In some research settings, the features are not known a priori. This paper shows how to generate features in this situation and how to select an adequate subset of features that takes into account a good compromise between model fit and model complexity, using a new version of least angle regression that restricts coefficients to be non-negative, called the Positive Lasso. It will be shown that features can be generated efficiently with Gray codes that are naturally linked to the FNMs. The model selection strategy makes use of the fact that FNM can be considered as univariate multiple regression model. A simulation study shows that the proposed strategy leads to satisfactory results if the number of objects is less than or equal to 22. If the number of objects is larger than 22, the number of features selected by our method exceeds the true number of features in some conditions.

Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

PubMed

Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

2014-01-01

The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Implementation strategies for collaborative primary care-mental health models.

PubMed

Franx, Gerdien; Dixon, Lisa; Wensing, Michel; Pincus, Harold

2013-09-01

Extensive research exists that collaborative primary care-mental health models can improve care and outcomes for patients. These programs are currently being implemented throughout the United States and beyond. The purpose of this study is to review the literature and to generate an overview of strategies currently used to implement such models in daily practice. Six overlapping strategies to implement collaborative primary care-mental health models were described in 18 selected studies. We identified interactive educational strategies, quality improvement change processes, technological support tools, stakeholder engagement in the design and execution of implementation plans, organizational changes in terms of expanding the task of nurses and financial strategies such as additional collaboration fees and pay for performance incentives. Considering the overwhelming evidence about the effectiveness of primary care-mental health models, there is a lack of good studies focusing on their implementation strategies. In practice, these strategies are multifaceted and locally defined, as a result of intensive and required stakeholder engagement. Although many barriers still exist, the implementation of collaborative models could have a chance to succeed in the United States, where new service delivery and payment models, such as the Patient-Centered Medical Home, the Health Home and the Accountable Care Organization, are being promoted.

A Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Weissman, Alexander

2006-01-01

A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…

An optimization modeling approach to awarding large fire support wildfire helicopter contracts from the US Forest Service

Treesearch

Stephanie A. Snyder; Keith D. Stockmann; Gaylord E. Morris

2012-01-01

The US Forest Service used contracted helicopter services as part of its wildfire suppression strategy. An optimization decision-modeling system was developed to assist in the contract selection process. Three contract award selection criteria were considered: cost per pound of delivered water, total contract cost, and quality ratings of the aircraft and vendors....

Identification of a Novel and Selective Series of Itk Inhibitors via a Template-Hopping Strategy

PubMed Central

2013-01-01

Inhibition of Itk potentially constitutes a novel, nonsteroidal treatment for asthma and other T-cell mediated diseases. In-house kinase cross-screening resulted in the identification of an aminopyrazole-based series of Itk inhibitors. Initial work on this series highlighted selectivity issues with several other kinases, particularly AurA and AurB. A template-hopping strategy was used to identify a series of aminobenzothiazole Itk inhibitors, which utilized an inherently more selective hinge binding motif. Crystallography and modeling were used to rationalize the observed selectivity. Initial exploration of the SAR around this series identified potent Itk inhibitors in both enzyme and cellular assays. PMID:24900590

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

PubMed

Ließ, Mareike; Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

Heart failure patients' attitudes, beliefs, expectations and experiences of self-management strategies: a qualitative synthesis.

PubMed

Wingham, Jennifer; Harding, Geoff; Britten, Nicky; Dalal, Hayes

2014-06-01

To develop a model of heart failure patients' attitudes, beliefs, expectations, and experiences based on published qualitative research that could influence the development of self-management strategies. A synthesis of 19 qualitative research studies using the method of meta-ethnography. This synthesis offers a conceptual model of the attitudes, beliefs, and expectations of patients with heart failure. Patients experienced a sense of disruption before developing a mental model of heart failure. Patients' reactions included becoming a strategic avoider, a selective denier, a well-intentioned manager, or an advanced self-manager. Patients responded by forming self-management strategies and finally assimilated the strategies into everyday life seeking to feel safe. This conceptual model suggests that there are a range of interplaying factors that facilitate the process of developing self-management strategies. Interventions should take into account patients' concepts of heart failure and their subsequent reactions.

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Solikhin

2016-06-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.

MicroRNA-integrated and network-embedded gene selection with diffusion distance.

PubMed

Huang, Di; Zhou, Xiaobo; Lyon, Christopher J; Hsueh, Willa A; Wong, Stephen T C

2010-10-29

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways.

Selection of trilateral continuums of life history strategies under food web interactions.

PubMed

Fujiwara, Masami

2018-03-14

The study of life history strategies has a long history in ecology and evolution, but determining the underlying mechanisms driving the evolution of life history variation and its consequences for population regulation remains a major challenge. In this study, a food web model with constant environmental conditions was used to demonstrate how multi-species consumer-resource interactions (food-web interactions) can create variation in the duration of the adult stage, age of maturation, and fecundity among species. The model included three key ecological processes: size-dependent species interactions, energetics, and transition among developmental stages. Resultant patterns of life history variation were consistent with previous empirical observations of the life history strategies of aquatic organisms referred to as periodic, equilibrium, and opportunistic strategies (trilateral continuums of life history strategies). Results from the simulation model suggest that these three life history strategies can emerge from food web interactions even when abiotic environmental conditions are held constant.

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

Modelling the Costs and Effects of Selective and Universal Hospital Admission Screening for Methicillin-Resistant Staphylococcus aureus

PubMed Central

Hubben, Gijs; Bootsma, Martin; Luteijn, Michiel; Glynn, Diarmuid; Bishai, David

2011-01-01

Background Screening at hospital admission for carriage of methicillin-resistant Staphylococcus aureus (MRSA) has been proposed as a strategy to reduce nosocomial infections. The objective of this study was to determine the long-term costs and health benefits of selective and universal screening for MRSA at hospital admission, using both PCR-based and chromogenic media-based tests in various settings. Methodology/Principal Findings A simulation model of MRSA transmission was used to determine costs and effects over 15 years from a US healthcare perspective. We compared admission screening together with isolation of identified carriers against a baseline policy without screening or isolation. Strategies included selective screening of high risk patients or universal admission screening, with PCR-based or chromogenic media-based tests, in medium (5%) or high nosocomial prevalence (15%) settings. The costs of screening and isolation per averted MRSA infection were lowest using selective chromogenic-based screening in high and medium prevalence settings, at $4,100 and $10,300, respectively. Replacing the chromogenic-based test with a PCR-based test costs $13,000 and $36,200 per additional infection averted, and subsequent extension to universal screening with PCR would cost $131,000 and $232,700 per additional infection averted, in high and medium prevalence settings respectively. Assuming $17,645 benefit per infection averted, the most cost-saving strategies in high and medium prevalence settings were selective screening with PCR and selective screening with chromogenic, respectively. Conclusions/Significance Admission screening costs $4,100–$21,200 per infection averted, depending on strategy and setting. Including financial benefits from averted infections, screening could well be cost saving. PMID:21483492

Strategies for nest-site selection by king eiders

USGS Publications Warehouse

Bentzen, R.L.; Powell, A.N.; Suydam, R.S.

2009-01-01

Nest site selection is a critical component of reproduction and has presumably evolved in relation to predation, local resources, and microclimate. We investigated nest-site choice by king eiders (Somateria spectabilis) on the coastal plain of northern Alaska, USA, 2003-2005. We hypothesized that nest-site selection is driven by predator avoidance and that a variety of strategies including concealment, seclusion, and conspecific or inter-specific nest defense might lead to improved nesting success. We systematically searched wetland basins for king eider nests and measured habitat and social variables at nests (n = 212) and random locations (n = 493). King eiders made use of both secluded and concealed breeding strategies; logistic regression models revealed that females selected nests close to water, on islands, and in areas with high willow (Salix spp.) cover but did not select sites near conspecific or glaucous gull (Larus hyperboreus) nests. The most effective nest-placement strategy may vary depending on density and types of nest predators; seclusion is likely a mammalian-predator avoidance tactic whereas concealment may provide protection from avian predators. We recommend that managers in northern Alaska attempt to maintain wetland basins with islands and complex shorelines to provide potential nest sites in the vicinity of water. ?? The Wildlife Society.

A global logrank test for adaptive treatment strategies based on observational studies.

PubMed

Li, Zhiguo; Valenstein, Marcia; Pfeiffer, Paul; Ganoczy, Dara

2014-02-28

In studying adaptive treatment strategies, a natural question that is of paramount interest is whether there is any significant difference among all possible treatment strategies. When the outcome variable of interest is time-to-event, we propose an inverse probability weighted logrank test for testing the equivalence of a fixed set of pre-specified adaptive treatment strategies based on data from an observational study. The weights take into account both the possible selection bias in an observational study and the fact that the same subject may be consistent with more than one treatment strategy. The asymptotic distribution of the weighted logrank statistic under the null hypothesis is obtained. We show that, in an observational study where the treatment selection probabilities need to be estimated, the estimation of these probabilities does not have an effect on the asymptotic distribution of the weighted logrank statistic, as long as the estimation of the parameters in the models for these probabilities is n-consistent. Finite sample performance of the test is assessed via a simulation study. We also show in the simulation that the test can be pretty robust to misspecification of the models for the probabilities of treatment selection. The method is applied to analyze data on antidepressant adherence time from an observational database maintained at the Department of Veterans Affairs' Serious Mental Illness Treatment Research and Evaluation Center. Copyright © 2013 John Wiley & Sons, Ltd.

Attention and Cognitive Styles.

ERIC Educational Resources Information Center

Wright, John C.; Vlietstra, Alice G.

This study investigated two methods for establishing a systematic, selective, attending strategy in a memory task for children. One method was direct training of a specific strategy, employing instructions, fading, modeling, and prompts to direct the child's attention to the relevant features and to organize systematic looking behavior. The second…

Randomness and diversity matter in the maintenance of the public resources

NASA Astrophysics Data System (ADS)

Liu, Aizhi; Zhang, Yanling; Chen, Xiaojie; Sun, Changyin

2017-03-01

Most previous models about the public goods game usually assume two possible strategies, i.e., investing all or nothing. The real-life situation is rarely all or nothing. In this paper, we consider that multiple strategies are adopted in a well-mixed population, and each strategy represents an investment to produce the public goods. Past efforts have found that randomness matters in the evolution of fairness in the ultimatum game. In the framework involving no other mechanisms, we study how diversity and randomness influence the average investment of the population defined by the mean value of all individuals' strategies. The level of diversity is increased by increasing the strategy number, and the level of randomness is increased by increasing the mutation probability, or decreasing the population size or the selection intensity. We find that a higher level of diversity and a higher level of randomness lead to larger average investment and favor more the evolution of cooperation. Under weak selection, the average investment changes very little with the strategy number, the population size, and the mutation probability. Under strong selection, the average investment changes very little with the strategy number and the population size, but changes a lot with the mutation probability. Under intermediate selection, the average investment increases significantly with the strategy number and the mutation probability, and decreases significantly with the population size. These findings are meaningful to study how to maintain the public resource.

Initial retrieval sequence and blending strategy

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

Pemwell, D.L.; Grenard, C.E.

1996-09-01

This report documents the initial retrieval sequence and the methodology used to select it. Waste retrieval, storage, pretreatment and vitrification were modeled for candidate single-shell tank retrieval sequences. Performance of the sequences was measured by a set of metrics (for example,high-level waste glass volume, relative risk and schedule).Computer models were used to evaluate estimated glass volumes,process rates, retrieval dates, and blending strategy effects.The models were based on estimates of component inventories and concentrations, sludge wash factors and timing, retrieval annex limitations, etc.

Improving ontology matching with propagation strategy and user feedback

NASA Astrophysics Data System (ADS)

Li, Chunhua; Cui, Zhiming; Zhao, Pengpeng; Wu, Jian; Xin, Jie; He, Tianxu

2015-07-01

Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. The existing approach requires a threshold to produce matching candidates and use a small set of constraints acting as filter to select the final alignments. We introduce novel match propagation strategy to model the influences between potential entity mappings across ontologies, which can help to identify the correct correspondences and produce missed correspondences. The estimation of appropriate threshold is a difficult task. We propose an interactive method for threshold selection through which we obtain an additional measurable improvement. Running experiments on a public dataset has demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

Select Components and Finish System Design of a Window Air Conditioner with Propane

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

Shen, Bo; Abdelaziz, Omar

This report describes the technical targets for developing a high efficiency window air conditioner (WAC) using propane (R-290). The baseline unit selected for this activity is a GE R-410A WAC. We established collaboration with a Chinese rotary compressor manufacturer, to select an R-290 compressor. We first modelled and calibrated the WAC system model using R-410A. Next, we applied the calibrated system model to design the R-290 WAC, and decided the strategies to reduce the system charge below 260 grams and achieve the capacity and efficiency targets.

The dynamics of sex ratio evolution: from the gene perspective to multilevel selection.

PubMed

Argasinski, Krzysztof

2013-01-01

The new dynamical game theoretic model of sex ratio evolution emphasizes the role of males as passive carriers of sex ratio genes. This shows inconsistency between population genetic models of sex ratio evolution and classical strategic models. In this work a novel technique of change of coordinates will be applied to the new model. This will reveal new aspects of the modelled phenomenon which cannot be shown or proven in the original formulation. The underlying goal is to describe the dynamics of selection of particular genes in the entire population, instead of in the same sex subpopulation, as in the previous paper and earlier population genetics approaches. This allows for analytical derivation of the unbiased strategic model from the model with rigorous non-simplified genetics. In effect, an alternative system of replicator equations is derived. It contains two subsystems: the first describes changes in gene frequencies (this is an alternative unbiased formalization of the Fisher-Dusing argument), whereas the second describes changes in the sex ratios in subpopulations of carriers of genes for each strategy. An intriguing analytical result of this work is that the fitness of a gene depends on the current sex ratio in the subpopulation of its carriers, not on the encoded individual strategy. Thus, the argument of the gene fitness function is not constant but is determined by the trajectory of the sex ratio among carriers of that gene. This aspect of the modelled phenomenon cannot be revealed by the static analysis. Dynamics of the sex ratio among gene carriers is driven by a dynamic "tug of war" between female carriers expressing the encoded strategic trait value and random partners of male carriers expressing the average population strategy (a primary sex ratio). This mechanism can be called "double-level selection". Therefore, gene interest perspective leads to multi-level selection.

Analyzing the impact of modeling choices and assumptions in compartmental epidemiological models

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

Nutaro, James J.; Pullum, Laura L.; Ramanathan, Arvind

In this study, computational models have become increasingly used as part of modeling, predicting, and understanding how infectious diseases spread within large populations. These models can be broadly classified into differential equation-based models (EBM) and agent-based models (ABM). Both types of models are central in aiding public health officials design intervention strategies in case of large epidemic outbreaks. We examine these models in the context of illuminating their hidden assumptions and the impact these may have on the model outcomes. Very few ABM/EBMs are evaluated for their suitability to address a particular public health concern, and drawing relevant conclusions aboutmore » their suitability requires reliable and relevant information regarding the different modeling strategies and associated assumptions. Hence, there is a need to determine how the different modeling strategies, choices of various parameters, and the resolution of information for EBMs and ABMs affect outcomes, including predictions of disease spread. In this study, we present a quantitative analysis of how the selection of model types (i.e., EBM vs. ABM), the underlying assumptions that are enforced by model types to model the disease propagation process, and the choice of time advance (continuous vs. discrete) affect the overall outcomes of modeling disease spread. Our study reveals that the magnitude and velocity of the simulated epidemic depends critically on the selection of modeling principles, various assumptions of disease process, and the choice of time advance.« less

Analyzing the impact of modeling choices and assumptions in compartmental epidemiological models

DOE PAGES

Nutaro, James J.; Pullum, Laura L.; Ramanathan, Arvind; ...

2016-05-01

In this study, computational models have become increasingly used as part of modeling, predicting, and understanding how infectious diseases spread within large populations. These models can be broadly classified into differential equation-based models (EBM) and agent-based models (ABM). Both types of models are central in aiding public health officials design intervention strategies in case of large epidemic outbreaks. We examine these models in the context of illuminating their hidden assumptions and the impact these may have on the model outcomes. Very few ABM/EBMs are evaluated for their suitability to address a particular public health concern, and drawing relevant conclusions aboutmore » their suitability requires reliable and relevant information regarding the different modeling strategies and associated assumptions. Hence, there is a need to determine how the different modeling strategies, choices of various parameters, and the resolution of information for EBMs and ABMs affect outcomes, including predictions of disease spread. In this study, we present a quantitative analysis of how the selection of model types (i.e., EBM vs. ABM), the underlying assumptions that are enforced by model types to model the disease propagation process, and the choice of time advance (continuous vs. discrete) affect the overall outcomes of modeling disease spread. Our study reveals that the magnitude and velocity of the simulated epidemic depends critically on the selection of modeling principles, various assumptions of disease process, and the choice of time advance.« less

Analysis of training sample selection strategies for regression-based quantitative landslide susceptibility mapping methods

NASA Astrophysics Data System (ADS)

Erener, Arzu; Sivas, A. Abdullah; Selcuk-Kestel, A. Sevtap; Düzgün, H. Sebnem

2017-07-01

All of the quantitative landslide susceptibility mapping (QLSM) methods requires two basic data types, namely, landslide inventory and factors that influence landslide occurrence (landslide influencing factors, LIF). Depending on type of landslides, nature of triggers and LIF, accuracy of the QLSM methods differs. Moreover, how to balance the number of 0 (nonoccurrence) and 1 (occurrence) in the training set obtained from the landslide inventory and how to select which one of the 1's and 0's to be included in QLSM models play critical role in the accuracy of the QLSM. Although performance of various QLSM methods is largely investigated in the literature, the challenge of training set construction is not adequately investigated for the QLSM methods. In order to tackle this challenge, in this study three different training set selection strategies along with the original data set is used for testing the performance of three different regression methods namely Logistic Regression (LR), Bayesian Logistic Regression (BLR) and Fuzzy Logistic Regression (FLR). The first sampling strategy is proportional random sampling (PRS), which takes into account a weighted selection of landslide occurrences in the sample set. The second method, namely non-selective nearby sampling (NNS), includes randomly selected sites and their surrounding neighboring points at certain preselected distances to include the impact of clustering. Selective nearby sampling (SNS) is the third method, which concentrates on the group of 1's and their surrounding neighborhood. A randomly selected group of landslide sites and their neighborhood are considered in the analyses similar to NNS parameters. It is found that LR-PRS, FLR-PRS and BLR-Whole Data set-ups, with order, yield the best fits among the other alternatives. The results indicate that in QLSM based on regression models, avoidance of spatial correlation in the data set is critical for the model's performance.

Variable speed limit strategies analysis with link transmission model on urban expressway

NASA Astrophysics Data System (ADS)

Li, Shubin; Cao, Danni

2018-02-01

The variable speed limit (VSL) is a kind of active traffic management method. Most of the strategies are used in the expressway traffic flow control in order to ensure traffic safety. However, the urban expressway system is the main artery, carrying most traffic pressure. It has similar traffic characteristics with the expressways between cities. In this paper, the improved link transmission model (LTM) combined with VSL strategies is proposed, based on the urban expressway network. The model can simulate the movement of the vehicles and the shock wave, and well balance the relationship between the amount of calculation and accuracy. Furthermore, the optimal VSL strategy can be proposed based on the simulation method. It can provide management strategies for managers. Finally, a simple example is given to illustrate the model and method. The selected indexes are the average density, the average speed and the average flow on the traffic network in the simulation. The simulation results show that the proposed model and method are feasible. The VSL strategy can effectively alleviate traffic congestion in some cases, and greatly promote the efficiency of the transportation system.

Simultaneously selecting appropriate partners for gaming and strategy adaptation to enhance network reciprocity in the prisoner's dilemma

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-01-01

Network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium in 2 × 2 prisoner's dilemma games. Previous studies have shown that cooperation can be enhanced by using a skewed, rather than a random, selection of partners for either strategy adaptation or the gaming process. Here we show that combining both processes for selecting a gaming partner and an adaptation partner further enhances cooperation, provided that an appropriate selection rule and parameters are adopted. We also show that this combined model significantly enhances cooperation by reducing the degree of activity in the underlying network; we measure the degree of activity with a quantity called effective degree. More precisely, during the initial evolutionary stage in which the global cooperation fraction declines because initially allocated cooperators becoming defectors, the model shows that weak cooperative clusters perish and only a few strong cooperative clusters survive. This finding is the most important key to attaining significant network reciprocity.

Prevention of Methamphetamine Abuse: Can Existing Evidence Inform Community Prevention?

ERIC Educational Resources Information Center

Birckmayer, Johanna; Fisher, Deborah A.; Holder, Harold D.; Yacoubian, George S.

2008-01-01

Little research exists on effective strategies to prevent methamphetamine production, distribution, sales, use, and harm. As a result, prevention practitioners (especially at the local level) have little guidance in selecting potentially effective strategies. This article presents a general causal model of methamphetamine use and harms that…

Strategies for Retaining Minority Students in Higher Education.

ERIC Educational Resources Information Center

Lang, Marvel, Ed.; Ford, Clinita A., Ed.

This volume contains selected papers presented at National Black Student Retention Conferences between 1988 and 1991, that examine ideas concerning educational access and retention. The volume and papers are divided into three groupings which address: (1) The Psycho-Social Implications; (2) Model Strategies and Programs; and (3) Impacts of Faculty…

Iterative Refinement of a Binding Pocket Model: Active Computational Steering of Lead Optimization

PubMed Central

2012-01-01

Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.” Beginning with a small number of molecules, based only on structures and activities, a model was constructed. Compound selection was done computationally, each time making five selections based on confident predictions of high activity and five selections based on a quantitative measure of three-dimensional structural novelty. Compound selection was followed by model refinement using the new data. Iterative computational candidate selection produced rapid improvements in selected compound activity, and incorporation of explicitly novel compounds uncovered much more diverse active inhibitors than strategies lacking active novelty selection. PMID:23046104

UNCERTAINTY ANALYSIS IN WATER QUALITY MODELING USING QUAL2E

EPA Science Inventory

A strategy for incorporating uncertainty analysis techniques (sensitivity analysis, first order error analysis, and Monte Carlo simulation) into the mathematical water quality model QUAL2E is described. The model, named QUAL2E-UNCAS, automatically selects the input variables or p...

Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

PubMed Central

Offman, Marc N; Tournier, Alexander L; Bates, Paul A

2008-01-01

Background Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection. Results In the context of an automatic modelling pipeline, we analysed each step separately, revealing several non-intuitive trends and explored a new strategy for protein conformation sampling using Genetic Algorithms (GA). We apply the concept of alternating evolutionary pressure (AEP), i.e. intermediate rounds within the GA runs where unrestrained, linear growth of the model populations is allowed. Conclusion This approach improves the overall performance of the GA by allowing models to overcome local energy barriers. AEP enabled the selection of the best models in 40% of all targets; compared to 25% for a normal GA. PMID:18673557

Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests.

PubMed

Posada, David; Buckley, Thomas R

2004-10-01

Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow for the estimation of phylogenies and model parameters using all available models (model-averaged inference or multimodel inference). We also describe how the relative importance of the different parameters included in substitution models can be depicted. To illustrate some of these points, we have applied AIC-based model averaging to 37 mitochondrial DNA sequences from the subgenus Ohomopterus(genus Carabus) ground beetles described by Sota and Vogler (2001).

Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models

PubMed Central

Ming, Wei; Xiong, Tao

2014-01-01

The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively. Built upon this hybrid ARIMA-SVMs models alike, this study goes further to extend them into the case of multistep-ahead prediction for air passengers traffic with the two most commonly used multistep-ahead prediction strategies, that is, iterated strategy and direct strategy. Additionally, the effectiveness of data preprocessing approaches, such as deseasonalization and detrending, is investigated and proofed along with the two strategies. Real data sets including four selected airlines' monthly series were collected to justify the effectiveness of the proposed approach. Empirical results demonstrate that the direct strategy performs better than iterative one in long term prediction case while iterative one performs better in the case of short term prediction. Furthermore, both deseasonalization and detrending can significantly improve the prediction accuracy for both strategies, indicating the necessity of data preprocessing. As such, this study contributes as a full reference to the planners from air transportation industries on how to tackle multistep-ahead prediction tasks in the implementation of either prediction strategy. PMID:24723814

Study on the intelligent decision making of soccer robot side-wall behavior

NASA Astrophysics Data System (ADS)

Zhang, Xiaochuan; Shao, Guifang; Tan, Zhi; Li, Zushu

2007-12-01

Side-wall is the static obstacle in soccer robot game, reasonably making use of the Side-wall can improve soccer robot competitive ability. As a kind of artificial life, the Side-wall processing strategy of soccer robot is influenced by many factors, such as game state, field region, attacking and defending situation and so on, each factor also has different influence degree, so, the Side-wall behavior selection is an intelligent selecting process. From the view point of human simulated, based on the idea of Side-wall processing priority[1], this paper builds the priority function for Side-wall processing, constructs the action predicative model for Side-wall obstacle, puts forward the Side-wall processing strategy, and forms the Side-wall behavior selection mechanism. Through the contrasting experiment between the strategy applied and none, proves that this strategy can improve the soccer robot capacity, it is feasible and effective, and has positive meaning for soccer robot stepped study.

Systematic Treatment Selection (STS): A Review and Future Directions

ERIC Educational Resources Information Center

Nguyen, Tam T.; Bertoni, Matteo; Charvat, Mylea; Gheytanchi, Anahita; Beutler, Larry E.

2007-01-01

Systematic Treatment Selection (STS) is a form of technical eclectism that develops and plans treatments using empirically founded principles of psychotherapy. It is a model that provides systematic guidelines for the utilization of different psychotherapeutic strategies based on patient qualities and problem characteristics. Historically, it…

Applying learning theories and instructional design models for effective instruction.

PubMed

Khalil, Mohammed K; Elkhider, Ihsan A

2016-06-01

Faculty members in higher education are involved in many instructional design activities without formal training in learning theories and the science of instruction. Learning theories provide the foundation for the selection of instructional strategies and allow for reliable prediction of their effectiveness. To achieve effective learning outcomes, the science of instruction and instructional design models are used to guide the development of instructional design strategies that elicit appropriate cognitive processes. Here, the major learning theories are discussed and selected examples of instructional design models are explained. The main objective of this article is to present the science of learning and instruction as theoretical evidence for the design and delivery of instructional materials. In addition, this article provides a practical framework for implementing those theories in the classroom and laboratory. Copyright © 2016 The American Physiological Society.

Toward a Multicultural Model of the Stress Process.

ERIC Educational Resources Information Center

Slavin, Lesley A.; And Others

1991-01-01

Attempts to expand Lazarus and Folkman's stress model to include culture-relevant dimensions. Discusses cultural factors that influence each component of the stress model, including types and frequency of events experienced, appraisals of stressfulness of events, appraisals of available coping resources, selection of coping strategies, and…

From information processing to decisions: Formalizing and comparing psychologically plausible choice models.

PubMed

Heck, Daniel W; Hilbig, Benjamin E; Moshagen, Morten

2017-08-01

Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Model uncertainty and multimodel inference in reliability estimation within a longitudinal framework.

PubMed

Alonso, Ariel; Laenen, Annouschka

2013-05-01

Laenen, Alonso, and Molenberghs (2007) and Laenen, Alonso, Molenberghs, and Vangeneugden (2009) proposed a method to assess the reliability of rating scales in a longitudinal context. The methodology is based on hierarchical linear models, and reliability coefficients are derived from the corresponding covariance matrices. However, finding a good parsimonious model to describe complex longitudinal data is a challenging task. Frequently, several models fit the data equally well, raising the problem of model selection uncertainty. When model uncertainty is high one may resort to model averaging, where inferences are based not on one but on an entire set of models. We explored the use of different model building strategies, including model averaging, in reliability estimation. We found that the approach introduced by Laenen et al. (2007, 2009) combined with some of these strategies may yield meaningful results in the presence of high model selection uncertainty and when all models are misspecified, in so far as some of them manage to capture the most salient features of the data. Nonetheless, when all models omit prominent regularities in the data, misleading results may be obtained. The main ideas are further illustrated on a case study in which the reliability of the Hamilton Anxiety Rating Scale is estimated. Importantly, the ambit of model selection uncertainty and model averaging transcends the specific setting studied in the paper and may be of interest in other areas of psychometrics. © 2012 The British Psychological Society.

Application of GRA for Sustainable Material Selection and Evaluation Using LCA

NASA Astrophysics Data System (ADS)

Jayakrishna, Kandasamy; Vinodh, Sekar; Sakthi Sanghvi, Vijayaselvan; Deepika, Chinadurai

2016-07-01

Material selection is identified as a successful key parameter in establishing any product to be sustainable, considering its end of life (EoL) characteristics. An accurate understanding of expected service conditions and environmental considerations are crucial in the selection of material plays a vital role with overwhelming customer expectations and stringent laws. Therefore, this article presents an integrated approach for sustainable material selection using grey relational analysis (GRA) considering the EoL disposal strategies with respect to an automotive product. GRA, an impact evaluation model measures the degree of similarity between the comparability (choice of material) sequence and reference (EoL strategies) sequence based on the relational grade. The ranking result shows that the outranking relationships in the order, ABS-REC > PP-INC > AL-REM > PP-LND > ABS-LND > ABS-INC > PU-LND > AL-REC > AL-LND > PU-INC > AL-INC. The best sustainable material selected was ABS and recycling was selected as the best EoL strategy with the grey relational value of 2.43856. The best material selected by this approach, ABS was evaluated for its viability using life cycle assessment and the estimated impacts also proved the practicability of the selected material highlighting the focus on dehumidification step in the manufacturing of the case product using this developed multi-criteria approach.

Milling strategies evaluation when simulating the forming dies' functional surfaces production

NASA Astrophysics Data System (ADS)

Ižol, Peter; Tomáš, Miroslav; Beňo, Jozef

2016-05-01

The paper deals with selection and evaluation of milling strategies, available in CAM systems and applicable when complicated shape parts are produced, such as forming dies. A method to obtain samples is proposed and this stems from real forming die surface machined by proper strategies. The strategy applicability for the whole part - forming die - is reviewed by the particular specimen evaluation. The presented methodology has been verified by machining model die and comparing it to the production procedure proposed in other CAM systems.

Improving stability of prediction models based on correlated omics data by using network approaches.

PubMed

Tissier, Renaud; Houwing-Duistermaat, Jeanine; Rodríguez-Girondo, Mar

2018-01-01

Building prediction models based on complex omics datasets such as transcriptomics, proteomics, metabolomics remains a challenge in bioinformatics and biostatistics. Regularized regression techniques are typically used to deal with the high dimensionality of these datasets. However, due to the presence of correlation in the datasets, it is difficult to select the best model and application of these methods yields unstable results. We propose a novel strategy for model selection where the obtained models also perform well in terms of overall predictability. Several three step approaches are considered, where the steps are 1) network construction, 2) clustering to empirically derive modules or pathways, and 3) building a prediction model incorporating the information on the modules. For the first step, we use weighted correlation networks and Gaussian graphical modelling. Identification of groups of features is performed by hierarchical clustering. The grouping information is included in the prediction model by using group-based variable selection or group-specific penalization. We compare the performance of our new approaches with standard regularized regression via simulations. Based on these results we provide recommendations for selecting a strategy for building a prediction model given the specific goal of the analysis and the sizes of the datasets. Finally we illustrate the advantages of our approach by application of the methodology to two problems, namely prediction of body mass index in the DIetary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome study (DILGOM) and prediction of response of each breast cancer cell line to treatment with specific drugs using a breast cancer cell lines pharmacogenomics dataset.

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.

Integrated Model to Assess Cloud Deployment Effectiveness When Developing an IT-strategy

NASA Astrophysics Data System (ADS)

Razumnikov, S.; Prankevich, D.

2016-04-01

Developing an IT-strategy of cloud deployment is a complex issue since even the stage of its formation necessitates revealing what applications will be the best possible to meet the requirements of a company business-strategy, evaluate reliability and safety of cloud providers and analyze staff satisfaction. A system of criteria, as well an integrated model to assess cloud deployment effectiveness is offered. The model makes it possible to identify what applications being at the disposal of a company, as well as new tools to be deployed are reliable and safe enough for implementation in the cloud environment. The data on practical use of the procedure to assess cloud deployment effectiveness by a provider of telecommunication services is presented. The model was used to calculate values of integral indexes of services to be assessed, then, ones, meeting the criteria and answering the business-strategy of a company, were selected.

Database Selection: One Size Does Not Fit All.

ERIC Educational Resources Information Center

Allison, DeeAnn; McNeil, Beth; Swanson, Signe

2000-01-01

Describes a strategy for selecting a delivery method for electronic resources based on experiences at the University of Nebraska-Lincoln. Considers local conditions, pricing, feature options, hardware costs, and network availability and presents a model for evaluating the decision based on dollar requirements and local issues. (Author/LRW)

Tuition Pricing and Aid Strategies: A Practical Approach. AIR 1994 Annual Forum Paper.

ERIC Educational Resources Information Center

Fine, Paul L.

This paper examines the applicability of net tuition revenue models for a highly selective, elite priced, private research university in the southern U.S. Pricing and aid strategies for this university seem to be driven by intuitive assumptions about the economy, market forces, needs-blind admissions, student satisfaction, net price…

The aquatic conservation strategy of the Northwest Forest Plan.

Treesearch

Gordon H. Reeves; Jack E. Williams; Kelly M. Burnett; Kirsten Gallo

2006-01-01

Implemented in 1994, the Aquatic Conservation Strategy of the Northwest Forest Plan was designed to restore and maintain ecological processes for aquatic and riparian area conservation on federal lands in the western portion of the Pacific Northwest. We used decision support models to quantitatively evaluate changes in the condition of selected watersheds. In the...

Cost-effectiveness of strategies to prevent methicillin-resistant Staphylococcus aureus transmission and infection in an intensive care unit.

PubMed

Gidengil, Courtney A; Gay, Charlene; Huang, Susan S; Platt, Richard; Yokoe, Deborah; Lee, Grace M

2015-01-01

OBJECTIVE To create a national policy model to evaluate the projected cost-effectiveness of multiple hospital-based strategies to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission and infection. DESIGN Cost-effectiveness analysis using a Markov microsimulation model that simulates the natural history of MRSA acquisition and infection. PATIENTS AND SETTING Hypothetical cohort of 10,000 adult patients admitted to a US intensive care unit. METHODS We compared 7 strategies to standard precautions using a hospital perspective: (1) active surveillance cultures; (2) active surveillance cultures plus selective decolonization; (3) universal contact precautions (UCP); (4) universal chlorhexidine gluconate baths; (5) universal decolonization; (6) UCP + chlorhexidine gluconate baths; and (7) UCP+decolonization. For each strategy, both efficacy and compliance were considered. Outcomes of interest were: (1) MRSA colonization averted; (2) MRSA infection averted; (3) incremental cost per colonization averted; (4) incremental cost per infection averted. RESULTS A total of 1989 cases of colonization and 544 MRSA invasive infections occurred under standard precautions per 10,000 patients. Universal decolonization was the least expensive strategy and was more effective compared with all strategies except UCP+decolonization and UCP+chlorhexidine gluconate. UCP+decolonization was more effective than universal decolonization but would cost $2469 per colonization averted and $9007 per infection averted. If MRSA colonization prevalence decreases from 12% to 5%, active surveillance cultures plus selective decolonization becomes the least expensive strategy. CONCLUSIONS Universal decolonization is cost-saving, preventing 44% of cases of MRSA colonization and 45% of cases of MRSA infection. Our model provides useful guidance for decision makers choosing between multiple available hospital-based strategies to prevent MRSA transmission.

Experimental comparison of residual stresses for a thermomechanical model for the simulation of selective laser melting

DOE PAGES

Hodge, N. E.; Ferencz, R. M.; Vignes, R. M.

2016-05-30

Selective laser melting (SLM) is an additive manufacturing process in which multiple, successive layers of metal powders are heated via laser in order to build a part. Modeling of SLM requires consideration of the complex interaction between heat transfer and solid mechanics. Here, the present work describes the authors initial efforts to validate their first generation model. In particular, the comparison of model-generated solid mechanics results, including both deformation and stresses, is presented. Additionally, results of various perturbations of the process parameters and modeling strategies are discussed.

[Teaching practices and learning strategies in health careers].

PubMed

Carrasco Z, Constanza; Pérez V, Cristhian; Torres A, Graciela; Fasce H, Eduardo

2016-09-01

Medical Education, according to the constructivist education paradigm, puts students as the protagonists of the teaching and learning process. It demands changes in the practice of teaching. However, it is unclear whether this new model is coherent with the teachers’ ways to cope with learning. To analyze the relationship between teaching practices and learning strategies among teachers of health careers in Chilean universities. The Teaching Practices Questionnaire and Learning Strategies Inventory of Schmeck were applied to 200 teachers aged 24 to 72 years (64% females). Teachers use different types of teaching practices. They commonly use deep and elaborative learning strategies. A multiple regression analysis showed that learning strategies had a 13% predictive value to identify student-centered teaching, but they failed to predict teacher-centered teaching. Teaching practices and learning strategies of teachers are related. Teachers frequently select constructivist model strategies, using different teaching practices in their work.

Evolution of Inbreeding Avoidance and Inbreeding Preference through Mate Choice among Interacting Relatives.

PubMed

Duthie, A Bradley; Reid, Jane M

2016-12-01

While extensive population genetic theory predicts conditions favoring evolution of self-fertilization versus outcrossing, there is no analogous theory that predicts conditions favoring evolution of inbreeding avoidance or inbreeding preference enacted through mate choice given obligate biparental reproduction. Multiple interacting processes complicate the dynamics of alleles underlying such inbreeding strategies, including sexual conflict, distributions of kinship, genetic drift, purging of mutation load, direct costs, and restricted kin discrimination. We incorporated these processes into an individual-based model to predict conditions where selection should increase or decrease frequencies of alleles causing inbreeding avoidance or inbreeding preference when females or males controlled mating. Selection for inbreeding avoidance occurred given strong inbreeding depression when either sex chose mates, while selection for inbreeding preference occurred given very weak inbreeding depression when females chose but never occurred when males chose. Selection for both strategies was constrained by direct costs and restricted kin discrimination. Purging was negligible, but allele frequencies were strongly affected by drift in small populations, while selection for inbreeding avoidance was weak in larger populations because inbreeding risk decreased. Therefore, while selection sometimes favored alleles underlying inbreeding avoidance or preference, evolution of such strategies may be much more restricted and stochastic than is commonly presumed.

A Latent Class Approach to Fitting the Weighted Euclidean Model, CLASCAL.

ERIC Educational Resources Information Center

Winsberg, Suzanne; De Soete, Geert

1993-01-01

A weighted Euclidean distance model is proposed that incorporates a latent class approach (CLASCAL). The contribution to the distance function between two stimuli is per dimension weighted identically by all subjects in the same latent class. A model selection strategy is proposed and illustrated. (SLD)

Modeling PPP Economic Benefits for Lunar ISRU

NASA Astrophysics Data System (ADS)

Blair, B.

2017-10-01

A new tool is needed for selecting the PPP strategy that could maximize the rate of lunar commercialization by attracting private capital into the development of critical infrastructure and robust capability. A PPP model under development for NASA-ESO will be described.

Cost-effectiveness of a new urinary biomarker-based risk score compared to standard of care in prostate cancer diagnostics - a decision analytical model.

PubMed

Dijkstra, Siebren; Govers, Tim M; Hendriks, Rianne J; Schalken, Jack A; Van Criekinge, Wim; Van Neste, Leander; Grutters, Janneke P C; Sedelaar, John P Michiel; van Oort, Inge M

2017-11-01

To assess the cost-effectiveness of a new urinary biomarker-based risk score (SelectMDx; MDxHealth, Inc., Irvine, CA, USA) to identify patients for transrectal ultrasonography (TRUS)-guided biopsy and to compare this with the current standard of care (SOC), using only prostate-specific antigen (PSA) to select for TRUS-guided biopsy. A decision tree and Markov model were developed to evaluate the cost-effectiveness of SelectMDx as a reflex test vs SOC in men with a PSA level of >3 ng/mL. Transition probabilities, utilities and costs were derived from the literature and expert opinion. Cost-effectiveness was expressed in quality-adjusted life years (QALYs) and healthcare costs of both diagnostic strategies, simulating the course of patients over a time horizon representing 18 years. Deterministic sensitivity analyses were performed to address uncertainty in assumptions. A diagnostic strategy including SelectMDx with a cut-off chosen at a sensitivity of 95.7% for high-grade prostate cancer resulted in savings of €128 and a gain of 0.025 QALY per patient compared to the SOC strategy. The sensitivity analyses showed that the disutility assigned to active surveillance had a high impact on the QALYs gained and the disutility attributed to TRUS-guided biopsy only slightly influenced the outcome of the model. Based on the currently available evidence, the reduction of over diagnosis and overtreatment due to the use of the SelectMDx test in men with PSA levels of >3 ng/mL may lead to a reduction in total costs per patient and a gain in QALYs. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

PubMed Central

Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction. PMID:27128736

The 'Toolbox' of strategies for managing Haemonchus contortus in goats: What's in and what's out.

PubMed

Kearney, P E; Murray, P J; Hoy, J M; Hohenhaus, M; Kotze, A

2016-04-15

A dynamic and innovative approach to managing the blood-consuming nematode Haemonchus contortus in goats is critical to crack dependence on veterinary anthelmintics. H. contortus management strategies have been the subject of intense research for decades, and must be selected to create a tailored, individualized program for goat farms. Through the selection and combination of strategies from the Toolbox, an effective management program for H. contortus can be designed according to the unique conditions of each particular farm. This Toolbox investigates strategies including vaccines, bioactive forages, pasture/grazing management, behavioural management, natural immunity, FAMACHA, Refugia and strategic drenching, mineral/vitamin supplementation, copper Oxide Wire Particles (COWPs), breeding and selection/selecting resistant and resilient individuals, biological control and anthelmintic drugs. Barbervax(®), the ground-breaking Haemonchus vaccine developed and currently commercially available on a pilot scale for sheep, is prime for trialling in goats and would be an invaluable inclusion to this Toolbox. The specialised behaviours of goats, specifically their preferences to browse a variety of plants and accompanying physiological adaptations to the consumption of secondary compounds contained in browse, have long been unappreciated and thus overlooked as a valuable, sustainable strategy for Haemonchus management. These strategies are discussed in this review as to their value for inclusion into the 'Toolbox' currently, and the future implications of ongoing research for goat producers. Combining and manipulating strategies such as browsing behaviour, pasture management, bioactive forages and identifying and treating individual animals for haemonchosis, in addition to continuous evaluation of strategy effectiveness, is conducted using a model farm scenario. Selecting strategies from the Toolbox, with regard to their current availability, feasibility, economical cost and potential ease of implementation depending on the systems of production and their complementary nature, is the future of managing H. contortus in farmed goats internationally and maintaining the remaining efficacy of veterinary anthelmintics. Copyright © 2016 Elsevier B.V. All rights reserved.

Applying Strategies of Selection, Optimization, and Compensation to Maintain Work Ability-A Psychosocial Resource Complementing the Job Demand-Control Model? Results From the Representative lidA Cohort Study on Work, Age, and Health in Germany.

PubMed

Riedel, Natalie; Müller, Andreas; Ebener, Melanie

2015-05-01

To investigate whether aging employees' selection, optimization, and compensation (SOC) strategies were associated with work ability over and above job demand and control variables, as well as across professions. Multivariable linear regressions were conducted using a representative sample of German employees born in 1959 and 1965 (N = 6057). SOC was assessed to have an independent effect on work ability. Associations of job demands and control variables with work ability were more prominent. The SOC tended to enhance the positive association between decision authority and work ability. Individual strategies of selection, optimization, and compensation could be considered as psychosocial resources adding up to a better work ability and complement prevention programs. Workplace interventions should deal with job demands and control to maintain older employees' work ability in times of working population shrinkage.

Forward vs. backwards selection for seed orchards and cooperative second-generation breeding in the US Pacific Northwest.

Treesearch

R. Johnson; K. Jayawickrama

2003-01-01

Gain from various orchard strategies were modeled. The scenario tested 2,000 first-generation open-pollinated families, from which orchards of 20 selections were formed, using either parents, progeny or both. This was followed by a second-generation breeding population in which 200 full-sib families were tested followed by a second-generation orchard of 20 selections....

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

An efficient adaptive sampling strategy for global surrogate modeling with applications in multiphase flow simulation

NASA Astrophysics Data System (ADS)

Mo, S.; Lu, D.; Shi, X.; Zhang, G.; Ye, M.; Wu, J.

2016-12-01

Surrogate models have shown remarkable computational efficiency in hydrological simulations involving design space exploration, sensitivity analysis, uncertainty quantification, etc. The central task of constructing a global surrogate models is to achieve a prescribed approximation accuracy with as few original model executions as possible, which requires a good design strategy to optimize the distribution of data points in the parameter domains and an effective stopping criterion to automatically terminate the design process when desired approximation accuracy is achieved. This study proposes a novel adaptive sampling strategy, which starts from a small number of initial samples and adaptively selects additional samples by balancing the collection in unexplored regions and refinement in interesting areas. We define an efficient and effective evaluation metric basing on Taylor expansion to select the most promising potential samples from candidate points, and propose a robust stopping criterion basing on the approximation accuracy at new points to guarantee the achievement of desired accuracy. The numerical results of several benchmark analytical functions indicate that the proposed approach is more computationally efficient and robust than the widely used maximin distance design and two other well-known adaptive sampling strategies. The application to two complicated multiphase flow problems further demonstrates the efficiency and effectiveness of our method in constructing global surrogate models for high-dimensional and highly nonlinear problems. Acknowledgements: This work was financially supported by the National Nature Science Foundation of China grants No. 41030746 and 41172206.

History matters: childhood weight trajectories as a basis for planning community-based obesity prevention to adolescents.

PubMed

Ekberg, J; Angbratt, M; Valter, L; Nordvall, M; Timpka, T

2012-04-01

To use epidemiological data and a standardized economic model to compare projected costs for obesity prevention in late adolescence accrued using a cross-sectional weight classification for selecting adolescents at age 15 years compared with a longitudinal classification. All children born in a Swedish county (population 440 000) in 1991 who participated in all regular measurements of height and weight at ages 5, 10 and 15 years (n=4312) were included in the study. The selection strategies were compared by calculating the projected financial load resulting from supply of obesity prevention services from providers at all levels in the health care system. The difference in marginal cost per 1000 children was used as the primary end point for the analyses. Using the cross-sectional selection strategy, 3.8% of adolescents at age 15 years were selected for evaluation by a pediatric specialist, and 96.2% were chosen for population-based interventions. In the trajectory-based strategy, 2.4% of the adolescents were selected for intensive pediatric care, 1.4% for individual clinical interventions in primary health care, 14.0% for individual primary obesity prevention using the Internet and 82.1% for population-based interventions. Costs for the cross-sectional selection strategy were projected to USD463 581 per 1000 adolescents and for the trajectory-based strategy were USD 302 016 per 1000 adolescents. Using projections from epidemiological data, we found that by basing the selection of adolescents for obesity prevention on weight trajectories, the load on highly specialized pediatric care can be reduced by one-third and total health service costs for obesity management among adolescents reduced by one-third. Before use in policies and prevention program planning, our findings warrant confirmation in prospective cost-benefit studies.

Disease Risk Mitigation: The Equivalence of Two Selective Mixing Strategies on Aggregate Contact Patterns & Resulting Epidemic Spread☆

PubMed Central

Morin, Benjamin R; Perrings, Charles; Levin, Simon; Kinzig, Ann

2014-01-01

The personal choices affecting the transmission of infectious diseases include the number of contacts an individual makes, and the risk-characteristics of those contacts. We consider whether these different choices have distinct implications for the course of an epidemic. We also consider whether choosing contact mitigation (how much to mix) and affinity mitigation (with whom to mix) strategies together has different epidemiological effects than choosing each separately. We use a set of differential equation compartmental models of the spread of disease, coupled with a model of selective mixing. We assess the consequences of varying contact or affinity mitigation as a response to disease risk. We do this by comparing disease incidence and dynamics under varying contact volume, contact type, and both combined across several different disease models. Specifically, we construct a change of variables that allows one to transition from contact mitigation to affinity mitigation, and vice versa. In the absence of asymptomatic infection we find no difference in the epidemiological impacts of the two forms of disease risk mitigation. Furthermore, since models that include both mitigation strategies are under-determined, varying both results in no outcome that could not be reached by choosing either separately. Which strategy is actually chosen then depends not on their epidemiological consequences, but on the relative cost of reducing contact volume versus altering contact type. Although there is no fundamental epidemiological difference between the two forms of mitigation, the social cost of alternative strategies can be very different. From a social perspective, therefore, whether one strategy should be promoted over another depends on economic not epidemiological factors. PMID:25150459

Disease risk mitigation: the equivalence of two selective mixing strategies on aggregate contact patterns and resulting epidemic spread.

PubMed

Morin, Benjamin R; Perrings, Charles; Levin, Simon; Kinzig, Ann

2014-12-21

The personal choices affecting the transmission of infectious diseases include the number of contacts an individual makes, and the risk-characteristics of those contacts. We consider whether these different choices have distinct implications for the course of an epidemic. We also consider whether choosing contact mitigation (how much to mix) and affinity mitigation (with whom to mix) strategies together has different epidemiological effects than choosing each separately. We use a set of differential equation compartmental models of the spread of disease, coupled with a model of selective mixing. We assess the consequences of varying contact or affinity mitigation as a response to disease risk. We do this by comparing disease incidence and dynamics under varying contact volume, contact type, and both combined across several different disease models. Specifically, we construct a change of variables that allows one to transition from contact mitigation to affinity mitigation, and vice versa. In the absence of asymptomatic infection we find no difference in the epidemiological impacts of the two forms of disease risk mitigation. Furthermore, since models that include both mitigation strategies are underdetermined, varying both results in no outcome that could not be reached by choosing either separately. Which strategy is actually chosen then depends not on their epidemiological consequences, but on the relative cost of reducing contact volume versus altering contact type. Although there is no fundamental epidemiological difference between the two forms of mitigation, the social cost of alternative strategies can be very different. From a social perspective, therefore, whether one strategy should be promoted over another depends on economic not epidemiological factors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Watershed Management Tool for Selection and Spacial Allocation of Non-Point Source Pollution Control Practices

EPA Science Inventory

Distributed-parameter watershed models are often utilized for evaluating the effectiveness of sediment and nutrient abatement strategies through the traditional {calibrate→ validate→ predict} approach. The applicability of the method is limited due to modeling approximations. In ...

Two-agent cooperative search using game models with endurance-time constraints

NASA Astrophysics Data System (ADS)

Sujit, P. B.; Ghose, Debasish

2010-07-01

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

Sage-grouse habitat selection during winter in Alberta

USGS Publications Warehouse

Carpenter, Jennifer L.; Aldridge, Cameron L.; Boyce, Mark S.

2010-01-01

Greater sage-grouse (Centrocercus urophasianus) are dependent on sagebrush (Artemisia spp.) for food and shelter during winter, yet few studies have assessed winter habitat selection, particularly at scales applicable to conservation planning. Small changes to availability of winter habitats have caused drastic reductions in some sage-grouse populations. We modeled winter habitat selection by sage-grouse in Alberta, Canada, by using a resource selection function. Our purpose was to 1) generate a robust winter habitat-selection model for Alberta sage-grouse; 2) spatially depict habitat suitability in a Geographic Information System to identify areas with a high probability of selection and thus, conservation importance; and 3) assess the relative influence of human development, including oil and gas wells, in landscape models of winter habitat selection. Terrain and vegetation characteristics, sagebrush cover, anthropogenic landscape features, and energy development were important in top Akaike's Information Criterionselected models. During winter, sage-grouse selected dense sagebrush cover and homogenous less rugged areas, and avoided energy development and 2-track truck trails. Sage-grouse avoidance of energy development highlights the need for comprehensive management strategies that maintain suitable habitats across all seasons. ?? 2010 The Wildlife Society.

Genetic grouping strategies in selection efficiency of composite beef cattle ( × ).

PubMed

Petrini, J; Pertile, S F N; Eler, J P; Ferraz, J B S; Mattos, E C; Figueiredo, L G G; Mourão, G B

2015-02-01

The inclusion of genetic groups in sire evaluation has been widely used to represent genetic differences among animals not accounted for by the absence of parentage data. However, the definition of these groups is still arbitrary, and studies assessing the effects of genetic grouping strategies on the selection efficiency are rare. Therefore, the aim in this study was to compare genetic grouping strategies for animals with unknown parentage in prediction of breeding values (EBV). The total of 179,302 records of weaning weight (WW), 29,825 records of scrotal circumference (SC), and 70,302 records of muscling score (MUSC) from Montana Tropical animals, a Brazilian composite beef cattle population, were used. Genetic grouping strategies involving year of birth, sex of the unknown parent, birth farm, breed composition, and their combinations were evaluated. Estimated breeding values were predicted for each approach simulating a loss of genealogy data. Thereafter, these EBV were compared to those obtained in an analysis involving a real relationship matrix to estimate selection efficiency and correlations between EBV and animal rankings. The analysis model included the fixed effects of contemporary groups and class of the dam age at calving, the covariates of additive and nonadditive genetic effects, and age, and the additive genetic effect of animal as random effects. A second model also included the fixed effects of genetic group. The use of genetic groups resulted in means of selection efficiency and correlation of 70.4 to 97.1% and 0.51 to 0.94 for WW, 85.8 to 98.8% and 0.82 to 0.98 for SC, and 85.1 to 98.6% and 0.74 to 0.97 for MUSC, respectively. High selection efficiencies were observed for year of birth and breed composition strategies. The maximum absolute difference in annual genetic gain estimated through the use of complete genealogy and genetic groups were 0.38 kg for WW, 0.02 cm for SC, and 0.01 for MUSC, with lower differences obtained when year of birth was adopted as a genetic group criterion. Grouping strategy must consider selection decisions and the number of genetic groups formed, in the way that genetic groups represent the genetic differences in population and allow an adequate prediction of EBV.

Selection of Authentic Modelling Practices as Contexts for Chemistry Education

ERIC Educational Resources Information Center

Prins, Gjalt T.; Bulte, Astrid M. W.; van Driel, Jan H.; Pilot, Albert

2008-01-01

In science education, students should come to understand the nature and significance of models. In the case of chemistry education it is argued that the present use of models is often not meaningful from the students' perspective. A strategy to overcome this problem is to use an authentic chemical modelling practice as a context for a curriculum…

Modernizing Selection and Promotion Procedures in the State Employment Security Service Agency.

ERIC Educational Resources Information Center

Derryck, Dennis A.; Leyes, Richard

The purpose of this feasibility study was to discover the types ofselection and promotion models, strategies, and processes that must be employed if current State Employment Security Service Agency selection practices are to be made more directly relevant to the various populations currently being served. Specifically, the study sought to…

Disregarding familiarity during recollection attempts: content-specific recapitulation as a retrieval orientation strategy.

PubMed

Gray, Stephen J; Gallo, David A

2015-01-01

People can use a content-specific recapitulation strategy to trigger memories (i.e., mentally reinstating encoding conditions), but how people deploy this strategy is unclear. Is recapitulation naturally used to guide all recollection attempts, or is it only used selectively, after retrieving incomplete information that requires additional monitoring? According to a retrieval orientation model, people use recapitulation whenever they search memory for specific information, regardless of what information might come to mind. In contrast, according to a postretrieval monitoring model, people selectively engage recapitulation only after retrieving ambiguous information in order to evaluate this information and guide additional retrieval attempts. We tested between these models using a criterial recollection task, and by manipulating the strength of ambiguous information associated with to-be-rejected foils (i.e., familiarity or noncriterial information). Replicating prior work, foil rejections were greater when people attempted to recollect targets studied at a semantic level (deep test) compared to an orthographic level (shallow test), implicating more accurate retrieval monitoring. To investigate the role of a recapitulation strategy in this monitoring process, a final test assessed memory for the foils that were earlier processed on these recollection tests. Performance on this foil recognition test suggested that people had engaged in more elaborative content-specific recapitulation when initially tested for deep compared to shallow recollections, and critically, this elaboration effect did not interact with the experimental manipulation of foil strength. These results support the retrieval orientation model, whereby a recapitulation strategy was used to orient retrieval toward specific information during every recollection attempt. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Games of multicellularity.

PubMed

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Behavior Management Strategies for Teachers: Achieving Instructional Effectiveness, Student Success, and Student Motivation--Every Teacher and Any Student Can! 2nd Edition.

ERIC Educational Resources Information Center

Harlan, Joan C.; Rowland, Sidney T.

This book provides tested methods for teachers to use in their behavior management and instructional efforts, offering strategies for maintaining and increasing appropriate behaviors as well as preventing and remediating inappropriate behaviors. Section 1, "Understanding Behavior and Selected Models," includes (1) "Understanding…

Incorporating Early Learning Strategies in the School Improvement Grants (SIG) Program

ERIC Educational Resources Information Center

Connors-Tadros, Lori; Dunn, Lenay; Martella, Jana; McCauley, Carlas

2015-01-01

The Center on Enhancing Early Learning Outcomes (CEELO) and the Center on School Turnaround (CST) collaborated to develop case studies of three selected schools receiving SIG funds that have, with the support of their districts, promoted the use of early childhood programming (PK-3) as a key strategy in their schools' turnaround models. The goal…

Evolution of precopulatory and post-copulatory strategies of inbreeding avoidance and associated polyandry.

PubMed

Duthie, A B; Bocedi, G; Germain, R R; Reid, J M

2018-01-01

Inbreeding depression is widely hypothesized to drive adaptive evolution of precopulatory and post-copulatory mechanisms of inbreeding avoidance, which in turn are hypothesized to affect evolution of polyandry (i.e. female multiple mating). However, surprisingly little theory or modelling critically examines selection for precopulatory or post-copulatory inbreeding avoidance, or both strategies, given evolutionary constraints and direct costs, or examines how evolution of inbreeding avoidance strategies might feed back to affect evolution of polyandry. Selection for post-copulatory inbreeding avoidance, but not for precopulatory inbreeding avoidance, requires polyandry, whereas interactions between precopulatory and post-copulatory inbreeding avoidance might cause functional redundancy (i.e. 'degeneracy') potentially generating complex evolutionary dynamics among inbreeding strategies and polyandry. We used individual-based modelling to quantify evolution of interacting precopulatory and post-copulatory inbreeding avoidance and associated polyandry given strong inbreeding depression and different evolutionary constraints and direct costs. We found that evolution of post-copulatory inbreeding avoidance increased selection for initially rare polyandry and that evolution of a costly inbreeding avoidance strategy became negligible over time given a lower-cost alternative strategy. Further, fixed precopulatory inbreeding avoidance often completely precluded evolution of polyandry and hence post-copulatory inbreeding avoidance, but fixed post-copulatory inbreeding avoidance did not preclude evolution of precopulatory inbreeding avoidance. Evolution of inbreeding avoidance phenotypes and associated polyandry is therefore affected by evolutionary feedbacks and degeneracy. All else being equal, evolution of precopulatory inbreeding avoidance and resulting low polyandry is more likely when post-copulatory inbreeding avoidance is precluded or costly, and evolution of post-copulatory inbreeding avoidance greatly facilitates evolution of costly polyandry. © The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

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

PubMed

Parto, Sahar; Lartillot, Nicolas

2017-06-23

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

Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment

NASA Astrophysics Data System (ADS)

Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

2017-03-01

Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.

A class of multi-period semi-variance portfolio for petroleum exploration and development

NASA Astrophysics Data System (ADS)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

Modeling Public School Partnerships: Merging Corporate and Community Issues.

ERIC Educational Resources Information Center

Clark, Cynthia E.; Brill, Dale A.

This paper describes a model that merges corporate community relations strategy and public relations pedagogy to accelerate the rate at which Internet-based technologies are integrated into the public schools system. The model provides Internet-based training for a select group of Key Contacts drawn from two urban middle schools. Training is…

Evolutionary dynamics of fearfulness and boldness.

PubMed

Ji, Ting; Zhang, Boyu; Sun, Yuehua; Tao, Yi

2009-02-21

A negative relationship between reproductive effort and survival is consistent with life-history. Evolutionary dynamics and evolutionarily stable strategy (ESS) for the trade-off between survival and reproduction are investigated using a simple model with two phenotypes, fearfulness and boldness. The dynamical stability of the pure strategy model and analysis of ESS conditions reveal that: (i) the simple coexistence of fearfulness and boldness is impossible; (ii) a small population size is favorable to fearfulness, but a large population size is favorable to boldness, i.e., neither fearfulness, nor boldness is always favored by natural selection; and (iii) the dynamics of population density is crucial for a proper understanding of the strategy dynamics.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA.

PubMed

Wu, Zheyang; Zhao, Hongyu

2012-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies.

ON MODEL SELECTION STRATEGIES TO IDENTIFY GENES UNDERLYING BINARY TRAITS USING GENOME-WIDE ASSOCIATION DATA

PubMed Central

Wu, Zheyang; Zhao, Hongyu

2013-01-01

For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies. PMID:23956610

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

PubMed

Karamintziou, Sofia D; Custódio, Ana Luísa; Piallat, Brigitte; Polosan, Mircea; Chabardès, Stéphan; Stathis, Pantelis G; Tagaris, George A; Sakas, Damianos E; Polychronaki, Georgia E; Tsirogiannis, George L; David, Olivier; Nikita, Konstantina S

2017-01-01

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

Rival approaches to mathematical modelling in immunology

NASA Astrophysics Data System (ADS)

Andrew, Sarah M.; Baker, Christopher T. H.; Bocharov, Gennady A.

2007-08-01

In order to formulate quantitatively correct mathematical models of the immune system, one requires an understanding of immune processes and familiarity with a range of mathematical techniques. Selection of an appropriate model requires a number of decisions to be made, including a choice of the modelling objectives, strategies and techniques and the types of model considered as candidate models. The authors adopt a multidisciplinary perspective.

Diversity in times of adversity: probabilistic strategies in microbial survival games.

PubMed

Wolf, Denise M; Vazirani, Vijay V; Arkin, Adam P

2005-05-21

Population diversification strategies are ubiquitous among microbes, encompassing random phase-variation (RPV) of pathogenic bacteria, viral latency as observed in some bacteriophage and HIV, and the non-genetic diversity of bacterial stress responses. Precise conditions under which these diversification strategies confer an advantage have not been well defined. We develop a model of population growth conditioned on dynamical environmental and cellular states. Transitions among cellular states, in turn, may be biased by possibly noisy readings of the environment from cellular sensors. For various types of environmental dynamics and cellular sensor capability, we apply game-theoretic analysis to derive the evolutionarily stable strategy (ESS) for an organism and determine when that strategy is diversification. We find that: (1) RPV, effecting a sort of Parrondo paradox wherein random alternations between losing strategies produce a winning strategy, is selected when transitions between different selective environments cannot be sensed, (2) optimal RPV cell switching rates are a function of environmental lifecycle asymmetries and environmental autocorrelation, (3) probabilistic diversification upon entering a new environment is selected when sensors can detect environmental transitions but have poor precision in identifying new environments, and (4) in the presence of excess additive noise, low-pass filtering is required for evolutionary stability. We show that even when RPV is not the ESS, it may minimize growth rate variance and the risk of extinction due to 'unlucky' environmental dynamics.

A chaotic model for advertising diffusion problem with competition

NASA Astrophysics Data System (ADS)

Ip, W. H.; Yung, K. L.; Wang, Dingwei

2012-08-01

In this article, the author extends Dawid and Feichtinger's chaotic advertising diffusion model into the duopoly case. A computer simulation system is used to test this enhanced model. Based on the analysis of simulation results, it is found that the best advertising strategy in duopoly is to increase the advertising investment to reach the best Win-Win situation where the oscillation of market portion will not occur. In order to effectively arrive at the best situation, we define a synthetic index and two thresholds. An estimation method for the parameters of the index and thresholds is proposed in this research. We can reach the Win-Win situation by simply selecting the control parameters to make the synthetic index close to the threshold of min-oscillation state. The numerical example and computational results indicated that the proposed chaotic model is useful to describe and analyse advertising diffusion process in duopoly, it is an efficient tool for the selection and optimisation of advertising strategy.

A performance analysis in AF full duplex relay selection network

NASA Astrophysics Data System (ADS)

Ngoc, Long Nguyen; Hong, Nhu Nguyen; Loan, Nguyen Thi Phuong; Kieu, Tam Nguyen; Voznak, Miroslav; Zdralek, Jaroslav

2018-04-01

This paper studies on the relaying selective matter in amplify-and-forward (AF) cooperation communication with full-duplex (FD) activity. Various relay choice models supposing the present of different instant information are investigated. We examine a maximal relaying choice that optimizes the instant FD channel capacity and asks for global channel state information (CSI) as well as partial CSI learning. To make comparison easy, accurate outage probability clauses and asymptote form of these strategies that give a diversity rank are extracted. From that, we can see clearly that the number of relays, noise factor, the transmittance coefficient as well as the information transfer power had impacted on their performance. Besides, the optimal relay selection (ORS) model can promote than that of the partial relay selection (PRS) model.

Effectiveness of diagnostic strategies in suspected delayed cerebral ischemia: a decision analysis.

PubMed

Rawal, Sapna; Barnett, Carolina; John-Baptiste, Ava; Thein, Hla-Hla; Krings, Timo; Rinkel, Gabriel J E

2015-01-01

Delayed cerebral ischemia (DCI) is a serious complication after aneurysmal subarachnoid hemorrhage. If DCI is suspected clinically, imaging methods designed to detect angiographic vasospasm or regional hypoperfusion are often used before instituting therapy. Uncertainty in the strength of the relationship between imaged vasospasm or perfusion deficits and DCI-related outcomes raises the question of whether imaging to select patients for therapy improves outcomes in clinical DCI. Decision analysis was performed using Markov models. Strategies were either to treat all patients immediately or to first undergo diagnostic testing by digital subtraction angiography or computed tomography angiography to assess for angiographic vasospasm, or computed tomography perfusion to assess for perfusion deficits. According to current practice guidelines, treatment consisted of induced hypertension. Outcomes were survival in terms of life-years and quality-adjusted life-years. When treatment was assumed to be ineffective in nonvasospasm patients, Treat All and digital subtraction angiography were equivalent strategies; when a moderate treatment effect was assumed in nonvasospasm patients, Treat All became the superior strategy. Treating all patients was also superior to selecting patients for treatment via computed tomography perfusion. One-way sensitivity analyses demonstrated that the models were robust; 2- and 3-way sensitivity analyses with variation of disease and treatment parameters reinforced dominance of the Treat All strategy. Imaging studies to test for the presence of angiographic vasospasm or perfusion deficits in patients with clinical DCI do not seem helpful in selecting which patients should undergo treatment and may not improve outcomes. Future directions include validating these results in prospective cohort studies. © 2014 American Heart Association, Inc.

Protein construct storage: Bayesian variable selection and prediction with mixtures.

PubMed

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

Heuristic Strategies for Persuader Selection in Contagions on Complex Networks.

PubMed

Wang, Peng; Zhang, Li-Jie; Xu, Xin-Jian; Xiao, Gaoxi

2017-01-01

Individual decision to accept a new idea or product is often driven by both self-adoption and others' persuasion, which has been simulated using a double threshold model [Huang et al., Scientific Reports 6, 23766 (2016)]. We extend the study to consider the case with limited persuasion. That is, a set of individuals is chosen from the population to be equipped with persuasion capabilities, who may succeed in persuading their friends to take the new entity when certain conditions are satisfied. Network node centrality is adopted to characterize each node's influence, based on which three heuristic strategies are applied to pick out persuaders. We compare these strategies for persuader selection on both homogeneous and heterogeneous networks. Two regimes of the underline networks are identified in which the system exhibits distinct behaviors: when networks are sufficiently sparse, selecting persuader nodes in descending order of node centrality achieves the best performance; when networks are sufficiently dense, however, selecting nodes with medium centralities to serve as the persuaders performs the best. Under respective optimal strategies for different types of networks, we further probe which centrality measure is most suitable for persuader selection. It turns out that for the first regime, degree centrality offers the best measure for picking out persuaders from homogeneous networks; while in heterogeneous networks, betweenness centrality takes its place. In the second regime, there is no significant difference caused by centrality measures in persuader selection for homogeneous network; while for heterogeneous networks, closeness centrality offers the best measure.

Single Broadband Phase-Shaped Pulse Stimulated Raman Spectroscopy for Standoff Trace Explosive Detection.

PubMed

Glenn, Rachel; Dantus, Marcos

2016-01-07

Recent success with trace explosives detection based on the single ultrafast pulse excitation for remote stimulated Raman scattering (SUPER-SRS) prompts us to provide new results and a Perspective that describes the theoretical foundation of the strategy used for achieving the desired sensitivity and selectivity. SUPER-SRS provides fast and selective imaging while being blind to optical properties of the substrate such as color, texture, or laser speckle. We describe the strategy of combining coherent vibrational excitation with a reference pulse in order to detect stimulated Raman gain or loss. A theoretical model is used to reproduce experimental spectra and to determine the ideal pulse parameters for best sensitivity, selectivity, and resolution when detecting one or more compounds simultaneously.

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data

PubMed Central

Xu, Lizhen; Paterson, Andrew D.; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects. PMID:26148172

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data.

PubMed

Xu, Lizhen; Paterson, Andrew D; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects.

Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory

NASA Astrophysics Data System (ADS)

Matsumura, Koki; Kawamoto, Masaru

This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2009-01-01

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Cost-effectiveness of molecular testing for thyroid nodules with atypia of undetermined significance cytology.

PubMed

Lee, Lawrence; How, Jacques; Tabah, Roger J; Mitmaker, Elliot J

2014-08-01

Novel molecular diagnostics, such as the gene expression classifier (GEC) and gene mutation panel (GMP) testing, may improve the management for thyroid nodules with atypia of undetermined significance (AUS) cytology. The cost-effectiveness of an approach combining both tests in different practice settings in North America is unknown. The aim of the study was to determine the cost-effectiveness of two diagnostic molecular tests, singly or in combination, for AUS thyroid nodules. We constructed a microsimulation model to investigate cost-effectiveness from US (Medicare) and Canadian healthcare system perspectives. Low-risk patients with AUS thyroid nodules were simulated. We examined five management strategies: 1) routine GEC; 2) routine GEC + selective GMP; 3) routine GMP; 4) routine GMP + selective GEC; and 5) standard management. Lifetime costs and quality-adjusted life-years were measured. From the US perspective, the routine GEC + selective GMP strategy was the dominant strategy. From the Canadian perspective, routine GEC + selective GMP cost and additional CAN$24 030 per quality-adjusted life-year gained over standard management, and was dominant over the other strategies. Sensitivity analyses reported that the decisions from both perspectives were sensitive to variations in the probability of malignancy in the nodule and the costs of the GEC and GMP. The probability of cost-effectiveness for routine GEC + selective GMP was low. In the US setting, the most cost-effective strategy was routine GEC + selective GMP. In the Canadian setting, standard management was most likely to be cost effective. The cost of these molecular diagnostics will need to be reduced to increase their cost-effectiveness for practice settings outside the United States.

Evolution of Site-Selection Stabilizes Population Dynamics, Promotes Even Distribution of Individuals, and Occasionally Causes Evolutionary Suicide.

PubMed

Parvinen, Kalle; Brännström, Åke

2016-08-01

Species that compete for access to or use of sites, such as parasitic mites attaching to honey bees or apple maggots laying eggs in fruits, can potentially increase their fitness by carefully selecting sites at which they face little or no competition. Here, we systematically investigate the evolution of site-selection strategies among animals competing for discrete sites. By developing and analyzing a mechanistic and population-dynamical model of site selection in which searching individuals encounter sites sequentially and can choose to accept or continue to search based on how many conspecifics are already there, we give a complete characterization of the different site-selection strategies that can evolve. We find that evolution of site-selection stabilizes population dynamics, promotes even distribution of individuals among sites, and occasionally causes evolutionary suicide. We also discuss the broader implications of our findings and propose how they can be reconciled with an earlier study (Nonaka et al. in J Theor Biol 317:96-104, 2013) that reported selection toward ever higher levels of aggregation among sites as a consequence of site-selection.

University Macro Analytic Simulation Model.

ERIC Educational Resources Information Center

Baron, Robert; Gulko, Warren

The University Macro Analytic Simulation System (UMASS) has been designed as a forecasting tool to help university administrators budgeting decisions. Alternative budgeting strategies can be tested on a computer model and then an operational alternative can be selected on the basis of the most desirable projected outcome. UMASS uses readily…

A dynamic replication management strategy in distributed GIS

NASA Astrophysics Data System (ADS)

Pan, Shaoming; Xiong, Lian; Xu, Zhengquan; Chong, Yanwen; Meng, Qingxiang

2018-03-01

Replication strategy is one of effective solutions to meet the requirement of service response time by preparing data in advance to avoid the delay of reading data from disks. This paper presents a brand-new method to create copies considering the selection of replicas set, the number of copies for each replica and the placement strategy of all copies. First, the popularities of all data are computed considering both the historical access records and the timeliness of the records. Then, replica set can be selected based on their recent popularities. Also, an enhanced Q-value scheme is proposed to assign the number of copies for each replica. Finally, a reasonable copies placement strategy is designed to meet the requirement of load balance. In addition, we present several experiments that compare the proposed method with techniques that use other replication management strategies. The results show that the proposed model has better performance than other algorithms in all respects. Moreover, the experiments based on different parameters also demonstrated the effectiveness and adaptability of the proposed algorithm.

Self-paced model learning for robust visual tracking

NASA Astrophysics Data System (ADS)

Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

2017-01-01

In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

Performance of Seven Tree Breeding Strategies Under Conditions of Inbreeding Depression.

PubMed

Wu, Harry X; Hallingbäck, Henrik R; Sánchez, Leopoldo

2016-01-06

In the domestication and breeding of tree species that suffer from inbreeding depression (ID), the long-term performance of different breeding strategies is poorly known. Therefore, seven tree breeding strategies including single population, subline, selfing, and nucleus breeding were simulated using a multi-locus model with additive, partial, and complete dominance allele effects, and with intermediate, U-shaped, and major allele distributions. The strategies were compared for genetic gain, inbreeding accumulation, capacity to show ID, the frequencies and fixations of unfavorable alleles, and genetic variances in breeding and production populations. Measured by genetic gain of production population, the nucleus breeding and the single breeding population with mass selection strategies were equal or superior to subline and single breeding population with within-family selection strategies in all simulated scenarios, in spite of their higher inbreeding coefficients. Inbreeding and cross-breeding effectively decreased ID and could in some scenarios produce genetic gains during the first few generations. However, in all scenarios, considerable fixation of unfavorable alleles rendered the purging performance of selfing and cross-breeding strategies ineffective, and resulted in substantial inferiority in comparison to the other strategies in the long-term. Copyright © 2016 Wu et al.

Performance of Seven Tree Breeding Strategies Under Conditions of Inbreeding Depression

PubMed Central

Wu, Harry X.; Hallingbäck, Henrik R.; Sánchez, Leopoldo

2016-01-01

In the domestication and breeding of tree species that suffer from inbreeding depression (ID), the long-term performance of different breeding strategies is poorly known. Therefore, seven tree breeding strategies including single population, subline, selfing, and nucleus breeding were simulated using a multi-locus model with additive, partial, and complete dominance allele effects, and with intermediate, U-shaped, and major allele distributions. The strategies were compared for genetic gain, inbreeding accumulation, capacity to show ID, the frequencies and fixations of unfavorable alleles, and genetic variances in breeding and production populations. Measured by genetic gain of production population, the nucleus breeding and the single breeding population with mass selection strategies were equal or superior to subline and single breeding population with within-family selection strategies in all simulated scenarios, in spite of their higher inbreeding coefficients. Inbreeding and cross-breeding effectively decreased ID and could in some scenarios produce genetic gains during the first few generations. However, in all scenarios, considerable fixation of unfavorable alleles rendered the purging performance of selfing and cross-breeding strategies ineffective, and resulted in substantial inferiority in comparison to the other strategies in the long-term. PMID:26739644

Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.

Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

NASA Astrophysics Data System (ADS)

Tsaur, Ruey-Chyn

2015-02-01

In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

Investigation of some selected strategies for multi-GNSS instantaneous RTK positioning

NASA Astrophysics Data System (ADS)

Paziewski, Jacek; Wielgosz, Pawel

2017-01-01

It is clear that we can benefit from multi-constellation GNSS in precise relative positioning. On the other hand, it is still an open problem how to combine multi-GNSS signals in a single functional model. This study presents methodology and quality assessment of selected methods allowing for multi-GNSS observations combining in relative kinematic positioning using baselines up to tens of kilometers. In specific, this paper characterizes loose and tight integration strategies applied to the ionosphere and troposphere weighted model. Performance assessment of the established strategies was based on the analyses of the integer ambiguity resolution and rover coordinates' repeatability obtained in the medium range instantaneous RTK positioning with the use of full constellation dual frequency GPS and Galileo signals. Since full constellation of Galileo satellites is not yet available, the observational data were obtained from a hardware GNSS signal simulator using regular geodetic GNSS receivers. The results indicate on similar and high performance of the loose, and tight integration with calibrated receiver ISBs strategies. These approaches have undeniable advantage over single system positioning in terms of reliability of the integer ambiguity resolution as well as rover coordinate repeatability.

The Systematic Development of an Internet-Based Smoking Cessation Intervention for Adults.

PubMed

Dalum, Peter; Brandt, Caroline Lyng; Skov-Ettrup, Lise; Tolstrup, Janne; Kok, Gerjo

2016-07-01

Objectives The objective of this project was to determine whether intervention mapping is a suitable strategy for developing an Internet- and text message-based smoking cessation intervention. Method We used the Intervention Mapping framework for planning health promotion programs. After a needs assessment, we identified important changeable determinants of cessation behavior, specified objectives for the intervention, selected theoretical methods for meeting our objectives, and operationalized change methods into practical intervention strategies. Results We found that "social cognitive theory," the "transtheoretical model/stages of change," "self-regulation theory," and "appreciative inquiry" were relevant theories for smoking cessation interventions. From these theories, we selected modeling/behavioral journalism, feedback, planning coping responses/if-then statements, gain frame/positive imaging, consciousness-raising, helping relationships, stimulus control, and goal-setting as suitable methods for an Internet- and text-based adult smoking cessation program. Furthermore, we identified computer tailoring as a useful strategy for adapting the intervention to individual users. Conclusion The Intervention Mapping method, with a clear link between behavioral goals, theoretical methods, and practical strategies and materials, proved useful for systematic development of a digital smoking cessation intervention for adults. © 2016 Society for Public Health Education.

A Compartmental Model for Zika Virus with Dynamic Human and Vector Populations

PubMed Central

Lee, Eva K; Liu, Yifan; Pietz, Ferdinand H

2016-01-01

The Zika virus (ZIKV) outbreak in South American countries and its potential association with microcephaly in newborns and Guillain-Barré Syndrome led the World Health Organization to declare a Public Health Emergency of International Concern. To understand the ZIKV disease dynamics and evaluate the effectiveness of different containment strategies, we propose a compartmental model with a vector-host structure for ZIKV. The model utilizes logistic growth in human population and dynamic growth in vector population. Using this model, we derive the basic reproduction number to gain insight on containment strategies. We contrast the impact and influence of different parameters on the virus trend and outbreak spread. We also evaluate different containment strategies and their combination effects to achieve early containment by minimizing total infections. This result can help decision makers select and invest in the strategies most effective to combat the infection spread. The decision-support tool demonstrates the importance of “digital disease surveillance” in response to waves of epidemics including ZIKV, Dengue, Ebola and cholera. PMID:28269870

An efficient sampling strategy for selection of biobank samples using risk scores.

PubMed

Björk, Jonas; Malmqvist, Ebba; Rylander, Lars; Rignell-Hydbom, Anna

2017-07-01

The aim of this study was to suggest a new sample-selection strategy based on risk scores in case-control studies with biobank data. An ongoing Swedish case-control study on fetal exposure to endocrine disruptors and overweight in early childhood was used as the empirical example. Cases were defined as children with a body mass index (BMI) ⩾18 kg/m 2 ( n=545) at four years of age, and controls as children with a BMI of ⩽17 kg/m 2 ( n=4472 available). The risk of being overweight was modelled using logistic regression based on available covariates from the health examination and prior to selecting samples from the biobank. A risk score was estimated for each child and categorised as low (0-5%), medium (6-13%) or high (⩾14%) risk of being overweight. The final risk-score model, with smoking during pregnancy ( p=0.001), birth weight ( p<0.001), BMI of both parents ( p<0.001 for both), type of residence ( p=0.04) and economic situation ( p=0.12), yielded an area under the receiver operating characteristic curve of 67% ( n=3945 with complete data). The case group ( n=416) had the following risk-score profile: low (12%), medium (46%) and high risk (43%). Twice as many controls were selected from each risk group, with further matching on sex. Computer simulations showed that the proposed selection strategy with stratification on risk scores yielded consistent improvements in statistical precision. Using risk scores based on available survey or register data as a basis for sample selection may improve possibilities to study heterogeneity of exposure effects in biobank-based studies.

The σ law of evolutionary dynamics in community-structured population.

PubMed

Tang, Changbing; Li, Xiang; Cao, Lang; Zhan, Jingyuan

2012-08-07

Evolutionary game dynamics in finite populations provide a new framework to understand the selection of traits with frequency-dependent fitness. Recently, a simple but fundamental law of evolutionary dynamics, which we call σ law, describes how to determine the selection between two competing strategies: in most evolutionary processes with two strategies, A and B, strategy A is favored over B in weak selection if and only if σR+S>T+σP. This relationship holds for a wide variety of structured populations with mutation rate and weak selection under certain assumptions. In this paper, we propose a model of games based on a community-structured population and revisit this law under the Moran process. By calculating the average payoffs of A and B individuals with the method of effective sojourn time, we find that σ features not only the structured population characteristics, but also the reaction rate between individuals. That is to say, an interaction between two individuals are not uniform, and we can take σ as a reaction rate between any two individuals with the same strategy. We verify this viewpoint by the modified replicator equation with non-uniform interaction rates in a simplified version of the prisoner's dilemma game (PDG). Copyright © 2012 Elsevier Ltd. All rights reserved.

HOW MUCH FAVORABLE SELECTION IS LEFT IN MEDICARE ADVANTAGE?

PubMed Central

PRICE, MARY; MCWILLIAMS, J. MICHAEL; HSU, JOHN; MCGUIRE, THOMAS G.

2015-01-01

The health economics literature contains two models of selection, one with endogenous plan characteristics to attract good risks and one with fixed plan characteristics; neither model contains a regulator. Medicare Advantage, a principal example of selection in the literature, is, however, subject to anti-selection regulations. Because selection causes economic inefficiency and because the historically favorable selection into Medicare Advantage plans increased government cost, the effectiveness of the anti-selection regulations is an important policy question, especially since the Medicare Advantage program has grown to comprise 30 percent of Medicare beneficiaries. Moreover, similar anti-selection regulations are being used in health insurance exchanges for those under 65. Contrary to earlier work, we show that the strengthened anti-selection regulations that Medicare introduced starting in 2004 markedly reduced government overpayment attributable to favorable selection in Medicare Advantage. At least some of the remaining selection is plausibly related to fixed plan characteristics of Traditional Medicare versus Medicare Advantage rather than changed selection strategies by Medicare Advantage plans. PMID:26389127

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

Modelling Sensory Limitation: The Role of Tree Selection, Memory and Information Transfer in Bats’ Roost Searching Strategies

PubMed Central

Ruczyński, Ireneusz; Bartoń, Kamil A.

2012-01-01

Sensory limitation plays an important role in the evolution of animal behaviour. Animals have to find objects of interest (e.g. food, shelters, predators). When sensory abilities are strongly limited, animals adjust their behaviour to maximize chances for success. Bats are nocturnal, live in complex environments, are capable of flight and must confront numerous perceptual challenges (e.g. limited sensory range, interfering clutter echoes). This makes them an excellent model for studying the role of compensating behaviours to decrease costs of finding resources. Cavity roosting bats are especially interesting because the availability of tree cavities is often limited, and their quality is vital for bats during the breeding season. From a bat’s sensory point of view, cavities are difficult to detect and finding them requires time and energy. However, tree cavities are also long lasting, allowing information transfer among conspecifics. Here, we use a simple simulation model to explore the benefits of tree selection, memory and eavesdropping (compensation behaviours) to searches for tree cavities by bats with short and long perception range. Our model suggests that memory and correct discrimination of tree suitability are the basic strategies decreasing the cost of roost finding, whereas perceptual range plays a minor role in this process. Additionally, eavesdropping constitutes a buffer that reduces the costs of finding new resources (such as roosts), especially when they occur in low density. We conclude that natural selection may promote different strategies of roost finding in relation to habitat conditions and cognitive skills of animals. PMID:23028666

[Variable selection methods combined with local linear embedding theory used for optimization of near infrared spectral quantitative models].

PubMed

Hao, Yong; Sun, Xu-Dong; Yang, Qiang

2012-12-01

Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include Monte Carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.

New strategy for determination of anthocyanins, polyphenols and antioxidant capacity of Brassica oleracea liquid extract using infrared spectroscopies and multivariate regression

NASA Astrophysics Data System (ADS)

de Oliveira, Isadora R. N.; Roque, Jussara V.; Maia, Mariza P.; Stringheta, Paulo C.; Teófilo, Reinaldo F.

2018-04-01

A new method was developed to determine the antioxidant properties of red cabbage extract (Brassica oleracea) by mid (MID) and near (NIR) infrared spectroscopies and partial least squares (PLS) regression. A 70% (v/v) ethanolic extract of red cabbage was concentrated to 9° Brix and further diluted (12 to 100%) in water. The dilutions were used as external standards for the building of PLS models. For the first time, this strategy was applied for building multivariate regression models. Reference analyses and spectral data were obtained from diluted extracts. The determinate properties were total and monomeric anthocyanins, total polyphenols and antioxidant capacity by ABTS (2,2-azino-bis(3-ethyl-benzothiazoline-6-sulfonate)) and DPPH (2,2-diphenyl-1-picrylhydrazyl) methods. Ordered predictors selection (OPS) and genetic algorithm (GA) were used for feature selection before PLS regression (PLS-1). In addition, a PLS-2 regression was applied to all properties simultaneously. PLS-1 models provided more predictive models than did PLS-2 regression. PLS-OPS and PLS-GA models presented excellent prediction results with a correlation coefficient higher than 0.98. However, the best models were obtained using PLS and variable selection with the OPS algorithm and the models based on NIR spectra were considered more predictive for all properties. Then, these models provided a simple, rapid and accurate method for determination of red cabbage extract antioxidant properties and its suitability for use in the food industry.

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

PubMed Central

Indiveri, Giacomo

2008-01-01

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention. PMID:27873818

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems.

PubMed

Indiveri, Giacomo

2008-09-03

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

Exploring different strategies for imbalanced ADME data problem: case study on Caco-2 permeability modeling.

PubMed

Pham-The, Hai; Casañola-Martin, Gerardo; Garrigues, Teresa; Bermejo, Marival; González-Álvarez, Isabel; Nguyen-Hai, Nam; Cabrera-Pérez, Miguel Ángel; Le-Thi-Thu, Huong

2016-02-01

In many absorption, distribution, metabolism, and excretion (ADME) modeling problems, imbalanced data could negatively affect classification performance of machine learning algorithms. Solutions for handling imbalanced dataset have been proposed, but their application for ADME modeling tasks is underexplored. In this paper, various strategies including cost-sensitive learning and resampling methods were studied to tackle the moderate imbalance problem of a large Caco-2 cell permeability database. Simple physicochemical molecular descriptors were utilized for data modeling. Support vector machine classifiers were constructed and compared using multiple comparison tests. Results showed that the models developed on the basis of resampling strategies displayed better performance than the cost-sensitive classification models, especially in the case of oversampling data where misclassification rates for minority class have values of 0.11 and 0.14 for training and test set, respectively. A consensus model with enhanced applicability domain was subsequently constructed and showed improved performance. This model was used to predict a set of randomly selected high-permeability reference drugs according to the biopharmaceutics classification system. Overall, this study provides a comparison of numerous rebalancing strategies and displays the effectiveness of oversampling methods to deal with imbalanced permeability data problems.

Stochastic Multiscale Modeling of Polycrystalline Materials

DTIC Science & Technology

2013-01-01

The single-grid strategy is adopted. The crystal visco-plastic constitutive model proposed in [7] along with a Voce type hardening model described...in [97] is used with γ̇0 = 1s−1 and m = 0.1. The parameters in the Voce type hardening law are selected according to [97]: κ0 = 47.0MPa, κ1 = 86.0MPa

A Structural Model of Depression Based on Interpersonal Relationships: The Mediating Role of Coping Strategies and Loneliness.

PubMed

Majd Ara, Elahe; Talepasand, Siavash; Rezaei, Ali Mohammad

2017-06-01

The present study was conducted with the aim of examining the structural model of interpersonal relationships and depression using coping strategies and loneliness as mediators. Using multistage random sampling, 301 high-school students were selected from Minudasht city, Iran. The participants were aksed to complete the Network of Relationships Inventory (NRI); the Ways of Coping Questionnaire (Lazarus and Folkman); the Children's Loneliness Scale (CLS); and the Depression, Anxiety, and Stress Scale (DASS-21). Structural equation modeling was used to examine the pattern of direct and indirect effects. Findings of the present study show that the data are well fitted to the model. The indirect effect of the positive quality of relationships was significant on depression through loneliness. Moreover, the indirect effects of the negative quality of relationships on depression through loneliness and through emotion-focused coping strategies were statistically significant. Although the effect of loneliness and emotion-focused coping strategies on depression was significant, problem-focused coping strategies did not have a significant effect on depression. Additionally, the findings suggested that the indirect effect through loneliness on depression was stronger compared with the indirect effect through emotion-focused coping strategies. The positive or negative quality of interpersonal relationships, loneliness, and emotion-focused coping strategy can significantly predict depression.

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum

PubMed Central

Ito, Makoto; Doya, Kenji

2015-01-01

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the “win-stay, lose-switch” strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum. PMID:26529522

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection.

PubMed

Mendes, M P; Ramalho, M A P; Abreu, A F B

2012-04-10

The objective of this study was to compare the BLUP selection method with different selection strategies in F(2:4) and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F(2:4) progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy.

PubMed

Kim, Yusung; Tomé, Wolfgang A

2008-01-01

Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans.

Using the Whole School, Whole Community, Whole Child Model: Implications for Practice

PubMed Central

Rooney, Laura E; Videto, Donna M; Birch, David A

2015-01-01

BACKGROUND Schools, school districts, and communities seeking to implement the Whole School, Whole Community, Whole Child (WSCC) model should carefully and deliberately select planning, implementation, and evaluation strategies. METHODS In this article, we identify strategies, steps, and resources within each phase that can be integrated into existing processes that help improve health outcomes and academic achievement. Implementation practices may vary across districts depending upon available resources and time commitments. RESULTS Obtaining and maintaining administrative support at the beginning of the planning phase is imperative for identifying and implementing strategies and sustaining efforts to improve student health and academic outcomes. Strategy selection hinges on priority needs, community assets, and resources identified through the planning process. Determining the results of implementing the WSCC is based upon a comprehensive evaluation that begins during the planning phase. Evaluation guides success in attaining goals and objectives, assesses strengths and weaknesses, provides direction for program adjustment, revision, and future planning, and informs stakeholders of the effect of WSCC, including the effect on academic indicators. CONCLUSIONS With careful planning, implementation, and evaluation efforts, use of the WSCC model has the potential of focusing family, community, and school education and health resources to increase the likelihood of better health and academic success for students and improve school and community life in the present and in the future. PMID:26440824

Contracting out : bench marking study : phase 1, part 2 : external data collection

DOT National Transportation Integrated Search

1999-11-10

This paper is a survey of several models used in the U.S. to estimate the impact of greenhouse gases (GHG) control strategies in the surface transport sector. The models chosen for review were selected to represent both the state-of-the-art, and the ...

Evolution of fairness in the one-shot anonymous Ultimatum Game

PubMed Central

Rand, David G.; Tarnita, Corina E.; Ohtsuki, Hisashi; Nowak, Martin A.

2013-01-01

Classical economic models assume that people are fully rational and selfish, while experiments often point to different conclusions. A canonical example is the Ultimatum Game: one player proposes a division of a sum of money between herself and a second player, who either accepts or rejects. Based on rational self-interest, responders should accept any nonzero offer and proposers should offer the smallest possible amount. Traditional, deterministic models of evolutionary game theory agree: in the one-shot anonymous Ultimatum Game, natural selection favors low offers and demands. Experiments instead show a preference for fairness: often responders reject low offers and proposers make higher offers than needed to avoid rejection. Here we show that using stochastic evolutionary game theory, where agents make mistakes when judging the payoffs and strategies of others, natural selection favors fairness. Across a range of parameters, the average strategy matches the observed behavior: proposers offer between 30% and 50%, and responders demand between 25% and 40%. Rejecting low offers increases relative payoff in pairwise competition between two strategies and is favored when selection is sufficiently weak. Offering more than you demand increases payoff when many strategies are present simultaneously and is favored when mutation is sufficiently high. We also perform a behavioral experiment and find empirical support for these theoretical findings: uncertainty about the success of others is associated with higher demands and offers; and inconsistency in the behavior of others is associated with higher offers but not predictive of demands. In an uncertain world, fairness finishes first. PMID:23341593

Evolution of fairness in the one-shot anonymous Ultimatum Game.

PubMed

Rand, David G; Tarnita, Corina E; Ohtsuki, Hisashi; Nowak, Martin A

2013-02-12

Classical economic models assume that people are fully rational and selfish, while experiments often point to different conclusions. A canonical example is the Ultimatum Game: one player proposes a division of a sum of money between herself and a second player, who either accepts or rejects. Based on rational self-interest, responders should accept any nonzero offer and proposers should offer the smallest possible amount. Traditional, deterministic models of evolutionary game theory agree: in the one-shot anonymous Ultimatum Game, natural selection favors low offers and demands. Experiments instead show a preference for fairness: often responders reject low offers and proposers make higher offers than needed to avoid rejection. Here we show that using stochastic evolutionary game theory, where agents make mistakes when judging the payoffs and strategies of others, natural selection favors fairness. Across a range of parameters, the average strategy matches the observed behavior: proposers offer between 30% and 50%, and responders demand between 25% and 40%. Rejecting low offers increases relative payoff in pairwise competition between two strategies and is favored when selection is sufficiently weak. Offering more than you demand increases payoff when many strategies are present simultaneously and is favored when mutation is sufficiently high. We also perform a behavioral experiment and find empirical support for these theoretical findings: uncertainty about the success of others is associated with higher demands and offers; and inconsistency in the behavior of others is associated with higher offers but not predictive of demands. In an uncertain world, fairness finishes first.

Evolution of trophic transmission in parasites: Why add intermediate hosts?

USGS Publications Warehouse

Choisy, Marc; Brown, Sam P.; Lafferty, Kevin D.; Thomas, Frédéric

2003-01-01

Although multihost complex life cycles (CLCs) are common in several distantly related groups of parasites, their evolution remains poorly understood. In this article, we argue that under particular circumstances, adding a second host to a single-host life cycle is likely to enhance transmission (i.e., reaching the target host). For instance, in several situations, the propagules of a parasite exploiting a predator species will achieve a higher host-finding success by encysting in a prey of the target predator than by other dispersal modes. In such a case, selection should favor the transition from a singleto a two-host life cycle that includes the prey species as an intermediate host. We use an optimality model to explore this idea, and we discuss it in relation to dispersal strategies known among free-living species, especially animal dispersal. The model found that selection favored a complex life cycle only if intermediate hosts were more abundant than definitive hosts. The selective value of a complex life cycle increased with predation rates by definitive hosts on intermediate hosts. In exploring trade-offs between transmission strategies, we found that more costly trade-offs made it more difficult to evolve a CLC while less costly trade-offs between traits could favor a mixed strategy.

Task-Specific Response Strategy Selection on the Basis of Recent Training Experience

PubMed Central

Fulvio, Jacqueline M.; Green, C. Shawn; Schrater, Paul R.

2014-01-01

The goal of training is to produce learning for a range of activities that are typically more general than the training task itself. Despite a century of research, predicting the scope of learning from the content of training has proven extremely difficult, with the same task producing narrowly focused learning strategies in some cases and broadly scoped learning strategies in others. Here we test the hypothesis that human subjects will prefer a decision strategy that maximizes performance and reduces uncertainty given the demands of the training task and that the strategy chosen will then predict the extent to which learning is transferable. To test this hypothesis, we trained subjects on a moving dot extrapolation task that makes distinct predictions for two types of learning strategy: a narrow model-free strategy that learns an input-output mapping for training stimuli, and a general model-based strategy that utilizes humans' default predictive model for a class of trajectories. When the number of distinct training trajectories is low, we predict better performance for the mapping strategy, but as the number increases, a predictive model is increasingly favored. Consonant with predictions, subject extrapolations for test trajectories were consistent with using a mapping strategy when trained on a small number of training trajectories and a predictive model when trained on a larger number. The general framework developed here can thus be useful both in interpreting previous patterns of task-specific versus task-general learning, as well as in building future training paradigms with certain desired outcomes. PMID:24391490

Model of Selective and Non-Selective Management of Badgers (Meles meles) to Control Bovine Tuberculosis in Badgers and Cattle

PubMed Central

Smith, Graham C.; Delahay, Richard J.; McDonald, Robbie A.

2016-01-01

Bovine tuberculosis (bTB) causes substantial economic losses to cattle farmers and taxpayers in the British Isles. Disease management in cattle is complicated by the role of the European badger (Meles meles) as a host of the infection. Proactive, non-selective culling of badgers can reduce the incidence of disease in cattle but may also have negative effects in the area surrounding culls that have been associated with social perturbation of badger populations. The selective removal of infected badgers would, in principle, reduce the number culled, but the effects of selective culling on social perturbation and disease outcomes are unclear. We used an established model to simulate non-selective badger culling, non-selective badger vaccination and a selective trap and vaccinate or remove (TVR) approach to badger management in two distinct areas: South West England and Northern Ireland. TVR was simulated with and without social perturbation in effect. The lower badger density in Northern Ireland caused no qualitative change in the effect of management strategies on badgers, although the absolute number of infected badgers was lower in all cases. However, probably due to differing herd density in Northern Ireland, the simulated badger management strategies caused greater variation in subsequent cattle bTB incidence. Selective culling in the model reduced the number of badgers killed by about 83% but this only led to an overall benefit for cattle TB incidence if there was no social perturbation of badgers. We conclude that the likely benefit of selective culling will be dependent on the social responses of badgers to intervention but that other population factors including badger and cattle density had little effect on the relative benefits of selective culling compared to other methods, and that this may also be the case for disease management in other wild host populations. PMID:27893809

Model of Selective and Non-Selective Management of Badgers (Meles meles) to Control Bovine Tuberculosis in Badgers and Cattle.

PubMed

Smith, Graham C; Delahay, Richard J; McDonald, Robbie A; Budgey, Richard

2016-01-01

Bovine tuberculosis (bTB) causes substantial economic losses to cattle farmers and taxpayers in the British Isles. Disease management in cattle is complicated by the role of the European badger (Meles meles) as a host of the infection. Proactive, non-selective culling of badgers can reduce the incidence of disease in cattle but may also have negative effects in the area surrounding culls that have been associated with social perturbation of badger populations. The selective removal of infected badgers would, in principle, reduce the number culled, but the effects of selective culling on social perturbation and disease outcomes are unclear. We used an established model to simulate non-selective badger culling, non-selective badger vaccination and a selective trap and vaccinate or remove (TVR) approach to badger management in two distinct areas: South West England and Northern Ireland. TVR was simulated with and without social perturbation in effect. The lower badger density in Northern Ireland caused no qualitative change in the effect of management strategies on badgers, although the absolute number of infected badgers was lower in all cases. However, probably due to differing herd density in Northern Ireland, the simulated badger management strategies caused greater variation in subsequent cattle bTB incidence. Selective culling in the model reduced the number of badgers killed by about 83% but this only led to an overall benefit for cattle TB incidence if there was no social perturbation of badgers. We conclude that the likely benefit of selective culling will be dependent on the social responses of badgers to intervention but that other population factors including badger and cattle density had little effect on the relative benefits of selective culling compared to other methods, and that this may also be the case for disease management in other wild host populations.

Quantifying male attractiveness.

PubMed Central

McNamara, John M; Houston, Alasdair I; Marques Dos Santos, Miguel; Kokko, Hanna; Brooks, Rob

2003-01-01

Genetic models of sexual selection are concerned with a dynamic process in which female preference and male trait values coevolve. We present a rigorous method for characterizing evolutionary endpoints of this process in phenotypic terms. In our phenotypic characterization the mate-choice strategy of female population members determines how attractive females should find each male, and a population is evolutionarily stable if population members are actually behaving in this way. This provides a justification of phenotypic explanations of sexual selection and the insights into sexual selection that they provide. Furthermore, the phenotypic approach also has enormous advantages over a genetic approach when computing evolutionarily stable mate-choice strategies, especially when strategies are allowed to be complex time-dependent preference rules. For simplicity and clarity our analysis deals with haploid mate-choice genetics and a male trait that is inherited phenotypically, for example by vertical cultural transmission. The method is, however, easily extendible to other cases. An example illustrates that the sexy son phenomenon can occur when there is phenotypic inheritance of the male trait. PMID:14561306

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.

Darwin's diagram of divergence of taxa as a causal model for the origin of species.

PubMed

Bouzat, Juan L

2014-03-01

On the basis that Darwin's theory of evolution encompasses two logically independent processes (common descent and natural selection), the only figure in On the Origin of Species (the Diagram of Divergence of Taxa) is often interpreted as illustrative of only one of these processes: the branching patterns representing common ancestry. Here, I argue that Darwin's Diagram of Divergence of Taxa represents a broad conceptual model of Darwin's theory, illustrating the causal efficacy of natural selection in producing well-defined varieties and ultimately species. The Tree Diagram encompasses the idea that natural selection explains common descent and the origin of organic diversity, thus representing a comprehensive model of Darwin's theory on the origin of species. I describe Darwin's Tree Diagram in relation to his argumentative strategy under the vera causa principle, and suggest that the testing of his theory based on the evidence from the geological record, the geographical distribution of organisms, and the mutual affinities of organic beings can be framed under the hypothetico-deductive method. Darwin's Diagram of Divergence of Taxa therefore represents a broad conceptual model that helps understanding the causal construction of Darwin's theory of evolution, the structure of his argumentative strategy, and the nature of his scientific methodology.

Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

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

Sukumar, Sreenivas R; Nutaro, James J

This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

A collaborative university model for employee wellness.

PubMed

Carter, Melondie R; Kelly, Rebecca C; Alexander, Chelley K; Holmes, Lauren M

2011-01-01

Universities are taking a more active approach in understanding and monitoring employees' modifiable health risk factors and chronic care conditions by developing strategies to encourage employees to start and sustain healthy behaviors. WellBama, the University of Alabama's signature health and wellness program, utilizes a collaborative model in partnership with select colleges and departments to implement strategies to improve employees' health status. The program provides onsite health screenings and assessments, timely health advising sessions, assistance in setting and monitoring individual health goals to promote improved health, and preventive examination referrals.

Modeling global vector fields of chaotic systems from noisy time series with the aid of structure-selection techniques.

PubMed

Xu, Daolin; Lu, Fangfang

2006-12-01

We address the problem of reconstructing a set of nonlinear differential equations from chaotic time series. A method that combines the implicit Adams integration and the structure-selection technique of an error reduction ratio is proposed for system identification and corresponding parameter estimation of the model. The structure-selection technique identifies the significant terms from a pool of candidates of functional basis and determines the optimal model through orthogonal characteristics on data. The technique with the Adams integration algorithm makes the reconstruction available to data sampled with large time intervals. Numerical experiment on Lorenz and Rossler systems shows that the proposed strategy is effective in global vector field reconstruction from noisy time series.

A combined Fuzzy and Naive Bayesian strategy can be used to assign event codes to injury narratives.

PubMed

Marucci-Wellman, H; Lehto, M; Corns, H

2011-12-01

Bayesian methods show promise for classifying injury narratives from large administrative datasets into cause groups. This study examined a combined approach where two Bayesian models (Fuzzy and Naïve) were used to either classify a narrative or select it for manual review. Injury narratives were extracted from claims filed with a worker's compensation insurance provider between January 2002 and December 2004. Narratives were separated into a training set (n=11,000) and prediction set (n=3,000). Expert coders assigned two-digit Bureau of Labor Statistics Occupational Injury and Illness Classification event codes to each narrative. Fuzzy and Naïve Bayesian models were developed using manually classified cases in the training set. Two semi-automatic machine coding strategies were evaluated. The first strategy assigned cases for manual review if the Fuzzy and Naïve models disagreed on the classification. The second strategy selected additional cases for manual review from the Agree dataset using prediction strength to reach a level of 50% computer coding and 50% manual coding. When agreement alone was used as the filtering strategy, the majority were coded by the computer (n=1,928, 64%) leaving 36% for manual review. The overall combined (human plus computer) sensitivity was 0.90 and positive predictive value (PPV) was >0.90 for 11 of 18 2-digit event categories. Implementing the 2nd strategy improved results with an overall sensitivity of 0.95 and PPV >0.90 for 17 of 18 categories. A combined Naïve-Fuzzy Bayesian approach can classify some narratives with high accuracy and identify others most beneficial for manual review, reducing the burden on human coders.

A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

PubMed Central

Balcarras, Matthew; Womelsdorf, Thilo

2016-01-01

Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context-specific selections to drive responses. PMID:27064794

Climate Change Implications for Tropical Islands: Interpolating and Interpreting Statistically Downscaled GCM Projections for Management and Planning

Treesearch

Azad Henareh Khalyani; William A. Gould; Eric Harmsen; Adam Terando; Maya Quinones; Jaime A. Collazo

2016-01-01

An Ontology of Power: Perception and Reality in Conflict

DTIC Science & Technology

2016-12-01

synthetic model was developed as the constant comparative analysis was resumed through the application of selected theory toward the original source...The synthetic model represents a series of maxims for the analysis of a complex social system, developed through a study of contemporary national...and categories. A model of strategic agency is proposed as an alternative framework for developing security strategy. The strategic agency model draws

Mechanical effort predicts the selection of ankle over hip strategies in nonstepping postural responses

PubMed Central

Jonkers, Ilse; De Schutter, Joris; De Groote, Friedl

2016-01-01

Experimental studies have shown that a continuum of ankle and hip strategies is used to restore posture following an external perturbation. Postural responses can be modeled by feedback control with feedback gains that optimize a specific objective. On the one hand, feedback gains that minimize effort have been used to predict muscle activity during perturbed standing. On the other hand, hip and ankle strategies have been predicted by minimizing postural instability and deviation from upright posture. It remains unclear, however, whether and how effort minimization influences the selection of a specific postural response. We hypothesize that the relative importance of minimizing mechanical work vs. postural instability influences the strategy used to restore upright posture. This hypothesis was investigated based on experiments and predictive simulations of the postural response following a backward support surface translation. Peak hip flexion angle was significantly correlated with three experimentally determined measures of effort, i.e., mechanical work, mean muscle activity and metabolic energy. Furthermore, a continuum of ankle and hip strategies was predicted in simulation when changing the relative importance of minimizing mechanical work and postural instability, with increased weighting of mechanical work resulting in an ankle strategy. In conclusion, the combination of experimental measurements and predictive simulations of the postural response to a backward support surface translation showed that the trade-off between effort and postural instability minimization can explain the selection of a specific postural response in the continuum of potential ankle and hip strategies. PMID:27489362

Physical approach to price momentum and its application to momentum strategy

NASA Astrophysics Data System (ADS)

Choi, Jaehyung

2014-12-01

We introduce various quantitative and mathematical definitions for price momentum of financial instruments. The price momentum is quantified with velocity and mass concepts originated from the momentum in physics. By using the physical momentum of price as a selection criterion, the weekly contrarian strategies are implemented in South Korea KOSPI 200 and US S&P 500 universes. The alternative strategies constructed by the physical momentum achieve the better expected returns and reward-risk measures than those of the traditional contrarian strategy in weekly scale. The portfolio performance is not understood by the Fama-French three-factor model.

Research on Correlation between Vehicle Cycle and Engine Cycle in Heavy-duty commercial vehicle

NASA Astrophysics Data System (ADS)

lin, Chen; Zhong, Wang; Shuai, Liu

2017-12-01

In order to study the correlation between vehicle cycle and engine cycle in heavy commercial vehicles, the conversion model of vehicle cycle to engine cycle is constructed based on the vehicle power system theory and shift strategy, which considers the verification on diesel truck. The results show that the model has high rationality and reliability in engine operation. In the acceleration process of high speed, the difference of model gear selection leads to the actual deviation. Compared with the drum test, the engine speed distribution obtained by the model deviates to right, which fits to the lower grade. The grade selection has high influence on the model.

Analyses of the most influential factors for vibration monitoring of planetary power transmissions in pellet mills by adaptive neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Milovančević, Miloš; Nikolić, Vlastimir; Anđelković, Boban

2017-01-01

Vibration-based structural health monitoring is widely recognized as an attractive strategy for early damage detection in civil structures. Vibration monitoring and prediction is important for any system since it can save many unpredictable behaviors of the system. If the vibration monitoring is properly managed, that can ensure economic and safe operations. Potentials for further improvement of vibration monitoring lie in the improvement of current control strategies. One of the options is the introduction of model predictive control. Multistep ahead predictive models of vibration are a starting point for creating a successful model predictive strategy. For the purpose of this article, predictive models of are created for vibration monitoring of planetary power transmissions in pellet mills. The models were developed using the novel method based on ANFIS (adaptive neuro fuzzy inference system). The aim of this study is to investigate the potential of ANFIS for selecting the most relevant variables for predictive models of vibration monitoring of pellet mills power transmission. The vibration data are collected by PIC (Programmable Interface Controller) microcontrollers. The goal of the predictive vibration monitoring of planetary power transmissions in pellet mills is to indicate deterioration in the vibration of the power transmissions before the actual failure occurs. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of vibration monitoring. It was also used to select the minimal input subset of variables from the initial set of input variables - current and lagged variables (up to 11 steps) of vibration. The obtained results could be used for simplification of predictive methods so as to avoid multiple input variables. It was preferable to used models with less inputs because of overfitting between training and testing data. While the obtained results are promising, further work is required in order to get results that could be directly applied in practice.

Sex-ratio control erodes sexual selection, revealing evolutionary feedback from adaptive plasticity.

PubMed

Fawcett, Tim W; Kuijper, Bram; Weissing, Franz J; Pen, Ido

2011-09-20

Female choice is a powerful selective force, driving the elaboration of conspicuous male ornaments. This process of sexual selection has profound implications for many life-history decisions, including sex allocation. For example, females with attractive partners should produce more sons, because these sons will inherit their father's attractiveness and enjoy high mating success, thereby yielding greater fitness returns than daughters. However, previous research has overlooked the fact that there is a reciprocal feedback from life-history strategies to sexual selection. Here, using a simple mathematical model, we show that if mothers adaptively control offspring sex in relation to their partner's attractiveness, sexual selection is weakened and male ornamentation declines. This weakening occurs because the ability to determine offspring sex reduces the fitness difference between females with attractive and unattractive partners. We use individual-based, evolutionary simulations to show that this result holds under more biologically realistic conditions. Sexual selection and sex allocation thus interact in a dynamic fashion: The evolution of conspicuous male ornaments favors sex-ratio adjustment, but this conditional strategy then undermines the very same process that generated it, eroding sexual selection. We predict that, all else being equal, the most elaborate sexual displays should be seen in species with little or no control over offspring sex. The feedback process we have described points to a more general evolutionary principle, in which a conditional strategy weakens directional selection on another trait by reducing fitness differences.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach

PubMed Central

Karamintziou, Sofia D.; Custódio, Ana Luísa; Piallat, Brigitte; Polosan, Mircea; Chabardès, Stéphan; Stathis, Pantelis G.; Tagaris, George A.; Sakas, Damianos E.; Polychronaki, Georgia E.; Tsirogiannis, George L.; David, Olivier; Nikita, Konstantina S.

2017-01-01

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson’s disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications. PMID:28222198

Facultative anadromy in salmonids: linking habitat, individual life history decisions, and population-level consequences

Treesearch

Steven F. Railsback; Bret C. Harvey; Jason L. White

2014-01-01

Modeling and management of facultative anadromous salmonids is complicated by their ability to select anadromous or resident life histories. Conventional theory for this behavior assumes individuals select the strategy offering highest expected reproductive success but does not predict how population-level consequences such as a stream’s smolt production emerge from...

Selective Planning of the First Year Experience in Higher Education: A Sweden-Australia Comparative Study of Support

ERIC Educational Resources Information Center

Christie, Michael; Penn-Edwards, Sorrel; Donnison, Sharn; Greenaway, Ruth

2018-01-01

Literature on the support of the First Year Experience (FYE) in institutions of Higher Education provides a range of modelled approaches. However, we argue that institutions still need to selectively plan which approach/es and attendant strategies are best suited to their particular contexts and institutional policy and practice frameworks and how…

The Models and Hard Cores: Selective Acculturation and Racial Stratification in Chinese Students' School Experience in Malaysia

ERIC Educational Resources Information Center

Kee, Geok Hwa

2010-01-01

Are the academic and social experiences of Chinese Malaysian students as much an outcome of the selective acculturation strategy of their parents as the linguistic assimilation policy of the government? Driven by economic necessity on one hand and pressured by cultural preservation on the other, Chinese parents first send their sons and daughters…

Multi-criteria evaluation of wastewater treatment plant control strategies under uncertainty.

PubMed

Flores-Alsina, Xavier; Rodríguez-Roda, Ignasi; Sin, Gürkan; Gernaey, Krist V

2008-11-01

The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models are not well characterized and some of the parameters can present uncertainty, e.g. the influent fractions arriving to the facility and the effect of either temperature or toxic compounds on the kinetic parameters, having a strong influence in the model predictions used during the evaluation of the alternatives and affecting the resulting rank of preferences. Using a simplified version of the IWA Benchmark Simulation Model No. 2 as a case study, this article shows the variations in the decision making when the uncertainty in activated sludge model (ASM) parameters is either included or not during the evaluation of WWTP control strategies. This paper comprises two main sections. Firstly, there is the evaluation of six WWTP control strategies using multi-criteria decision analysis setting the ASM parameters at their default value. In the following section, the uncertainty is introduced, i.e. input uncertainty, which is characterized by probability distribution functions based on the available process knowledge. Next, Monte Carlo simulations are run to propagate input through the model and affect the different outcomes. Thus (i) the variation in the overall degree of satisfaction of the control objectives for the generated WWTP control strategies is quantified, (ii) the contributions of environmental, legal, technical and economic objectives to the existing variance are identified and finally (iii) the influence of the relative importance of the control objectives during the selection of alternatives is analyzed. The results show that the control strategies with an external carbon source reduce the output uncertainty in the criteria used to quantify the degree of satisfaction of environmental, technical and legal objectives, but increasing the economical costs and their variability as a trade-off. Also, it is shown how a preliminary selected alternative with cascade ammonium controller becomes less desirable when input uncertainty is included, having simpler alternatives more chance of success.

Public goods games in populations with fluctuating size.

PubMed

McAvoy, Alex; Fraiman, Nicolas; Hauert, Christoph; Wakeley, John; Nowak, Martin A

2018-05-01

Many mathematical frameworks of evolutionary game dynamics assume that the total population size is constant and that selection affects only the relative frequency of strategies. Here, we consider evolutionary game dynamics in an extended Wright-Fisher process with variable population size. In such a scenario, it is possible that the entire population becomes extinct. Survival of the population may depend on which strategy prevails in the game dynamics. Studying cooperative dilemmas, it is a natural feature of such a model that cooperators enable survival, while defectors drive extinction. Although defectors are favored for any mixed population, random drift could lead to their elimination and the resulting pure-cooperator population could survive. On the other hand, if the defectors remain, then the population will quickly go extinct because the frequency of cooperators steadily declines and defectors alone cannot survive. In a mutation-selection model, we find that (i) a steady supply of cooperators can enable long-term population survival, provided selection is sufficiently strong, and (ii) selection can increase the abundance of cooperators but reduce their relative frequency. Thus, evolutionary game dynamics in populations with variable size generate a multifaceted notion of what constitutes a trait's long-term success. Copyright © 2018 Elsevier Inc. All rights reserved.

Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

PubMed Central

McGregor, Heather R.; Pun, Henry C. H.; Buckingham, Gavin; Gribble, Paul L.

2016-01-01

The human sensorimotor system is routinely capable of making accurate predictions about an object's weight, which allows for energetically efficient lifts and prevents objects from being dropped. Often, however, poor predictions arise when the weight of an object can vary and sensory cues about object weight are sparse (e.g., picking up an opaque water bottle). The question arises, what strategies does the sensorimotor system use to make weight predictions when one is dealing with an object whose weight may vary? For example, does the sensorimotor system use a strategy that minimizes prediction error (minimal squared error) or one that selects the weight that is most likely to be correct (maximum a posteriori)? In this study we dissociated the predictions of these two strategies by having participants lift an object whose weight varied according to a skewed probability distribution. We found, using a small range of weight uncertainty, that four indexes of sensorimotor prediction (grip force rate, grip force, load force rate, and load force) were consistent with a feedforward strategy that minimizes the square of prediction errors. These findings match research in the visuomotor system, suggesting parallels in underlying processes. We interpret our findings within a Bayesian framework and discuss the potential benefits of using a minimal squared error strategy. NEW & NOTEWORTHY Using a novel experimental model of object lifting, we tested whether the sensorimotor system models the weight of objects by minimizing lifting errors or by selecting the statistically most likely weight. We found that the sensorimotor system minimizes the square of prediction errors for object lifting. This parallels the results of studies that investigated visually guided reaching, suggesting an overlap in the underlying mechanisms between tasks that involve different sensory systems. PMID:27760821

Hospitals' strategies for orchestrating selection of physician preference items.

PubMed

Montgomery, Kathleen; Schneller, Eugene S

2007-06-01

This article analyzes hospitals' strategies to shape physicians' behavior and counter suppliers' power in purchasing physician preference items. Two models of standardization are limitations on the range of manufacturers or products (the "formulary" model) and price ceilings for particular item categories (the "payment-cap" model), both requiring processes to define product equivalencies often with inadequate product comparison data. The formulary model is more difficult to implement because of physicians' resistance to top-down dictates. The payment-cap model is more feasible because it preserves physicians' choice while also restraining manufacturers' power. Hospitals may influence physicians' involvement through a process of orchestration that includes committing to improve clinical facilities, scheduling, and training and fostering a culture of mutual trust and respect.

Hospitals' Strategies for Orchestrating Selection of Physician Preference Items

PubMed Central

Montgomery, Kathleen; Schneller, Eugene S

2007-01-01

This article analyzes hospitals' strategies to shape physicians' behavior and counter suppliers' power in purchasing physician preference items. Two models of standardization are limitations on the range of manufacturers or products (the “formulary” model) and price ceilings for particular item categories (the “payment-cap” model), both requiring processes to define product equivalencies often with inadequate product comparison data. The formulary model is more difficult to implement because of physicians' resistance to top-down dictates. The payment-cap model is more feasible because it preserves physicians' choice while also restraining manufacturers' power. Hospitals may influence physicians' involvement through a process of orchestration that includes committing to improve clinical facilities, scheduling, and training and fostering a culture of mutual trust and respect. PMID:17517118

Selection of experimental modal data sets for damage detection via model update

NASA Technical Reports Server (NTRS)

Doebling, S. W.; Hemez, F. M.; Barlow, M. S.; Peterson, L. D.; Farhat, C.

1993-01-01

When using a finite element model update algorithm for detecting damage in structures, it is important that the experimental modal data sets used in the update be selected in a coherent manner. In the case of a structure with extremely localized modal behavior, it is necessary to use both low and high frequency modes, but many of the modes in between may be excluded. In this paper, we examine two different mode selection strategies based on modal strain energy, and compare their success to the choice of an equal number of modes based merely on lowest frequency. Additionally, some parameters are introduced to enable a quantitative assessment of the success of our damage detection algorithm when using the various set selection criteria.

Cost-Effectiveness Analysis of Hepatitis B Vaccination Strategies to Prevent Perinatal Transmission in North Korea: Selective Vaccination vs. Universal Vaccination.

PubMed

Lee, Donghoon; Park, Sang Min

2016-01-01

To tackle the high prevalence of Hepatitis B virus (HBV) infection in North Korea, it is essential that birth doses of HBV vaccines should be administered within 24 hours of birth. As the country fails to provide a Timely Birth Dose (TBD) of HBV vaccine, the efforts of reducing the high prevalence of HBV have been significantly hampered. To examine the cost-effectiveness of vaccination strategies to prevent perinatal transmission of HBV in North Korea, we established a decision tree with a Markov model consisting of selective, universal, and the country's current vaccination program against HBV. The cost-effectiveness analysis was performed from societal and payer's perspectives and evaluated by Disability Adjusted Life Year (DALY). The results suggest that introducing the universal vaccination would prevent 1,866 cases of perinatal infections per 100,000 of the birth cohort of 2013. Furthermore, 900 cases of perinatal infections per 100,000 could be additionally averted if switching to the selective vaccination. The current vaccination is a dominated strategy both from the societal and payer's perspective. The Incremental Cost-Effectiveness Ratio (ICER) between universal and selective vaccination is $267 from the societal perspective and is reported as $273 from the payer's perspective. Based on the assumption that the 2012 Gross Domestic Product (GDP) per capita in North Korea, $582.6 was set for cost-effectiveness criteria, the result of this study indicates that selective vaccination may be a highly cost-effective strategy compared to universal vaccination.

Goals and hurdles for a successful implementation of genomic selection in breeding programme for selected annual and perennial crops.

PubMed

Jonas, Elisabeth; de Koning, Dirk Jan

Genomic Selection is an important topic in quantitative genetics and breeding. Not only does it allow the full use of current molecular genetic technologies, it stimulates also the development of new methods and models. Genomic selection, if fully implemented in commercial farming, should have a major impact on the productivity of various agricultural systems. But suggested approaches need to be applicable in commercial breeding populations. Many of the published research studies focus on methodologies. We conclude from the reviewed publications, that a stronger focus on strategies for the implementation of genomic selection in advanced breeding lines, introduction of new varieties, hybrids or multi-line crosses is needed. Efforts to find solutions for a better prediction and integration of environmental influences need to continue within applied breeding schemes. Goals of the implementation of genomic selection into crop breeding should be carefully defined and crop breeders in the private sector will play a substantial part in the decision-making process. However, the lack of published results from studies within, or in collaboration with, private companies diminishes the knowledge on the status of genomic selection within applied breeding programmes. Studies on the implementation of genomic selection in plant breeding need to evaluate models and methods with an enhanced emphasis on population-specific requirements and production environments. Adaptation of methods to breeding schemes or changes to breeding programmes for a better integration of genomic selection strategies are needed across species. More openness with a continuous exchange will contribute to successes.

Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

PubMed Central

Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

Intermediate School Game Curriculum. A Balance of the Traditional and the Contemporary.

ERIC Educational Resources Information Center

Gabbard, Carl; Miller, Glen

1987-01-01

This article describes the traditional game curriculum and presents strategies for a model that incorporates selected contemporary applications. Discussed are conventional games, low organization games, and cooperative and creative games. (MT)

A model of directional selection applied to the evolution of drug resistance in HIV-1.

PubMed

Seoighe, Cathal; Ketwaroo, Farahnaz; Pillay, Visva; Scheffler, Konrad; Wood, Natasha; Duffet, Rodger; Zvelebil, Marketa; Martinson, Neil; McIntyre, James; Morris, Lynn; Hide, Winston

2007-04-01

Understanding how pathogens acquire resistance to drugs is important for the design of treatment strategies, particularly for rapidly evolving viruses such as HIV-1. Drug treatment can exert strong selective pressures and sites within targeted genes that confer resistance frequently evolve far more rapidly than the neutral rate. Rapid evolution at sites that confer resistance to drugs can be used to help elucidate the mechanisms of evolution of drug resistance and to discover or corroborate novel resistance mutations. We have implemented standard maximum likelihood methods that are used to detect diversifying selection and adapted them for use with serially sampled reverse transcriptase (RT) coding sequences isolated from a group of 300 HIV-1 subtype C-infected women before and after single-dose nevirapine (sdNVP) to prevent mother-to-child transmission. We have also extended the standard models of codon evolution for application to the detection of directional selection. Through simulation, we show that the directional selection model can provide a substantial improvement in sensitivity over models of diversifying selection. Five of the sites within the RT gene that are known to harbor mutations that confer resistance to nevirapine (NVP) strongly supported the directional selection model. There was no evidence that other mutations that are known to confer NVP resistance were selected in this cohort. The directional selection model, applied to serially sampled sequences, also had more power than the diversifying selection model to detect selection resulting from factors other than drug resistance. Because inference of selection from serial samples is unlikely to be adversely affected by recombination, the methods we describe may have general applicability to the analysis of positive selection affecting recombining coding sequences when serially sampled data are available.

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

User's Guide to the Stand Prognosis Model

Treesearch

William R. Wykoff; Nicholas L. Crookston; Albert R. Stage

1982-01-01

The Stand Prognosis Model is a computer program that projects the development of forest stands in the Northern Rocky Mountains. Thinning options allow for simulation of a variety of management strategies. Input consists of a stand inventory, including sample tree records, and a set of option selection instructions. Output includes data normally found in stand, stock,...

Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs - AMS Testbed Selection Criteria

DOT National Transportation Integrated Search

2016-06-16

The primary objective of this project is to develop multiple simulation Testbeds/transportation models to evaluate the impacts of DMA connected vehicle applications and the active and dynamic transportation management (ATDM) strategies. The outputs (...

Calibration sets selection strategy for the construction of robust PLS models for prediction of biodiesel/diesel blends physico-chemical properties using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Palou, Anna; Miró, Aira; Blanco, Marcelo; Larraz, Rafael; Gómez, José Francisco; Martínez, Teresa; González, Josep Maria; Alcalà, Manel

2017-06-01

Even when the feasibility of using near infrared (NIR) spectroscopy combined with partial least squares (PLS) regression for prediction of physico-chemical properties of biodiesel/diesel blends has been widely demonstrated, inclusion in the calibration sets of the whole variability of diesel samples from diverse production origins still remains as an important challenge when constructing the models. This work presents a useful strategy for the systematic selection of calibration sets of samples of biodiesel/diesel blends from diverse origins, based on a binary code, principal components analysis (PCA) and the Kennard-Stones algorithm. Results show that using this methodology the models can keep their robustness over time. PLS calculations have been done using a specialized chemometric software as well as the software of the NIR instrument installed in plant, and both produced RMSEP under reproducibility values of the reference methods. The models have been proved for on-line simultaneous determination of seven properties: density, cetane index, fatty acid methyl esters (FAME) content, cloud point, boiling point at 95% of recovery, flash point and sulphur.

Evolutionarily stable and convergent stable strategies in reaction-diffusion models for conditional dispersal.

PubMed

Lam, King-Yeung; Lou, Yuan

2014-02-01

We consider a mathematical model of two competing species for the evolution of conditional dispersal in a spatially varying, but temporally constant environment. Two species are different only in their dispersal strategies, which are a combination of random dispersal and biased movement upward along the resource gradient. In the absence of biased movement or advection, Hastings showed that the mutant can invade when rare if and only if it has smaller random dispersal rate than the resident. When there is a small amount of biased movement or advection, we show that there is a positive random dispersal rate that is both locally evolutionarily stable and convergent stable. Our analysis of the model suggests that a balanced combination of random and biased movement might be a better habitat selection strategy for populations.

Selectivity Mechanism of ATP-Competitive Inhibitors for PKB and PKA.

PubMed

Wu, Ke; Pang, Jingzhi; Song, Dong; Zhu, Ying; Wu, Congwen; Shao, Tianqu; Chen, Haifeng

2015-07-01

Protein kinase B (PKB) acts as a central node on the PI3K kinase pathway. Constitutive activation and overexpression of PKB have been identified to involve in various cancers. However, protein kinase A (PKA) sharing high homology with PKB is essential for metabolic regulation. Therefore, specific targeting on PKB is crucial strategy in drug design and development for antitumor. Here, we had revealed the selectivity mechanism for PKB inhibitors with molecular dynamics simulation and 3D-QSAR methods. Selective inhibitors of PKB could form more hydrogen bonds and hydrophobic contacts with PKB than those with PKA. This could explain that selective inhibitor M128 is more potent to PKB than to PKA. Then, 3D-QSAR models were constructed for these selective inhibitors and evaluated by test set compounds. 3D-QSAR model comparison of PKB inhibitors and PKA inhibitors reveals possible methods to improve the selectivity of inhibitors. These models can be used to design new chemical entities and make quantitative prediction of the specific selective inhibitors before resorting to in vitro and in vivo experiment. © 2014 John Wiley & Sons A/S.

Elitist Binary Wolf Search Algorithm for Heuristic Feature Selection in High-Dimensional Bioinformatics Datasets.

PubMed

Li, Jinyan; Fong, Simon; Wong, Raymond K; Millham, Richard; Wong, Kelvin K L

2017-06-28

Due to the high-dimensional characteristics of dataset, we propose a new method based on the Wolf Search Algorithm (WSA) for optimising the feature selection problem. The proposed approach uses the natural strategy established by Charles Darwin; that is, 'It is not the strongest of the species that survives, but the most adaptable'. This means that in the evolution of a swarm, the elitists are motivated to quickly obtain more and better resources. The memory function helps the proposed method to avoid repeat searches for the worst position in order to enhance the effectiveness of the search, while the binary strategy simplifies the feature selection problem into a similar problem of function optimisation. Furthermore, the wrapper strategy gathers these strengthened wolves with the classifier of extreme learning machine to find a sub-dataset with a reasonable number of features that offers the maximum correctness of global classification models. The experimental results from the six public high-dimensional bioinformatics datasets tested demonstrate that the proposed method can best some of the conventional feature selection methods up to 29% in classification accuracy, and outperform previous WSAs by up to 99.81% in computational time.

Associations among selective attention, memory bias, cognitive errors and symptoms of anxiety in youth.

PubMed

Watts, Sarah E; Weems, Carl F

2006-12-01

The purpose of this study was to examine the linkages among selective attention, memory bias, cognitive errors, and anxiety problems by testing a model of the interrelations among these cognitive variables and childhood anxiety disorder symptoms. A community sample of 81 youth (38 females and 43 males) aged 9-17 years and their parents completed measures of the child's anxiety disorder symptoms. Youth completed assessments measuring selective attention, memory bias, and cognitive errors. Results indicated that selective attention, memory bias, and cognitive errors were each correlated with childhood anxiety problems and provide support for a cognitive model of anxiety which posits that these three biases are associated with childhood anxiety problems. Only limited support for significant interrelations among selective attention, memory bias, and cognitive errors was found. Finally, results point towards an effective strategy for moving the assessment of selective attention to younger and community samples of youth.

Identifying optimum performance trade-offs using a cognitively bounded rational analysis model of discretionary task interleaving.

PubMed

Janssen, Christian P; Brumby, Duncan P; Dowell, John; Chater, Nick; Howes, Andrew

2011-01-01

We report the results of a dual-task study in which participants performed a tracking and typing task under various experimental conditions. An objective payoff function was used to provide explicit feedback on how participants should trade off performance between the tasks. Results show that participants' dual-task interleaving strategy was sensitive to changes in the difficulty of the tracking task and resulted in differences in overall task performance. To test the hypothesis that people select strategies that maximize payoff, a Cognitively Bounded Rational Analysis model was developed. This analysis evaluated a variety of dual-task interleaving strategies to identify the optimal strategy for maximizing payoff in each condition. The model predicts that the region of optimum performance is different between experimental conditions. The correspondence between human data and the prediction of the optimal strategy is found to be remarkably high across a number of performance measures. This suggests that participants were honing their behavior to maximize payoff. Limitations are discussed. Copyright © 2011 Cognitive Science Society, Inc.

On Voxel based Iso-Tumor Control Probabilty and Iso-Complication Maps for Selective Boosting and Selective Avoidance Intensity Modulated Radiotherapy

PubMed Central

Kim, Yusung; Tomé, Wolfgang A.

2010-01-01

Summary Voxel based iso-Tumor Control Probability (TCP) maps and iso-Complication maps are proposed as a plan-review tool especially for functional image-guided intensity-modulated radiotherapy (IMRT) strategies such as selective boosting (dose painting) and conformal avoidance IMRT. The maps employ voxel-based phenomenological biological dose-response models for target volumes and normal organs. Two IMRT strategies for prostate cancer, namely conventional uniform IMRT delivering an EUD = 84 Gy (equivalent uniform dose) to the entire PTV and selective boosting delivering an EUD = 82 Gy to the entire PTV, are investigated, to illustrate the advantages of this approach over iso-dose maps. Conventional uniform IMRT did yield a more uniform isodose map to the entire PTV while selective boosting did result in a nonuniform isodose map. However, when employing voxel based iso-TCP maps selective boosting exhibited a more uniform tumor control probability map compared to what could be achieved using conventional uniform IMRT, which showed TCP cold spots in high-risk tumor subvolumes despite delivering a higher EUD to the entire PTV. Voxel based iso-Complication maps are presented for rectum and bladder, and their utilization for selective avoidance IMRT strategies are discussed. We believe as the need for functional image guided treatment planning grows, voxel based iso-TCP and iso-Complication maps will become an important tool to assess the integrity of such treatment plans. PMID:21151734

Short human occupations in the Middle Palaeolithic level i of the Abric Romani rock-shelter (Capellades, Barcelona, Spain)

USGS Publications Warehouse

Vallerdu, J.; Allue, E.; Bischoff, J.L.; Caceres, I.; Carbonell, E.; Cebria, A.; Garcia-Anton, D.; Huguet, R.; Ibanez, N.; Martinez, K.; Pasto, I.; Rosell, J.; Saladie, P.; Vaquero, Manola

2005-01-01

The small occupation surfaces and restricted provisioning strategies suggest short settlements in the Abric Romani. This shorter occupation model complements the longer diversified provisioning strategy recorded in both small and medium-sized occupied surfaces. The selection of precise elements for transport and the possible deferred consumption in the diversified provision strategy suggest an individual supply. In this respect, Neanderthal occupations in the Romani rock-shelter show a direct relation to: 1) hunting strategic resources; 2) high, linear mobility.

Research in Science Education, Volume 1990. Selected Refereed Papers from the Annual Conference of the Australasian Science Education Research Association (21st, Perth, Western Australia, July 1990).

ERIC Educational Resources Information Center

Gardner, Paul L., Ed.

1990-01-01

This book contains selected refereed papers from the 21st Annual Conference of the Australasian Science Education Research Association. The papers are as follows: "A Learning Model for Science Education: Developing Teaching Strategies" (Appleton); "Researching Balance between Cognition and Affect in Science Teaching" (Baird et…

Cloud computing task scheduling strategy based on improved differential evolution algorithm

NASA Astrophysics Data System (ADS)

Ge, Junwei; He, Qian; Fang, Yiqiu

2017-04-01

In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

Perspectives of Probabilistic Inferences: Reinforcement Learning and an Adaptive Network Compared

ERIC Educational Resources Information Center

Rieskamp, Jorg

2006-01-01

The assumption that people possess a strategy repertoire for inferences has been raised repeatedly. The strategy selection learning theory specifies how people select strategies from this repertoire. The theory assumes that individuals select strategies proportional to their subjective expectations of how well the strategies solve particular…

Effects of strategy sequences and response-stimulus intervals on children's strategy selection and strategy execution: a study in computational estimation.

PubMed

Lemaire, Patrick; Brun, Fleur

2014-07-01

The present study investigates how children's better strategy selection and strategy execution on a given problem are influenced by which strategy was used on the immediately preceding problem and by the duration between their answer to the previous problem and current problem display. These goals are pursued in the context of an arithmetic problem solving task. Third and fifth graders were asked to select the better strategy to find estimates to two-digit addition problems like 36 + 78. On each problem, children could choose rounding-down (i.e., rounding both operands down to the closest smaller decades, like doing 40 + 60 to solve 42 + 67) or rounding-up strategies (i.e., rounding both operands up to the closest larger decades, like doing 50 + 70 to solve 42 + 67). Children were tested under a short RSI condition (i.e., the next problem was displayed 900 ms after participants' answer) or under a long RSI condition (i.e., the next problem was displayed 1,900 ms after participants' answer). Results showed that both strategy selection (e.g., children selected the better strategy more often under long RSI condition and after selecting the poorer strategy on the immediately preceding problem) and strategy execution (e.g., children executed strategy more efficiently under long RSI condition and were slower when switching strategy over two consecutive problems) were influenced by RSI and which strategy was used on the immediately preceding problem. Moreover, data showed age-related changes in effects of RSI and strategy sequence on mean percent better strategy selection and on strategy performance. The present findings have important theoretical and empirical implications for our understanding of general and specific processes involved in strategy selection, strategy execution, and strategic development.

Information access in a dual-task context: testing a model of optimal strategy selection.

PubMed

Wickens, C D; Seidler, K S

1997-09-01

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

Information access in a dual-task context: testing a model of optimal strategy selection

NASA Technical Reports Server (NTRS)

Wickens, C. D.; Seidler, K. S.

1997-01-01

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

Visually based path-planning by Japanese monkeys.

PubMed

Mushiake, H; Saito, N; Sakamoto, K; Sato, Y; Tanji, J

2001-03-01

To construct an animal model of strategy formation, we designed a maze path-finding task. First, we asked monkeys to capture a goal in the maze by moving a cursor on the screen. Cursor movement was linked to movements of each wrist. When the animals learned the association between cursor movement and wrist movement, we established a start and a goal in the maze, and asked them to find a path between them. We found that the animals took the shortest pathway, rather than approaching the goal randomly. We further found that the animals adopted a strategy of selecting a fixed intermediate point in the visually presented maze to select one of the shortest pathways, suggesting a visually based path planning. To examine their capacity to use that strategy flexibly, we transformed the task by blocking pathways in the maze, providing a problem to solve. The animals then developed a strategy of solving the problem by planning a novel shortest path from the start to the goal and rerouting the path to bypass the obstacle.

Modeling strategies for pharmaceutical blend monitoring and end-point determination by near-infrared spectroscopy.

PubMed

Igne, Benoît; de Juan, Anna; Jaumot, Joaquim; Lallemand, Jordane; Preys, Sébastien; Drennen, James K; Anderson, Carl A

2014-10-01

The implementation of a blend monitoring and control method based on a process analytical technology such as near infrared spectroscopy requires the selection and optimization of numerous criteria that will affect the monitoring outputs and expected blend end-point. Using a five component formulation, the present article contrasts the modeling strategies and end-point determination of a traditional quantitative method based on the prediction of the blend parameters employing partial least-squares regression with a qualitative strategy based on principal component analysis and Hotelling's T(2) and residual distance to the model, called Prototype. The possibility to monitor and control blend homogeneity with multivariate curve resolution was also assessed. The implementation of the above methods in the presence of designed experiments (with variation of the amount of active ingredient and excipients) and with normal operating condition samples (nominal concentrations of the active ingredient and excipients) was tested. The impact of criteria used to stop the blends (related to precision and/or accuracy) was assessed. Results demonstrated that while all methods showed similarities in their outputs, some approaches were preferred for decision making. The selectivity of regression based methods was also contrasted with the capacity of qualitative methods to determine the homogeneity of the entire formulation. Copyright © 2014. Published by Elsevier B.V.

Stochastic evolutionary voluntary public goods game with punishment in a Quasi-birth-and-death process.

PubMed

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2017-11-23

Traditional replication dynamic model and the corresponding concept of evolutionary stable strategy (ESS) only takes into account whether the system can return to the equilibrium after being subjected to a small disturbance. In the real world, due to continuous noise, the ESS of the system may not be stochastically stable. In this paper, a model of voluntary public goods game with punishment is studied in a stochastic situation. Unlike the existing model, we describe the evolutionary process of strategies in the population as a generalized quasi-birth-and-death process. And we investigate the stochastic stable equilibrium (SSE) instead. By numerical experiments, we get all possible SSEs of the system for any combination of parameters, and investigate the influence of parameters on the probabilities of the system to select different equilibriums. It is found that in the stochastic situation, the introduction of the punishment and non-participation strategies can change the evolutionary dynamics of the system and equilibrium of the game. There is a large range of parameters that the system selects the cooperative states as its SSE with a high probability. This result provides us an insight and control method for the evolution of cooperation in the public goods game in stochastic situations.

Rank-based methods for modeling dependence between loss triangles.

PubMed

Côté, Marie-Pier; Genest, Christian; Abdallah, Anas

2016-01-01

In order to determine the risk capital for their aggregate portfolio, property and casualty insurance companies must fit a multivariate model to the loss triangle data relating to each of their lines of business. As an inadequate choice of dependence structure may have an undesirable effect on reserve estimation, a two-stage inference strategy is proposed in this paper to assist with model selection and validation. Generalized linear models are first fitted to the margins. Standardized residuals from these models are then linked through a copula selected and validated using rank-based methods. The approach is illustrated with data from six lines of business of a large Canadian insurance company for which two hierarchical dependence models are considered, i.e., a fully nested Archimedean copula structure and a copula-based risk aggregation model.

The price of being seen to be just: an intention signalling strategy for indirect reciprocity.

PubMed

Tanaka, Hiroki; Ohtsuki, Hisashi; Ohtsubo, Yohsuke

2016-07-27

Cooperation among strangers is a marked characteristic of human sociality. One prominent evolutionary explanation for this form of human cooperation is indirect reciprocity, whereby each individual selectively helps people with a 'good' reputation, but not those with a 'bad' reputation. Some evolutionary analyses have underscored the importance of second-order reputation information (the reputation of a current partner's previous partner) for indirect reciprocity as it allows players to discriminate justified 'good' defectors, who selectively deny giving help to 'bad' partners, from unjustified 'bad' defectors. Nevertheless, it is not clear whether people in fact make use of second-order information in indirect reciprocity settings. As an alternative, we propose the intention signalling strategy, whereby defectors are given the option to abandon a resource as a means of expunging their 'bad' reputation. Our model deviates from traditional modelling approaches in the indirect reciprocity literature in a crucial way-we show that first-order information is sufficient to maintain cooperation if players are given an option to signal their intention. Importantly, our model is robust against invasion by both unconditionally cooperative and uncooperative strategies, a first step towards demonstrating its viability as an evolutionarily stable strategy. Furthermore, in two behavioural experiments, when participants were given the option to abandon a resource so as to mend a tarnished reputation, participants not only spontaneously began to use this option, they also interpreted others' use of this option as a signal of cooperative intent. © 2016 The Author(s).

Performance and robustness of hybrid model predictive control for controllable dampers in building models

NASA Astrophysics Data System (ADS)

Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

2016-04-01

A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

USGS Publications Warehouse

Williams, Perry J.; Kendall, William L.

2017-01-01

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem.A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose (Branta hutchinsii minima) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the a priori strategy, and then by examining trade-offs in the Pareto set using the a posteriori strategy. We used four approaches for selecting a final solution within the a posteriori strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.

Selection of relevant input variables in storm water quality modeling by multiobjective evolutionary polynomial regression paradigm

NASA Astrophysics Data System (ADS)

Creaco, E.; Berardi, L.; Sun, Siao; Giustolisi, O.; Savic, D.

2016-04-01

The growing availability of field data, from information and communication technologies (ICTs) in "smart" urban infrastructures, allows data modeling to understand complex phenomena and to support management decisions. Among the analyzed phenomena, those related to storm water quality modeling have recently been gaining interest in the scientific literature. Nonetheless, the large amount of available data poses the problem of selecting relevant variables to describe a phenomenon and enable robust data modeling. This paper presents a procedure for the selection of relevant input variables using the multiobjective evolutionary polynomial regression (EPR-MOGA) paradigm. The procedure is based on scrutinizing the explanatory variables that appear inside the set of EPR-MOGA symbolic model expressions of increasing complexity and goodness of fit to target output. The strategy also enables the selection to be validated by engineering judgement. In such context, the multiple case study extension of EPR-MOGA, called MCS-EPR-MOGA, is adopted. The application of the proposed procedure to modeling storm water quality parameters in two French catchments shows that it was able to significantly reduce the number of explanatory variables for successive analyses. Finally, the EPR-MOGA models obtained after the input selection are compared with those obtained by using the same technique without benefitting from input selection and with those obtained in previous works where other data-modeling techniques were used on the same data. The comparison highlights the effectiveness of both EPR-MOGA and the input selection procedure.

Search strategy selection in the Morris water maze indicates allocentric map formation during learning that underpins spatial memory formation.

PubMed

Rogers, Jake; Churilov, Leonid; Hannan, Anthony J; Renoir, Thibault

2017-03-01

Using a Matlab classification algorithm, we demonstrate that a highly salient distal cue array is required for significantly increased likelihoods of spatial search strategy selection during Morris water maze spatial learning. We hypothesized that increased spatial search strategy selection during spatial learning would be the key measure demonstrating the formation of an allocentric map to the escape location. Spatial memory, as indicated by quadrant preference for the area of the pool formally containing the hidden platform, was assessed as the main measure that this allocentric map had formed during spatial learning. Our C57BL/6J wild-type (WT) mice exhibit quadrant preference in the highly salient cue paradigm but not the low, corresponding with a 120% increase in the odds of a spatial search strategy selection during learning. In contrast, quadrant preference remains absent in serotonin 1A receptor (5-HT 1A R) knockout (KO) mice, who exhibit impaired search strategy selection during spatial learning. Additionally, we also aimed to assess the impact of the quality of the distal cue array on the spatial learning curves of both latency to platform and path length using mixed-effect regression models and found no significant associations or interactions. In contrast, we demonstrated that the spatial learning curve for search strategy selection was absent during training in the low saliency paradigm. Therefore, we propose that allocentric search strategy selection during spatial learning is the learning parameter in mice that robustly indicates the formation of a cognitive map for the escape goal location. These results also suggest that both latency to platform and path length spatial learning curves do not discriminate between allocentric and egocentric spatial learning and do not reliably predict spatial memory formation. We also show that spatial memory, as indicated by the absolute time in the quadrant formerly containing the hidden platform alone (without reference to the other areas of the pool), was not sensitive to cue saliency or impaired in 5-HT 1A R KO mice. Importantly, in the absence of a search strategy analysis, this suggests that to establish that the Morris water maze has worked (i.e. control mice have formed an allocentric map to the escape goal location), a measure of quadrant preference needs to be reported to establish spatial memory formation. This has implications for studies that claim hippocampal functioning is impaired using latency to platform or path length differences within the existing Morris water maze literature. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies

PubMed Central

Khamassi, Mehdi; Humphries, Mark D.

2012-01-01

Behavior in spatial navigation is often organized into map-based (place-driven) vs. map-free (cue-driven) strategies; behavior in operant conditioning research is often organized into goal-directed vs. habitual strategies. Here we attempt to unify the two. We review one powerful theory for distinct forms of learning during instrumental conditioning, namely model-based (maintaining a representation of the world) and model-free (reacting to immediate stimuli) learning algorithms. We extend these lines of argument to propose an alternative taxonomy for spatial navigation, showing how various previously identified strategies can be distinguished as “model-based” or “model-free” depending on the usage of information and not on the type of information (e.g., cue vs. place). We argue that identifying “model-free” learning with dorsolateral striatum and “model-based” learning with dorsomedial striatum could reconcile numerous conflicting results in the spatial navigation literature. From this perspective, we further propose that the ventral striatum plays key roles in the model-building process. We propose that the core of the ventral striatum is positioned to learn the probability of action selection for every transition between states of the world. We further review suggestions that the ventral striatal core and shell are positioned to act as “critics” contributing to the computation of a reward prediction error for model-free and model-based systems, respectively. PMID:23205006

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.

Positive interventions: An emotion regulation perspective.

PubMed

Quoidbach, Jordi; Mikolajczak, Moïra; Gross, James J

2015-05-01

The rapid growth of the literature on positive interventions to increase "happiness" has suggested the need for an overarching conceptual framework to integrate the many and apparently disparate findings. In this review, we used the process model of emotion regulation (Gross, 1998) to organize the existing literature on positive interventions and to advance theory by clarifying the mechanisms underlying their effectiveness. We have proposed that positive emotions can be increased both in the short- and longer-term through 5 families of emotion regulation strategies (i.e., situation selection, situation modification, attentional deployment, cognitive change, and response modulation), showing how these emotion regulation strategies can be applied before, during, and after positive emotional events. Regarding short-term increases in positive emotions, our review found that attentional deployment, cognitive change, and response modulation strategies have received the most empirical support, whereas more work is needed to establish the effectiveness of situation selection and situation modification strategies. Regarding longer-term increases in positive emotions, strategies such as situation selection during an event and attentional deployment before, during, and after an event have received strong empirical support and are at the center of many positive interventions. However, more work is needed to establish the specific benefits of the other strategies, especially situation modification. We argue that our emotion regulation framework clarifies existing interventions and points the way for new interventions that might be used to increase positive emotions in both nonclinical and clinical populations. (c) 2015 APA, all rights reserved).

Pharmacophore modeling, docking, and principal component analysis based clustering: combined computer-assisted approaches to identify new inhibitors of the human rhinovirus coat protein.

PubMed

Steindl, Theodora M; Crump, Carolyn E; Hayden, Frederick G; Langer, Thierry

2005-10-06

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

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.

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies.

PubMed

Ng'oma, Enoch; Perinchery, Anna M; King, Elizabeth G

2017-06-28

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the 'omic' opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory. © 2017 The Author(s).

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

PubMed Central

2017-01-01

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the ‘omic’ opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory. PMID:28637856

Development and Application of a Category System to Describe Pre-Service Science Teachers' Activities in the Process of Scientific Modelling

NASA Astrophysics Data System (ADS)

Krell, Moritz; Walzer, Christine; Hergert, Susann; Krüger, Dirk

2017-09-01

As part of their professional competencies, science teachers need an elaborate meta-modelling knowledge as well as modelling skills in order to guide and monitor modelling practices of their students. However, qualitative studies about (pre-service) science teachers' modelling practices are rare. This study provides a category system which is suitable to analyse and to describe pre-service science teachers' modelling activities and to infer modelling strategies. The category system was developed based on theoretical considerations and was inductively refined within the methodological frame of qualitative content analysis. For the inductive refinement, modelling practices of pre-service teachers (n = 4) have been video-taped and analysed. In this study, one case was selected to demonstrate the application of the category system to infer modelling strategies. The contribution of this study for science education research and science teacher education is discussed.

Solving multistage stochastic programming models of portfolio selection with outstanding liabilities

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

Edirisinghe, C.

1994-12-31

Models for portfolio selection in the presence of an outstanding liability have received significant attention, for example, models for pricing options. The problem may be described briefly as follows: given a set of risky securities (and a riskless security such as a bond), and given a set of cash flows, i.e., outstanding liability, to be met at some future date, determine an initial portfolio and a dynamic trading strategy for the underlying securities such that the initial cost of the portfolio is within a prescribed wealth level and the expected cash surpluses arising from trading is maximized. While the tradingmore » strategy should be self-financing, there may also be other restrictions such as leverage and short-sale constraints. Usually the treatment is limited to binomial evolution of uncertainty (of stock price), with possible extensions for developing computational bounds for multinomial generalizations. Posing as stochastic programming models of decision making, we investigate alternative efficient solution procedures under continuous evolution of uncertainty, for discrete time economies. We point out an important moment problem arising in the portfolio selection problem, the solution (or bounds) on which provides the basis for developing efficient computational algorithms. While the underlying stochastic program may be computationally tedious even for a modest number of trading opportunities (i.e., time periods), the derived algorithms may used to solve problems whose sizes are beyond those considered within stochastic optimization.« less

Cultural differences in strategic behavior: a study in computational estimation.

PubMed

Imbo, Ineke; Lefevre, Jo-Anne

2011-09-01

Imbo and LeFevre (2009) observed that Asians (responding in their 2nd language) selected strategies less adaptively than did non-Asians (responding in their 1st language). In the present research, we tested whether adaptive strategy selection is (a) really more resource demanding for Asians than for non-Asians or (b) more resource demanding for participants answering in a nonpreferred language. Three groups of participants were tested on a computational estimation task (e.g., 42 × 57 ≈ ?) in no-load and load conditions: 40 Belgian-educated adults who answered in their first language (Dutch), 40 Chinese-educated adults who answered in their first language (Chinese), and 40 Chinese-educated adults who answered in their second language (English). Although the Chinese were faster and more accurate than the Belgians, they selected strategies less adaptively. That is, the Chinese were less likely to choose the strategy that produced the best estimate; this was especially so when their working memory was loaded. Further, we also observed that the Chinese who answered in English were slower than the Chinese who answered in Chinese; this difference was larger for difficult strategies and under working memory load. These results are interpreted in terms of the encoding complex model, whereas the explanation for the adaptivity results is based on cultural differences in educational history. (c) 2011 APA, all rights reserved.

A Novel Nanoparticle Mediated Selective Inner Retinal Photocoagulation for Diseases of the Inner Retina.

PubMed

Singh, Rupesh; Rajaraman, Srinivas; Balasubramanian, Madhusudhanan

2017-10-01

A novel nanoparticle mediated methodology for laser photocoagulation of the inner retina to achieve tissue selective treatment is presented. Transport of 527, 577, and 810 nm laser, heat deposition, and eventual thermal damage in vitreous, retina, RPE, choroid, and sclera were modeled using Bouguer-Beer-Lambert law of absorption and solved numerically using the finite volume method. Nanoparticles were designed using Mie theory of scattering. Performance of the new photocoagulation strategy using gold nanospheres and gold-silica nanoshells was compared with that of conventional methods without nanoparticles. For experimental validation, vitreous cavity of ex vivo porcine eyes was infused with gold nanospheres. After ~6 h of nanoparticle diffusion, the porcine retina was irradiated with a green laser and imaged simultaneously using a spectral domain optical coherence tomography (Spectralis SD-OCT, Heidelberg Engineering). Our computational model predicted a significant spatial shift in the peak temperature from RPE to the inner retinal region when infused with nanoparticles. Arrhenius thermal damage in the mid-retinal location was achieved in ~14 ms for 527 nm laser thereby reducing the irradiation duration by ~30 ms compared with the treatment without nanoparticles. In ex vivo porcine eyes infused with gold nanospheres, SD-OCT retinal images revealed a lower thermal damage and expansion at RPE due to laser photocoagulation. Nanoparticle infused laser photocoagulation strategy provided a selective inner retinal thermal damage with significant decrease in laser power and laser exposure time. The proposed treatment strategy shows possibilities for an efficient and highly selective inner retinal laser treatment.

Genetic and economic benefits of selection based on performance recording and genotyping in lower tiers of multi-tiered sheep breeding schemes.

PubMed

Santos, Bruno F S; van der Werf, Julius H J; Gibson, John P; Byrne, Timothy J; Amer, Peter R

2017-01-17

Performance recording and genotyping in the multiplier tier of multi-tiered sheep breeding schemes could potentially reduce the difference in the average genetic merit between nucleus and commercial flocks, and create additional economic benefits for the breeding structure. The genetic change in a multiple-trait breeding objective was predicted for various selection strategies that included performance recording, parentage testing and genomic selection. A deterministic simulation model was used to predict selection differentials and the flow of genetic superiority through the different tiers. Cumulative discounted economic benefits were calculated based on trait gains achieved in each of the tiers and considering the extra revenue and associated costs of applying recording, genotyping and selection practices in the multiplier tier of the breeding scheme. Performance recording combined with genomic or parentage information in the multiplier tier reduced the genetic lag between the nucleus and commercial flock by 2 to 3 years. The overall economic benefits of improved performance in the commercial tier offset the costs of recording the multiplier. However, it took more than 18 years before the cumulative net present value of benefits offset the costs at current test prices. Strategies in which recorded multiplier ewes were selected as replacements for the nucleus flock did modestly increase profitability when compared to a closed nucleus structure. Applying genomic selection is the most beneficial strategy if testing costs can be reduced or by genotyping only a proportion of the selection candidates. When the cost of genotyping was reduced, scenarios that combine performance recording with genomic selection were more profitable and reached breakeven point about 10 years earlier. Economic benefits can be generated in multiplier flocks by implementing performance recording in conjunction with either DNA pedigree recording or genomic technology. These recording practices reduce the long genetic lag between the nucleus and commercial flocks in multi-tiered breeding programs. Under current genotyping costs, the time to breakeven was found to be generally very long, although this varied between strategies. Strategies using either genomic selection or DNA pedigree verification were found to be economically viable provided the price paid for the tests is lower than current prices, in the long-term.

Rationality Validation of a Layered Decision Model for Network Defense

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

Wei, Huaqiang; Alves-Foss, James; Zhang, Du

2007-08-31

We propose a cost-effective network defense strategy built on three key: three decision layers: security policies, defense strategies, and real-time defense tactics for countering immediate threats. A layered decision model (LDM) can be used to capture this decision process. The LDM helps decision-makers gain insight into the hierarchical relationships among inter-connected entities and decision types, and supports the selection of cost-effective defense mechanisms to safeguard computer networks. To be effective as a business tool, it is first necessary to validate the rationality of model before applying it to real-world business cases. This paper describes our efforts in validating the LDMmore » rationality through simulation.« less

Multivariate Bayesian variable selection exploiting dependence structure among outcomes: Application to air pollution effects on DNA methylation.

PubMed

Lee, Kyu Ha; Tadesse, Mahlet G; Baccarelli, Andrea A; Schwartz, Joel; Coull, Brent A

2017-03-01

The analysis of multiple outcomes is becoming increasingly common in modern biomedical studies. It is well-known that joint statistical models for multiple outcomes are more flexible and more powerful than fitting a separate model for each outcome; they yield more powerful tests of exposure or treatment effects by taking into account the dependence among outcomes and pooling evidence across outcomes. It is, however, unlikely that all outcomes are related to the same subset of covariates. Therefore, there is interest in identifying exposures or treatments associated with particular outcomes, which we term outcome-specific variable selection. In this work, we propose a variable selection approach for multivariate normal responses that incorporates not only information on the mean model, but also information on the variance-covariance structure of the outcomes. The approach effectively leverages evidence from all correlated outcomes to estimate the effect of a particular covariate on a given outcome. To implement this strategy, we develop a Bayesian method that builds a multivariate prior for the variable selection indicators based on the variance-covariance of the outcomes. We show via simulation that the proposed variable selection strategy can boost power to detect subtle effects without increasing the probability of false discoveries. We apply the approach to the Normative Aging Study (NAS) epigenetic data and identify a subset of five genes in the asthma pathway for which gene-specific DNA methylations are associated with exposures to either black carbon, a marker of traffic pollution, or sulfate, a marker of particles generated by power plants. © 2016, The International Biometric Society.

Cost-Effectiveness of HBV and HCV Screening Strategies – A Systematic Review of Existing Modelling Techniques

PubMed Central

Geue, Claudia; Wu, Olivia; Xin, Yiqiao; Heggie, Robert; Hutchinson, Sharon; Martin, Natasha K.; Fenwick, Elisabeth; Goldberg, David

2015-01-01

Introduction Studies evaluating the cost-effectiveness of screening for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) are generally heterogeneous in terms of risk groups, settings, screening intervention, outcomes and the economic modelling framework. It is therefore difficult to compare cost-effectiveness results between studies. This systematic review aims to summarise and critically assess existing economic models for HBV and HCV in order to identify the main methodological differences in modelling approaches. Methods A structured search strategy was developed and a systematic review carried out. A critical assessment of the decision-analytic models was carried out according to the guidelines and framework developed for assessment of decision-analytic models in Health Technology Assessment of health care interventions. Results The overall approach to analysing the cost-effectiveness of screening strategies was found to be broadly consistent for HBV and HCV. However, modelling parameters and related structure differed between models, producing different results. More recent publications performed better against a performance matrix, evaluating model components and methodology. Conclusion When assessing screening strategies for HBV and HCV infection, the focus should be on more recent studies, which applied the latest treatment regimes, test methods and had better and more complete data on which to base their models. In addition to parameter selection and associated assumptions, careful consideration of dynamic versus static modelling is recommended. Future research may want to focus on these methodological issues. In addition, the ability to evaluate screening strategies for multiple infectious diseases, (HCV and HIV at the same time) might prove important for decision makers. PMID:26689908

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.

Cost-effectiveness of lower extremity compression ultrasound in emergency department patients with a high risk of hemodynamically stable pulmonary embolism.

PubMed

Ward, Michael J; Sodickson, Aaron; Diercks, Deborah B; Raja, Ali S

2011-01-01

Computed tomography angiograms (CTAs) for patients with suspected pulmonary embolism (PE) are being ordered with increasing frequency from the emergency department (ED). Strategies are needed to safely decrease the utilization of CTs to control rising health care costs and minimize the associated risks of anaphylaxis, contrast-induced nephropathy, and radiation-induced carcinogenesis. The use of compression ultrasonography (US) to identify deep vein thromboses (DVTs) in hemodynamically stable patients with signs and symptoms suggestive of PE is highly specific for the diagnosis of PE and may represent a cost-effective alternative to CT imaging.   The objective was to analyze the cost-effectiveness of a selective CT strategy incorporating the use of compression US to diagnose and treat DVT in patients with a high pretest probability of PE. The authors constructed a decision analytic model to evaluate the scenario of an otherwise healthy 59-year-old female in whom PE was being considered as a diagnosis. Two strategies were used. The selective CT strategy began with a screening compression US. Negative studies were followed up with a CTA, while patients with positive studies identifying a DVT were treated as though they had a PE and were anticoagulated. The universal CT strategy used CTA as the initial test, and anticoagulation was based on the CT result. Costs were estimated from the 2009 Medicare data for hospital reimbursement, and professional fees were obtained from the 2009 National Physician Fee Schedule. Clinical probabilities were obtained from existing published data, and sensitivity analyses were performed across plausible ranges for all clinical variables. In the base case, the selective CT strategy cost $1,457.70 less than the universal CT strategy and resulted in a gain of 0.0213 quality-adjusted life-years (QALYs). Sensitivity analyses confirm that the selective CT strategy is dominant above both a pretest probability for PE of 8.3% and a compression US specificity of 87.4%. A selective CT strategy using compression US is cost-effective for patients provided they have a high pretest probability of PE. This may reduce the need for, and decrease the adverse events associated with, CTAs. © 2010 by the Society for Academic Emergency Medicine.

Tissue-specific selection of stable reference genes for real-time PCR normalization in an obese rat model.

PubMed

Cabiati, Manuela; Raucci, Serena; Caselli, Chiara; Guzzardi, Maria Angela; D'Amico, Andrea; Prescimone, Tommaso; Giannessi, Daniela; Del Ry, Silvia

2012-06-01

Obesity is a complex pathology with interacting and confounding causes due to the environment, hormonal signaling patterns, and genetic predisposition. At present, the Zucker rat is an eligible genetic model for research on obesity and metabolic syndrome, allowing scrutiny of gene expression profiles. Real-time PCR is the benchmark method for measuring mRNA expressions, but the accuracy and reproducibility of its data greatly depend on appropriate normalization strategies. In the Zucker rat model, no specific reference genes have been identified in myocardium, kidney, and lung, the main organs involved in this syndrome. The aim of this study was to select among ten candidates (Actb, Gapdh, Polr2a, Ywhag, Rpl13a, Sdha, Ppia, Tbp, Hprt1 and Tfrc) a set of reference genes that can be used for the normalization of mRNA expression data obtained by real-time PCR in obese and lean Zucker rats both at fasting and during acute hyperglycemia. The most stable genes in the heart were Sdha, Tbp, and Hprt1; in kidney, Tbp, Actb, and Gapdh were chosen, while Actb, Ywhag, and Sdha were selected as the most stably expressed set for pulmonary tissue. The normalization strategy was used to analyze mRNA expression of tumor necrosis factor α, the main inflammatory mediator in obesity, whose variations were more significant when normalized with the appropriately selected reference genes. The findings obtained in this study underline the importance of having three stably expressed reference gene sets for use in the cardiac, renal, and pulmonary tissues of an experimental model of obese and hyperglycemic Zucker rats.

Appropriateness guidelines and predictive rules to select patients for upper endoscopy: a nationwide multicenter study.

PubMed

Buri, Luigi; Hassan, Cesare; Bersani, Gianluca; Anti, Marcello; Bianco, Maria Antonietta; Cipolletta, Livio; Di Giulio, Emilio; Di Matteo, Giovanni; Familiari, Luigi; Ficano, Leonardo; Loriga, Pietro; Morini, Sergio; Pietropaolo, Vincenzo; Zambelli, Alessandro; Grossi, Enzo; Intraligi, Marco; Buscema, Massimo

2010-06-01

Selecting patients appropriately for upper endoscopy (EGD) is crucial for efficient use of endoscopy. The objective of this study was to compare different clinical strategies and statistical methods to select patients for EGD, namely appropriateness guidelines, age and/or alarm features, and multivariate and artificial neural network (ANN) models. A nationwide, multicenter, prospective study was undertaken in which consecutive patients referred for EGD during a 1-month period were enrolled. Before EGD, the endoscopist assessed referral appropriateness according to the American Society for Gastrointestinal Endoscopy (ASGE) guidelines, also collecting clinical and demographic variables. Outcomes of the study were detection of relevant findings and new diagnosis of malignancy at EGD. The accuracy of the following clinical strategies and predictive rules was compared: (i) ASGE appropriateness guidelines (indicated vs. not indicated), (ii) simplified rule (>or=45 years or alarm features vs. <45 years without alarm features), (iii) logistic regression model, and (iv) ANN models. A total of 8,252 patients were enrolled in 57 centers. Overall, 3,803 (46%) relevant findings and 132 (1.6%) new malignancies were detected. Sensitivity, specificity, and area under the receiver-operating characteristic curve (AUC) of the simplified rule were similar to that of the ASGE guidelines for both relevant findings (82%/26%/0.55 vs. 88%/27%/0.52) and cancer (97%/22%/0.58 vs. 98%/20%/0.58). Both logistic regression and ANN models seemed to be substantially more accurate in predicting new cases of malignancy, with an AUC of 0.82 and 0.87, respectively. A simple predictive rule based on age and alarm features is similarly effective to the more complex ASGE guidelines in selecting patients for EGD. Regression and ANN models may be useful in identifying a relatively small subgroup of patients at higher risk of cancer.

Cost-Effectiveness Analysis of Hepatitis B Vaccination Strategies to Prevent Perinatal Transmission in North Korea: Selective Vaccination vs. Universal Vaccination

PubMed Central

Lee, Donghoon; Park, Sang Min

2016-01-01

Background To tackle the high prevalence of Hepatitis B virus (HBV) infection in North Korea, it is essential that birth doses of HBV vaccines should be administered within 24 hours of birth. As the country fails to provide a Timely Birth Dose (TBD) of HBV vaccine, the efforts of reducing the high prevalence of HBV have been significantly hampered. Methods To examine the cost-effectiveness of vaccination strategies to prevent perinatal transmission of HBV in North Korea, we established a decision tree with a Markov model consisting of selective, universal, and the country’s current vaccination program against HBV. The cost-effectiveness analysis was performed from societal and payer’s perspectives and evaluated by Disability Adjusted Life Year (DALY). Results The results suggest that introducing the universal vaccination would prevent 1,866 cases of perinatal infections per 100,000 of the birth cohort of 2013. Furthermore, 900 cases of perinatal infections per 100,000 could be additionally averted if switching to the selective vaccination. The current vaccination is a dominated strategy both from the societal and payer’s perspective. The Incremental Cost-Effectiveness Ratio (ICER) between universal and selective vaccination is $267 from the societal perspective and is reported as $273 from the payer’s perspective. Conclusion Based on the assumption that the 2012 Gross Domestic Product (GDP) per capita in North Korea, $582.6 was set for cost-effectiveness criteria, the result of this study indicates that selective vaccination may be a highly cost-effective strategy compared to universal vaccination. PMID:27802340

Optimality and stability of symmetric evolutionary games with applications in genetic selection.

PubMed

Huang, Yuanyuan; Hao, Yiping; Wang, Min; Zhou, Wen; Wu, Zhijun

2015-06-01

Symmetric evolutionary games, i.e., evolutionary games with symmetric fitness matrices, have important applications in population genetics, where they can be used to model for example the selection and evolution of the genotypes of a given population. In this paper, we review the theory for obtaining optimal and stable strategies for symmetric evolutionary games, and provide some new proofs and computational methods. In particular, we review the relationship between the symmetric evolutionary game and the generalized knapsack problem, and discuss the first and second order necessary and sufficient conditions that can be derived from this relationship for testing the optimality and stability of the strategies. Some of the conditions are given in different forms from those in previous work and can be verified more efficiently. We also derive more efficient computational methods for the evaluation of the conditions than conventional approaches. We demonstrate how these conditions can be applied to justifying the strategies and their stabilities for a special class of genetic selection games including some in the study of genetic disorders.

The limits of weak selection and large population size in evolutionary game theory.

PubMed

Sample, Christine; Allen, Benjamin

2017-11-01

Evolutionary game theory is a mathematical approach to studying how social behaviors evolve. In many recent works, evolutionary competition between strategies is modeled as a stochastic process in a finite population. In this context, two limits are both mathematically convenient and biologically relevant: weak selection and large population size. These limits can be combined in different ways, leading to potentially different results. We consider two orderings: the [Formula: see text] limit, in which weak selection is applied before the large population limit, and the [Formula: see text] limit, in which the order is reversed. Formal mathematical definitions of the [Formula: see text] and [Formula: see text] limits are provided. Applying these definitions to the Moran process of evolutionary game theory, we obtain asymptotic expressions for fixation probability and conditions for success in these limits. We find that the asymptotic expressions for fixation probability, and the conditions for a strategy to be favored over a neutral mutation, are different in the [Formula: see text] and [Formula: see text] limits. However, the ordering of limits does not affect the conditions for one strategy to be favored over another.

Biomechanical Diversity of Mating Structures among Harvestmen Species Is Consistent with a Spectrum of Precopulatory Strategies

PubMed Central

Burns, Mercedes; Shultz, Jeffrey W.

2015-01-01

Diversity in reproductive structures is frequently explained by selection acting at individual to generational timescales, but interspecific differences predicted by such models (e.g., female choice or sexual conflict) are often untestable in a phylogenetic framework. An alternative approach focuses on clade- or function-specific hypotheses that predict evolutionary patterns in terms neutral to specific modes of sexual selection. Here we test a hypothesis that diversity of reproductive structures in leiobunine harvestmen (daddy longlegs) of eastern North America reflects two sexually coevolved but non-overlapping precopulatory strategies, a primitive solicitous strategy (females enticed by penis-associated nuptial gifts), and a multiply derived antagonistic strategy (penis exerts mechanical force against armature of the female pregenital opening). Predictions of sexual coevolution and fidelity to precopulatory categories were tested using 10 continuously varying functional traits from 28 species. Multivariate analyses corroborated sexual coevolution but failed to partition species by precopulatory strategy, with multiple methods placing species along a spectrum of mechanical antagonistic potential. These findings suggest that precopulatory features within species reflect different co-occurring levels of solicitation and antagonism, and that gradualistic evolutionary pathways exist between extreme strategies. The ability to quantify antagonistic potential of precopulatory structures invites comparison with ecological variables that may promote evolutionary shifts in precopulatory strategies. PMID:26352413

Biomechanical Diversity of Mating Structures among Harvestmen Species Is Consistent with a Spectrum of Precopulatory Strategies.

PubMed

Burns, Mercedes; Shultz, Jeffrey W

2015-01-01

Diversity in reproductive structures is frequently explained by selection acting at individual to generational timescales, but interspecific differences predicted by such models (e.g., female choice or sexual conflict) are often untestable in a phylogenetic framework. An alternative approach focuses on clade- or function-specific hypotheses that predict evolutionary patterns in terms neutral to specific modes of sexual selection. Here we test a hypothesis that diversity of reproductive structures in leiobunine harvestmen (daddy longlegs) of eastern North America reflects two sexually coevolved but non-overlapping precopulatory strategies, a primitive solicitous strategy (females enticed by penis-associated nuptial gifts), and a multiply derived antagonistic strategy (penis exerts mechanical force against armature of the female pregenital opening). Predictions of sexual coevolution and fidelity to precopulatory categories were tested using 10 continuously varying functional traits from 28 species. Multivariate analyses corroborated sexual coevolution but failed to partition species by precopulatory strategy, with multiple methods placing species along a spectrum of mechanical antagonistic potential. These findings suggest that precopulatory features within species reflect different co-occurring levels of solicitation and antagonism, and that gradualistic evolutionary pathways exist between extreme strategies. The ability to quantify antagonistic potential of precopulatory structures invites comparison with ecological variables that may promote evolutionary shifts in precopulatory strategies.

Computational methods in the development of a knowledge-based system for the prediction of solid catalyst performance.

PubMed

Procelewska, Joanna; Galilea, Javier Llamas; Clerc, Frederic; Farrusseng, David; Schüth, Ferdi

2007-01-01

The objective of this work is the construction of a correlation between characteristics of heterogeneous catalysts, encoded in a descriptor vector, and their experimentally measured performances in the propene oxidation reaction. In this paper the key issue in the modeling process, namely the selection of adequate input variables, is explored. Several data-driven feature selection strategies were applied in order to obtain an estimate of the differences in variance and information content of various attributes, furthermore to compare their relative importance. Quantitative property activity relationship techniques using probabilistic neural networks have been used for the creation of various semi-empirical models. Finally, a robust classification model, assigning selected attributes of solid compounds as input to an appropriate performance class in the model reaction was obtained. It has been evident that the mathematical support for the primary attributes set proposed by chemists can be highly desirable.

Cost-effectiveness analysis of microdose clinical trials in drug development.

PubMed

Yamane, Naoe; Igarashi, Ataru; Kusama, Makiko; Maeda, Kazuya; Ikeda, Toshihiko; Sugiyama, Yuichi

2013-01-01

Microdose (MD) clinical trials have been introduced to obtain human pharmacokinetic data early in drug development. Here we assessed the cost-effectiveness of microdose integrated drug development in a hypothetical model, as there was no such quantitative research that weighed the additional effectiveness against the additional time and/or cost. First, we calculated the cost and effectiveness (i.e., success rate) of 3 types of MD integrated drug development strategies: liquid chromatography-tandem mass spectrometry, accelerator mass spectrometry, and positron emission tomography. Then, we analyzed the cost-effectiveness of 9 hypothetical scenarios where 100 drug candidates entering into a non-clinical toxicity study were selected by different methods as the conventional scenario without MD. In the base-case, where 70 drug candidates were selected without MD and 30 selected evenly by one of the three MD methods, incremental cost-effectiveness ratio per one additional drug approved was JPY 12.7 billion (US$ 0.159 billion), whereas the average cost-effectiveness ratio of the conventional strategy was JPY 24.4 billion, which we set as a threshold. Integrating MD in the conventional drug development was cost-effective in this model. This quantitative analytical model which allows various modifications according to each company's conditions, would be helpful for guiding decisions early in clinical development.

Development of variable pathlength UV-vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring.

PubMed

Chen, Baisheng; Wu, Huanan; Li, Sam Fong Yau

2014-03-01

To overcome the challenging task to select an appropriate pathlength for wastewater chemical oxygen demand (COD) monitoring with high accuracy by UV-vis spectroscopy in wastewater treatment process, a variable pathlength approach combined with partial-least squares regression (PLSR) was developed in this study. Two new strategies were proposed to extract relevant information of UV-vis spectral data from variable pathlength measurements. The first strategy was by data fusion with two data fusion levels: low-level data fusion (LLDF) and mid-level data fusion (MLDF). Predictive accuracy was found to improve, indicated by the lower root-mean-square errors of prediction (RMSEP) compared with those obtained for single pathlength measurements. Both fusion levels were found to deliver very robust PLSR models with residual predictive deviations (RPD) greater than 3 (i.e. 3.22 and 3.29, respectively). The second strategy involved calculating the slopes of absorbance against pathlength at each wavelength to generate slope-derived spectra. Without the requirement to select the optimal pathlength, the predictive accuracy (RMSEP) was improved by 20-43% as compared to single pathlength spectroscopy. Comparing to nine-factor models from fusion strategy, the PLSR model from slope-derived spectroscopy was found to be more parsimonious with only five factors and more robust with residual predictive deviation (RPD) of 3.72. It also offered excellent correlation of predicted and measured COD values with R(2) of 0.936. In sum, variable pathlength spectroscopy with the two proposed data analysis strategies proved to be successful in enhancing prediction performance of COD in wastewater and showed high potential to be applied in on-line water quality monitoring. Copyright © 2013 Elsevier B.V. All rights reserved.

Black-Box System Testing of Real-Time Embedded Systems Using Random and Search-Based Testing

NASA Astrophysics Data System (ADS)

Arcuri, Andrea; Iqbal, Muhammad Zohaib; Briand, Lionel

Testing real-time embedded systems (RTES) is in many ways challenging. Thousands of test cases can be potentially executed on an industrial RTES. Given the magnitude of testing at the system level, only a fully automated approach can really scale up to test industrial RTES. In this paper we take a black-box approach and model the RTES environment using the UML/MARTE international standard. Our main motivation is to provide a more practical approach to the model-based testing of RTES by allowing system testers, who are often not familiar with the system design but know the application domain well-enough, to model the environment to enable test automation. Environment models can support the automation of three tasks: the code generation of an environment simulator, the selection of test cases, and the evaluation of their expected results (oracles). In this paper, we focus on the second task (test case selection) and investigate three test automation strategies using inputs from UML/MARTE environment models: Random Testing (baseline), Adaptive Random Testing, and Search-Based Testing (using Genetic Algorithms). Based on one industrial case study and three artificial systems, we show how, in general, no technique is better than the others. Which test selection technique to use is determined by the failure rate (testing stage) and the execution time of test cases. Finally, we propose a practical process to combine the use of all three test strategies.

Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments

NASA Astrophysics Data System (ADS)

Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng

2016-11-01

To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.

Identifying species conservation strategies to reduce disease-associated declines

USGS Publications Warehouse

Gerber, Brian D.; Converse, Sarah J.; Muths, Erin L.; Crockett, Harry J.; Mosher, Brittany A.; Bailey, Larissa L.

2018-01-01

Emerging infectious diseases (EIDs) are a salient threat to many animal taxa, causing local and global extinctions, altering communities and ecosystem function. The EID chytridiomycosis is a prominent driver of amphibian declines, which is caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd). To guide conservation policy, we developed a predictive decision-analytic model that combines empirical knowledge of host-pathogen metapopulation dynamics with expert judgment regarding effects of management actions, to select from potential conservation strategies. We apply our approach to a boreal toad (Anaxyrus boreas boreas) and Bd system, identifying optimal strategies that balance tradeoffs in maximizing toad population persistence and landscape-level distribution, while considering costs. The most robust strategy is expected to reduce the decline of toad breeding sites from 53% to 21% over 50 years. Our findings are incorporated into management policy to guide conservation planning. Our online modeling application provides a template for managers of other systems challenged by EIDs.

Sinusoidal Analysis-Synthesis of Audio Using Perceptual Criteria

NASA Astrophysics Data System (ADS)

Painter, Ted; Spanias, Andreas

2003-12-01

This paper presents a new method for the selection of sinusoidal components for use in compact representations of narrowband audio. The method consists of ranking and selecting the most perceptually relevant sinusoids. The idea behind the method is to maximize the matching between the auditory excitation pattern associated with the original signal and the corresponding auditory excitation pattern associated with the modeled signal that is being represented by a small set of sinusoidal parameters. The proposed component-selection methodology is shown to outperform the maximum signal-to-mask ratio selection strategy in terms of subjective quality.

Flowering time and seed dormancy control use external coincidence to generate life history strategy.

PubMed

Springthorpe, Vicki; Penfield, Steven

2015-03-31

Climate change is accelerating plant developmental transitions coordinated with the seasons in temperate environments. To understand the importance of these timing advances for a stable life history strategy, we constructed a full life cycle model of Arabidopsis thaliana. Modelling and field data reveal that a cryptic function of flowering time control is to limit seed set of winter annuals to an ambient temperature window which coincides with a temperature-sensitive switch in seed dormancy state. This coincidence is predicted to be conserved independent of climate at the expense of flowering date, suggesting that temperature control of flowering time has evolved to constrain seed set environment and therefore frequency of dormant and non-dormant seed states. We show that late flowering can disrupt this bet-hedging germination strategy. Our analysis shows that life history modelling can reveal hidden fitness constraints and identify non-obvious selection pressures as emergent features.

A MODEL SYSTEM TO STUDY ANTIMICROBIAL STRATEGIES IN ENDODONTIC BIOFILMS

PubMed Central

Estrela, Carlos; Sydney, Gilson Blitzkow; Figueiredo, José Antonio Poli; Estrela, Cyntia Rodrigues de Araújo

2009-01-01

The purpose of this work was to develop a model system to study antimicrobial strategies in endodontic biofilms. Enterococcus faecalis suspension was colonized in 10 human root canals. Five milliliters of Brain Heart Infusion (BHI) were mixed with 5 mL of the bacterial inoculums (E. faecalis) and inoculated with sufficient volume to fill the root canal during 60 days. This procedure was repeated every 72 h, always using 24-h pure culture prepared and adjusted to No. 1 MacFarland turbidity standard. Biofilm formation was analyzed by scanning electron microscopy (SEM). E. faecalis consistently adhered to collagen structure, colonized dentin surface, progressed towards the dentinal tubules and formed a biofilm. The proposed biofilm model seems to be viable for studies on antimicrobial strategies, and allows for a satisfactory colonization time of selected bacterial species with virulence and adherence properties. PMID:19274391

Comprehensive sector-wide strategies to prevent and control obesity: what are the potential health and broader societal benefits? A case study from Australia.

PubMed

Kite, James; Hector, Debra J; St George, Alexis; Pedisic, Zeljko; Phongsavan, Philayrath; Bauman, Adrian; Mitchell, Jo; Bellew, Bill

2015-09-30

Several countries have recently established multistakeholder strategies to prevent or control overweight and obesity; however, studies have not yet been done on their effectiveness and likely impact. This study's objectives were to (i) explore sector-wide benefits and impacts likely to accrue from implementing an obesity prevention strategy in the Australian state of New South Wales; (ii) discuss the wider implications of the findings for research and practice; and (iii) strengthen the case for sustained implementation of a comprehensive, intersectoral approach. A case study approach, including evidence reviews and illustrative epidemiological models, was used to show potential benefits from meeting selected targets and objectives specified in the strategy. For adults, improved health outcomes potentially include reductions in all-cause mortality, cardiovascular disease, type 2 diabetes, various cancers, osteoarthritis, infant mortality and healthcare costs. Potential benefits beyond the health sector involve disability payments, absenteeism, worker productivity, workplace injuries and insurance claims. For children and adolescents, improved health outcomes potentially include metabolic risk factors, dental health, prehypertension/hypertension, cardiovascular disease risk factors, depression, rates of mortality in hospitalised children, bullying and otitis media. Sector-wide health, social and economic benefits from successful implementation of multisector obesity prevention strategies are likely to be substantial if specified targets are achieved. Epidemiological modelling described in this paper for selected examples provides illustrative rather than comprehensive evidence for potential benefits. Process evaluation of the extent of implementation of these multisectoral strategies, together with the accumulated data on intervention effectiveness, will determine their potential population health benefit. Quantifying the health and social benefits that are likely to accrue if comprehensive sector-wide obesity prevention and control strategies are established can strengthen advocacy for their sustained implementation.

Comparative Analysis of Vitamin A (Retinol) Regulated Genes in African-American and Caucasian Prostate Cancer Patients

DTIC Science & Technology

2007-03-01

chemoprevention strategies and to the development of novel therapies for this disease. 14. SUBJECT TERMS 15. NUMBER OF PAGES 13Retinoids, Vitamin A...the TRAMP model will ultimately lead to improved chemoprevention strategies and to the development of novel therapies for prostate cancer...Selective retinoids and rexinoids in cancer therapy and chemoprevention. Drug Discov Today, 7: 1165-1174, 2002. 5. Wei, L. N. Retinoid receptors and

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India

PubMed Central

Sarkar, Mriganka Shekhar; Johnson, Jeyaraj A.; Sen, Subharanjan

2017-01-01

Background Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals’ ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger (Panthera tigris), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. Methods We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly’s selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D2 method and the Boyce index. Results There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Discussion Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve. PMID:29114438

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India.

PubMed

Sarkar, Mriganka Shekhar; Krishnamurthy, Ramesh; Johnson, Jeyaraj A; Sen, Subharanjan; Saha, Goutam Kumar

2017-01-01

Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals' ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger ( Panthera tigris ), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly's selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D 2 method and the Boyce index. There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

Variable mechanical ventilation

PubMed Central

Fontela, Paula Caitano; Prestes, Renata Bernardy; Forgiarini Jr., Luiz Alberto; Friedman, Gilberto

2017-01-01

Objective To review the literature on the use of variable mechanical ventilation and the main outcomes of this technique. Methods Search, selection, and analysis of all original articles on variable ventilation, without restriction on the period of publication and language, available in the electronic databases LILACS, MEDLINE®, and PubMed, by searching the terms "variable ventilation" OR "noisy ventilation" OR "biologically variable ventilation". Results A total of 36 studies were selected. Of these, 24 were original studies, including 21 experimental studies and three clinical studies. Conclusion Several experimental studies reported the beneficial effects of distinct variable ventilation strategies on lung function using different models of lung injury and healthy lungs. Variable ventilation seems to be a viable strategy for improving gas exchange and respiratory mechanics and preventing lung injury associated with mechanical ventilation. However, further clinical studies are necessary to assess the potential of variable ventilation strategies for the clinical improvement of patients undergoing mechanical ventilation. PMID:28444076

The development of an adolescent smoking cessation intervention--an Intervention Mapping approach to planning.

PubMed

Dalum, Peter; Schaalma, Herman; Kok, Gerjo

2012-02-01

The objective of this project was to develop a theory- and evidence-based adolescent smoking cessation intervention using both new and existing materials. We used the Intervention Mapping framework for planning health promotion programmes. Based on a needs assessment, we identified important and changeable determinants of cessation behaviour, specified change objectives for the intervention programme, selected theoretical change methods for accomplishing intervention objectives and finally operationalized change methods into practical intervention strategies. We found that guided practice, modelling, self-monitoring, coping planning, consciousness raising, dramatic relief and decisional balance were suitable methods for adolescent smoking cessation. We selected behavioural journalism, guided practice and Motivational Interviewing as strategies in our intervention. Intervention Mapping helped us to develop as systematic adolescent smoking cessation intervention with a clear link between behavioural goals, theoretical methods, practical strategies and materials and with a strong focus on implementation and recruitment. This paper does not present evaluation data.

Software selection based on analysis and forecasting methods, practised in 1C

NASA Astrophysics Data System (ADS)

Vazhdaev, A. N.; Chernysheva, T. Y.; Lisacheva, E. I.

2015-09-01

The research focuses on the problem of a “1C: Enterprise 8” platform inboard mechanisms for data analysis and forecasting. It is important to evaluate and select proper software to develop effective strategies for customer relationship management in terms of sales, as well as implementation and further maintenance of software. Research data allows creating new forecast models to schedule further software distribution.

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

PubMed

Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrovseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert

2016-09-01

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.

Green supply chain management strategy selection using analytic network process: case study at PT XYZ

NASA Astrophysics Data System (ADS)

Adelina, W.; Kusumastuti, R. D.

2017-01-01

This study is about business strategy selection for green supply chain management (GSCM) for PT XYZ by using Analytic Network Process (ANP). GSCM is initiated as a response to reduce environmental impacts from industrial activities. The purposes of this study are identifying criteria and sub criteria in selecting GSCM Strategy, and analysing a suitable GSCM strategy for PT XYZ. This study proposes ANP network with 6 criteria and 29 sub criteria, which are obtained from the literature and experts’ judgements. One of the six criteria contains GSCM strategy options, namely risk-based strategy, efficiency-based strategy, innovation-based strategy, and closed loop strategy. ANP solves complex GSCM strategy-selection by using a more structured process and considering green perspectives from experts. The result indicates that innovation-based strategy is the most suitable green supply chain management strategy for PT XYZ.

Rare earth separations by selective borate crystallization

PubMed Central

Yin, Xuemiao; Wang, Yaxing; Bai, Xiaojing; Wang, Yumin; Chen, Lanhua; Xiao, Chengliang; Diwu, Juan; Du, Shiyu; Chai, Zhifang; Albrecht-Schmitt, Thomas E.; Wang, Shuao

2017-01-01

Lanthanides possess similar chemical properties rendering their separation from one another a challenge of fundamental chemical and global importance given their incorporation into many advanced technologies. New separation strategies combining green chemistry with low cost and high efficiency remain highly desirable. We demonstrate that the subtle bonding differences among trivalent lanthanides can be amplified during the crystallization of borates, providing chemical recognition of specific lanthanides that originates from Ln3+ coordination alterations, borate polymerization diversity and soft ligand coordination selectivity. Six distinct phases are obtained under identical reaction conditions across lanthanide series, further leading to an efficient and cost-effective separation strategy via selective crystallization. As proof of concept, Nd/Sm and Nd/Dy are used as binary models to demonstrate solid/aqueous and solid/solid separation processes. Controlling the reaction kinetics gives rise to enhanced separation efficiency of Nd/Sm system and a one-step quantitative separation of Nd/Dy with the aid of selective density-based flotation. PMID:28290448

Automatic insertion of simulated microcalcification clusters in a software breast phantom

NASA Astrophysics Data System (ADS)

Shankla, Varsha; Pokrajac, David D.; Weinstein, Susan P.; DeLeo, Michael; Tuite, Catherine; Roth, Robyn; Conant, Emily F.; Maidment, Andrew D.; Bakic, Predrag R.

2014-03-01

An automated method has been developed to insert realistic clusters of simulated microcalcifications (MCs) into computer models of breast anatomy. This algorithm has been developed as part of a virtual clinical trial (VCT) software pipeline, which includes the simulation of breast anatomy, mechanical compression, image acquisition, image processing, display and interpretation. An automated insertion method has value in VCTs involving large numbers of images. The insertion method was designed to support various insertion placement strategies, governed by probability distribution functions (pdf). The pdf can be predicated on histological or biological models of tumor growth, or estimated from the locations of actual calcification clusters. To validate the automated insertion method, a 2-AFC observer study was designed to compare two placement strategies, undirected and directed. The undirected strategy could place a MC cluster anywhere within the phantom volume. The directed strategy placed MC clusters within fibroglandular tissue on the assumption that calcifications originate from epithelial breast tissue. Three radiologists were asked to select between two simulated phantom images, one from each placement strategy. Furthermore, questions were posed to probe the rationale behind the observer's selection. The radiologists found the resulting cluster placement to be realistic in 92% of cases, validating the automated insertion method. There was a significant preference for the cluster to be positioned on a background of adipose or mixed adipose/fibroglandular tissues. Based upon these results, this automated lesion placement method will be included in our VCT simulation pipeline.

Medical school dropout--testing at admission versus selection by highest grades as predictors.

PubMed

O'Neill, Lotte; Hartvigsen, Jan; Wallstedt, Birgitta; Korsholm, Lars; Eika, Berit

2011-11-01

Very few studies have reported on the effect of admission tests on medical school dropout. The main aim of this study was to evaluate the predictive validity of non-grade-based admission testing versus grade-based admission relative to subsequent dropout. This prospective cohort study followed six cohorts of medical students admitted to the medical school at the University of Southern Denmark during 2002-2007 (n=1544). Half of the students were admitted based on their prior achievement of highest grades (Strategy 1) and the other half took a composite non-grade-based admission test (Strategy 2). Educational as well as social predictor variables (doctor-parent, origin, parenthood, parents living together, parent on benefit, university-educated parents) were also examined. The outcome of interest was students' dropout status at 2 years after admission. Multivariate logistic regression analysis was used to model dropout. Strategy 2 (admission test) students had a lower relative risk for dropping out of medical school within 2 years of admission (odds ratio 0.56, 95% confidence interval 0.39-0.80). Only the admission strategy, the type of qualifying examination and the priority given to the programme on the national application forms contributed significantly to the dropout model. Social variables did not predict dropout and neither did Strategy 2 admission test scores. Selection by admission testing appeared to have an independent, protective effect on dropout in this setting. © Blackwell Publishing Ltd 2011.

Contract Source Selection: An Analysis of Lowest Price Technically Acceptable and Tradeoff Strategies

DTIC Science & Technology

2016-06-15

selection strategy is key to minimizing risk and ensuring best value for all stakeholders. On the basis of thorough market research , acquisition...administrative lead-time, Contractor Performance Assessment Reporting System ratings, and earned value management assessments) and source selection strategy ...Postgraduate School A. PURPOSE This research analyzes LPTA and tradeoff source selection strategies and contract outcomes to determine if a relationship

Resource allocation for mitigating regional air pollution–related mortality: A summertime case study for five cities in the United States

PubMed Central

Liao, Kuo-Jen; Hou, Xiangting; Strickland, Matthew J.

2016-01-01

ABSTRACT An important issue of regional air quality management is to allocate air quality management funds to maximize environmental and human health benefits. In this study, we use an innovative approach to tackle this air quality management issue. We develop an innovative resource allocation model that allows identification of air pollutant emission control strategies that maximize mortality avoidances subject to a resource constraint. We first present the development of the resource allocation model and then a case study to show how the model can be used to identify resource allocation strategies that maximize mortality avoidances for top five Metropolitan Statistical Areas (MSAs) (i.e., New York, Los Angeles, Chicago, Dallas-Fort Worth, and Philadelphia) in the continental United States collectively. Given budget constraints in the U.S. Environmental Protection Agency’s (EPA) Clean Air Act assessment, the results of the case study suggest that controls of sulfur dioxide (SO2) and primary carbon (PC) emissions from EPA Regions 2, 3, 5, 6, and 9 would have significant health benefits for the five selected cities collectively. Around 30,800 air pollution–related mortalities could be avoided during the selected 2-week summertime episode for the five cities collectively if the budget could be allocated based on the results of the resource allocation model. Although only five U.S. cities during a 2-week episode are considered in the case study, the resource allocation model can be used by decision-makers to plan air pollution mitigation strategies to achieve the most significant health benefits for other seasons and more cities over a region or the continental U.S.Implications: Effective allocations of air quality management resources are challenging and complicated, and it is desired to have a tool that can help decision-makers better allocate the funds to maximize health benefits of air pollution mitigation. An innovative resource allocation model developed in this study can help decision-makers identify the best resource allocation strategies for multiple cities collectively. The results of a case study suggest that controls of primary carbon and sulfur dioxides emissions would achieve the most significant health benefits for five selected cities collectively. PMID:27441782

Linking Conservation Actions with Population Viability Models: Reducing Uncertainty to Better Predict Management Effects on Viability

DTIC Science & Technology

2011-05-01

selected results .......................................................................... 101  Appendix B. Scientific Publications ...159  Scientific Publications ...are being achieved. Thus, public review (and political tradeoffs) can be incorporated in choosing short-term management strategies, but ultimate

Principles and Models of Early Childhood Development in Thai Cultural Ways: Selected Research Findings Relating to Social Context and Child's Transition from Home to School.

ERIC Educational Resources Information Center

Khemmani, Tisana; And Others

To develop innovative, developmentally appropriate models of child rearing in Thailand, several studies examined Thai child-rearing practices, principles which should be used in early child rearing, and models and strategies which could be used in child rearing in this cultural setting. Six different studies were conducted, using a variety of…

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach

PubMed Central

Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

2015-01-01

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447–2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8–30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics. PMID:26452043

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach.

PubMed

Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

2015-01-01

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447-2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8-30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics.

Modeling of the competition life cycle using the software complex of cellular automata PyCAlab

NASA Astrophysics Data System (ADS)

Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.

2015-11-01

The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.

A comparative research of different ensemble surrogate models based on set pair analysis for the DNAPL-contaminated aquifer remediation strategy optimization.

PubMed

Hou, Zeyu; Lu, Wenxi; Xue, Haibo; Lin, Jin

2017-08-01

Surrogate-based simulation-optimization technique is an effective approach for optimizing the surfactant enhanced aquifer remediation (SEAR) strategy for clearing DNAPLs. The performance of the surrogate model, which is used to replace the simulation model for the aim of reducing computation burden, is the key of corresponding researches. However, previous researches are generally based on a stand-alone surrogate model, and rarely make efforts to improve the approximation accuracy of the surrogate model to the simulation model sufficiently by combining various methods. In this regard, we present set pair analysis (SPA) as a new method to build ensemble surrogate (ES) model, and conducted a comparative research to select a better ES modeling pattern for the SEAR strategy optimization problems. Surrogate models were developed using radial basis function artificial neural network (RBFANN), support vector regression (SVR), and Kriging. One ES model is assembling RBFANN model, SVR model, and Kriging model using set pair weights according their performance, and the other is assembling several Kriging (the best surrogate modeling method of three) models built with different training sample datasets. Finally, an optimization model, in which the ES model was embedded, was established to obtain the optimal remediation strategy. The results showed the residuals of the outputs between the best ES model and simulation model for 100 testing samples were lower than 1.5%. Using an ES model instead of the simulation model was critical for considerably reducing the computation time of simulation-optimization process and maintaining high computation accuracy simultaneously. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of control strategies for wave energy converters

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

Coe, Ryan G.; Bacelli, Giorgio; Wilson, David G.

In this study, we employ a numerical model to compare the performance of a number of wave energy converter control strategies. The controllers selected for evaluation span a wide range in their requirements for implementation. Each control strategy is evaluated using a single numerical model with a set of sea states to represent a deployment site off the coast of Newport, OR. A number of metrics, ranging from power absorption to kinematics, are employed to provide a comparison of each control strategy’s performance that accounts for both relative benefits and costs. The results show a wide range of performances frommore » the different controllers and highlight the need for a holistic design approach which considers control design as a parallel component within the larger process WEC design.« less

A comparison of control strategies for wave energy converters

DOE PAGES

Coe, Ryan G.; Bacelli, Giorgio; Wilson, David G.; ...

2017-11-15

In this study, we employ a numerical model to compare the performance of a number of wave energy converter control strategies. The controllers selected for evaluation span a wide range in their requirements for implementation. Each control strategy is evaluated using a single numerical model with a set of sea states to represent a deployment site off the coast of Newport, OR. A number of metrics, ranging from power absorption to kinematics, are employed to provide a comparison of each control strategy’s performance that accounts for both relative benefits and costs. The results show a wide range of performances frommore » the different controllers and highlight the need for a holistic design approach which considers control design as a parallel component within the larger process WEC design.« less

Global-local feature attention network with reranking strategy for image caption generation

NASA Astrophysics Data System (ADS)

Wu, Jie; Xie, Si-ya; Shi, Xin-bao; Chen, Yao-wen

2017-11-01

In this paper, a novel framework, named as global-local feature attention network with reranking strategy (GLAN-RS), is presented for image captioning task. Rather than only adopting unitary visual information in the classical models, GLAN-RS explores the attention mechanism to capture local convolutional salient image maps. Furthermore, we adopt reranking strategy to adjust the priority of the candidate captions and select the best one. The proposed model is verified using the Microsoft Common Objects in Context (MSCOCO) benchmark dataset across seven standard evaluation metrics. Experimental results show that GLAN-RS significantly outperforms the state-of-the-art approaches, such as multimodal recurrent neural network (MRNN) and Google NIC, which gets an improvement of 20% in terms of BLEU4 score and 13 points in terms of CIDER score.

Data article on the effect of work engagement strategies on faculty staff behavioural outcomes in private universities.

PubMed

Falola, Hezekiah Olubusayo; Olokundun, Maxwell Ayodele; Salau, Odunayo Paul; Oludayo, Olumuyiwa Akinrole; Ibidunni, Ayodotun Stephen

2018-06-01

The main objective of this study was to present a data article that investigate the effect of work engagement strategies on faculty behavioural outcomes. Few studies analyse how work engagement strategies could help in driving standard work behaviour particularly in higher institutions. In an attempt to bridge this gap, this study was carried out using descriptive research method and Structural Equation Model (AMOS 22) for the analysis of four hundred and forty one (441) valid questionnaire which were completed by the faculty members of the six selected private universities in Nigeria using stratified and simple random sampling techniques. Factor model which shows high-reliability and good fit was generated, while construct validity was provided through convergent and discriminant analyses.

Extrapolating Weak Selection in Evolutionary Games

PubMed Central

Wu, Bin; García, Julián; Hauert, Christoph; Traulsen, Arne

2013-01-01

In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By “qualitatively valid” we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies . In particular, rank changes are almost certain for , which jeopardizes the predictive power of results derived for weak selection. PMID:24339769

Optimization of European call options considering physical delivery network and reservoir operation rules

NASA Astrophysics Data System (ADS)

Cheng, Wei-Chen; Hsu, Nien-Sheng; Cheng, Wen-Ming; Yeh, William W.-G.

2011-10-01

This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.

Assessment of combating-desertification strategies using the linear assignment method

NASA Astrophysics Data System (ADS)

Hassan Sadeghravesh, Mohammad; Khosravi, Hassan; Ghasemian, Soudeh

2016-04-01

Nowadays desertification, as a global problem, affects many countries in the world, especially developing countries like Iran. With respect to increasing importance of desertification and its complexity, the necessity of attention to the optimal combating-desertification alternatives is essential. Selecting appropriate strategies according to all effective criteria to combat the desertification process can be useful in rehabilitating degraded lands and avoiding degradation in vulnerable fields. This study provides systematic and optimal strategies of combating desertification by use of a group decision-making model. To this end, the preferences of indexes were obtained through using the Delphi model, within the framework of multi-attribute decision making (MADM). Then, priorities of strategies were evaluated by using linear assignment (LA) method. According to the results, the strategies to prevent improper change of land use (A18), development and reclamation of plant cover (A23), and control overcharging of groundwater resources (A31) were identified as the most important strategies for combating desertification in this study area. Therefore, it is suggested that the aforementioned ranking results be considered in projects which control and reduce the effects of desertification and rehabilitate degraded lands.

Using "Omics" and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases.

PubMed

Rebollar, Eria A; Antwis, Rachael E; Becker, Matthew H; Belden, Lisa K; Bletz, Molly C; Brucker, Robert M; Harrison, Xavier A; Hughey, Myra C; Kueneman, Jordan G; Loudon, Andrew H; McKenzie, Valerie; Medina, Daniel; Minbiole, Kevin P C; Rollins-Smith, Louise A; Walke, Jenifer B; Weiss, Sophie; Woodhams, Douglas C; Harris, Reid N

2016-01-01

Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called "omics," are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov-Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.

The Appropriate Use of Neuroimaging in the Diagnostic Work-Up of Dementia

PubMed Central

Bermingham, SL

2014-01-01

Background Structural brain imaging is often performed to establish the underlying causes of dementia. However, recommendations differ as to who should receive neuroimaging and whether computed tomography (CT) or magnetic resonance imaging (MRI) should be used. Objectives This study aimed to determine the cost-effectiveness in Ontario of offering structural imaging to all patients with mild to moderate dementia compared with offering it selectively according to guidelines from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCC). We compared the cost-effectiveness of CT and MRI as first-line strategies. Methods We performed a systematic literature search (2000 to 2013) to identify cost-effectiveness studies of clinical prediction rules and structural imaging modalities. Studies were assessed for quality and applicability to Ontario. We also developed a model to evaluate the cost-effectiveness of clinical guidelines (image all versus according to CCC) and modalities (CT versus MRI). Transition probabilities, utilities, and costs were obtained from published literature or expert opinion. Results were expressed in terms of costs and quality adjusted life years (QALYs). Results No relevant cost-effectiveness analyses were identified in the published literature. According to the base-case results of our model, the most effective and cost-effective strategy is to image patients who meet CCC criteria with CT and to follow-up with MRI for suspected cases of space-occupying lesions (SOL). However, the results were sensitive to the specificity of MRI for detecting vascular causes of dementia. At a specificity of 64%, the most cost-effective strategy is CCC followed by MRI. Limitations Studies used to estimate diagnostic accuracy were limited by a lack of a gold standard test for establishing the cause of dementia. The model does not include costs to patients and their families, nor does it account for patient preferences about diagnostic information. Conclusions Given the relative prevalence of vascular dementia and SOLs, and the improvement in QALYs associated with treatment, the strategy with the greatest combined sensitivity (CCC with CT followed by MRI for patients with SOLs) results in the greatest number of QALYs and is the least costly. Due to limitations in the clinical data and challenges in the interpretation of this evidence, the model should be considered a framework for assessing uncertainty in the evidence base rather than providing definitive answers to the research questions. Plain Language Summary There is wide debate about whether or not brain scans should routinely be used to assess patients with mild to moderate dementia. Proponents say that imaging is important to detect or rule out possible underlying causes of dementia, such as silent strokes and tumours. Opponents call for a more selective approach, considering the need for clinical judgement and the cost of the technology. Using data from published research, a model was developed to study the cost-effectiveness of different approaches to brain imaging for a hypothetical group of patients with dementia. The model compared 2 strategies: imaging all patients and imaging selectively based on clinical practice guidelines from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCC). It also compared 2 types of technology: computed tomography (CT) and magnetic resonance imaging (MRI). The results of the model depended on the accuracy of CT and MRI in diagnosing dementia caused by vascular disease. Unfortunately, because there is no “gold standard” approach to diagnosing dementia, interpreting the published research is challenging. Based on current evidence, in which diagnostic strategies are assessed using a mix of methods, the model showed that the most effective and least costly strategy is to image selectively according to the CCC guidelines, using CT first and then MRI as a follow-up for patients suspected of having space-occupying lesions such as tumours. However, if we assumed that MRI plus clinical assessment is the gold standard, then imaging all patients with MRI is the most cost-effective strategy, despite the higher cost of this technology. The model did not take into account the value that physicians, patients, and families place on having diagnostic information, even if effective treatment does not yet exist. The model was not able to answer the specific research questions with confidence, but it provides a framework for identifying areas where more research is needed to support decision-making in the diagnosis of dementia. PMID:24592297

Social dilemma structure hidden behind traffic flow with route selection

NASA Astrophysics Data System (ADS)

Tanimoto, Jun; Nakamura, Kousuke

2016-10-01

Several traffic flows contain social dilemma structures. Herein, we explored a route-selection problem using a cellular automaton simulation dovetailed with evolutionary game theory. In our model, two classes of driver-agents coexist: D agents (defective strategy), which refer to traffic information for route selection to move fast, and C agents (cooperative strategy), which are insensitive to information and less inclined to move fast. Although no evidence suggests that the social dilemma structure in low density causes vehicles to move freely and that in high density causes traffic jams, we found a structure that corresponds to an n-person (multiplayer) Chicken (n-Chicken) game if the provided traffic information is inappropriate. If appropriate traffic information is given to the agents, the n-Chicken game can be solved. The information delivered to vehicles is crucial for easing the social dilemma due to urban traffic congestion when developing technologies to support the intelligent transportation system (ITS).

Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

NASA Astrophysics Data System (ADS)

Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

2018-01-01

Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

Fishing diseased abalone to promote yield and conservation

PubMed Central

Ben-Horin, Tal; Bidegain, Gorka; Lenihan, Hunter S.

2016-01-01

Past theoretical models suggest fishing disease-impacted stocks can reduce parasite transmission, but this is a good management strategy only when the exploitation required to reduce transmission does not overfish the stock. We applied this concept to a red abalone fishery so impacted by an infectious disease (withering syndrome) that stock densities plummeted and managers closed the fishery. In addition to the non-selective fishing strategy considered by past disease-fishing models, we modelled targeting (culling) infected individuals, which is plausible in red abalone because modern diagnostic tools can determine infection without harming landed abalone and the diagnostic cost is minor relative to the catch value. The non-selective abalone fishing required to eradicate parasites exceeded thresholds for abalone sustainability, but targeting infected abalone allowed the fishery to generate yield and reduce parasite prevalence while maintaining stock densities at or above the densities attainable if the population was closed to fishing. The effect was strong enough that stock and yield increased even when the catch was one-third uninfected abalone. These results could apply to other fisheries as the diagnostic costs decline relative to catch value. PMID:26880843

Fishing diseased abalone to promote yield and conservation.

PubMed

Ben-Horin, Tal; Lafferty, Kevin D; Bidegain, Gorka; Lenihan, Hunter S

2016-03-05

Past theoretical models suggest fishing disease-impacted stocks can reduce parasite transmission, but this is a good management strategy only when the exploitation required to reduce transmission does not overfish the stock. We applied this concept to a red abalone fishery so impacted by an infectious disease (withering syndrome) that stock densities plummeted and managers closed the fishery. In addition to the non-selective fishing strategy considered by past disease-fishing models, we modelled targeting (culling) infected individuals, which is plausible in red abalone because modern diagnostic tools can determine infection without harming landed abalone and the diagnostic cost is minor relative to the catch value. The non-selective abalone fishing required to eradicate parasites exceeded thresholds for abalone sustainability, but targeting infected abalone allowed the fishery to generate yield and reduce parasite prevalence while maintaining stock densities at or above the densities attainable if the population was closed to fishing. The effect was strong enough that stock and yield increased even when the catch was one-third uninfected abalone. These results could apply to other fisheries as the diagnostic costs decline relative to catch value. © 2016 The Author(s).

Fishing diseased abalone to promote yield and conservation

USGS Publications Warehouse

Ben-Horin, Tal; Lafferty, Kevin D.; Bidegain, Gorka; Lenihan, Hunter S.

2016-01-01

Past theoretical models suggest fishing disease-impacted stocks can reduce parasite transmission, but this is a good management strategy only when the exploitation required to reduce transmission does not overfish the stock. We applied this concept to a red abalone fishery so impacted by an infectious disease (withering syndrome) that stock densities plummeted and managers closed the fishery. In addition to the non-selective fishing strategy considered by past disease-fishing models, we modelled targeting (culling) infected individuals, which is plausible in red abalone because modern diagnostic tools can determine infection without harming landed abalone and the diagnostic cost is minor relative to the catch value. The non-selective abalone fishing required to eradicate parasites exceeded thresholds for abalone sustainability, but targeting infected abalone allowed the fishery to generate yield and reduce parasite prevalence while maintaining stock densities at or above the densities attainable if the population was closed to fishing. The effect was strong enough that stock and yield increased even when the catch was one-third uninfected abalone. These results could apply to other fisheries as the diagnostic costs decline relative to catch value.

Using Denatured Egg White as a Macroscopic Model for Teaching Protein Structure and Introducing Protein Synthesis for High School Students

NASA Astrophysics Data System (ADS)

Correia, Paulo R. M.; Torres, Bayardo B.

2007-12-01

The success of teaching molecular and atomic phenomena depends on the didactical strategy and the media selection adopted, in consideration of the level of abstraction of the subject to be taught and the students' capability to deal with abstract operations. Dale's cone of experience was employed to plan three 50-minute classes to discuss protein denaturation from a chemical point of view. Only low abstraction level activities were selected: (i) two demonstrations showing the denaturation of albumin by heating and by changing the solvent, (ii) the assembly of a macroscopic model representing the protein molecule, and (iii) a role-play for simulating glucagon synthesis. A student-centered approach and collaborative learning were used throughout the classes. The use of macroscopic models is a powerful didactical strategy to represent molecular and atomic events. They can convert microscopic entities into touchable objects, reducing the abstraction level required to discuss chemistry with high school students. Thus, interesting topics involving molecules and their behavior can take place efficiently when mediated by concrete experiences.

Skin lesion computational diagnosis of dermoscopic images: Ensemble models based on input feature manipulation.

PubMed

Oliveira, Roberta B; Pereira, Aledir S; Tavares, João Manuel R S

2017-10-01

The number of deaths worldwide due to melanoma has risen in recent times, in part because melanoma is the most aggressive type of skin cancer. Computational systems have been developed to assist dermatologists in early diagnosis of skin cancer, or even to monitor skin lesions. However, there still remains a challenge to improve classifiers for the diagnosis of such skin lesions. The main objective of this article is to evaluate different ensemble classification models based on input feature manipulation to diagnose skin lesions. Input feature manipulation processes are based on feature subset selections from shape properties, colour variation and texture analysis to generate diversity for the ensemble models. Three subset selection models are presented here: (1) a subset selection model based on specific feature groups, (2) a correlation-based subset selection model, and (3) a subset selection model based on feature selection algorithms. Each ensemble classification model is generated using an optimum-path forest classifier and integrated with a majority voting strategy. The proposed models were applied on a set of 1104 dermoscopic images using a cross-validation procedure. The best results were obtained by the first ensemble classification model that generates a feature subset ensemble based on specific feature groups. The skin lesion diagnosis computational system achieved 94.3% accuracy, 91.8% sensitivity and 96.7% specificity. The input feature manipulation process based on specific feature subsets generated the greatest diversity for the ensemble classification model with very promising results. Copyright © 2017 Elsevier B.V. All rights reserved.

[MINNI, the national integrated modelling system for assessing the impacts of atmospheric pollution and the effectiveness of the emissions abatement strategies].

PubMed

Zanini, Gabriele

2009-01-01

Selecting the best emissions abatement strategy is very difficult due to the complexity of the processes that determine the impact of atmospheric pollutants and to the connection with climate change issues. Atmospheric pollution models can provide policy makers with a tool for assessing the effectiveness of abatement measures and their associated costs. The MINNI integrated model has been developed to link policy and atmospheric science and to assess the costs of the measures. The results have been carefully verified in order to identify uncertainties and the models are continuously updated to represent the state of the art in atmospheric science. The fine spatial and temporal resolution of the simulations provide a strong basis for assessing impacts on environment and health.

[Measurement of Water COD Based on UV-Vis Spectroscopy Technology].

PubMed

Wang, Xiao-ming; Zhang, Hai-liang; Luo, Wei; Liu, Xue-mei

2016-01-01

Ultraviolet/visible (UV/Vis) spectroscopy technology was used to measure water COD. A total of 135 water samples were collected from Zhejiang province. Raw spectra with 3 different pretreatment methods (Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV) and 1st Derivatives were compared to determine the optimal pretreatment method for analysis. Spectral variable selection is an important strategy in spectrum modeling analysis, because it tends to parsimonious data representation and can lead to multivariate models with better performance. In order to simply calibration models, the preprocessed spectra were then used to select sensitive wavelengths by competitive adaptive reweighted sampling (CARS), Random frog and Successive Genetic Algorithm (GA) methods. Different numbers of sensitive wavelengths were selected by different variable selection methods with SNV preprocessing method. Partial least squares (PLS) was used to build models with the full spectra, and Extreme Learning Machine (ELM) was applied to build models with the selected wavelength variables. The overall results showed that ELM model performed better than PLS model, and the ELM model with the selected wavelengths based on CARS obtained the best results with the determination coefficient (R2), RMSEP and RPD were 0.82, 14.48 and 2.34 for prediction set. The results indicated that it was feasible to use UV/Vis with characteristic wavelengths which were obtained by CARS variable selection method, combined with ELM calibration could apply for the rapid and accurate determination of COD in aquaculture water. Moreover, this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other water quality parameters.

Anchor Selection Strategies for DIF Analysis: Review, Assessment, and New Approaches

ERIC Educational Resources Information Center

Kopf, Julia; Zeileis, Achim; Strobl, Carolin

2015-01-01

Differential item functioning (DIF) indicates the violation of the invariance assumption, for instance, in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g., for the reference and the focal group) is necessary. In the Rasch model,…

The Prediction of the Students' Academic Underachievement in Mathematics Using the DEA Model: A Developing Country Case Study

ERIC Educational Resources Information Center

Moradi, Fatemeh; Amiripour, Parvaneh

2017-01-01

In this study, an attempt was made to predict the students' mathematical academic underachievement at the Islamic Azad University-Yadegare-Imam branch and the appropriate strategies in mathematical academic achievement to be applied using the Data Envelopment Analysis (DEA) model. Survey research methods were used to select 91 students from the…

Considerations for IEL Courseware Design and the Next Generation of E-Learning

ERIC Educational Resources Information Center

Sözcü, Ömer Faruk; Ipek, Ismail

2013-01-01

The purpose of this study is to discuss strategies for developing integrated e-learning (IEL) courseware based on instructional design and technology (IDT) models and approaches as well as new discussions of e-learning. For this purpose, the study begins with the selection of one or more IDT models to conduct an e-courseware design including IEL…

The process of trying to quit smoking from the perspective of patients with chronic obstructive pulmonary disease.

PubMed

Lundh, Lena; Hylander, Ingrid; Törnkvist, Lena

2012-09-01

To investigate why some patients with chronic obstructive pulmonary disease (COPD) have difficulty quitting smoking and to develop a theoretical model that describes their perspectives on these difficulties. Grounded theory method was used from the selection of participants to the analyses of semi-structured interviews with 14 patients with COPD. Four additional interviews were conducted to ensure relevance. The analysis resulted in a theoretical model that illustrates the process of 'Patients with COPD trying to quit smoking'. The model illuminates factors related to the decision to try to quit smoking, including pressure-filled mental states and constructive or destructive pressure-relief strategies. The constructive strategies lead either to success in quitting or to continuing to try to quit. The destructive strategies can lead to losing hope and becoming resigned to continuing to smoke. The theoretical model 'Patients trying to quit smoking' contributes to a better understanding of the pressure-filled mental states and destructive strategies experienced by some patients with COPD in the process of trying to quit. This better understanding can help nurses individualise counselling. Moreover, patients' own awareness of these states and strategies may facilitate their efforts to quit. The information in the model can also be used as a supplement to methods such as motivational interviewing (MI). © 2011 The Authors. Scandinavian Journal of Caring Sciences © 2011 Nordic College of Caring Science.

Binary classification of aqueous solubility using support vector machines with reduction and recombination feature selection.

PubMed

Cheng, Tiejun; Li, Qingliang; Wang, Yanli; Bryant, Stephen H

2011-02-28

Aqueous solubility is recognized as a critical parameter in both the early- and late-stage drug discovery. Therefore, in silico modeling of solubility has attracted extensive interests in recent years. Most previous studies have been limited in using relatively small data sets with limited diversity, which in turn limits the predictability of derived models. In this work, we present a support vector machines model for the binary classification of solubility by taking advantage of the largest known public data set that contains over 46 000 compounds with experimental solubility. Our model was optimized in combination with a reduction and recombination feature selection strategy. The best model demonstrated robust performance in both cross-validation and prediction of two independent test sets, indicating it could be a practical tool to select soluble compounds for screening, purchasing, and synthesizing. Moreover, our work may be used for comparative evaluation of solubility classification studies ascribe to the use of completely public resources.

Proteolysis targeting peptide (PROTAP) strategy for protein ubiquitination and degradation.

PubMed

Zheng, Jing; Tan, Chunyan; Xue, Pengcheng; Cao, Jiakun; Liu, Feng; Tan, Ying; Jiang, Yuyang

2016-02-19

Ubiquitination proteasome pathway (UPP) is the most important and selective way to degrade proteins in vivo. Here, a novel proteolysis targeting peptide (PROTAP) strategy, composed of a target protein binding peptide, a linker and a ubiquitin E3 ligase recognition peptide, was designed to recruit both target protein and E3 ligase and then induce polyubiquitination and degradation of the target protein through UPP. In our study, the PROTAP strategy was proved to be a general method with high specificity using Bcl-xL protein as model target in vitro and in cells, which indicates that the strategy has great potential for in vivo application. Copyright © 2016 Elsevier Inc. All rights reserved.

Power Teaching

ERIC Educational Resources Information Center

Fluellen, Jerry E., Jr.

2007-01-01

Power Teaching weaves four factors into a seamless whole: standards, teaching thinking, research based strategies, and critical inquiry. As a prototype in its first year of development with an urban fifth grade class, the power teaching model connects selected district standards, thinking routines from Harvard University Project Zero Research…

Learning strategy selection in the water maze and hippocampal CREB phosphorylation differ in two inbred strains of mice.

PubMed

Sung, Jin-Young; Goo, June-Seo; Lee, Dong-Eun; Jin, Da-Qing; Bizon, Jennifer L; Gallagher, Michela; Han, Jung-Soo

2008-04-01

Learning strategy selection was assessed in two different inbred strains of mice, C57BL/6 and DBA/2, which are used for developing genetically modified mouse models. Male mice received a training protocol in a water maze using alternating blocks of visible and hidden platform trials, during which mice escaped to a single location. After training, mice were required to choose between the spatial location where the platform had been during training (a place strategy) and a visible platform presented in a new location (a cued/response strategy). Both strains of mice had similar escape performance on the visible and hidden platform trials during training. However, in the strategy preference test, C57BL/6 mice selected a place strategy significantly more often than DBA/2 mice. Because much evidence implicates the hippocampus and striatum as important neural substrates for spatial/place and cued/response learning, respectively, the engagement of the hippocampus was then assessed after either place or cue training by determining levels of cAMP response element-binding protein (CREB) and phosphorylated CREB (pCREB) in these two mouse strains. Results revealed that hippocampal CREB levels in both strains of mice were significantly increased after place in comparison to cued training. However, the relation of hippocampal pCREB levels to training was strain dependent; pCREB was significantly higher in C57BL/6 mice than in DBA/2 mice after place training, while hippocampal pCREB levels did not differ between strains after cued training. These findings indicate that pCREB, specifically associated with place/spatial training, is closely tied to differences in spatial/place strategy preference between C57BL/6 and DBA/2 mice.

Strategies for Addressing the Challenges of Patient-Centered Medical Home Implementation: Lessons from Oregon.

PubMed

Gelmon, Sherril; Bouranis, Nicole; Sandberg, Billie; Petchel, Shauna

2018-01-01

Patient-centered medical homes (PCMHs) are at the forefront of the transformation of primary care as part of health systems reform. Despite robust literature describing implementation challenges, few studies describe strategies being used to overcome these challenges. This article addresses this gap through observations of exemplary PCMHs in Oregon, where the Oregon Health Authority supports and recognizes Patient-Centered Primary Care Homes (PCPCH). Twenty exemplary PCPCHs were selected using program scores, with considerations for diversity in clinic characteristics. Between 2015 and 2016, semistructured interviews and focus groups were completed with 85 key informants. Clinics reported similar challenges implementing the PCPCH model, including shifting patterns of care use, fidelity to the PCPCH model, and refining care processes. The following ten implementation strategies emerged: expanding access through care teams, preventing unnecessary emergency department visits through patient outreach, improved communication and referral tracking with outside providers, prioritization of selected program metrics, implementing patient-centered practices, developing continuous improvement capacity through committees and "champions," incorporating preventive services and chronic disease management, standardization of workflows, customizing electronic health records, and integration of mental health. Clinic leaders benefited from understanding the local context in which they were operating. Despite differences in size, ownership, geography, and population, all clinic leaders were observed to be proponents of strategies commonly associated with a "learning organization": systems thinking, personal mastery, mental models, shared vision, and team. Clinics can draw on their own characteristics, use state resources, and look to established PCMHs to build the evidence base for implementation in primary care. © Copyright 2018 by the American Board of Family Medicine.

A new O6-alkylguanine-DNA alkyltransferase inhibitor associated with a nitrosourea (cystemustine) validates a strategy of melanoma-targeted therapy in murine B16 and human-resistant M4Beu melanoma xenograft models.

PubMed

Rapp, Maryse; Maurizis, Jean C; Papon, Janine; Labarre, Pierre; Wu, Ting-Di; Croisy, Alain; Guerquin-Kern, Jean L; Madelmont, Jean C; Mounetou, Emmanuelle

2008-07-01

Chemoresistance to O(6)-alkylating agents is a major barrier to successful treatment of melanoma. It is mainly due to a DNA repair suicide protein, O(6)-alkylguanine-DNA alkyltransferase (AGT). Although AGT inactivation is a powerful clinical strategy for restoring tumor chemosensitivity, it was limited by increased toxicity to nontumoral cells resulting from a lack of tumor selectivity. Achieving enhanced chemosensitization via AGT inhibition preferably in the tumor should protect normal tissue. To this end, we have developed a strategy to target AGT inhibitors. In this study, we tested a new potential melanoma-directed AGT inhibitor [2-amino-6-(4-iodobenzyloxy)-9-[4-(diethylamino) ethylcarbamoylbenzyl] purine; IBgBZ] designed as a conjugate of O(6)-(4-iododbenzyl)guanine (IBg) as the AGT inactivator and a N,N-diethylaminoethylenebenzamido (BZ) moiety as the carrier to the malignant melanocytes. IBgBZ demonstrated AGT inactivation ability and potentiation of O(6)-alkylating agents (cystemustine, a chloroethylnitrosourea) in M4Beu highly chemoresistant human melanoma cells both in vitro and in tumor models. The biodisposition study on mice bearing B16 melanoma, the standard model for the evaluation of melanoma-directed agents, and the secondary ion mass spectrometry imaging confirmed the concentration of IBgBZ in the tumor and in particular in the intracytoplasmic melanosomes. These results validate the potential of IBgBZ as a new, more tumor-selective, AGT inhibitor in a strategy of melanoma-targeted therapy.

Arms races and the evolution of big fierce societies.

PubMed

Boswell, G P; Franks, N R; Britton, N F

2001-08-22

The causes of biological gigantism have received much attention, but only for individual organisms. What selection pressures might favour the evolution of gigantic societies? Here we consider the largest single-queen insect societies, those of the Old World army ant Dorylus, single colonies of which can have 20 million workers. We propose that colony gigantism in Dorylus arises as a result of an arms race and test this prediction by developing a size-structured mathematical model. We use this model for exploring and potentially explaining differences in colony size, colony aggression and colony propagation strategies in populations of New World army ants Eciton and Old World army ants Dorylus. The model shows that, by determining evolutionarily stable strategies (ESSs), differences in the trophic levels at which these army ants live feed forwards into differences in their densities and collision rates and, hence, into different strategies of growth, aggression and propagation. The model predicts large colony size and the occurrence of battles and a colony-propagation strategy involving highly asymmetrical divisions in Dorylus and that Eciton colonies should be smaller, non-combative and exhibit equitable binary fission. These ESSs are in excellent agreement with field observations and demonstrate that gargantuan societies can arise through arms races.

Is there a role for amplifiers in sexual selection?

PubMed

Gualla, Filippo; Cermelli, Paolo; Castellano, Sergio

2008-05-21

The amplifier hypothesis states that selection could favour the evolution of traits in signallers that improve the ability of receivers to extract honest information from other signals or cues. We provide a formal definition of amplifiers based on the receiver's mechanisms of signal perception and we present a game-theoretical model in which males advertise their quality and females use sequential-sampling tactics to choose among prospective mates. The main effect of an amplifier on the female mating strategy is to increase her mating threshold, making the female more selective as the effectiveness of the amplifier increases. The effects of the amplifier on male advertising strategy depends both on the context and on the types of the amplifier involved. We consider two different contexts for the evolution of amplifiers (when the effect of amplifiers is on signals and when it is on cues) and two types of amplifiers (the 'neutral amplifier', when it improves quality assessment without altering male attractiveness, and the 'attractive amplifier', when it improves both quality assessment and male attractiveness). The game-theoretical model provides two main results. First, neutral and attractive amplifiers represent, respectively, a conditional and an unconditional signalling strategy. In fact, at the equilibrium, neutral amplifiers are displayed only by males whose advertising level lays above the female acceptance threshold, whereas attractive amplifiers are displayed by all signalling males, independent of their quality. Second, amplifiers of signals increase the differences in advertising levels between amplifying and not-amplifying males, but they decrease the differences within each group, so that the system converges towards an 'all-or-nothing' signalling strategy. By applying concepts from information theory, we show that the increase in information transfer at the perception level due to the amplifier of signals is contrasted by a decrease in information transfer at the emitter level due to the increased stereotypy of male advertising strategy.

Improve SSME power balance model

NASA Technical Reports Server (NTRS)

Karr, Gerald R.

1992-01-01

Effort was dedicated to development and testing of a formal strategy for reconciling uncertain test data with physically limited computational prediction. Specific weaknesses in the logical structure of the current Power Balance Model (PBM) version are described with emphasis given to the main routing subroutines BAL and DATRED. Selected results from a variational analysis of PBM predictions are compared to Technology Test Bed (TTB) variational study results to assess PBM predictive capability. The motivation for systematic integration of uncertain test data with computational predictions based on limited physical models is provided. The theoretical foundation for the reconciliation strategy developed in this effort is presented, and results of a reconciliation analysis of the Space Shuttle Main Engine (SSME) high pressure fuel side turbopump subsystem are examined.

Using Computational Cognitive Modeling to Diagnose Possible Sources of Aviation Error

NASA Technical Reports Server (NTRS)

Byrne, M. D.; Kirlik, Alex

2003-01-01

We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

DOE PAGES

Christensen, A. J.; Srinivasan, V.; Hart, J. C.; ...

2018-03-17

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

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

Christensen, A. J.; Srinivasan, V.; Hart, J. C.

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security.

PubMed

Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy

2018-05-01

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in "big data" analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

PubMed Central

Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy

2018-01-01

Abstract Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields. PMID:29562368

Evolution with Stochastic Fitness and Stochastic Migration

PubMed Central

Rice, Sean H.; Papadopoulos, Anthony

2009-01-01

Background Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration. Methodology/Principal Findings We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter. Conclusions/Significance As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory. PMID:19816580

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

An Entangled Model for Sustainability Indicators

PubMed Central

Cedano, Karla G.; Martínez, Manuel; Jensen, Henrik J.

2015-01-01

Nowadays the challenge for humanity is to find pathways towards sustainable development. Decision makers require a set of sustainability indicators to know if the sustainability strategies are following those pathways. There are more than one hundred sustainability indicators but they differ on their relative importance according to the size of the locality and change on time. The resources needed to follow these sustainability indicators are scarce and in some instances finite, especially in smaller regions. Therefore strategies to select set of these indicators are useful for decision makers responsible for monitoring sustainability. In this paper we propose a model for the identification and selection of a set of sustainability indicators that adequately represents human systems. In developing this model, we applied evolutionary dynamics in a space where sustainability indicators are fundamental entities interconnected by an interaction matrix. we used a fixed interaction that simulates the current context for the city of Cuernavaca, México as an example. We were able to identify and define relevant sets indicators for the system by using the Pareto principle. In this case we identified a set of sixteen sustainability indicators with more than 80% of the total strength. This set presents resilience to perturbations. For the Tangled Nature framework we provided a manner of treating different contexts (i.e., cities, counties, states, regions, countries, continents or the whole planet), dealing with small dimensions. This model provides decision makers with a valuable tool to select sustainability indicators set for towns, cities, regions, countries, continents or the entire planet according to a coevolutionary framework. The social legitimacy can arise from the fact that each individual indicator must be selected from those that are most important for the subject community. PMID:26295948

An Entangled Model for Sustainability Indicators.

PubMed

Vázquez, Pável; Del Río, Jesús A; Cedano, Karla G; Martínez, Manuel; Jensen, Henrik J

2015-01-01

Nowadays the challenge for humanity is to find pathways towards sustainable development. Decision makers require a set of sustainability indicators to know if the sustainability strategies are following those pathways. There are more than one hundred sustainability indicators but they differ on their relative importance according to the size of the locality and change on time. The resources needed to follow these sustainability indicators are scarce and in some instances finite, especially in smaller regions. Therefore strategies to select set of these indicators are useful for decision makers responsible for monitoring sustainability. In this paper we propose a model for the identification and selection of a set of sustainability indicators that adequately represents human systems. In developing this model, we applied evolutionary dynamics in a space where sustainability indicators are fundamental entities interconnected by an interaction matrix. we used a fixed interaction that simulates the current context for the city of Cuernavaca, México as an example. We were able to identify and define relevant sets indicators for the system by using the Pareto principle. In this case we identified a set of sixteen sustainability indicators with more than 80% of the total strength. This set presents resilience to perturbations. For the Tangled Nature framework we provided a manner of treating different contexts (i.e., cities, counties, states, regions, countries, continents or the whole planet), dealing with small dimensions. This model provides decision makers with a valuable tool to select sustainability indicators set for towns, cities, regions, countries, continents or the entire planet according to a coevolutionary framework. The social legitimacy can arise from the fact that each individual indicator must be selected from those that are most important for the subject community.

Vector control of wind turbine on the basis of the fuzzy selective neural net*

NASA Astrophysics Data System (ADS)

Engel, E. A.; Kovalev, I. V.; Engel, N. E.

2016-04-01

An article describes vector control of wind turbine based on fuzzy selective neural net. Based on the wind turbine system’s state, the fuzzy selective neural net tracks an maximum power point under random perturbations. Numerical simulations are accomplished to clarify the applicability and advantages of the proposed vector wind turbine’s control on the basis of the fuzzy selective neuronet. The simulation results show that the proposed intelligent control of wind turbine achieves real-time control speed and competitive performance, as compared to a classical control model with PID controllers based on traditional maximum torque control strategy.

The Effects of Relationship Type, Partner Intent, and Gender on the Selection of Relationship Maintenance Strategies.

ERIC Educational Resources Information Center

Shea, B. Christine; Pearson, Judy C.

1986-01-01

Indicates that relationship type did not affect the maintenance strategies that partners chose; however, the partners' relationship intent and the sex-composition of the dyad had a significant impact on the selection of directness strategies. Suggests that individuals are not necessarily more likely to select directness strategies than balance or…

The Effect of Vocabulary Self-Selection Strategy and Input Enhancement Strategy on the Vocabulary Knowledge of Iranian EFL Learners

ERIC Educational Resources Information Center

Masoudi, Golfam

2017-01-01

The present study was designed to investigate empirically the effect of Vocabulary Self-Selection strategy and Input Enhancement strategy on the vocabulary knowledge of Iranian EFL Learners. After taking a diagnostic pretest, both experimental groups enrolled in two classes. Learners who practiced Vocabulary Self-Selection were allowed to…

An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data. PMID:23593445

Consumer-oriented health care reform strategies: a review of the evidence on managed competition and consumer-directed health insurance.

PubMed

Buchmueller, Thomas C

2009-12-01

For many years, leading health care reform proposals have been based on market-oriented strategies. In the 1990s, a number of reform proposals were built around the concept of "managed competition," but more recently, "consumer-directed health care" models have received attention. Although price-conscious consumer demand plays a critical role in both the managed competition and consumer-directed health care models, the two strategies are based on different visions of the health care marketplace and the best way to use market forces to achieve greater systemwide efficiencies. This article reviews the research literature that tests the main hypotheses concerning the two policy strategies. Numerous studies provide consistent evidence that consumers' health plan choices are sensitive to out-of-pocket premiums. The elasticity of demand appears to vary with consumers' health risk, with younger, healthier individuals being more price sensitive. This heterogeneity increases the potential for adverse selection. Biased risk selection also is a concern when the menu of health plan options includes consumer-directed health plans. Several studies confirm that such plans tend to attract healthier enrollees. A smaller number of studies test the main hypothesis regarding consumer-directed health plans, which is that they result in lower medical spending than do more generous plans. These studies find little support for this claim. The experiences of employers that have adopted key elements of managed competition are generally consistent with the key hypotheses underlying that strategy. Research in this area, however, has focused on only a narrow range of questions. Because consumer-directed health care is such a recent phenomenon, research on this strategy is even more limited. Additional studies on both topics would be valuable.

Consumer-Oriented Health Care Reform Strategies: A Review of the Evidence on Managed Competition and Consumer-Directed Health Insurance

PubMed Central

Buchmueller, Thomas C

2009-01-01

Context: For many years, leading health care reform proposals have been based on market-oriented strategies. In the 1990s, a number of reform proposals were built around the concept of “managed competition,” but more recently, “consumer-directed health care” models have received attention. Although price-conscious consumer demand plays a critical role in both the managed competition and consumer-directed health care models, the two strategies are based on different visions of the health care marketplace and the best way to use market forces to achieve greater systemwide efficiencies. Methods: This article reviews the research literature that tests the main hypotheses concerning the two policy strategies. Findings: Numerous studies provide consistent evidence that consumers’ health plan choices are sensitive to out-of-pocket premiums. The elasticity of demand appears to vary with consumers’ health risk, with younger, healthier individuals being more price sensitive. This heterogeneity increases the potential for adverse selection. Biased risk selection also is a concern when the menu of health plan options includes consumer-directed health plans. Several studies confirm that such plans tend to attract healthier enrollees. A smaller number of studies test the main hypothesis regarding consumer-directed health plans, which is that they result in lower medical spending than do more generous plans. These studies find little support for this claim. Conclusions: The experiences of employers that have adopted key elements of managed competition are generally consistent with the key hypotheses underlying that strategy. Research in this area, however, has focused on only a narrow range of questions. Because consumer-directed health care is such a recent phenomenon, research on this strategy is even more limited. Additional studies on both topics would be valuable. PMID:20021587

Habitat selection by a focal predator (Canis lupus) in a multiprey ecosystem of the northern Rockies

USGS Publications Warehouse

Milakovic, B.; Parker, K.L.; Gustine, D.D.; Lay, R.J.; Walker, A.B.D.; Gillingham, M.P.

2011-01-01

Large predators respond to land cover and physiography that maximize the likelihood of encountering prey. Using locations from global positioning system-collared wolves (Canis lupus), we examined whether land cover, vegetation productivity or change, or habitat-selection value for ungulate prey species themselves most influenced patterns of selection by wolves in a large, intact multiprey system of northern British Columbia. Selection models based on land cover, in combination with topographical features, consistently outperformed models based on indexes of vegetation quantity and quality (using normalized difference vegetation index) or on selection value to prey species (moose [Alces americanus], elk [Cervus elaphus], woodland caribou [Rangifer tarandus], and Stone's sheep [Ovis dalli stonei]). Wolves generally selected for shrub communities and high diversity of cover across seasons and avoided conifer stands and non-vegetated areas and west aspects year-round. Seasonal selection strategies were not always reflected in use patterns, which showed highest frequency of use in riparian, shrub, and conifer classes. Patterns of use and selection for individual wolf packs did not always conform to global models, and appeared related to the distribution of land cover and terrain within respective home ranges. Our findings corroborate the biological linkages between wolves and their habitat related to ease of movement and potential prey associations. ?? American 2011 Society of Mammalogists.

Preoperative localization strategies for primary hyperparathyroidism: an economic analysis.

PubMed

Lubitz, Carrie C; Stephen, Antonia E; Hodin, Richard A; Pandharipande, Pari

2012-12-01

Strategies for localizing parathyroid pathology preoperatively vary in cost and accuracy. Our purpose was to compute and compare comprehensive costs associated with common localization strategies. A decision-analytic model was developed to evaluate comprehensive, short-term costs of parathyroid localization strategies for patients with primary hyperparathyroidism. Eight strategies were compared. Probabilities of accurate localization were extracted from the literature, and costs associated with each strategy were based on 2011 Medicare reimbursement schedules. Differential cost considerations included outpatient versus inpatient surgeries, operative time, and costs of imaging. Sensitivity analyses were performed to determine effects of variability in key model parameters upon model results. Ultrasound (US) followed by 4D-CT was the least expensive strategy ($5,901), followed by US alone ($6,028), and 4D-CT alone ($6,110). Strategies including sestamibi (SM) were more expensive, with associated expenditures of up to $6,329 for contemporaneous US and SM. Four-gland, bilateral neck exploration (BNE) was the most expensive strategy ($6,824). Differences in cost were dependent upon differences in the sensitivity of each strategy for detecting single-gland disease, which determined the proportion of patients able to undergo outpatient minimally invasive parathyroidectomy. In sensitivity analysis, US alone was preferred over US followed by 4D-CT only when both the sensitivity of US alone for detecting an adenoma was ≥ 94 %, and the sensitivity of 4D-CT following negative US was ≤ 39 %. 4D-CT alone was the least costly strategy when US sensitivity was ≤ 31 %. Among commonly used strategies for preoperative localization of parathyroid pathology, US followed by selective 4D-CT is the least expensive.

Industrial waste recycling strategies optimization problem: mixed integer programming model and heuristics

NASA Astrophysics Data System (ADS)

Tang, Jiafu; Liu, Yang; Fung, Richard; Luo, Xinggang

2008-12-01

Manufacturers have a legal accountability to deal with industrial waste generated from their production processes in order to avoid pollution. Along with advances in waste recovery techniques, manufacturers may adopt various recycling strategies in dealing with industrial waste. With reuse strategies and technologies, byproducts or wastes will be returned to production processes in the iron and steel industry, and some waste can be recycled back to base material for reuse in other industries. This article focuses on a recovery strategies optimization problem for a typical class of industrial waste recycling process in order to maximize profit. There are multiple strategies for waste recycling available to generate multiple byproducts; these byproducts are then further transformed into several types of chemical products via different production patterns. A mixed integer programming model is developed to determine which recycling strategy and which production pattern should be selected with what quantity of chemical products corresponding to this strategy and pattern in order to yield maximum marginal profits. The sales profits of chemical products and the set-up costs of these strategies, patterns and operation costs of production are considered. A simulated annealing (SA) based heuristic algorithm is developed to solve the problem. Finally, an experiment is designed to verify the effectiveness and feasibility of the proposed method. By comparing a single strategy to multiple strategies in an example, it is shown that the total sales profit of chemical products can be increased by around 25% through the simultaneous use of multiple strategies. This illustrates the superiority of combinatorial multiple strategies. Furthermore, the effects of the model parameters on profit are discussed to help manufacturers organize their waste recycling network.

Experiential Education for Urban African Americans.

ERIC Educational Resources Information Center

Smith, Jennifer G.; McGinnis, J. Randy

1995-01-01

Stresses the importance of experiential educators being prepared to teach environmental education to students in specific contexts. A model for urban African American students includes the introduction and selection of a relevant local environmental issue; teaching strategies to investigate the issue; and techniques for initiating environmental…

Exploring Instructional Strategies and Learning Theoretical Foundations of eHealth and mHealth Education Interventions.

PubMed

Tamim, Suha R; Grant, Michael M

2016-05-19

This qualitative study aimed at exploring how health professionals use theories and models from the field of education to create ehealth and mhealth education interventions in an effort to provide insights for future research and practice on the development and implementation of health promotion initiatives. A purposeful sample of 12 participants was selected, using criterion and snowballing sampling strategies. Data were collected and analyzed from semistructured interviews, planning materials, and artifacts. The findings revealed that none of the participants used a specific learning theory or an instructional model in their interventions. However, based on participants' description, three themes emerged: (1) connections to behaviorist approaches to learning, (2) connections to cognitivist approaches to learning, and (3) connections to constructivist approaches to learning. Suggested implications for practice are (1) the design of a guidebook on the interplay of learning theories, instructional models, and health education and (2) the establishment of communities of practice. Further research can (1) investigate how learning theories and models intertwine with health behavior theories and models, (2) evaluate how the different instructional strategies presented in this study affect learning outcomes and health behavior change processes, and (3) investigate factors behind the instructional strategies choices made by health professionals. © 2016 Society for Public Health Education.

Tenacious self-reliance in health maintenance may jeopardize late life survival.

PubMed

Hamm, Jeremy M; Chipperfield, Judith G; Perry, Raymond P; Parker, Patti C; Heckhausen, Jutta

2017-11-01

Although an active pursuit of health goals is typically adaptive, there may be circumstances in very late life when it is not. Our 10-year study of community-dwelling individuals (n = 220, 79-98 years-old) examined whether investing substantial effort into personal health (high selective primary control) in the absence of help-seeking strategies (low compensatory primary control) jeopardized survival for very old adults who varied in functional independence (low, high). Cox proportional hazard models showed selective primary control (SPC) predicted 10-year mortality risk for only those with low compensatory primary control (CPC) and high initial functional independence. For these individuals, each standard deviation increase in SPC predicted a 101% higher risk of death. Results are consistent with the lines-of-defense model (Heckhausen et al., 2013) and suggest that, for very old adults with little previous need for help-seeking strategies, tenacious self-reliance (high SPC, low CPC) may have life-shortening consequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Burstiness and tie activation strategies in time-varying social networks.

PubMed

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-13

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks' evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Responding to home maintenance challenge scenarios: the role of selection, optimization, and compensation in aging-in-place.

PubMed

Kelly, Andrew John; Fausset, Cara Bailey; Rogers, Wendy; Fisk, Arthur D

2014-12-01

This study examined potential issues faced by older adults in managing their homes and their proposed solutions for overcoming hypothetical difficulties. Forty-four diverse, independently living older adults (66-85) participated in structured group interviews in which they discussed potential solutions to manage difficulties presented in four scenarios: perceptual, mobility, physical, and cognitive difficulties. The proposed solutions were classified using the Selection, Optimization, and Compensation (SOC) model. Participants indicated they would continue performing most tasks and reported a range of strategies to manage home maintenance challenges. Most participants reported that they would manage home maintenance challenges using compensation; the most frequently mentioned compensation strategy was using tools and technologies. There were also differences across the scenarios: Optimization was discussed most frequently with perceptual and cognitive difficulty scenarios. These results provide insights into supporting older adults' potential needs for aging-in-place and provide evidence of the value of the SOC model in applied research. © The Author(s) 2012.

Evidentiary Pluralism as a Strategy for Research and Evidence-Based Practice in Rehabilitation Psychology

PubMed Central

Tucker, Jalie A.; Reed, Geoffrey M.

2008-01-01

This paper examines the utility of evidentiary pluralism, a research strategy that selects methods in service of content questions, in the context of rehabilitation psychology. Hierarchical views that favor randomized controlled clinical trials (RCTs) over other evidence are discussed, and RCTs are considered as they intersect with issues in the field. RCTs are vital for establishing treatment efficacy, but whether they are uniformly the best evidence to inform practice is critically evaluated. We argue that because treatment is only one of several variables that influence functioning, disability, and participation over time, an expanded set of conceptual and data analytic approaches should be selected in an informed way to support an expanded research agenda that investigates therapeutic and extra-therapeutic influences on rehabilitation processes and outcomes. The benefits of evidentiary pluralism are considered, including helping close the gap between the narrower clinical rehabilitation model and a public health disability model. KEY WORDS: evidence-based practice, evidentiary pluralism, rehabilitation psychology, randomized controlled trials PMID:19649150

Burstiness and tie activation strategies in time-varying social networks

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-01

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Siderophore production and the evolution of investment in a public good: An adaptive dynamics approach to kin selection.

PubMed

Lee, William; van Baalen, Minus; Jansen, Vincent A A

2016-01-07

Like many other bacteria, Pseudomonas aeruginosa sequesters iron from the environment through the secretion, and subsequent uptake, of iron-binding molecules. As these molecules can be taken up by other bacteria in the population than those who secreted them, this is a form of cooperation through a public good. Traditionally, this problem has been studied by comparing the relative fitnesses of siderophore-producing and non-producing strains, but this gives no information about the fate of strains that do produce intermediate amounts of siderophores. Here, we investigate theoretically how the amount invested in this form of cooperation evolves. We use a mechanistic description of the laboratory protocols used in experimental evolution studies to describe the competition and cooperation of the bacteria. From this dynamical model we derive the fitness following the adaptive dynamics method. The results show how selection is driven by local siderophore production and local competition. Because siderophore production reduces the growth rate, local competition decreases with the degree of relatedness (which is a dynamical variable in our model). Our model is not restricted to the analysis of small phenotypic differences and allows for theoretical exploration of the effects of large phenotypic differences between cooperators and cheats. We predict that an intermediate ESS level of cooperation (molecule production) should exist. The adaptive dynamics approach allows us to assess evolutionary stability, which is often not possible in other kin-selection models. We found that selection can lead to an intermediate strategy which in our model is always evolutionarily stable, yet can allow invasion of strategies that are much more cooperative. Our model describes the evolution of a public good in the context of the ecology of the microorganism, which allows us to relate the extent of production of the public good to the details of the interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Building and testing models with extended Higgs sectors

NASA Astrophysics Data System (ADS)

Ivanov, Igor P.

2017-07-01

Models with non-minimal Higgs sectors represent a mainstream direction in theoretical exploration of physics opportunities beyond the Standard Model. Extended scalar sectors help alleviate difficulties of the Standard Model and lead to a rich spectrum of characteristic collider signatures and astroparticle consequences. In this review, we introduce the reader to the world of extended Higgs sectors. Not pretending to exhaustively cover the entire body of literature, we walk through a selection of the most popular examples: the two- and multi-Higgs-doublet models, as well as singlet and triplet extensions. We will show how one typically builds models with extended Higgs sectors, describe the main goals and the challenges which arise on the way, and mention some methods to overcome them. We will also describe how such models can be tested, what are the key observables one focuses on, and illustrate the general strategy with a subjective selection of results.

Alzheimer's disease: the amyloid hypothesis and the Inverse Warburg effect

PubMed Central

Demetrius, Lloyd A.; Magistretti, Pierre J.; Pellerin, Luc

2014-01-01

Epidemiological and biochemical studies show that the sporadic forms of Alzheimer's disease (AD) are characterized by the following hallmarks: (a) An exponential increase with age; (b) Selective neuronal vulnerability; (c) Inverse cancer comorbidity. The present article appeals to these hallmarks to evaluate and contrast two competing models of AD: the amyloid hypothesis (a neuron-centric mechanism) and the Inverse Warburg hypothesis (a neuron-astrocytic mechanism). We show that these three hallmarks of AD conflict with the amyloid hypothesis, but are consistent with the Inverse Warburg hypothesis, a bioenergetic model which postulates that AD is the result of a cascade of three events—mitochondrial dysregulation, metabolic reprogramming (the Inverse Warburg effect), and natural selection. We also provide an explanation for the failures of the clinical trials based on amyloid immunization, and we propose a new class of therapeutic strategies consistent with the neuroenergetic selection model. PMID:25642192

A Behavioral Theory of the Merger: Dynamics of the Post-Merger Integration Process

DTIC Science & Technology

2014-05-01

management’s integration strategy that often accompanies a merger. Although, some real-world managers do indeed take a laissez faire approach to...1971). Future models might instead utilize other theoretical characteristics to select exchange partners, such as relative expertise, leadership ...Byrne, 1971). Future modelers could also consider other characteristics such as relative expertise, leadership style, and resource availability in this

Cost-effectiveness of early detection of breast cancer in Catalonia (Spain)

PubMed Central

2011-01-01

Background Breast cancer (BC) causes more deaths than any other cancer among women in Catalonia. Early detection has contributed to the observed decline in BC mortality. However, there is debate on the optimal screening strategy. We performed an economic evaluation of 20 screening strategies taking into account the cost over time of screening and subsequent medical costs, including diagnostic confirmation, initial treatment, follow-up and advanced care. Methods We used a probabilistic model to estimate the effect and costs over time of each scenario. The effect was measured as years of life (YL), quality-adjusted life years (QALY), and lives extended (LE). Costs of screening and treatment were obtained from the Early Detection Program and hospital databases of the IMAS-Hospital del Mar in Barcelona. The incremental cost-effectiveness ratio (ICER) was used to compare the relative costs and outcomes of different scenarios. Results Strategies that start at ages 40 or 45 and end at 69 predominate when the effect is measured as YL or QALYs. Biennial strategies 50-69, 45-69 or annual 45-69, 40-69 and 40-74 were selected as cost-effective for both effect measures (YL or QALYs). The ICER increases considerably when moving from biennial to annual scenarios. Moving from no screening to biennial 50-69 years represented an ICER of 4,469€ per QALY. Conclusions A reduced number of screening strategies have been selected for consideration by researchers, decision makers and policy planners. Mathematical models are useful to assess the impact and costs of BC screening in a specific geographical area. PMID:21605383

The role of selective attention and action selection in the development of multiple action capabilities

NASA Astrophysics Data System (ADS)

Simione, Luca; Nolfi, Stefano

2014-10-01

In this paper we illustrate how the capacity to select the most appropriate actions when handling contexts affording multiple conflicting actions can be solved either through a selective attention strategy (in which the stimuli affording alternative actions are filtered out at the perceptual level through top-down regulation) or at later processing stages through an action selection strategy (through the suppression of the premotor information eliciting alternative actions). By carrying out a series of experiments in which a neuro-robot develops an ability to choose between conflicting actions, we were able to identify the conditions that lead to the development of solutions based on one strategy or another. Overall, the results indicate that the selective attention strategy constitutes the most simple and straightforward mechanism enabling the acquisition of such capacities. Moreover, the characteristics of the adaptive/learning process influence whether the adaptive robot converges towards a selective attention and/or action selection strategy.

Evaluative methodology for prioritizing transportation energy conservation strategies

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

Pang, L.M.G.

An analytical methodology was developed for the purpose of prioritizing a set of transportation energy conservation (TEC) strategies within an urban environment. Steps involved in applying the methodology consist of 1) defining the goals, objectives and constraints of the given urban community, 2) identifying potential TEC strategies, 3) assessing the impact of the strategies, 4) applying the TEC evaluation model, and 5) utilizing a selection process to determine the optimal set of strategies for implementation. This research provides an overview of 21 TEC strategies, a quick-response technique for estimating energy savings, a multiattribute utility theory approach for assessing subjective impacts,more » and a computer program for making the strategy evaluations, all of which assist in expediting the execution of the entire methodology procedure. The critical element of the methodology is the strategy evaluation model which incorporates a number of desirable concepts including 1) a comprehensive accounting of all relevant impacts, 2) the application of multiobjective decision-making techniques, 3) an approach to assure compatibilty among quantitative and qualitative impact measures, 4) the inclusion of the decision maker's preferences in the evaluation procedure, and 5) the cost-effectiveness concept. Application of the methodolgy to Salt Lake City, Utah demonstrated its utility, ease of use and favorability by decision makers.« less

In vitro Development of Chemotherapy and Targeted Therapy Drug-Resistant Cancer Cell Lines: A Practical Guide with Case Studies

PubMed Central

McDermott, Martina; Eustace, Alex J.; Busschots, Steven; Breen, Laura; Crown, John; Clynes, Martin; O’Donovan, Norma; Stordal, Britta

2014-01-01

The development of a drug-resistant cell line can take from 3 to 18 months. However, little is published on the methodology of this development process. This article will discuss key decisions to be made prior to starting resistant cell line development; the choice of parent cell line, dose of selecting agent, treatment interval, and optimizing the dose of drug for the parent cell line. Clinically relevant drug-resistant cell lines are developed by mimicking the conditions cancer patients experience during chemotherapy and cell lines display between two- and eight-fold resistance compared to their parental cell line. Doses of drug administered are low, and a pulsed treatment strategy is often used where the cells recover in drug-free media. High-level laboratory models are developed with the aim of understanding potential mechanisms of resistance to chemotherapy agents. Doses of drug are higher and escalated over time. It is common to have difficulty developing stable clinically relevant drug-resistant cell lines. A comparative selection strategy of multiple cell lines or multiple chemotherapeutic agents mitigates this risk and gives insight into which agents or type of cell line develops resistance easily. Successful selection strategies from our research are presented. Pulsed-selection produced platinum or taxane-resistant large cell lung cancer (H1299 and H460) and temozolomide-resistant melanoma (Malme-3M and HT144) cell lines. Continuous selection produced a lapatinib-resistant breast cancer cell line (HCC1954). Techniques for maintaining drug-resistant cell lines are outlined including; maintaining cells with chemotherapy, pulse treating with chemotherapy, or returning to master drug-resistant stocks. The heterogeneity of drug-resistant models produced from the same parent cell line with the same chemotherapy agent is explored with reference to P-glycoprotein. Heterogeneity in drug-resistant cell lines reflects the heterogeneity that can occur in clinical drug resistance. PMID:24639951

Evolution of conditional cooperation under multilevel selection.

PubMed

Zhang, Huanren; Perc, Matjaž

2016-03-11

We study the emergence of conditional cooperation in the presence of both intra-group and inter-group selection. Individuals play public goods games within their groups using conditional strategies, which are represented as piecewise linear response functions. Accordingly, groups engage in conflicts with a certain probability. In contrast to previous studies, we consider continuous contribution levels and a rich set of conditional strategies, allowing for a wide range of possible interactions between strategies. We find that the existence of conditional strategies enables the stabilization of cooperation even under strong intra-group selection. The strategy that eventually dominates in the population has two key properties: (i) It is unexploitable with strong intra-group selection; (ii) It can achieve full contribution to outperform other strategies in the inter-group selection. The success of this strategy is robust to initial conditions as well as changes to important parameters. We also investigate the influence of different factors on cooperation levels, including group conflicts, group size, and migration rate. Their effect on cooperation can be attributed to and explained by their influence on the relative strength of intra-group and inter-group selection.

High Drinking in the Dark Mice: A genetic model of drinking to intoxication

PubMed Central

Barkley-Levenson, Amanda M.; Crabbe, John C.

2014-01-01

Drinking to intoxication is a critical component of risky drinking behaviors in humans, such as binge drinking. Previous rodent models of alcohol consumption largely failed to demonstrate that animals were patterning drinking in such a way as to experience intoxication. Therefore, few rodent models of binge-like drinking and no specifically genetic models were available to study possible predisposing genes. The High Drinking in the Dark (HDID) selective breeding project was started to help fill this void, with HDID mice selected for reaching high blood alcohol levels in a limited access procedure. HDID mice now represent a genetic model of drinking to intoxication and can be used to help answer questions regarding predisposition toward this trait as well as potential correlated responses. They should also prove useful for the eventual development of better therapeutic strategies. PMID:24360287

Maximum entropy perception-action space: a Bayesian model of eye movement selection

NASA Astrophysics Data System (ADS)

Colas, Francis; Bessière, Pierre; Girard, Benoît

2011-03-01

In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps predict the eye movements of subjects recorded in a psychophysics experiment. Finally, based on experimental data, we postulate that the complex logarithmic mapping has a functional relevance, as the density of objects in this space in more uniform than expected. This may indicate that the representation space and control strategies are such that the object density is of maximum entropy.

Selective pre-priming of HA-specific CD4 T cells restores immunological reactivity to HA on heterosubtypic influenza infection.

PubMed

Alam, Shabnam; Chan, Cory; Qiu, Xing; Shannon, Ian; White, Chantelle L; Sant, Andrea J; Nayak, Jennifer L

2017-01-01

A hallmark of the immune response to influenza is repeated encounters with proteins containing both genetically conserved and variable components. Therefore, the B and T cell repertoire is continually being remodeled, with competition between memory and naïve lymphocytes. Our previous work using a mouse model of secondary heterosubtypic influenza infection has shown that this competition results in a focusing of CD4 T cell response specificity towards internal virion proteins with a selective decrease in CD4 T cell reactivity to the novel HA epitopes. Strikingly, this shift in CD4 T cell specificity was associated with a diminished anti-HA antibody response. Here, we sought to determine whether the loss in HA-specific reactivity that occurs as a consequence of immunological memory could be reversed by selectively priming HA-specific CD4 T cells prior to secondary infection. Using a peptide-based priming strategy, we found that selective expansion of the anti-HA CD4 T cell memory repertoire enhanced HA-specific antibody production upon heterosubtypic infection. These results suggest that the potentially deleterious consequences of repeated exposure to conserved influenza internal virion proteins could be reversed by vaccination strategies that selectively arm the HA-specific CD4 T cell compartment. This could be a potentially useful pre-pandemic vaccination strategy to promote accelerated neutralizing antibody production on challenge with a pandemic influenza strain that contains few conserved HA epitopes.

A comparison of different strategies in multivariate regression models for the direct determination of Mn, Cr, and Ni in steel samples using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; Gonzaga, Fabiano B.; da Rocha, Werickson F. C.; Lima, Igor C. A.

2018-01-01

Laser-induced breakdown spectroscopy (LIBS) analysis was carried out on eleven steel samples to quantify the concentrations of chromium, nickel, and manganese. LIBS spectral data were correlated to known concentrations of the samples using different strategies in partial least squares (PLS) regression models. For the PLS analysis, one predictive model was separately generated for each element, while different approaches were used for the selection of variables (VIP: variable importance in projection and iPLS: interval partial least squares) in the PLS model to quantify the contents of the elements. The comparison of the performance of the models showed that there was no significant statistical difference using the Wilcoxon signed rank test. The elliptical joint confidence region (EJCR) did not detect systematic errors in these proposed methodologies for each metal.

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).

Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

PubMed

Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P

2011-05-19

There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

Choice-Based Segmentation as an Enrollment Management Tool

ERIC Educational Resources Information Center

Young, Mark R.

2002-01-01

This article presents an approach to enrollment management based on target marketing strategies developed from a choice-based segmentation methodology. Students are classified into "switchable" or "non-switchable" segments based on their probability of selecting specific majors. A modified multinomial logit choice model is used to identify…

On the evolution of dispersal via heterogeneity in spatial connectivity

PubMed Central

Henriques-Silva, Renato; Boivin, Frédéric; Calcagno, Vincent; Urban, Mark C.; Peres-Neto, Pedro R.

2015-01-01

Dispersal has long been recognized as a mechanism that shapes many observed ecological and evolutionary processes. Thus, understanding the factors that promote its evolution remains a major goal in evolutionary ecology. Landscape connectivity may mediate the trade-off between the forces in favour of dispersal propensity (e.g. kin-competition, local extinction probability) and those against it (e.g. energetic or survival costs of dispersal). It remains, however, an open question how differing degrees of landscape connectivity may select for different dispersal strategies. We implemented an individual-based model to study the evolution of dispersal on landscapes that differed in the variance of connectivity across patches ranging from networks with all patches equally connected to highly heterogeneous networks. The parthenogenetic individuals dispersed based on a flexible logistic function of local abundance. Our results suggest, all else being equal, that landscapes differing in their connectivity patterns will select for different dispersal strategies and that these strategies confer a long-term fitness advantage to individuals at the regional scale. The strength of the selection will, however, vary across network types, being stronger on heterogeneous landscapes compared with the ones where all patches have equal connectivity. Our findings highlight how landscape connectivity can determine the evolution of dispersal strategies, which in turn affects how we think about important ecological dynamics such as metapopulation persistence and range expansion. PMID:25673685

Comparison of empirical strategies to maximize GENEHUNTER lod scores.

PubMed

Chen, C H; Finch, S J; Mendell, N R; Gordon, D

1999-01-01

We compare four strategies for finding the settings of genetic parameters that maximize the lod scores reported in GENEHUNTER 1.2. The four strategies are iterated complete factorial designs, iterated orthogonal Latin hypercubes, evolutionary operation, and numerical optimization. The genetic parameters that are set are the phenocopy rate, penetrance, and disease allele frequency; both recessive and dominant models are considered. We selected the optimization of a recessive model on the Collaborative Study on the Genetics of Alcoholism (COGA) data of chromosome 1 for complete analysis. Convergence to a setting producing a local maximum required the evaluation of over 100 settings (for a time budget of 800 minutes on a Pentium II 300 MHz PC). Two notable local maxima were detected, suggesting the need for a more extensive search before claiming that a global maximum had been found. The orthogonal Latin hypercube design was the best strategy for finding areas that produced high lod scores with small numbers of evaluations. Numerical optimization starting from a region producing high lod scores was the strategy that found the highest maximum observed.

Studying Children's Intrapersonal Emotion Regulation Strategies from the Process Model of Emotion Regulation.

PubMed

López-Pérez, Belén; Gummerum, Michaela; Wilson, Ellie; Dellaria, Giulia

2017-01-01

The authors relied on the Process Model of Emotion Regulation (PMER; J. J. Gross, 2007 ) to investigate children's abilities to regulate their emotions and to assess how distinct emotion regulation strategies are used by children of different ages. In Study 1, 180 parents of children aged between 3 and 8 years old reported about a situation in which their child had been able to change what she or he was feeling. In Study 2, 126 children 3-8 years old answered 2 questions about how they regulate their own emotions. Results from both studies showed age differences in children's reported emotion regulation abilities and the strategies they used. As expected, strategies such as situation selection, situation modification, and cognitive change were used more frequently by 5-6- and 7-8-year-olds, whereas attention deployment was mainly used by 3-4-year-olds. No age differences were found for response modulation. The present research contributes to the existing body of literature on emotion regulation by adding more information about the developmental patterns for each specific emotion regulation strategy.

Detection of genomic loci associated with environmental variables using generalized linear mixed models.

PubMed

Lobréaux, Stéphane; Melodelima, Christelle

2015-02-01

We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress. Copyright © 2014 Elsevier Inc. All rights reserved.

Selection of head and whisker coordination strategies during goal-oriented active touch.

PubMed

Schroeder, Joseph B; Ritt, Jason T

2016-04-01

In the rodent whisker system, a key model for neural processing and behavioral choices during active sensing, whisker motion is increasingly recognized as only part of a broader motor repertoire employed by rodents during active touch. In particular, recent studies suggest whisker and head motions are tightly coordinated. However, conditions governing the selection and temporal organization of such coordinated sensing strategies remain poorly understood. We videographically reconstructed head and whisker motions of freely moving mice searching for a randomly located rewarded aperture, focusing on trials in which animals appeared to rapidly "correct" their trajectory under tactile guidance. Mice orienting after unilateral contact repositioned their whiskers similarly to previously reported head-turning asymmetry. However, whisker repositioning preceded head turn onsets and was not bilaterally symmetric. Moreover, mice selectively employed a strategy we term contact maintenance, with whisking modulated to counteract head motion and facilitate repeated contacts on subsequent whisks. Significantly, contact maintenance was not observed following initial contact with an aperture boundary, when the mouse needed to make a large corrective head motion to the front of the aperture, but only following contact by the same whisker field with the opposite aperture boundary, when the mouse needed to precisely align its head with the reward spout. Together these results suggest that mice can select from a diverse range of sensing strategies incorporating both knowledge of the task and whisk-by-whisk sensory information and, moreover, suggest the existence of high level control (not solely reflexive) of sensing motions coordinated between multiple body parts. Copyright © 2016 the American Physiological Society.

Transformation from gold nanoclusters to plasmonic nanoparticles: A general strategy towards selective detection of organophosphorothioate pesticides.

PubMed

Lu, Qian; Zhou, Tingyao; Wang, Yaping; Gong, Lingshan; Liu, Jinbin

2018-01-15

Luminescent gold nanoclusters (AuNCs) synthesized using non-thiolate DNA ligands were reported to show both optical and structure responses toward diethyposphorthioate (DEP) derived from the hydrolysis of chlorpyrifos (CP). After incubation of AuNCs with DEP, the non-thiolate DNA ligands were immediately replaced and the tiny AuNCs with ultrasmall size transformed gradually to plasmonic nanoparticles, which resulted in significant luminescence quenching of the AuNCs, offering a new possibility to selectively detect organophosphorothioate pesticides that could be easily hydrolyzed to form the special structures such as DEP containing two binding sites (e.g. S and O atoms). Therefore, selecting CP as a model analyte, we here developed a general strategy for the construction of a novel chemosensor for the determination of CP using the non-thiolate DNA coated AuNCs as an optical probe. Based on aggregation-induced luminescence quenching, this strategy exhibited highly sensitive and selective responses towards CP with a limit of detection (LOD) of 0.50μM, and was applied successfully to the analysis of CP in real sample. More interestingly, this facile strategy could easily distinguish CP from other thiol reagents through solution color change in spite of the existence of the coordination between Au and S atom for both of them, and the response mechanisms for them were studied in detail. In additional, it could be extended to detect the other organophosphorothioate pesticides with the similar structure as CP, which exploits a new platform for the construction of chemosensor and application. Copyright © 2017 Elsevier B.V. All rights reserved.

Selection of head and whisker coordination strategies during goal-oriented active touch

PubMed Central

2016-01-01

In the rodent whisker system, a key model for neural processing and behavioral choices during active sensing, whisker motion is increasingly recognized as only part of a broader motor repertoire employed by rodents during active touch. In particular, recent studies suggest whisker and head motions are tightly coordinated. However, conditions governing the selection and temporal organization of such coordinated sensing strategies remain poorly understood. We videographically reconstructed head and whisker motions of freely moving mice searching for a randomly located rewarded aperture, focusing on trials in which animals appeared to rapidly “correct” their trajectory under tactile guidance. Mice orienting after unilateral contact repositioned their whiskers similarly to previously reported head-turning asymmetry. However, whisker repositioning preceded head turn onsets and was not bilaterally symmetric. Moreover, mice selectively employed a strategy we term contact maintenance, with whisking modulated to counteract head motion and facilitate repeated contacts on subsequent whisks. Significantly, contact maintenance was not observed following initial contact with an aperture boundary, when the mouse needed to make a large corrective head motion to the front of the aperture, but only following contact by the same whisker field with the opposite aperture boundary, when the mouse needed to precisely align its head with the reward spout. Together these results suggest that mice can select from a diverse range of sensing strategies incorporating both knowledge of the task and whisk-by-whisk sensory information and, moreover, suggest the existence of high level control (not solely reflexive) of sensing motions coordinated between multiple body parts. PMID:26792880

Process identification of the SCR system of coal-fired power plant for de-NOx based on historical operation data.

PubMed

Li, Jian; Shi, Raoqiao; Xu, Chuanlong; Wang, Shimin

2018-05-08

The selective catalytic reduction (SCR) system, as one principal flue gas treatment method employed for the NO x emission control of the coal-fired power plant, is nonlinear and time-varying with great inertia and large time delay. It is difficult for the present SCR control system to achieve satisfactory performance with the traditional feedback and feedforward control strategies. Although some improved control strategies, such as the Smith predictor control and the model predictive control, have been proposed for this issue, a well-matched identification model is essentially required to realize a superior control of the SCR system. Industrial field experiment is an alternative way to identify the SCR system model in the coal-fired power plant. But it undesirably disturbs the operation system and is costly in time and manpower. In this paper, a process identification model of the SCR system is proposed and developed by applying the asymptotic method to the sufficiently excited data, selected from the original historical operation database of a 350 MW coal-fired power plant according to the condition number of the Fisher information matrix. Numerical simulations are carried out based on the practical historical operation data to evaluate the performance of the proposed model. Results show that the proposed model can efficiently achieve the process identification of the SCR system.

Optimisation of strain selection in evolutionary continuous culture

NASA Astrophysics Data System (ADS)

Bayen, T.; Mairet, F.

2017-12-01

In this work, we study a minimal time control problem for a perfectly mixed continuous culture with n ≥ 2 species and one limiting resource. The model that we consider includes a mutation factor for the microorganisms. Our aim is to provide optimal feedback control laws to optimise the selection of the species of interest. Thanks to Pontryagin's Principle, we derive optimality conditions on optimal controls and introduce a sub-optimal control law based on a most rapid approach to a singular arc that depends on the initial condition. Using adaptive dynamics theory, we also study a simplified version of this model which allows to introduce a near optimal strategy.

Developing a framework for energy technology portfolio selection

NASA Astrophysics Data System (ADS)

Davoudpour, Hamid; Ashrafi, Maryam

2012-11-01

Today, the increased consumption of energy in world, in addition to the risk of quick exhaustion of fossil resources, has forced industrial firms and organizations to utilize energy technology portfolio management tools viewed both as a process of diversification of energy sources and optimal use of available energy sources. Furthermore, the rapid development of technologies, their increasing complexity and variety, and market dynamics have made the task of technology portfolio selection difficult. Considering high level of competitiveness, organizations need to strategically allocate their limited resources to the best subset of possible candidates. This paper presents the results of developing a mathematical model for energy technology portfolio selection at a R&D center maximizing support of the organization's strategy and values. The model balances the cost and benefit of the entire portfolio.

A Comparative Study of Thought Fusion Beliefs and Thought Control Strategies in Patient With Obsessive-Compulsive Disorder, Major Depressive Disorder and Normal People

PubMed Central

Amiri Pichakolaei, Ahmad; Fahimi, Samad; Bakhshipour Roudsari, Abbas; Fakhari, Ali; Akbari, Ebrahim; Rahimkhanli, Masoumeh

2014-01-01

Objective: The present study aimed to investigate the metacognitive model of obsessive-compulsive disorder (OCD), through a comparative study of thought fusion beliefs and thought control strategies between patients with OCD, depression, and normal people. Methods: This is a causal-comparative study. About 20 patients were selected with OCD, and 20 patients with major depression disorder (MDD), and 20 normal individuals. Participants completed a thought fusion instrument and thought control questionnaire. Data were analyzed using multivariate analysis of variance. Results: Results indicated that patients with OCD obtained higher scores than two other groups. Also, there was a statistical significant difference between the three groups in thought control strategies and punishment, worry, and distraction subscales. Conclusion: Therefore, the results of the present study supported the metacognitive model of obsessive and showed thought fusion beliefs and thought control strategies can be effective in onset and continuity of OCD. PMID:25780373

The rock-paper-scissors game and the evolution of alternative male strategies

NASA Astrophysics Data System (ADS)

Sinervo, B.; Lively, C. M.

1996-03-01

MANY species exhibit colour polymorphisms associated with alternative male reproductive strategies, including territorial males and 'sneaker males' that behave and look like females1-3. The prevalence of multiple morphs is a challenge to evolutionary theory because a single strategy should prevail unless morphs have exactly equal fitness4,5 or a fitness advantage when rare6,7. We report here the application of an evolutionary stable strategy model to a three-morph mating system in the side-blotched lizard. Using parameter estimates from field data, the model predicted oscillations in morph frequency, and the frequencies of the three male morphs were found to oscillate over a six-year period in the field. The fitnesses of each morph relative to other morphs were non-transitive in that each morph could invade another morph when rare, but was itself invadable by another morph when common. Concordance between frequency-dependent selection and the among-year changes in morph fitnesses suggest that male interactions drive a dynamic 'rock-paper-scissors' game7.

Coping with Fear of and Exposure to Terrorism among Expatriates.

PubMed

Beutell, Nicholas J; O'Hare, Marianne M; Schneer, Joy A; Alstete, Jeffrey W

2017-07-19

This paper examines existing research on the impact of terrorism on expatriate coping strategies. We consider pre-assignment fear of terrorism, in-country coping strategies, and anxiety and posttraumatic stress disorder (PTSD) associated with repatriation. The extant research is small but growing. Our model for expatriate coping at the pre-departure, in-country, and repatriation stages includes strategies specific to each stage. Preparation using proactive coping, systematic desensitization, problem and emotion focused coping, social support, and virtual reality explorations are recommended. Selecting expatriate candidates who are well-adjusted, emotionally intelligent, and possessing good coping skills is essential for successful assignments in terror-prone regions.

Coping with Fear of and Exposure to Terrorism among Expatriates

PubMed Central

O’Hare, Marianne M.

2017-01-01

This paper examines existing research on the impact of terrorism on expatriate coping strategies. We consider pre-assignment fear of terrorism, in-country coping strategies, and anxiety and posttraumatic stress disorder (PTSD) associated with repatriation. The extant research is small but growing. Our model for expatriate coping at the pre-departure, in-country, and repatriation stages includes strategies specific to each stage. Preparation using proactive coping, systematic desensitization, problem and emotion focused coping, social support, and virtual reality explorations are recommended. Selecting expatriate candidates who are well-adjusted, emotionally intelligent, and possessing good coping skills is essential for successful assignments in terror-prone regions. PMID:28753940

Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections.

PubMed

Don, Rob; Ioset, Jean-Robert

2014-01-01

The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.

On the preservation of cooperation in two-strategy games with nonlocal interactions.

PubMed

Aydogmus, Ozgur; Zhou, Wen; Kang, Yun

2017-03-01

Nonlocal interactions such as spatial interaction are ubiquitous in nature and may alter the equilibrium in evolutionary dynamics. Models including nonlocal spatial interactions can provide a further understanding on the preservation and emergence of cooperation in evolutionary dynamics. In this paper, we consider a variety of two-strategy evolutionary spatial games with nonlocal interactions based on an integro-differential replicator equation. By defining the invasion speed and minimal traveling wave speed for the derived model, we study the effects of the payoffs, the selection pressure and the spatial parameter on the preservation of cooperation. One of our most interesting findings is that, for the Prisoners Dilemma games in which the defection is the only evolutionary stable strategy for unstructured populations, analyses on its asymptotic speed of propagation suggest that, in contrast with spatially homogeneous games, the cooperators can invade the habitat under proper conditions. Other two-strategy evolutionary spatial games are also explored. Both our theoretical and numerical studies show that the nonlocal spatial interaction favors diversity in strategies in a population and is able to preserve cooperation in a competing environment. A real data application in a virus mutation study echoes our theoretical observations. In addition, we compare the results of our model to the partial differential equation approach to demonstrate the importance of including non-local interaction component in evolutionary game models. Copyright © 2016 Elsevier Inc. All rights reserved.

Simulation of the evolution of root water foraging strategies in dry and shallow soils.

PubMed

Renton, Michael; Poot, Pieter

2014-09-01

The dynamic structural development of plants can be seen as a strategy for exploiting the limited resources available within their environment, and we would expect that evolution would lead to efficient strategies that reduce costs while maximizing resource acquisition. In particular, perennial species endemic to habitats with shallow soils in seasonally dry environments have been shown to have a specialized root system morphology that may enhance access to water resources in the underlying rock. This study aimed to explore these hypotheses by applying evolutionary algorithms to a functional-structural root growth model. A simulation model of a plant's root system was developed, which represents the dynamics of water uptake and structural growth. The model is simple enough for evolutionary optimization to be computationally feasible, yet flexible enough to allow a range of structural development strategies to be explored. The model was combined with an evolutionary algorithm in order to investigate a case study habitat with a highly heterogeneous distribution of resources, both spatially and temporally--the situation of perennial plants occurring on shallow soils in seasonally dry environments. Evolution was simulated under two contrasting fitness criteria: (1) the ability to find wet cracks in underlying rock, and (2) maximizing above-ground biomass. The novel approach successfully resulted in the evolution of more efficient structural development strategies for both fitness criteria. Different rooting strategies evolved when different criteria were applied, and each evolved strategy made ecological sense in terms of the corresponding fitness criterion. Evolution selected for root system morphologies which matched those of real species from corresponding habitats. Specialized root morphology with deeper rather than shallower lateral branching enhances access to water resources in underlying rock. More generally, the approach provides insights into both evolutionary processes and ecological costs and benefits of different plant growth strategies.

The Process Model of Group-Based Emotion: Integrating Intergroup Emotion and Emotion Regulation Perspectives.

PubMed

Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J

2016-05-01

Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and occur in response to situations perceived as relevant for that group. We propose a model for examining group-based emotion regulation that integrates intergroup emotions theory and the process model of emotion regulation. This synergy expands intergroup emotion theory by facilitating further investigation of different goals (i.e., hedonic or instrumental) and strategies (e.g., situation selection and modification strategies) used to regulate group-based emotions. It also expands emotion regulation research by emphasizing the role of self-categorization (e.g., as an individual or a group member) in the emotional process. Finally, we discuss the promise of this theoretical synergy and suggest several directions for future research on group-based emotion regulation. © 2015 by the Society for Personality and Social Psychology, Inc.

Flowering time and seed dormancy control use external coincidence to generate life history strategy

PubMed Central

Springthorpe, Vicki; Penfield, Steven

2015-01-01

Climate change is accelerating plant developmental transitions coordinated with the seasons in temperate environments. To understand the importance of these timing advances for a stable life history strategy, we constructed a full life cycle model of Arabidopsis thaliana. Modelling and field data reveal that a cryptic function of flowering time control is to limit seed set of winter annuals to an ambient temperature window which coincides with a temperature-sensitive switch in seed dormancy state. This coincidence is predicted to be conserved independent of climate at the expense of flowering date, suggesting that temperature control of flowering time has evolved to constrain seed set environment and therefore frequency of dormant and non-dormant seed states. We show that late flowering can disrupt this bet-hedging germination strategy. Our analysis shows that life history modelling can reveal hidden fitness constraints and identify non-obvious selection pressures as emergent features. DOI: http://dx.doi.org/10.7554/eLife.05557.001 PMID:25824056

Animal models of cartilage repair

PubMed Central

Cook, J. L.; Hung, C. T.; Kuroki, K.; Stoker, A. M.; Cook, C. R.; Pfeiffer, F. M.; Sherman, S. L.; Stannard, J. P.

2014-01-01

Cartilage repair in terms of replacement, or regeneration of damaged or diseased articular cartilage with functional tissue, is the ‘holy grail’ of joint surgery. A wide spectrum of strategies for cartilage repair currently exists and several of these techniques have been reported to be associated with successful clinical outcomes for appropriately selected indications. However, based on respective advantages, disadvantages, and limitations, no single strategy, or even combination of strategies, provides surgeons with viable options for attaining successful long-term outcomes in the majority of patients. As such, development of novel techniques and optimisation of current techniques need to be, and are, the focus of a great deal of research from the basic science level to clinical trials. Translational research that bridges scientific discoveries to clinical application involves the use of animal models in order to assess safety and efficacy for regulatory approval for human use. This review article provides an overview of animal models for cartilage repair. Cite this article: Bone Joint Res 2014;4:89–94. PMID:24695750

Plan selection strategy for rectum cancer patients: An interobserver study to assess clinical feasibility.

PubMed

de Jong, Rianne; Lutkenhaus, Lotte; van Wieringen, Niek; Visser, Jorrit; Wiersma, Jan; Crama, Koen; Geijsen, Debby; Bel, Arjan

2016-08-01

In radiotherapy for rectum cancer, the target volume is highly deformable. An adaptive plan selection strategy can mitigate the effect of these variations. The purpose of this study was to evaluate the feasibility of an adaptive strategy by assessing the interobserver variation in CBCT-based plan selection. Eleven patients with rectum cancer, treated with a non-adaptive strategy, were selected. Five CBCT scans were available per patient. To simulate the plan selection strategy, per patient three PTVs were created by varying the anterior upper mesorectum margin. For each CBCT scan, twenty observers selected the smallest PTV that encompassed the target volume. After this initial baseline measurement, the gold standard was determined during a consensus meeting, followed by a second measurement one month later. Differences between both measurements were assessed using the Wilcoxon signed-rank test. In the baseline measurement, the concordance with the gold standard was 69% (range: 60-82%), which improved to 75% (range: 60-87%) in the second measurement (p=0.01). For the second measurement, 10% of plan selections were smaller than the gold standard. With a plan selection consistency between observers of 75%, a plan selection strategy for rectum cancer patients is feasible. Copyright © 2016 Elsevier Ireland 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

Multi-period response management to contaminated water distribution networks: dynamic programming versus genetic algorithms

NASA Astrophysics Data System (ADS)

Bashi-Azghadi, Seyyed Nasser; Afshar, Abbas; Afshar, Mohammad Hadi

2018-03-01

Previous studies on consequence management assume that the selected response action including valve closure and/or hydrant opening remains unchanged during the entire management period. This study presents a new embedded simulation-optimization methodology for deriving time-varying operational response actions in which the network topology may change from one stage to another. Dynamic programming (DP) and genetic algorithm (GA) are used in order to minimize selected objective functions. Two networks of small and large sizes are used in order to illustrate the performance of the proposed modelling schemes if a time-dependent consequence management strategy is to be implemented. The results show that for a small number of decision variables even in large-scale networks, DP is superior in terms of accuracy and computer runtime. However, as the number of potential actions grows, DP loses its merit over the GA approach. This study clearly proves the priority of the proposed dynamic operation strategy over the commonly used static strategy.

Metacognition for strategy selection during arithmetic problem-solving in young and older adults.

PubMed

Geurten, Marie; Lemaire, Patrick

2018-04-19

We examined participants' strategy choices and metacognitive judgments during arithmetic problem-solving. Metacognitive judgments were collected either prospectively or retrospectively. We tested whether metacognitive judgments are related to strategy choices on the current problems and on the immediately following problems, and age-related differences in relations between metacognition and strategy choices. Data showed that both young and older adults were able to make accurate retrospective, but not prospective, judgments. Moreover, the accuracy of retrospective judgments was comparable in young and older adults when participants had to select and execute the better strategy. Metacognitive accuracy was even higher in older adults when participants had to only select the better strategy. Finally, low-confidence judgments on current items were more frequently followed by better strategy selection on immediately succeeding items than high-confidence judgments in both young and older adults. Implications of these findings to further our understanding of age-related differences and similarities in adults' metacognitive monitoring and metacognitive regulation for strategy selection in the context of arithmetic problem solving are discussed.

Entropy-based gene ranking without selection bias for the predictive classification of microarray data.

PubMed

Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe

2003-11-06

We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process). With E-RFE, we speed up the recursive feature elimination (RFE) with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

PubMed

Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

PubMed Central

Gundogar, Emin; Yılmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

Life history consequences of mammal sibling rivalry.

PubMed

Stockley, P; Parker, G A

2002-10-01

Mammal life history traits relating to growth and reproduction are extremely diverse. Sibling rivalry may contribute to selection pressures influencing this diversity, because individuals that are relatively large at birth typically have an advantage in competition for milk. However, selection for increased growth rate is likely to be constrained by kin selection and physiological costs. Here, we present and test a model examining the ESS (evolutionarily stable strategy) balance between these constraints and advantages associated with increased prenatal growth in mammal sibling rivalry. Predictions of the model are supported by results of comparative analyses for the Carnivora and Insectivora, which demonstrate an increase in prenatal growth rate with increasing intensity of postnatal scramble competition, and a decrease in postnatal growth rate relative to size at birth. Because increased prenatal growth rates are predicted to select for reduced gestation length under certain conditions, our study also indicates that sibling rivalry may contribute to selection pressures influencing variation in altriciality and precociality among mammals.

The impact of rural-exposure strategies on the intention of dental students and dental graduates to practice in rural areas: a systematic review and meta-analysis

PubMed Central

Suphanchaimat, Rapeepong; Cetthakrikul, Nisachol; Dalliston, Alexander; Putthasri, Weerasak

2016-01-01

Background and objectives The objective of this study was to assess the impact of strategies on the intention of dental students/graduates to practice in rural areas. The strategies included the recruitment of dental students from rural backgrounds and clinical rotations in rural areas during the training of dental students. Materials and methods The study undertook a systematic review and utilized meta-analysis to assess these strategies. International literature published between 2000 and 2015 was retrieved from three main search engines: Medline, Embase, and Scopus. The selected articles were scanned to extract the main content. The impact of the strategies was quantitatively assessed by meta-analysis, using the random-effect model. The pooled effect was reported in terms of odds ratios (ORs) with 95% confidence intervals. Sensitivity and subgroup analyses were performed. Publication bias was assessed by the Funnel plot and Egger’s test. Results Seven of the initially selected 897 articles were included for the full review. The majority of the selected articles had been published in developed countries. The meta-analysis results revealed that the pooled OR of rural exposure on the intention to practice in rural areas was approximately 4.1, statistically significant. Subgroup analysis showed that clinical rotations in rural areas tended to have a slightly greater influence on rural dental practice than recruiting students from rural backgrounds (OR 4.3 versus 4.2). There was weaker evidence of publication bias, which was derived from small-study effects. Conclusion Enrolling students with rural backgrounds and imposing compulsory clinical rotation in rural areas during their study appeared to be effective strategies in tackling the shortage and maldistribution of dentists in rural areas. PMID:27822134

Constructing a Bayesian network model for improving safety behavior of employees at workplaces.

PubMed

Mohammadfam, Iraj; Ghasemi, Fakhradin; Kalatpour, Omid; Moghimbeigi, Abbas

2017-01-01

Unsafe behavior increases the risk of accident at workplaces and needs to be managed properly. The aim of the present study was to provide a model for managing and improving safety behavior of employees using the Bayesian networks approach. The study was conducted in several power plant construction projects in Iran. The data were collected using a questionnaire composed of nine factors, including management commitment, supporting environment, safety management system, employees' participation, safety knowledge, safety attitude, motivation, resource allocation, and work pressure. In order for measuring the score of each factor assigned by a responder, a measurement model was constructed for each of them. The Bayesian network was constructed using experts' opinions and Dempster-Shafer theory. Using belief updating, the best intervention strategies for improving safety behavior also were selected. The result of the present study demonstrated that the majority of employees do not tend to consider safety rules, regulation, procedures and norms in their behavior at the workplace. Safety attitude, safety knowledge, and supporting environment were the best predictor of safety behavior. Moreover, it was determined that instantaneous improvement of supporting environment and employee participation is the best strategy to reach a high proportion of safety behavior at the workplace. The lack of a comprehensive model that can be used for explaining safety behavior was one of the most problematic issues of the study. Furthermore, it can be concluded that belief updating is a unique feature of Bayesian networks that is very useful in comparing various intervention strategies and selecting the best one form them. Copyright © 2016 Elsevier Ltd. All rights reserved.

Investigating the effectiveness of response strategies for vulnerabilities to corruption in the chinese public construction sector.

PubMed

Shan, Ming; Chan, Albert P C; Le, Yun; Hu, Yi

2015-06-01

Response strategy is a key for preventing widespread corruption vulnerabilities in the public construction sector. Although several studies have been devoted to this area, the effectiveness of response strategies has seldom been evaluated in China. This study aims to fill this gap by investigating the effectiveness of response strategies for corruption vulnerabilities through a survey in the Chinese public construction sector. Survey data obtained from selected experts involved in the Chinese public construction sector were analyzed by factor analysis and partial least squares-structural equation modeling. Analysis results showed that four response strategies of leadership, rules and regulations, training, and sanctions, only achieved an acceptable level in preventing corruption vulnerabilities in the Chinese public construction sector. This study contributes to knowledge by improving the understanding of the effectiveness of response strategies for corruption vulnerabilities in the public construction sector of developing countries.

Security-Oriented and Load-Balancing Wireless Data Routing Game in the Integration of Advanced Metering Infrastructure Network in Smart Grid

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

He, Fulin; Cao, Yang; Zhang, Jun Jason

Ensuring flexible and reliable data routing is indispensable for the integration of Advanced Metering Infrastructure (AMI) networks, we propose a secure-oriented and load-balancing wireless data routing scheme. A novel utility function is designed based on security routing scheme. Then, we model the interactive security-oriented routing strategy among meter data concentrators or smart grid meters as a mixed-strategy network formation game. Finally, such problem results in a stable probabilistic routing scheme with proposed distributed learning algorithm. One contributions is that we studied that different types of applications affect the routing selection strategy and the strategy tendency. Another contributions is that themore » chosen strategy of our mixed routing can adaptively to converge to a new mixed strategy Nash equilibrium (MSNE) during the learning process in the smart grid.« less

Shifts in growth strategies reflect tradeoffs in cellular economics

PubMed Central

Molenaar, Douwe; van Berlo, Rogier; de Ridder, Dick; Teusink, Bas

2009-01-01

The growth rate-dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self-replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self-replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies. PMID:19888218

Tripartite equilibrium strategy for a carbon tax setting problem in air passenger transport.

PubMed

Xu, Jiuping; Qiu, Rui; Tao, Zhimiao; Xie, Heping

2018-03-01

Carbon emissions in air passenger transport have become increasing serious with the rapidly development of aviation industry. Combined with a tripartite equilibrium strategy, this paper proposes a multi-level multi-objective model for an air passenger transport carbon tax setting problem (CTSP) among an international organization, an airline and passengers with the fuzzy uncertainty. The proposed model is simplified to an equivalent crisp model by a weighted sum procedure and a Karush-Kuhn-Tucker (KKT) transformation method. To solve the equivalent crisp model, a fuzzy logic controlled genetic algorithm with entropy-Bolitzmann selection (FLC-GA with EBS) is designed as an integrated solution method. Then, a numerical example is provided to demonstrate the practicality and efficiency of the optimization method. Results show that the cap tax mechanism is an important part of air passenger trans'port carbon emission mitigation and thus, it should be effectively applied to air passenger transport. These results also indicate that the proposed method can provide efficient ways of mitigating carbon emissions for air passenger transport, and therefore assist decision makers in formulating relevant strategies under multiple scenarios.

Review of retrofit strategies decision system in historic perspective

NASA Astrophysics Data System (ADS)

Bostenaru Dan, M. D.

2004-06-01

Urban development is a process. In structuring and developing its phases different actors are implied, who act under different, sometimes opposite, dynamic conditions and within different reference systems. This paper aims to explore the contribution of participatism to disaster mitigation, when this concerns earthquake impact on urban settlements, through the support provided to multi-criteria decision in matters of retrofit. The research broadness in field of decision making on one side and the lack of a specific model for the retrofit of existing buildings on another side led to an extensive review of the state of the art in related models to address the issue. Core idea in the selection of existing models has been the preoccupation for collaborative issues, in other words, the consideration for the different actors implied in the planning process. The historic perspective on participative planning models is made from the view of two generations of citizen implication. The first approaches focus on the participation of the building owner/inhabitant in the planning process of building construction. As current strategies building rehabilitation and selection from alternative retrofit strategies are presented. New developments include innovative models using the internet or spatial databases. The investigated participation approaches show, that participation and communication as a more comprehensive term are an old topic in the field politics-democratisation-urbanism. In all cases it can be talked of "successful learning processes", of the improvement of the level of the professional debate. More than 30 years history of participation marked a transition in understanding the concept: from participation, based on a central decision process leading to a solution controlled and steered by the political-administrative system, to communication, characterised by simultaneous decision processes taking place outside politics and administration in co-operative procedures.

Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.

PubMed

Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang

2016-01-01

To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible-exposed-infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009-2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics.

Efficient Vaccine Distribution Based on a Hybrid Compartmental Model

PubMed Central

Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang

2016-01-01

To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible—exposed—infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009–2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics. PMID:27233015

A TiS2 nanosheet enhanced fluorescence polarization biosensor for ultra-sensitive detection of biomolecules

NASA Astrophysics Data System (ADS)

Li, Xiang; Ding, Xuelian; Li, Yongfang; Wang, Linsong; Fan, Jing

2016-05-01

Development of new strategies for the sensitive and selective detection of ultra-low concentrations of specific cancer markers is of great importance for assessing cancer therapeutics due to its crucial role in early clinical diagnoses and biomedical applications. In this work, we have developed two types of fluorescence polarization (FP) amplification assay strategies for the detection of biomolecules by using TiS2 as a FP enhancer and Zn2+-dependent self-hydrolyzing deoxyribozymes as catalysts to realize enzyme-catalyzed target-recycling signal amplification. One approach is based on the terminal protection of small-molecule-linked DNA, in which biomolecular binding to small molecules in DNA-small-molecule chimeras can protect the conjugated DNA from degradation by exonuclease I (Exo I); the other approach is based on the terminal protection of biomolecular bound aptamer DNA, in which biomolecules directly bound to the single strand aptamer DNA can protect the ssDNA from degradation by Exo I. We select folate receptor (FR) and thrombin (Tb) as model analytes to verify the current concept. It is shown that under optimized conditions, our strategies exhibit high sensitivity and selectivity for the quantification of FR and Tb with low detection limits (0.003 ng mL-1 and 0.01 pM, respectively). Additionally, this strategy is a simple ``mix and detect'' approach, and does not require any separation steps. This biosensor is also utilized in the analysis of real biological samples, the results agree well with those obtained by the enzyme-linked immunosorbent assay (ELISA).Development of new strategies for the sensitive and selective detection of ultra-low concentrations of specific cancer markers is of great importance for assessing cancer therapeutics due to its crucial role in early clinical diagnoses and biomedical applications. In this work, we have developed two types of fluorescence polarization (FP) amplification assay strategies for the detection of biomolecules by using TiS2 as a FP enhancer and Zn2+-dependent self-hydrolyzing deoxyribozymes as catalysts to realize enzyme-catalyzed target-recycling signal amplification. One approach is based on the terminal protection of small-molecule-linked DNA, in which biomolecular binding to small molecules in DNA-small-molecule chimeras can protect the conjugated DNA from degradation by exonuclease I (Exo I); the other approach is based on the terminal protection of biomolecular bound aptamer DNA, in which biomolecules directly bound to the single strand aptamer DNA can protect the ssDNA from degradation by Exo I. We select folate receptor (FR) and thrombin (Tb) as model analytes to verify the current concept. It is shown that under optimized conditions, our strategies exhibit high sensitivity and selectivity for the quantification of FR and Tb with low detection limits (0.003 ng mL-1 and 0.01 pM, respectively). Additionally, this strategy is a simple ``mix and detect'' approach, and does not require any separation steps. This biosensor is also utilized in the analysis of real biological samples, the results agree well with those obtained by the enzyme-linked immunosorbent assay (ELISA). Electronic supplementary information (ESI) available: Tables S1-S4, Scheme S1, Fig. S1-S10. See DOI: 10.1039/c6nr00946h

Territory surveillance and prey management: Wolves keep track of space and time.

PubMed

Schlägel, Ulrike E; Merrill, Evelyn H; Lewis, Mark A

2017-10-01

Identifying behavioral mechanisms that underlie observed movement patterns is difficult when animals employ sophisticated cognitive-based strategies. Such strategies may arise when timing of return visits is important, for instance to allow for resource renewal or territorial patrolling. We fitted spatially explicit random-walk models to GPS movement data of six wolves ( Canis lupus ; Linnaeus, 1758) from Alberta, Canada to investigate the importance of the following: (1) territorial surveillance likely related to renewal of scent marks along territorial edges, to reduce intraspecific risk among packs, and (2) delay in return to recently hunted areas, which may be related to anti-predator responses of prey under varying prey densities. The movement models incorporated the spatiotemporal variable "time since last visit," which acts as a wolf's memory index of its travel history and is integrated into the movement decision along with its position in relation to territory boundaries and information on local prey densities. We used a model selection framework to test hypotheses about the combined importance of these variables in wolf movement strategies. Time-dependent movement for territory surveillance was supported by all wolf movement tracks. Wolves generally avoided territory edges, but this avoidance was reduced as time since last visit increased. Time-dependent prey management was weak except in one wolf. This wolf selected locations with longer time since last visit and lower prey density, which led to a longer delay in revisiting high prey density sites. Our study shows that we can use spatially explicit random walks to identify behavioral strategies that merge environmental information and explicit spatiotemporal information on past movements (i.e., "when" and "where") to make movement decisions. The approach allows us to better understand cognition-based movement in relation to dynamic environments and resources.

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.

Reliable inference of light curve parameters in the presence of systematics

NASA Astrophysics Data System (ADS)

Gibson, Neale P.

2016-10-01

Time-series photometry and spectroscopy of transiting exoplanets allow us to study their atmospheres. Unfortunately, the required precision to extract atmospheric information surpasses the design specifications of most general purpose instrumentation. This results in instrumental systematics in the light curves that are typically larger than the target precision. Systematics must therefore be modelled, leaving the inference of light-curve parameters conditioned on the subjective choice of systematics models and model-selection criteria. Here, I briefly review the use of systematics models commonly used for transmission and emission spectroscopy, including model selection, marginalisation over models, and stochastic processes. These form a hierarchy of models with increasing degree of objectivity. I argue that marginalisation over many systematics models is a minimal requirement for robust inference. Stochastic models provide even more flexibility and objectivity, and therefore produce the most reliable results. However, no systematics models are perfect, and the best strategy is to compare multiple methods and repeat observations where possible.

Developing Social Competence in Children. Choices Briefs, Number 3.

ERIC Educational Resources Information Center

Schwartz, Wendy

This brief presents an overview of effective strategies for developing prosocial attitudes and behaviors in elementary school children. The description of approaches and activities can help educators integrate an antiviolence education program into their schools and classrooms, select a program to implement from many models in use around the…

Communication and Persuasion: Factors Influencing a Patient's Behavior.

ERIC Educational Resources Information Center

Logan, Henrietta L.

1991-01-01

Three elements of persuasion (source, message, and audience) are discussed, and a paradigm for persuasion, the Elaboration Likelihood Model, which unifies many existing attitude theories, is described. Selected concepts and research on attitudes and persuasion are also examined as a context for teaching preventive behaviors and strategies in…

Solutions for Failing High Schools: Converging Visions and Promising Models.

ERIC Educational Resources Information Center

Legters, Nettie; Balfanz, Robert; McPartland, James

Promising solutions to the failings of traditional comprehensive high schools were reviewed to identify basic principles and strategies for improving high schools nationwide. Selected research studies, policy documents, and promising high school programs were reviewed. The review revealed the following principles for helping high schools better…

Engaging Watershed Stakeholders for Cost-Effective Environmental Management Planning with "Watershed Manager"

ERIC Educational Resources Information Center

Williams, Jeffery R.; Smith, Craig M.; Roe, Josh D.; Leatherman, John C.; Wilson, Robert M.

2012-01-01

"Watershed Manager" is a spreadsheet-based model that is used in extension education programs for learning about and selecting cost-effective watershed management practices to reduce soil, nitrogen, and phosphorus losses from cropland. It can facilitate Watershed Restoration and Protection Strategy (WRAPS) stakeholder groups' development…

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,…

Identification of Hierarchies of Student Learning about Percentages Using Rasch Analysis

ERIC Educational Resources Information Center

Burfitt, Joan

2013-01-01

A review of the research literature indicated that there were probable orders in which students develop understandings and skills for calculating with percentages. Such calculations might include using models to represent percentages, knowing fraction equivalents, selection of strategies to solve problems and determination of percentage change. To…

Incident Management, Fast-Trac, Phase Iib Deliverables, #20. The Model Analysis Report On The Benefits Of Scats In Alleviating The Impacts Of Incidents

DOT National Transportation Integrated Search

1996-01-01

FAST-TRAC : SELECTING THE MOST APPROPRIATE TRAFFIC CONTROL STRATEGY FOR INCIDENT CONGESTION MANAGEMENT CAN HAVE A MAJOR IMPACT ON THE EXTENT AND DURATION OF THE RESULTING CONGESTION. THIS RESEARCH INVESTIGATED THE EFFECTIVENESSES OF SEVERAL CONTRO...

Applying Learning Theories and Instructional Design Models for Effective Instruction

ERIC Educational Resources Information Center

Khalil, Mohammed K.; Elkhider, Ihsan A.

2016-01-01

Faculty members in higher education are involved in many instructional design activities without formal training in learning theories and the science of instruction. Learning theories provide the foundation for the selection of instructional strategies and allow for reliable prediction of their effectiveness. To achieve effective learning…

Learning from Avatars: Learning Assistants Practice Physics Pedagogy in a Classroom Simulator

ERIC Educational Resources Information Center

Chini, Jacquelyn J.; Straub, Carrie L.; Thomas, Kevin H.

2016-01-01

Undergraduate students are increasingly being used to support course transformations that incorporate research-based instructional strategies. While such students are typically selected based on strong content knowledge and possible interest in teaching, they often do not have previous pedagogical training. The current training models make use of…

An Application of Markov Chains and a Monte-Carlo Simulation to Decision-Making Behavior of an Educational Administrator

ERIC Educational Resources Information Center

Yoda, Koji

1973-01-01

Develops models to systematically forecast the tendency of an educational administrator in charge of personnel selection processes to shift from one decision strategy to another under generally stable environmental conditions. Urges further research on these processes by educational planners. (JF)

International Management: Creating a More Realistic Global Planning Environment.

ERIC Educational Resources Information Center

Waldron, Darryl G.

2000-01-01

Discusses the need for realistic global planning environments in international business education, introducing a strategic planning model that has teams interacting with teams to strategically analyze a selected multinational company. This dynamic process must result in a single integrated written analysis that specifies an optimal strategy for…

Extensively Parameterized Mutation-Selection Models Reliably Capture Site-Specific Selective Constraint.

PubMed

Spielman, Stephanie J; Wilke, Claus O

2016-11-01

The mutation-selection model of coding sequence evolution has received renewed attention for its use in estimating site-specific amino acid propensities and selection coefficient distributions. Two computationally tractable mutation-selection inference frameworks have been introduced: One framework employs a fixed-effects, highly parameterized maximum likelihood approach, whereas the other employs a random-effects Bayesian Dirichlet Process approach. While both implementations follow the same model, they appear to make distinct predictions about the distribution of selection coefficients. The fixed-effects framework estimates a large proportion of highly deleterious substitutions, whereas the random-effects framework estimates that all substitutions are either nearly neutral or weakly deleterious. It remains unknown, however, how accurately each method infers evolutionary constraints at individual sites. Indeed, selection coefficient distributions pool all site-specific inferences, thereby obscuring a precise assessment of site-specific estimates. Therefore, in this study, we use a simulation-based strategy to determine how accurately each approach recapitulates the selective constraint at individual sites. We find that the fixed-effects approach, despite its extensive parameterization, consistently and accurately estimates site-specific evolutionary constraint. By contrast, the random-effects Bayesian approach systematically underestimates the strength of natural selection, particularly for slowly evolving sites. We also find that, despite the strong differences between their inferred selection coefficient distributions, the fixed- and random-effects approaches yield surprisingly similar inferences of site-specific selective constraint. We conclude that the fixed-effects mutation-selection framework provides the more reliable software platform for model application and future development. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Choosing experiments to accelerate collective discovery

PubMed Central

Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.

2015-01-01

A scientist’s choice of research problem affects his or her personal career trajectory. Scientists’ combined choices affect the direction and efficiency of scientific discovery as a whole. In this paper, we infer preferences that shape problem selection from patterns of published findings and then quantify their efficiency. We represent research problems as links between scientific entities in a knowledge network. We then build a generative model of discovery informed by qualitative research on scientific problem selection. We map salient features from this literature to key network properties: an entity’s importance corresponds to its degree centrality, and a problem’s difficulty corresponds to the network distance it spans. Drawing on millions of papers and patents published over 30 years, we use this model to infer the typical research strategy used to explore chemical relationships in biomedicine. This strategy generates conservative research choices focused on building up knowledge around important molecules. These choices become more conservative over time. The observed strategy is efficient for initial exploration of the network and supports scientific careers that require steady output, but is inefficient for science as a whole. Through supercomputer experiments on a sample of the network, we study thousands of alternatives and identify strategies much more efficient at exploring mature knowledge networks. We find that increased risk-taking and the publication of experimental failures would substantially improve the speed of discovery. We consider institutional shifts in grant making, evaluation, and publication that would help realize these efficiencies. PMID:26554009

Evolutionary Study of Interethnic Cooperation

NASA Astrophysics Data System (ADS)

Kvasnicka, Vladimir; Pospichal, Jiri

The purpose of this communication is to present an evolutionary study of cooperation between two ethnic groups. The used model is stimulated by the seminal paper of J. D. Fearon and D. D. Laitin (Explaining Interethnic Cooperation, American Political Science Review, 90 (1996), pp. 715-735), where the iterated prisoner's dilemma was used to model intra- and interethnic interactions. We reformulated their approach in a form of evolutionary prisoner's dilemma method, where a population of strategies is evolved by applying simple reproduction process with a Darwin metaphor of natural selection (a probability of selection to the reproduction is proportional to a fitness). Our computer simulations show that an application of a principle of collective guilt does not lead to an emergence of an interethnic cooperation. When an administrator is introduced, then an emergence of interethnic cooperation may be observed. Furthermore, if the ethnic groups are of very different sizes, then the principle of collective guilt may be very devastating for smaller group so that intraethnic cooperation is destroyed. The second strategy of cooperation is called the personal responsibility, where agents that defected within interethnic interactions are punished inside of their ethnic groups. It means, unlikely to the principle of collective guilt, that there exists only one type of punishment, loosely speaking, agents are punished "personally." All the substantial computational results were checked and interpreted analytically within the theory of evolutionary stable strategies. Moreover, this theoretical approach offers mechanisms of simple scenarios explaining why some particular strategies are stable or not.

Nonstationary decision model for flood risk decision scaling

NASA Astrophysics Data System (ADS)

Spence, Caitlin M.; Brown, Casey M.

2016-11-01

Hydroclimatic stationarity is increasingly questioned as a default assumption in flood risk management (FRM), but successor methods are not yet established. Some potential successors depend on estimates of future flood quantiles, but methods for estimating future design storms are subject to high levels of uncertainty. Here we apply a Nonstationary Decision Model (NDM) to flood risk planning within the decision scaling framework. The NDM combines a nonstationary probability distribution of annual peak flow with optimal selection of flood management alternatives using robustness measures. The NDM incorporates structural and nonstructural FRM interventions and valuation of flows supporting ecosystem services to calculate expected cost of a given FRM strategy. A search for the minimum-cost strategy under incrementally varied representative scenarios extending across the plausible range of flood trend and value of the natural flow regime discovers candidate FRM strategies that are evaluated and compared through a decision scaling analysis (DSA). The DSA selects a management strategy that is optimal or close to optimal across the broadest range of scenarios or across the set of scenarios deemed most likely to occur according to estimates of future flood hazard. We illustrate the decision framework using a stylized example flood management decision based on the Iowa City flood management system, which has experienced recent unprecedented high flow episodes. The DSA indicates a preference for combining infrastructural and nonstructural adaptation measures to manage flood risk and makes clear that options-based approaches cannot be assumed to be "no" or "low regret."

Modeling ozone episodes in the Baltimore-Washington region

NASA Technical Reports Server (NTRS)

Ryan, William F.

1994-01-01

Surface ozone (O3) concentrations in excess of the National Ambient Air Quality Standard (NAAQS) continue to occur in metropolitan areas in the United States despite efforts to control emissions of O3 precursors. Future O3 control strategies will be based on results from modeling efforts that have just begun in many areas. Two initial questions that arise are model sensitivity to domain-specific conditions and the selection of episodes for model evaluation and control strategy development. For the Baltimore-Washington region (B-W), the presence of the Chesapeake Bay introduces a number of issues relevant to model sensitivity. In this paper, the specific questions of the determination of model volume (mixing height) for the Urban Airshed Model (UAM) is discussed and various alternative methods compared. For the latter question, several analytic approaches, Cluster Analysis and classification and Regression Tree (CART) analysis are undertaken to determine meteorological conditions associated with severe O3 events in the B-W domain.

Force on Force Modeling with Formal Task Structures and Dynamic Geometry

DTIC Science & Technology

2017-03-24

task framework, derived using the MMF methodology to structure a complex mission. It further demonstrated the integration of effects from a range of...application methodology was intended to support a combined developmental testing (DT) and operational testing (OT) strategy for selected systems under test... methodology to develop new or modify existing Models and Simulations (M&S) to: • Apply data from multiple, distributed sources (including test

Optimization-Based Selection of Influential Agents in a Rural Afghan Social Network

DTIC Science & Technology

2010-06-01

nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent assignment strategy producing the greatest...leader social network, and 3) the nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent...NATO Coalition in Afghanistan. 55 for Afghanistan ( [54], [31], [48], [55], [30]). While Arab tribes tend to be more hierarchical, Pashtun tribes are

2002 Defense Modeling and Simulation Office (DMSO) Laboratory for Human Behavior Model Interchange Standards

DTIC Science & Technology

2003-07-01

standard release with the publicly available "mod" interface allows us to avoid purchasing a game engine license (approximate cost $350,000) from Epic...depletion is accurately simulated for ammunition * Both contain target detection, target identification, target selection, and collision avoidance and...into other game genres such as Real-Time Strategy (RTS) games and Massively Multiplayer Online Role- Playing Games ( MMORPG ). Unfortunately these game

Glucose Injections into the Dorsal Hippocampus or Dorsolateral Striatum of Rats Prior to T-Maze Training: Modulation of Learning Rates and Strategy Selection

ERIC Educational Resources Information Center

Canal, Clinton E.; Stutz, Sonja J.; Gold, Paul E.

2005-01-01

The present experiments examined the effects of injecting glucose into the dorsal hippocampus or dorsolateral striatum on learning rates and on strategy selection in rats trained on a T-maze that can be solved by using either a hippocampus-sensitive place or striatum-sensitive response strategy. Percentage strategy selection on a probe trial…

A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.

PubMed

Moore, Jason H; Gilbert, Joshua C; Tsai, Chia-Ti; Chiang, Fu-Tien; Holden, Todd; Barney, Nate; White, Bill C

2006-07-21

Detecting, characterizing, and interpreting gene-gene interactions or epistasis in studies of human disease susceptibility is both a mathematical and a computational challenge. To address this problem, we have previously developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension (i.e. constructive induction) thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe a comprehensive and flexible framework for detecting and interpreting gene-gene interactions that utilizes advances in information theory for selecting interesting single-nucleotide polymorphisms (SNPs), MDR for constructive induction, machine learning methods for classification, and finally graphical models for interpretation. We illustrate the usefulness of this strategy using artificial datasets simulated from several different two-locus and three-locus epistasis models. We show that the accuracy, sensitivity, specificity, and precision of a naïve Bayes classifier are significantly improved when SNPs are selected based on their information gain (i.e. class entropy removed) and reduced to a single attribute using MDR. We then apply this strategy to detecting, characterizing, and interpreting epistatic models in a genetic study (n = 500) of atrial fibrillation and show that both classification and model interpretation are significantly improved.

Non-ignorable missingness in logistic regression.

PubMed

Wang, Joanna J J; Bartlett, Mark; Ryan, Louise

2017-08-30

Nonresponses and missing data are common in observational studies. Ignoring or inadequately handling missing data may lead to biased parameter estimation, incorrect standard errors and, as a consequence, incorrect statistical inference and conclusions. We present a strategy for modelling non-ignorable missingness where the probability of nonresponse depends on the outcome. Using a simple case of logistic regression, we quantify the bias in regression estimates and show the observed likelihood is non-identifiable under non-ignorable missing data mechanism. We then adopt a selection model factorisation of the joint distribution as the basis for a sensitivity analysis to study changes in estimated parameters and the robustness of study conclusions against different assumptions. A Bayesian framework for model estimation is used as it provides a flexible approach for incorporating different missing data assumptions and conducting sensitivity analysis. Using simulated data, we explore the performance of the Bayesian selection model in correcting for bias in a logistic regression. We then implement our strategy using survey data from the 45 and Up Study to investigate factors associated with worsening health from the baseline to follow-up survey. Our findings have practical implications for the use of the 45 and Up Study data to answer important research questions relating to health and quality-of-life. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Cascades in the Threshold Model for varying system sizes

NASA Astrophysics Data System (ADS)

Karampourniotis, Panagiotis; Sreenivasan, Sameet; Szymanski, Boleslaw; Korniss, Gyorgy

2015-03-01

A classical model in opinion dynamics is the Threshold Model (TM) aiming to model the spread of a new opinion based on the social drive of peer pressure. Under the TM a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. Cascades in the TM depend on multiple parameters, such as the number and selection strategy of the initially active nodes (initiators), and the threshold distribution of the nodes. For a uniform threshold in the network there is a critical fraction of initiators for which a transition from small to large cascades occurs, which for ER graphs is largerly independent of the system size. Here, we study the spread contribution of each newly assigned initiator under the TM for different initiator selection strategies for synthetic graphs of various sizes. We observe that for ER graphs when large cascades occur, the spread contribution of the added initiator on the transition point is independent of the system size, while the contribution of the rest of the initiators converges to zero at infinite system size. This property is used for the identification of large transitions for various threshold distributions. Supported in part by ARL NS-CTA, ARO, ONR, and DARPA.

Evaluation of parallel reduction strategies for fusion of sensory information from a robot team

NASA Astrophysics Data System (ADS)

Lyons, Damian M.; Leroy, Joseph

2015-05-01

The advantage of using a team of robots to search or to map an area is that by navigating the robots to different parts of the area, searching or mapping can be completed more quickly. A crucial aspect of the problem is the combination, or fusion, of data from team members to generate an integrated model of the search/mapping area. In prior work we looked at the issue of removing mutual robots views from an integrated point cloud model built from laser and stereo sensors, leading to a cleaner and more accurate model. This paper addresses a further challenge: Even with mutual views removed, the stereo data from a team of robots can quickly swamp a WiFi connection. This paper proposes and evaluates a communication and fusion approach based on the parallel reduction operation, where data is combined in a series of steps of increasing subsets of the team. Eight different strategies for selecting the subsets are evaluated for bandwidth requirements using three robot missions, each carried out with teams of four Pioneer 3-AT robots. Our results indicate that selecting groups to combine based on similar pose but distant location yields the best results.

Model-Based Fault Tolerant Control

NASA Technical Reports Server (NTRS)

Kumar, Aditya; Viassolo, Daniel

2008-01-01

The Model Based Fault Tolerant Control (MBFTC) task was conducted under the NASA Aviation Safety and Security Program. The goal of MBFTC is to develop and demonstrate real-time strategies to diagnose and accommodate anomalous aircraft engine events such as sensor faults, actuator faults, or turbine gas-path component damage that can lead to in-flight shutdowns, aborted take offs, asymmetric thrust/loss of thrust control, or engine surge/stall events. A suite of model-based fault detection algorithms were developed and evaluated. Based on the performance and maturity of the developed algorithms two approaches were selected for further analysis: (i) multiple-hypothesis testing, and (ii) neural networks; both used residuals from an Extended Kalman Filter to detect the occurrence of the selected faults. A simple fusion algorithm was implemented to combine the results from each algorithm to obtain an overall estimate of the identified fault type and magnitude. The identification of the fault type and magnitude enabled the use of an online fault accommodation strategy to correct for the adverse impact of these faults on engine operability thereby enabling continued engine operation in the presence of these faults. The performance of the fault detection and accommodation algorithm was extensively tested in a simulation environment.

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

PubMed

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

2007-02-08

Models of codon evolution have proven useful for investigating the strength and direction of natural selection. In some cases, a priori biological knowledge has been used successfully to model heterogeneous evolutionary dynamics among codon sites. These are called fixed-effect models, and they require that all codon sites are assigned to one of several partitions which are permitted to have independent parameters for selection pressure, evolutionary rate, transition to transversion ratio or codon frequencies. For single gene analysis, partitions might be defined according to protein tertiary structure, and for multiple gene analysis partitions might be defined according to a gene's functional category. Given a set of related fixed-effect models, the task of selecting the model that best fits the data is not trivial. In this study, we implement a set of fixed-effect codon models which allow for different levels of heterogeneity among partitions in the substitution process. We describe strategies for selecting among these models by a backward elimination procedure, Akaike information criterion (AIC) or a corrected Akaike information criterion (AICc). We evaluate the performance of these model selection methods via a simulation study, and make several recommendations for real data analysis. Our simulation study indicates that the backward elimination procedure can provide a reliable method for model selection in this setting. We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria). Fixed-effect models have advantages and disadvantages. Fixed-effect models are desirable when data partitions are known to exhibit significant heterogeneity or when a statistical test of such heterogeneity is desired. They have the disadvantage of requiring a priori knowledge for partitioning sites. We recommend: (i) selection of models by using backward elimination rather than AIC or AICc, (ii) use a stringent cut-off, e.g., p = 0.0001, and (iii) conduct sensitivity analysis of results. With thoughtful application, fixed-effect codon models should provide a useful tool for large scale multi-gene analyses.

CACNA1C gene regulates behavioral strategies in operant rule learning

PubMed Central

Berger, Stefan; Bartsch, Dusan; Gass, Peter

2017-01-01

Behavioral experiments are usually designed to tap into a specific cognitive function, but animals may solve a given task through a variety of different and individual behavioral strategies, some of them not foreseen by the experimenter. Animal learning may therefore be seen more as the process of selecting among, and adapting, potential behavioral policies, rather than mere strengthening of associative links. Calcium influx through high-voltage-gated Ca2+ channels is central to synaptic plasticity, and altered expression of Cav1.2 channels and the CACNA1C gene have been associated with severe learning deficits and psychiatric disorders. Given this, we were interested in how specifically a selective functional ablation of the Cacna1c gene would modulate the learning process. Using a detailed, individual-level analysis of learning on an operant cue discrimination task in terms of behavioral strategies, combined with Bayesian selection among computational models estimated from the empirical data, we show that a Cacna1c knockout does not impair learning in general but has a much more specific effect: the majority of Cacna1c knockout mice still managed to increase reward feedback across trials but did so by adapting an outcome-based strategy, while the majority of matched controls adopted the experimentally intended cue-association rule. Our results thus point to a quite specific role of a single gene in learning and highlight that much more mechanistic insight could be gained by examining response patterns in terms of a larger repertoire of potential behavioral strategies. The results may also have clinical implications for treating psychiatric disorders. PMID:28604818

CACNA1C gene regulates behavioral strategies in operant rule learning.

PubMed

Koppe, Georgia; Mallien, Anne Stephanie; Berger, Stefan; Bartsch, Dusan; Gass, Peter; Vollmayr, Barbara; Durstewitz, Daniel

2017-06-01

Behavioral experiments are usually designed to tap into a specific cognitive function, but animals may solve a given task through a variety of different and individual behavioral strategies, some of them not foreseen by the experimenter. Animal learning may therefore be seen more as the process of selecting among, and adapting, potential behavioral policies, rather than mere strengthening of associative links. Calcium influx through high-voltage-gated Ca2+ channels is central to synaptic plasticity, and altered expression of Cav1.2 channels and the CACNA1C gene have been associated with severe learning deficits and psychiatric disorders. Given this, we were interested in how specifically a selective functional ablation of the Cacna1c gene would modulate the learning process. Using a detailed, individual-level analysis of learning on an operant cue discrimination task in terms of behavioral strategies, combined with Bayesian selection among computational models estimated from the empirical data, we show that a Cacna1c knockout does not impair learning in general but has a much more specific effect: the majority of Cacna1c knockout mice still managed to increase reward feedback across trials but did so by adapting an outcome-based strategy, while the majority of matched controls adopted the experimentally intended cue-association rule. Our results thus point to a quite specific role of a single gene in learning and highlight that much more mechanistic insight could be gained by examining response patterns in terms of a larger repertoire of potential behavioral strategies. The results may also have clinical implications for treating psychiatric disorders.

Comprehensive clone screening and evaluation of fed-batch strategies in a microbioreactor and lab scale stirred tank bioreactor system: application on Pichia pastoris producing Rhizopus oryzae lipase

PubMed Central

2014-01-01

Background In Pichia pastoris bioprocess engineering, classic approaches for clone selection and bioprocess optimization at small/micro scale using the promoter of the alcohol oxidase 1 gene (PAOX1), induced by methanol, present low reproducibility leading to high time and resource consumption. Results An automated microfermentation platform (RoboLector) was successfully tested to overcome the chronic problems of clone selection and optimization of fed-batch strategies. Different clones from Mut+P. pastoris phenotype strains expressing heterologous Rhizopus oryzae lipase (ROL), including a subset also overexpressing the transcription factor HAC1, were tested to select the most promising clones. The RoboLector showed high performance for the selection and optimization of cultivation media with minimal cost and time. Syn6 medium was better than conventional YNB medium in terms of production of heterologous protein. The RoboLector microbioreactor was also tested for different fed-batch strategies with three clones producing different lipase levels. Two mixed substrates fed-batch strategies were evaluated. The first strategy was the enzymatic release of glucose from a soluble glucose polymer by a glucosidase, and methanol addition every 24 hours. The second strategy used glycerol as co-substrate jointly with methanol at two different feeding rates. The implementation of these simple fed-batch strategies increased the levels of lipolytic activity 80-fold compared to classical batch strategies used in clone selection. Thus, these strategies minimize the risk of errors in the clone selection and increase the detection level of the desired product. Finally, the performance of two fed-batch strategies was compared for lipase production between the RoboLector microbioreactor and 5 liter stirred tank bioreactor for three selected clones. In both scales, the same clone ranking was achieved. Conclusion The RoboLector showed excellent performance in clone selection of P. pastoris Mut+ phenotype. The use of fed-batch strategies using mixed substrate feeds resulted in increased biomass and lipolytic activity. The automated processing of fed-batch strategies by the RoboLector considerably facilitates the operation of fermentation processes, while reducing error-prone clone selection by increasing product titers. The scale-up from microbioreactor to lab scale stirred tank bioreactor showed an excellent correlation, validating the use of microbioreactor as a powerful tool for evaluating fed-batch operational strategies. PMID:24606982

The cost of being queen: investment across Pogonomyrmex harvester ant gynes that differ in degree of claustrality.

PubMed

Enzmann, Brittany L; Gibbs, Allen G; Nonacs, Peter

2014-11-01

The role of the ant colony largely consists of non-reproductive tasks, such as foraging, tending brood, and defense. However, workers are vitally linked to reproduction through their provisioning of sexual offspring, which are produced annually to mate and initiate new colonies. Gynes (future queens) have size-associated variation in colony founding strategy (claustrality), with each strategy requiring different energetic investments from their natal colony. We compared the per capita production cost required for semi-claustral, facultative, and claustral gynes across four species of Pogonomyrmex harvester ants. We found that the claustral founding strategy is markedly expensive, costing approximately 70% more energy than that of the semi-claustral strategy. Relative to males, claustral gynes also had the largest differential investment and smallest size variation. We applied these investment costs to a model by Brown and Bonhoeffer (2003) that predicts founding strategy based on investment cost and foraging survivorship. The model predicts that non-claustral foundresses must survive the foraging period with a probability of 30-36% in order for a foraging strategy to be selectively favored. These results highlight the importance of incorporating resource investment at the colony level when investigating the evolution of colony founding strategies in ants. Copyright © 2014 Elsevier Ltd. All rights reserved.

Drought-avoiding plants with low water use can achieve high rainfall retention without jeopardising survival on green roofs.

PubMed

Szota, Christopher; Farrell, Claire; Williams, Nicholas S G; Arndt, Stefan K; Fletcher, Tim D

2017-12-15

Green roofs are increasingly being used among the suite of tools designed to reduce the volume of surface water runoff generated by cities. Plants provide the primary mechanism for restoring the rainfall retention capacity of green roofs, but selecting plants with high water use is likely to increase drought stress. Using empirically-derived plant physiological parameters, we used a water balance model to assess the trade-off between rainfall retention and plant drought stress under a 30-year climate scenario. We compared high and low water users with either drought avoidance or drought tolerance strategies. Green roofs with low water-using, drought-avoiding species achieved high rainfall retention (66-81%) without experiencing significant drought stress. Roofs planted with other strategies showed high retention (72-90%), but they also experienced >50days of drought stress per year. However, not all species with the same strategy behaved similarly, therefore selecting plants based on water use and drought strategy alone does not guarantee survival in shallow substrates where drought stress can develop quickly. Despite this, it is more likely that green roofs will achieve high rainfall retention with minimal supplementary irrigation if planted with low water users with drought avoidance strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Lifelong learning strategies in nursing: A systematic review.

PubMed

Qalehsari, Mojtaba Qanbari; Khaghanizadeh, Morteza; Ebadi, Abbas

2017-10-01

Lifelong learning is an expectation in the professional performance of nurses, which is directly related to the success of students in nursing schools. In spite of the considerable attention paid to this issue, lifelong learning strategies are not fully understood. The aim of this study was to clarify lifelong learning strategies of nursing students with respect to international experience. In this systematic review, an extensive investigation was carried out using Persian and English studies in Pub Med, ProQuest, Cochrane, Ovid, Scopus, Web of Science, SID, and Iran Doc using the following keywords: lifelong learning, self-directed learning, lifelong learning model, continuing education, nursing education, and lifelong program. Finally, 22 articles published from 1994 to 2016 were selected for the final analysis. Data extracted from the selected articles was summarized and classified based on the research questions. In this study, 8 main themes, namely intellectual and practical independence, collaborative (cooperative) learning, researcher thinking, persistence in learning, need-based learning, learning management, suitable learning environment, and inclusive growth, were extracted from the article data. Having identified and clarified lifelong learning strategies in nursing, it is recommended to use the research findings in the programs and teaching systems of nursing schools. Use of strategies of lifelong learning will led to increased quality of education, development of nursing competency and finally, increased quality of patient care.

Cultural differences in complex addition: efficient Chinese versus adaptive Belgians and Canadians.

PubMed

Imbo, Ineke; LeFevre, Jo-Anne

2009-11-01

In the present study, the authors tested the effects of working-memory load on math problem solving in 3 different cultures: Flemish-speaking Belgians, English-speaking Canadians, and Chinese-speaking Chinese currently living in Canada. Participants solved complex addition problems (e.g., 58 + 76) in no-load and working-memory load conditions, in which either the central executive or the phonological loop was loaded. The authors used the choice/no-choice method to obtain unbiased measures of strategy selection and strategy efficiency. The Chinese participants were faster than the Belgians, who were faster and more accurate than the Canadians. The Chinese also required fewer working-memory resources than did the Belgians and Canadians. However, the Chinese chose less adaptively from the available strategies than did the Belgians and Canadians. These cultural differences in math problem solving are likely the result of different instructional approaches during elementary school (practice and training in Asian countries vs. exploration and flexibility in non-Asian countries), differences in the number language, and informal cultural norms and standards. The relevance of being adaptive is discussed as well as the implications of the results in regards to the strategy choice and discovery simulation model of strategy selection (J. Shrager & R. S. Siegler, 1998).

Logic-Based Retrieval: Technology for Content-Oriented and Analytical Querying of Patent Data

NASA Astrophysics Data System (ADS)

Klampanos, Iraklis Angelos; Wu, Hengzhi; Roelleke, Thomas; Azzam, Hany

Patent searching is a complex retrieval task. An initial document search is only the starting point of a chain of searches and decisions that need to be made by patent searchers. Keyword-based retrieval is adequate for document searching, but it is not suitable for modelling comprehensive retrieval strategies. DB-like and logical approaches are the state-of-the-art techniques to model strategies, reasoning and decision making. In this paper we present the application of logical retrieval to patent searching. The two grand challenges are expressiveness and scalability, where high degree of expressiveness usually means a loss in scalability. In this paper we report how to maintain scalability while offering the expressiveness of logical retrieval required for solving patent search tasks. We present logical retrieval background, and how to model data-source selection and results' fusion. Moreover, we demonstrate the modelling of a retrieval strategy, a technique by which patent professionals are able to express, store and exchange their strategies and rationales when searching patents or when making decisions. An overview of the architecture and technical details complement the paper, while the evaluation reports preliminary results on how query processing times can be guaranteed, and how quality is affected by trading off responsiveness.

The Role of Task Understanding on Younger and Older Adults' Performance.

PubMed

Frank, David J; Touron, Dayna R

2016-12-16

Age-related performance decrements have been linked to inferior strategic choices. Strategy selection models argue that accurate task representations are necessary for choosing appropriate strategies. But no studies to date have compared task representations in younger and older adults. Metacognition research suggests age-related deficits in updating and utilizing strategy knowledge, but other research suggests age-related sparing when information can be consolidated into a coherent mental model. Study 1 validated the use of concept mapping as a tool for measuring task representation accuracy. Study 2 measured task representations before and after a complex strategic task to test for age-related decrements in task representation formation and updating. Task representation accuracy and task performance were equivalent across age groups. Better task representations were related to better performance. However, task representation scores remained fairly stable over the task with minimal evidence of updating. Our findings mirror those in the mental model literature suggesting age-related sparing of strategy use when information can be integrated into a coherent mental model. Future research should manipulate the presence of a unifying context to better evaluate this hypothesis. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.